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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue693/hash-microbenchmark/SpookyV2.cc
|
// Spooky Hash
// A 128-bit noncryptographic hash, for checksums and table lookup
// By Bob Jenkins. Public domain.
// Oct 31 2010: published framework, disclaimer ShortHash isn't right
// Nov 7 2010: disabled ShortHash
// Oct 31 2011: replace End, ShortMix, ShortEnd, enable ShortHash again
// April 10 2012: buffer overflow on platforms without unaligned reads
// July 12 2012: was passing out variables in final to in/out in short
// July 30 2012: I reintroduced the buffer overflow
// August 5 2012: SpookyV2: d = should be d += in short hash, and remove extra mix from long hash
#include <memory.h>
#include "SpookyV2.h"
#define ALLOW_UNALIGNED_READS 1
//
// short hash ... it could be used on any message,
// but it's used by Spooky just for short messages.
//
void SpookyHash::Short(
const void *message,
size_t length,
uint64 *hash1,
uint64 *hash2) {
uint64 buf[2 * sc_numVars];
union {
const uint8 *p8;
uint32 *p32;
uint64 *p64;
size_t i;
}
u;
u.p8 = (const uint8 *)message;
if (!ALLOW_UNALIGNED_READS && (u.i & 0x7)) {
memcpy(buf, message, length);
u.p64 = buf;
}
size_t remainder = length % 32;
uint64 a = *hash1;
uint64 b = *hash2;
uint64 c = sc_const;
uint64 d = sc_const;
if (length > 15) {
const uint64 *end = u.p64 + (length / 32) * 4;
// handle all complete sets of 32 bytes
for (; u.p64 < end; u.p64 += 4) {
c += u.p64[0];
d += u.p64[1];
ShortMix(a, b, c, d);
a += u.p64[2];
b += u.p64[3];
}
//Handle the case of 16+ remaining bytes.
if (remainder >= 16) {
c += u.p64[0];
d += u.p64[1];
ShortMix(a, b, c, d);
u.p64 += 2;
remainder -= 16;
}
}
// Handle the last 0..15 bytes, and its length
d += ((uint64)length) << 56;
switch (remainder) {
case 15:
d += ((uint64)u.p8[14]) << 48;
case 14:
d += ((uint64)u.p8[13]) << 40;
case 13:
d += ((uint64)u.p8[12]) << 32;
case 12:
d += u.p32[2];
c += u.p64[0];
break;
case 11:
d += ((uint64)u.p8[10]) << 16;
case 10:
d += ((uint64)u.p8[9]) << 8;
case 9:
d += (uint64)u.p8[8];
case 8:
c += u.p64[0];
break;
case 7:
c += ((uint64)u.p8[6]) << 48;
case 6:
c += ((uint64)u.p8[5]) << 40;
case 5:
c += ((uint64)u.p8[4]) << 32;
case 4:
c += u.p32[0];
break;
case 3:
c += ((uint64)u.p8[2]) << 16;
case 2:
c += ((uint64)u.p8[1]) << 8;
case 1:
c += (uint64)u.p8[0];
break;
case 0:
c += sc_const;
d += sc_const;
}
ShortEnd(a, b, c, d);
*hash1 = a;
*hash2 = b;
}
// do the whole hash in one call
void SpookyHash::Hash128(
const void *message,
size_t length,
uint64 *hash1,
uint64 *hash2) {
if (length < sc_bufSize) {
Short(message, length, hash1, hash2);
return;
}
uint64 h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11;
uint64 buf[sc_numVars];
uint64 *end;
union {
const uint8 *p8;
uint64 *p64;
size_t i;
}
u;
size_t remainder;
h0 = h3 = h6 = h9 = *hash1;
h1 = h4 = h7 = h10 = *hash2;
h2 = h5 = h8 = h11 = sc_const;
u.p8 = (const uint8 *)message;
end = u.p64 + (length / sc_blockSize) * sc_numVars;
// handle all whole sc_blockSize blocks of bytes
if (ALLOW_UNALIGNED_READS || ((u.i & 0x7) == 0)) {
while (u.p64 < end) {
Mix(u.p64, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
u.p64 += sc_numVars;
}
} else {
while (u.p64 < end) {
memcpy(buf, u.p64, sc_blockSize);
Mix(buf, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
u.p64 += sc_numVars;
}
}
// handle the last partial block of sc_blockSize bytes
remainder = (length - ((const uint8 *)end - (const uint8 *)message));
memcpy(buf, end, remainder);
memset(((uint8 *)buf) + remainder, 0, sc_blockSize - remainder);
((uint8 *)buf)[sc_blockSize - 1] = remainder;
// do some final mixing
End(buf, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
*hash1 = h0;
*hash2 = h1;
}
// init spooky state
void SpookyHash::Init(uint64 seed1, uint64 seed2) {
m_length = 0;
m_remainder = 0;
m_state[0] = seed1;
m_state[1] = seed2;
}
// add a message fragment to the state
void SpookyHash::Update(const void *message, size_t length) {
uint64 h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11;
size_t newLength = length + m_remainder;
uint8 remainder;
union {
const uint8 *p8;
uint64 *p64;
size_t i;
}
u;
const uint64 *end;
// Is this message fragment too short? If it is, stuff it away.
if (newLength < sc_bufSize) {
memcpy(&((uint8 *)m_data)[m_remainder], message, length);
m_length = length + m_length;
m_remainder = (uint8)newLength;
return;
}
// init the variables
if (m_length < sc_bufSize) {
h0 = h3 = h6 = h9 = m_state[0];
h1 = h4 = h7 = h10 = m_state[1];
h2 = h5 = h8 = h11 = sc_const;
} else {
h0 = m_state[0];
h1 = m_state[1];
h2 = m_state[2];
h3 = m_state[3];
h4 = m_state[4];
h5 = m_state[5];
h6 = m_state[6];
h7 = m_state[7];
h8 = m_state[8];
h9 = m_state[9];
h10 = m_state[10];
h11 = m_state[11];
}
m_length = length + m_length;
// if we've got anything stuffed away, use it now
if (m_remainder) {
uint8 prefix = sc_bufSize - m_remainder;
memcpy(&(((uint8 *)m_data)[m_remainder]), message, prefix);
u.p64 = m_data;
Mix(u.p64, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
Mix(&u.p64[sc_numVars], h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
u.p8 = ((const uint8 *)message) + prefix;
length -= prefix;
} else {
u.p8 = (const uint8 *)message;
}
// handle all whole blocks of sc_blockSize bytes
end = u.p64 + (length / sc_blockSize) * sc_numVars;
remainder = (uint8)(length - ((const uint8 *)end - u.p8));
if (ALLOW_UNALIGNED_READS || (u.i & 0x7) == 0) {
while (u.p64 < end) {
Mix(u.p64, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
u.p64 += sc_numVars;
}
} else {
while (u.p64 < end) {
memcpy(m_data, u.p8, sc_blockSize);
Mix(m_data, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
u.p64 += sc_numVars;
}
}
// stuff away the last few bytes
m_remainder = remainder;
memcpy(m_data, end, remainder);
// stuff away the variables
m_state[0] = h0;
m_state[1] = h1;
m_state[2] = h2;
m_state[3] = h3;
m_state[4] = h4;
m_state[5] = h5;
m_state[6] = h6;
m_state[7] = h7;
m_state[8] = h8;
m_state[9] = h9;
m_state[10] = h10;
m_state[11] = h11;
}
// report the hash for the concatenation of all message fragments so far
void SpookyHash::Final(uint64 *hash1, uint64 *hash2) {
// init the variables
if (m_length < sc_bufSize) {
*hash1 = m_state[0];
*hash2 = m_state[1];
Short(m_data, m_length, hash1, hash2);
return;
}
const uint64 *data = (const uint64 *)m_data;
uint8 remainder = m_remainder;
uint64 h0 = m_state[0];
uint64 h1 = m_state[1];
uint64 h2 = m_state[2];
uint64 h3 = m_state[3];
uint64 h4 = m_state[4];
uint64 h5 = m_state[5];
uint64 h6 = m_state[6];
uint64 h7 = m_state[7];
uint64 h8 = m_state[8];
uint64 h9 = m_state[9];
uint64 h10 = m_state[10];
uint64 h11 = m_state[11];
if (remainder >= sc_blockSize) {
// m_data can contain two blocks; handle any whole first block
Mix(data, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
data += sc_numVars;
remainder -= sc_blockSize;
}
// mix in the last partial block, and the length mod sc_blockSize
memset(&((uint8 *)data)[remainder], 0, (sc_blockSize - remainder));
((uint8 *)data)[sc_blockSize - 1] = remainder;
// do some final mixing
End(data, h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
*hash1 = h0;
*hash2 = h1;
}
| 8,549 |
C++
| 25.635514 | 99 | 0.51468 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue693/hash-microbenchmark/fast_hash.h
|
#ifndef FAST_HASH_H
#define FAST_HASH_H
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
namespace fast_hash {
static_assert(sizeof(unsigned int) == 4, "unsigned int has unexpected size");
/*
Internal class storing the state of the hashing process. It should only be
instantiated by functions in this file.
*/
class HashState {
std::uint32_t hash;
public:
HashState()
: hash(0xdeadbeef) {
}
void feed(std::uint32_t value) {
hash ^= value + 0x9e3779b9 + (hash << 6) + (hash >> 2);
}
std::uint32_t get_hash32() {
return hash;
}
std::uint64_t get_hash64() {
return (static_cast<std::uint64_t>(hash) << 32) | hash;
}
};
/*
These functions add a new object to an existing HashState object.
To add hashing support for a user type X, provide an override
for utils::feed(HashState &hash_state, const X &value).
*/
static_assert(
sizeof(int) == sizeof(std::uint32_t),
"int and uint32_t have different sizes");
inline void feed(HashState &hash_state, int value) {
hash_state.feed(static_cast<std::uint32_t>(value));
}
static_assert(
sizeof(unsigned int) == sizeof(std::uint32_t),
"unsigned int and uint32_t have different sizes");
inline void feed(HashState &hash_state, unsigned int value) {
hash_state.feed(static_cast<std::uint32_t>(value));
}
inline void feed(HashState &hash_state, std::uint64_t value) {
hash_state.feed(static_cast<std::uint32_t>(value));
value >>= 32;
hash_state.feed(static_cast<std::uint32_t>(value));
}
template<typename T>
void feed(HashState &hash_state, const T *p) {
// This is wasteful in 32-bit mode, but we plan to discontinue 32-bit compiles anyway.
feed(hash_state, reinterpret_cast<std::uint64_t>(p));
}
template<typename T1, typename T2>
void feed(HashState &hash_state, const std::pair<T1, T2> &p) {
feed(hash_state, p.first);
feed(hash_state, p.second);
}
template<typename T>
void feed(HashState &hash_state, const std::vector<T> &vec) {
/*
Feed vector size to ensure that no two different vectors of the same type
have the same code prefix.
*/
feed(hash_state, vec.size());
for (const T &item : vec) {
feed(hash_state, item);
}
}
/*
Public hash functions.
get_hash() is used internally by the HashMap and HashSet classes below. In
more exotic use cases, such as implementing a custom hash table, you can also
use `get_hash32()`, `get_hash64()` and `get_hash()` directly.
*/
template<typename T>
std::uint32_t get_hash32(const T &value) {
HashState hash_state;
feed(hash_state, value);
return hash_state.get_hash32();
}
template<typename T>
std::uint64_t get_hash64(const T &value) {
HashState hash_state;
feed(hash_state, value);
return hash_state.get_hash64();
}
template<typename T>
std::size_t get_hash(const T &value) {
return static_cast<std::size_t>(get_hash64(value));
}
// This struct should only be used by HashMap and HashSet below.
template<typename T>
struct Hash {
std::size_t operator()(const T &val) const {
return get_hash(val);
}
};
/*
Aliases for hash sets and hash maps in user code. All user code should use
utils::UnorderedSet and utils::UnorderedMap instead of std::unordered_set and
std::unordered_map.
To hash types that are not supported out of the box, implement utils::feed.
*/
template<typename T1, typename T2>
using HashMap = std::unordered_map<T1, T2, Hash<T1>>;
template<typename T>
using HashSet = std::unordered_set<T, Hash<T>>;
/* Transitional aliases and functions */
template<typename T1, typename T2>
using UnorderedMap = std::unordered_map<T1, T2>;
template<typename T>
using UnorderedSet = std::unordered_set<T>;
}
#endif
| 3,848 |
C
| 24.66 | 90 | 0.677755 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue693/hash-microbenchmark/SpookyV2.h
|
//
// SpookyHash: a 128-bit noncryptographic hash function
// By Bob Jenkins, public domain
// Oct 31 2010: alpha, framework + SpookyHash::Mix appears right
// Oct 31 2011: alpha again, Mix only good to 2^^69 but rest appears right
// Dec 31 2011: beta, improved Mix, tested it for 2-bit deltas
// Feb 2 2012: production, same bits as beta
// Feb 5 2012: adjusted definitions of uint* to be more portable
// Mar 30 2012: 3 bytes/cycle, not 4. Alpha was 4 but wasn't thorough enough.
// August 5 2012: SpookyV2 (different results)
//
// Up to 3 bytes/cycle for long messages. Reasonably fast for short messages.
// All 1 or 2 bit deltas achieve avalanche within 1% bias per output bit.
//
// This was developed for and tested on 64-bit x86-compatible processors.
// It assumes the processor is little-endian. There is a macro
// controlling whether unaligned reads are allowed (by default they are).
// This should be an equally good hash on big-endian machines, but it will
// compute different results on them than on little-endian machines.
//
// Google's CityHash has similar specs to SpookyHash, and CityHash is faster
// on new Intel boxes. MD4 and MD5 also have similar specs, but they are orders
// of magnitude slower. CRCs are two or more times slower, but unlike
// SpookyHash, they have nice math for combining the CRCs of pieces to form
// the CRCs of wholes. There are also cryptographic hashes, but those are even
// slower than MD5.
//
#include <stddef.h>
#ifdef _MSC_VER
# define INLINE __forceinline
typedef unsigned __int64 uint64;
typedef unsigned __int32 uint32;
typedef unsigned __int16 uint16;
typedef unsigned __int8 uint8;
#else
# include <stdint.h>
# define INLINE inline
typedef uint64_t uint64;
typedef uint32_t uint32;
typedef uint16_t uint16;
typedef uint8_t uint8;
#endif
class SpookyHash {
public:
//
// SpookyHash: hash a single message in one call, produce 128-bit output
//
static void Hash128(
const void *message, // message to hash
size_t length, // length of message in bytes
uint64 *hash1, // in/out: in seed 1, out hash value 1
uint64 *hash2); // in/out: in seed 2, out hash value 2
//
// Hash64: hash a single message in one call, return 64-bit output
//
static uint64 Hash64(
const void *message, // message to hash
size_t length, // length of message in bytes
uint64 seed) { // seed
uint64 hash1 = seed;
Hash128(message, length, &hash1, &seed);
return hash1;
}
//
// Hash32: hash a single message in one call, produce 32-bit output
//
static uint32 Hash32(
const void *message, // message to hash
size_t length, // length of message in bytes
uint32 seed) { // seed
uint64 hash1 = seed, hash2 = seed;
Hash128(message, length, &hash1, &hash2);
return (uint32)hash1;
}
//
// Init: initialize the context of a SpookyHash
//
void Init(
uint64 seed1, // any 64-bit value will do, including 0
uint64 seed2); // different seeds produce independent hashes
//
// Update: add a piece of a message to a SpookyHash state
//
void Update(
const void *message, // message fragment
size_t length); // length of message fragment in bytes
//
// Final: compute the hash for the current SpookyHash state
//
// This does not modify the state; you can keep updating it afterward
//
// The result is the same as if SpookyHash() had been called with
// all the pieces concatenated into one message.
//
void Final(
uint64 *hash1, // out only: first 64 bits of hash value.
uint64 *hash2); // out only: second 64 bits of hash value.
//
// left rotate a 64-bit value by k bytes
//
static INLINE uint64 Rot64(uint64 x, int k) {
return (x << k) | (x >> (64 - k));
}
//
// This is used if the input is 96 bytes long or longer.
//
// The internal state is fully overwritten every 96 bytes.
// Every input bit appears to cause at least 128 bits of entropy
// before 96 other bytes are combined, when run forward or backward
// For every input bit,
// Two inputs differing in just that input bit
// Where "differ" means xor or subtraction
// And the base value is random
// When run forward or backwards one Mix
// I tried 3 pairs of each; they all differed by at least 212 bits.
//
static INLINE void Mix(
const uint64 *data,
uint64 &s0, uint64 &s1, uint64 &s2, uint64 &s3,
uint64 &s4, uint64 &s5, uint64 &s6, uint64 &s7,
uint64 &s8, uint64 &s9, uint64 &s10, uint64 &s11) {
s0 += data[0];
s2 ^= s10;
s11 ^= s0;
s0 = Rot64(s0, 11);
s11 += s1;
s1 += data[1];
s3 ^= s11;
s0 ^= s1;
s1 = Rot64(s1, 32);
s0 += s2;
s2 += data[2];
s4 ^= s0;
s1 ^= s2;
s2 = Rot64(s2, 43);
s1 += s3;
s3 += data[3];
s5 ^= s1;
s2 ^= s3;
s3 = Rot64(s3, 31);
s2 += s4;
s4 += data[4];
s6 ^= s2;
s3 ^= s4;
s4 = Rot64(s4, 17);
s3 += s5;
s5 += data[5];
s7 ^= s3;
s4 ^= s5;
s5 = Rot64(s5, 28);
s4 += s6;
s6 += data[6];
s8 ^= s4;
s5 ^= s6;
s6 = Rot64(s6, 39);
s5 += s7;
s7 += data[7];
s9 ^= s5;
s6 ^= s7;
s7 = Rot64(s7, 57);
s6 += s8;
s8 += data[8];
s10 ^= s6;
s7 ^= s8;
s8 = Rot64(s8, 55);
s7 += s9;
s9 += data[9];
s11 ^= s7;
s8 ^= s9;
s9 = Rot64(s9, 54);
s8 += s10;
s10 += data[10];
s0 ^= s8;
s9 ^= s10;
s10 = Rot64(s10, 22);
s9 += s11;
s11 += data[11];
s1 ^= s9;
s10 ^= s11;
s11 = Rot64(s11, 46);
s10 += s0;
}
//
// Mix all 12 inputs together so that h0, h1 are a hash of them all.
//
// For two inputs differing in just the input bits
// Where "differ" means xor or subtraction
// And the base value is random, or a counting value starting at that bit
// The final result will have each bit of h0, h1 flip
// For every input bit,
// with probability 50 +- .3%
// For every pair of input bits,
// with probability 50 +- 3%
//
// This does not rely on the last Mix() call having already mixed some.
// Two iterations was almost good enough for a 64-bit result, but a
// 128-bit result is reported, so End() does three iterations.
//
static INLINE void EndPartial(
uint64 &h0, uint64 &h1, uint64 &h2, uint64 &h3,
uint64 &h4, uint64 &h5, uint64 &h6, uint64 &h7,
uint64 &h8, uint64 &h9, uint64 &h10, uint64 &h11) {
h11 += h1;
h2 ^= h11;
h1 = Rot64(h1, 44);
h0 += h2;
h3 ^= h0;
h2 = Rot64(h2, 15);
h1 += h3;
h4 ^= h1;
h3 = Rot64(h3, 34);
h2 += h4;
h5 ^= h2;
h4 = Rot64(h4, 21);
h3 += h5;
h6 ^= h3;
h5 = Rot64(h5, 38);
h4 += h6;
h7 ^= h4;
h6 = Rot64(h6, 33);
h5 += h7;
h8 ^= h5;
h7 = Rot64(h7, 10);
h6 += h8;
h9 ^= h6;
h8 = Rot64(h8, 13);
h7 += h9;
h10 ^= h7;
h9 = Rot64(h9, 38);
h8 += h10;
h11 ^= h8;
h10 = Rot64(h10, 53);
h9 += h11;
h0 ^= h9;
h11 = Rot64(h11, 42);
h10 += h0;
h1 ^= h10;
h0 = Rot64(h0, 54);
}
static INLINE void End(
const uint64 *data,
uint64 &h0, uint64 &h1, uint64 &h2, uint64 &h3,
uint64 &h4, uint64 &h5, uint64 &h6, uint64 &h7,
uint64 &h8, uint64 &h9, uint64 &h10, uint64 &h11) {
h0 += data[0];
h1 += data[1];
h2 += data[2];
h3 += data[3];
h4 += data[4];
h5 += data[5];
h6 += data[6];
h7 += data[7];
h8 += data[8];
h9 += data[9];
h10 += data[10];
h11 += data[11];
EndPartial(h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
EndPartial(h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
EndPartial(h0, h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11);
}
//
// The goal is for each bit of the input to expand into 128 bits of
// apparent entropy before it is fully overwritten.
// n trials both set and cleared at least m bits of h0 h1 h2 h3
// n: 2 m: 29
// n: 3 m: 46
// n: 4 m: 57
// n: 5 m: 107
// n: 6 m: 146
// n: 7 m: 152
// when run forwards or backwards
// for all 1-bit and 2-bit diffs
// with diffs defined by either xor or subtraction
// with a base of all zeros plus a counter, or plus another bit, or random
//
static INLINE void ShortMix(uint64 &h0, uint64 &h1, uint64 &h2, uint64 &h3) {
h2 = Rot64(h2, 50);
h2 += h3;
h0 ^= h2;
h3 = Rot64(h3, 52);
h3 += h0;
h1 ^= h3;
h0 = Rot64(h0, 30);
h0 += h1;
h2 ^= h0;
h1 = Rot64(h1, 41);
h1 += h2;
h3 ^= h1;
h2 = Rot64(h2, 54);
h2 += h3;
h0 ^= h2;
h3 = Rot64(h3, 48);
h3 += h0;
h1 ^= h3;
h0 = Rot64(h0, 38);
h0 += h1;
h2 ^= h0;
h1 = Rot64(h1, 37);
h1 += h2;
h3 ^= h1;
h2 = Rot64(h2, 62);
h2 += h3;
h0 ^= h2;
h3 = Rot64(h3, 34);
h3 += h0;
h1 ^= h3;
h0 = Rot64(h0, 5);
h0 += h1;
h2 ^= h0;
h1 = Rot64(h1, 36);
h1 += h2;
h3 ^= h1;
}
//
// Mix all 4 inputs together so that h0, h1 are a hash of them all.
//
// For two inputs differing in just the input bits
// Where "differ" means xor or subtraction
// And the base value is random, or a counting value starting at that bit
// The final result will have each bit of h0, h1 flip
// For every input bit,
// with probability 50 +- .3% (it is probably better than that)
// For every pair of input bits,
// with probability 50 +- .75% (the worst case is approximately that)
//
static INLINE void ShortEnd(uint64 &h0, uint64 &h1, uint64 &h2, uint64 &h3) {
h3 ^= h2;
h2 = Rot64(h2, 15);
h3 += h2;
h0 ^= h3;
h3 = Rot64(h3, 52);
h0 += h3;
h1 ^= h0;
h0 = Rot64(h0, 26);
h1 += h0;
h2 ^= h1;
h1 = Rot64(h1, 51);
h2 += h1;
h3 ^= h2;
h2 = Rot64(h2, 28);
h3 += h2;
h0 ^= h3;
h3 = Rot64(h3, 9);
h0 += h3;
h1 ^= h0;
h0 = Rot64(h0, 47);
h1 += h0;
h2 ^= h1;
h1 = Rot64(h1, 54);
h2 += h1;
h3 ^= h2;
h2 = Rot64(h2, 32);
h3 += h2;
h0 ^= h3;
h3 = Rot64(h3, 25);
h0 += h3;
h1 ^= h0;
h0 = Rot64(h0, 63);
h1 += h0;
}
private:
//
// Short is used for messages under 192 bytes in length
// Short has a low startup cost, the normal mode is good for long
// keys, the cost crossover is at about 192 bytes. The two modes were
// held to the same quality bar.
//
static void Short(
const void *message, // message (array of bytes, not necessarily aligned)
size_t length, // length of message (in bytes)
uint64 *hash1, // in/out: in the seed, out the hash value
uint64 *hash2); // in/out: in the seed, out the hash value
// number of uint64's in internal state
static const size_t sc_numVars = 12;
// size of the internal state
static const size_t sc_blockSize = sc_numVars * 8;
// size of buffer of unhashed data, in bytes
static const size_t sc_bufSize = 2 * sc_blockSize;
//
// sc_const: a constant which:
// * is not zero
// * is odd
// * is a not-very-regular mix of 1's and 0's
// * does not need any other special mathematical properties
//
static const uint64 sc_const = 0xdeadbeefdeadbeefLL;
uint64 m_data[2 * sc_numVars]; // unhashed data, for partial messages
uint64 m_state[sc_numVars]; // internal state of the hash
size_t m_length; // total length of the input so far
uint8 m_remainder; // length of unhashed data stashed in m_data
};
| 12,673 |
C
| 29.539759 | 82 | 0.530103 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/v4-random-seeds.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
def main(revisions=None):
suite=suites.suite_optimal_strips()
suite.extend(suites.suite_ipc14_opt_strips())
# only DFP configs
configs = {
# label reduction with seed 2016
IssueConfig('dfp-b50k-lrs2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false,random_seed=2016)))']),
IssueConfig('dfp-ginf-lrs2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false,random_seed=2016)))']),
IssueConfig('dfp-f50k-lrs2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true,random_seed=2016)))']),
# shrink fh/rnd with seed 2016
IssueConfig('dfp-f50ks2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000,random_seed=2016),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
IssueConfig('dfp-rnd50ks2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_random(max_states=50000,random_seed=2016),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
# shrink fh/rnd with seed 2016 and with label reduction with seed 2016
IssueConfig('dfp-f50ks2016-lrs2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000,random_seed=2016),label_reduction=exact(before_shrinking=false,before_merging=true,random_seed=2016)))']),
IssueConfig('dfp-rnd50ks2016-lrs2016', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_random(max_states=50000,random_seed=2016),label_reduction=exact(before_shrinking=false,before_merging=true,random_seed=2016)))']),
}
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suite,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step()
exp()
main(revisions=['issue645-v4'])
| 4,037 |
Python
| 52.839999 | 271 | 0.711667 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
suite=suites.suite_optimal_strips()
suite.extend(suites.suite_ipc14_opt_strips())
configs = {
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
}
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suite,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
if matplotlib:
for attribute in ["memory", "total_time"]:
for config in configs:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
)
exp()
main(revisions=['issue645-v3', 'issue645-v4'])
| 5,128 |
Python
| 56.629213 | 280 | 0.695983 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, suite, revisions=[], configs={}, grid_priority=None,
path=None, test_suite=None, email=None, processes=None,
**kwargs):
"""
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
*configs* must be a non-empty list of IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(..., suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(..., suite=suites.suite_all())
IssueExperiment(..., suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(..., suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(..., grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(..., test_suite=["depot:pfile1", "tpp:p01.pddl"])
If *email* is specified, it should be an email address. This
email address will be notified upon completion of the experiments
if it is run on the cluster.
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment(processes=processes)
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(
priority=grid_priority, email=email)
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
repo = get_repo_base()
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
repo,
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self.add_suite(os.path.join(repo, "benchmarks"), suite)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(self.eval_dir,
get_experiment_name() + "." +
report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step('publish-absolute-report',
subprocess.call,
['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ "." + report.output_format)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ ".html")
subprocess.call(['publish', outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step("publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,481 |
Python
| 33.963585 | 83 | 0.594904 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/suites.py
|
# Benchmark suites from the Fast Downward benchmark collection.
def suite_alternative_formulations():
return ['airport-adl', 'no-mprime', 'no-mystery']
def suite_ipc98_to_ipc04_adl():
return [
'assembly', 'miconic-fulladl', 'miconic-simpleadl',
'optical-telegraphs', 'philosophers', 'psr-large',
'psr-middle', 'schedule',
]
def suite_ipc98_to_ipc04_strips():
return [
'airport', 'blocks', 'depot', 'driverlog', 'freecell', 'grid',
'gripper', 'logistics00', 'logistics98', 'miconic', 'movie',
'mprime', 'mystery', 'pipesworld-notankage', 'psr-small',
'satellite', 'zenotravel',
]
def suite_ipc98_to_ipc04():
# All IPC1-4 domains, including the trivial Movie.
return sorted(suite_ipc98_to_ipc04_adl() + suite_ipc98_to_ipc04_strips())
def suite_ipc06_adl():
return [
'openstacks',
'pathways',
'trucks',
]
def suite_ipc06_strips_compilations():
return [
'openstacks-strips',
'pathways-noneg',
'trucks-strips',
]
def suite_ipc06_strips():
return [
'pipesworld-tankage',
'rovers',
'storage',
'tpp',
]
def suite_ipc06():
return sorted(suite_ipc06_adl() + suite_ipc06_strips())
def suite_ipc08_common_strips():
return [
'parcprinter-08-strips',
'pegsol-08-strips',
'scanalyzer-08-strips',
]
def suite_ipc08_opt_adl():
return ['openstacks-opt08-adl']
def suite_ipc08_opt_strips():
return sorted(suite_ipc08_common_strips() + [
'elevators-opt08-strips',
'openstacks-opt08-strips',
'sokoban-opt08-strips',
'transport-opt08-strips',
'woodworking-opt08-strips',
])
def suite_ipc08_opt():
return sorted(suite_ipc08_opt_strips() + suite_ipc08_opt_adl())
def suite_ipc08_sat_adl():
return ['openstacks-sat08-adl']
def suite_ipc08_sat_strips():
return sorted(suite_ipc08_common_strips() + [
# Note: cyber-security is missing.
'elevators-sat08-strips',
'openstacks-sat08-strips',
'sokoban-sat08-strips',
'transport-sat08-strips',
'woodworking-sat08-strips',
])
def suite_ipc08_sat():
return sorted(suite_ipc08_sat_strips() + suite_ipc08_sat_adl())
def suite_ipc08():
return sorted(set(suite_ipc08_opt() + suite_ipc08_sat()))
def suite_ipc11_opt():
return [
'barman-opt11-strips',
'elevators-opt11-strips',
'floortile-opt11-strips',
'nomystery-opt11-strips',
'openstacks-opt11-strips',
'parcprinter-opt11-strips',
'parking-opt11-strips',
'pegsol-opt11-strips',
'scanalyzer-opt11-strips',
'sokoban-opt11-strips',
'tidybot-opt11-strips',
'transport-opt11-strips',
'visitall-opt11-strips',
'woodworking-opt11-strips',
]
def suite_ipc11_sat():
return [
'barman-sat11-strips',
'elevators-sat11-strips',
'floortile-sat11-strips',
'nomystery-sat11-strips',
'openstacks-sat11-strips',
'parcprinter-sat11-strips',
'parking-sat11-strips',
'pegsol-sat11-strips',
'scanalyzer-sat11-strips',
'sokoban-sat11-strips',
'tidybot-sat11-strips',
'transport-sat11-strips',
'visitall-sat11-strips',
'woodworking-sat11-strips',
]
def suite_ipc11():
return sorted(suite_ipc11_opt() + suite_ipc11_sat())
def suite_ipc14_agl_adl():
return [
'cavediving-agl14-adl',
'citycar-agl14-adl',
'maintenance-agl14-adl',
]
def suite_ipc14_agl_strips():
return [
'barman-agl14-strips',
'childsnack-agl14-strips',
'floortile-agl14-strips',
'ged-agl14-strips',
'hiking-agl14-strips',
'openstacks-agl14-strips',
'parking-agl14-strips',
'tetris-agl14-strips',
'thoughtful-agl14-strips',
'transport-agl14-strips',
'visitall-agl14-strips',
]
def suite_ipc14_agl():
return sorted(suite_ipc14_agl_adl() + suite_ipc14_agl_strips())
def suite_ipc14_mco_adl():
return [
'cavediving-mco14-adl',
'citycar-mco14-adl',
'maintenance-mco14-adl',
]
def suite_ipc14_mco_strips():
return [
'barman-mco14-strips',
'childsnack-mco14-strips',
'floortile-mco14-strips',
'ged-mco14-strips',
'hiking-mco14-strips',
'openstacks-mco14-strips',
'parking-mco14-strips',
'tetris-mco14-strips',
'thoughtful-mco14-strips',
'transport-mco14-strips',
'visitall-mco14-strips',
]
def suite_ipc14_mco():
return sorted(suite_ipc14_mco_adl() + suite_ipc14_mco_strips())
def suite_ipc14_opt_adl():
return [
'cavediving-opt14-adl',
'citycar-opt14-adl',
'maintenance-opt14-adl',
]
def suite_ipc14_opt_strips():
return [
'barman-opt14-strips',
'childsnack-opt14-strips',
'floortile-opt14-strips',
'ged-opt14-strips',
'hiking-opt14-strips',
'openstacks-opt14-strips',
'parking-opt14-strips',
'tetris-opt14-strips',
'tidybot-opt14-strips',
'transport-opt14-strips',
'visitall-opt14-strips',
]
def suite_ipc14_opt():
return sorted(suite_ipc14_opt_adl() + suite_ipc14_opt_strips())
def suite_ipc14_sat_adl():
return [
'cavediving-sat14-adl',
'citycar-sat14-adl',
'maintenance-sat14-adl',
]
def suite_ipc14_sat_strips():
return [
'barman-sat14-strips',
'childsnack-sat14-strips',
'floortile-sat14-strips',
'ged-sat14-strips',
'hiking-sat14-strips',
'openstacks-sat14-strips',
'parking-sat14-strips',
'tetris-sat14-strips',
'thoughtful-sat14-strips',
'transport-sat14-strips',
'visitall-sat14-strips',
]
def suite_ipc14_sat():
return sorted(suite_ipc14_sat_adl() + suite_ipc14_sat_strips())
def suite_ipc14():
return sorted(
suite_ipc14_agl() + suite_ipc14_mco() +
suite_ipc14_opt() + suite_ipc14_sat())
def suite_unsolvable():
# TODO: Add other unsolvable problems (Miconic-FullADL).
# TODO: Add 'fsc-grid-r:prize5x5_R.pddl' and 't0-uts:uts_r-02.pddl'
# if the extra-domains branch is merged.
return sorted(
['mystery:prob%02d.pddl' % index
for index in [4, 5, 7, 8, 12, 16, 18, 21, 22, 23, 24]] +
['miconic-fulladl:f21-3.pddl', 'miconic-fulladl:f30-2.pddl'])
def suite_optimal_adl():
return sorted(
suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() +
suite_ipc08_opt_adl())
def suite_optimal_strips():
return sorted(
suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() +
suite_ipc06_strips_compilations() + suite_ipc08_opt_strips() +
suite_ipc11_opt())
def suite_optimal():
return sorted(suite_optimal_adl() + suite_optimal_strips())
def suite_satisficing_adl():
return sorted(
suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() +
suite_ipc08_sat_adl())
def suite_satisficing_strips():
return sorted(
suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() +
suite_ipc06_strips_compilations() + suite_ipc08_sat_strips() +
suite_ipc11_sat())
def suite_satisficing():
return sorted(suite_satisficing_adl() + suite_satisficing_strips())
def suite_all():
return sorted(
suite_ipc98_to_ipc04() + suite_ipc06() +
suite_ipc06_strips_compilations() + suite_ipc08() +
suite_ipc11() + suite_alternative_formulations())
| 7,695 |
Python
| 23.35443 | 77 | 0.596231 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int)
parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[t=.+s\]', required=False, type=float)
def check_ms_constructed(content, props):
ms_construction_time = props.get('ms_construction_time')
abstraction_constructed = False
if ms_construction_time is not None:
abstraction_constructed = True
props['ms_abstraction_constructed'] = abstraction_constructed
parser.add_function(check_ms_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
def check_proved_unsolvability(content, props):
proved_unsolvability = False
if props['coverage'] == 0:
for line in content.splitlines():
if line == 'Completely explored state space -- no solution!':
proved_unsolvability = True
break
props['proved_unsolvability'] = proved_unsolvability
parser.add_function(check_proved_unsolvability)
def count_dfp_no_goal_relevant_ts(content, props):
counter = 0
for line in content.splitlines():
if line == 'found no goal relevant pair':
counter += 1
props['ms_dfp_nogoalrelevantpair_counter'] = counter
parser.add_function(count_dfp_no_goal_relevant_ts)
parser.parse()
| 3,074 |
Python
| 36.5 | 135 | 0.665582 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
suite=suites.suite_optimal_strips()
suite.extend(suites.suite_ipc14_opt_strips())
configs = {
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
}
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suite,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
for attribute in ["memory", "total_time"]:
for config in configs:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
)
exp()
main(revisions=['issue645-base', 'issue645-v1'])
| 4,932 |
Python
| 58.433734 | 280 | 0.701541 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 3,921 |
Python
| 35.654205 | 84 | 0.597042 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
#from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
suite=suites.suite_optimal_strips()
suite.extend(suites.suite_ipc14_opt_strips())
configs = {
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
}
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suite,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
ms_dfp_nogoalrelevantpair_counter = Attribute('ms_dfp_nogoalrelevantpair_counter', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
ms_dfp_nogoalrelevantpair_counter,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue645-v2', 'issue645-v3'])
| 3,499 |
Python
| 43.303797 | 246 | 0.671906 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue645/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
suite=suites.suite_optimal_strips()
suite.extend(suites.suite_ipc14_opt_strips())
configs = {
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']),
}
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suite,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
for attribute in ["memory", "total_time"]:
for config in configs:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
)
exp()
main(revisions=['issue645-v1', 'issue645-v2'])
| 3,328 |
Python
| 42.233766 | 246 | 0.669772 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue67/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
from relativescatter import RelativeScatterPlotReport
REVS = ["issue67-v4-base", "issue67-v4"]
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"astar_blind": [
"--search",
"astar(blind())"],
"astar_lmcut": [
"--search",
"astar(lmcut())"],
"astar_lm_zg": [
"--search",
"astar(lmcount(lm_zg(), admissible=true, optimal=true))"],
}
exp = common_setup.IssueExperiment(
search_revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_comparison_table_step()
exp.add_report(
RelativeScatterPlotReport(
attributes=["total_time"],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile='issue67-v4-total-time.png'
)
exp()
| 833 |
Python
| 19.85 | 66 | 0.613445 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue67/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-%s-compare.html" %
(self.name, rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in self.get_supported_attributes(
config_nick, attributes):
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,856 |
Python
| 34.913408 | 79 | 0.612943 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue67/issue67.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue67-v1-base", "issue67-v1"]
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"astar_blind": [
"--search",
"astar(blind())"],
"astar_lmcut": [
"--search",
"astar(lmcut())"],
"astar_lm_zg": [
"--search",
"astar(lmcount(lm_zg(), admissible=true, optimal=true))"],
}
exp = common_setup.IssueExperiment(
search_revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_comparison_table_step()
exp()
| 587 |
Python
| 17.967741 | 66 | 0.577513 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue67/relativescatter.py
|
# -*- coding: utf-8 -*-
#
# downward uses the lab package to conduct experiments with the
# Fast Downward planning system.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from collections import defaultdict
import os
from lab import tools
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 4,690 |
Python
| 35.937008 | 84 | 0.624947 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v1-lama.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("lama-no-syn-pref-{pref}".format(**locals()), [
"--if-unit-cost",
"--evaluator",
"hlm=lmcount(lm_rhw(reasonable_orders=true), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff=ff()",
"--search", """iterated([
lazy_greedy([hff,hlm],preferred=[hff,hlm]),
lazy_wastar([hff,hlm],preferred=[hff,hlm],w=5),
lazy_wastar([hff,hlm],preferred=[hff,hlm],w=3),
lazy_wastar([hff,hlm],preferred=[hff,hlm],w=2),
lazy_wastar([hff,hlm],preferred=[hff,hlm],w=1)
],repeat_last=true,continue_on_fail=true)""",
"--if-non-unit-cost",
"--evaluator",
"hlm1=lmcount(lm_rhw(reasonable_orders=true), transform=adapt_costs(one), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff1=ff(transform=adapt_costs(one))",
"--evaluator",
"hlm2=lmcount(lm_rhw(reasonable_orders=true), transform=adapt_costs(plusone), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff2=ff(transform=adapt_costs(plusone))",
"--search", """iterated([
lazy_greedy([hff1,hlm1],preferred=[hff1,hlm1],
cost_type=one,reopen_closed=false),
lazy_greedy([hff2,hlm2],preferred=[hff2,hlm2],
reopen_closed=false),
lazy_wastar([hff2,hlm2],preferred=[hff2,hlm2],w=5),
lazy_wastar([hff2,hlm2],preferred=[hff2,hlm2],w=3),
lazy_wastar([hff2,hlm2],preferred=[hff2,hlm2],w=2),
lazy_wastar([hff2,hlm2],preferred=[hff2,hlm2],w=1)
],repeat_last=true,continue_on_fail=true)""",
"--always"])
for pref in ["none", "simple", "all"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for rev in REVISIONS
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.ANYTIME_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step(filter_algorithm=["issue846-v1-lama-no-syn-pref-none", "issue846-v1-lama-no-syn-pref-simple", "issue846-v1-lama-no-syn-pref-all"])
#exp.add_comparison_table_step()
exp.run_steps()
| 3,606 |
Python
| 37.784946 | 159 | 0.610649 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v1-lama-first-ignore-pref.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("lama-first-pref-{pref}".format(**locals()), [
"--evaluator",
"hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true), transform=adapt_costs(one), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff=ff(transform=adapt_costs(one))",
"--search", "lazy_greedy([hff,hlm],preferred=[hff,hlm],"
"cost_type=one,reopen_closed=false)"])
for pref in ["none", "simple"]
] + [
("lama-first-pref-{pref}-ignore".format(**locals()), [
"--evaluator",
"hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true), transform=adapt_costs(one), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff=ff(transform=adapt_costs(one))",
"--search", "lazy_greedy([hff,hlm],preferred=[hff],"
"cost_type=one,reopen_closed=false)"])
for pref in ["simple"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for rev in REVISIONS
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
#exp.add_comparison_table_step()
exp.run_steps()
| 2,448 |
Python
| 30.805194 | 140 | 0.671977 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v2-lama-first.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-base", "issue846-v2"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("lama-first-pref-{pref}".format(**locals()), [
"--evaluator",
"hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true), transform=adapt_costs(one), pref={pref})".format(**locals()),
"--evaluator", "hff=ff(transform=adapt_costs(one))",
"--search", "lazy_greedy([hff,hlm],preferred=[hff,hlm],"
"cost_type=one,reopen_closed=false)"])
for pref in ["true", "false"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
exp.run_steps()
| 1,943 |
Python
| 28.014925 | 125 | 0.691714 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v1-lama-first.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("lama-first-pref-{pref}".format(**locals()), [
"--evaluator",
"hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true), transform=adapt_costs(one), preferred_operators={pref})".format(**locals()),
"--evaluator", "hff=ff(transform=adapt_costs(one))",
"--search", "lazy_greedy([hff,hlm],preferred=[hff,hlm],"
"cost_type=one,reopen_closed=false)"])
for pref in ["none", "simple", "all"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for rev in REVISIONS
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step(filter_algorithm=["issue846-v1-lama-first-pref-none", "issue846-v1-lama-first-pref-simple", "issue846-v1-lama-first-pref-all"])
#exp.add_comparison_table_step()
exp.run_steps()
| 2,132 |
Python
| 29.913043 | 156 | 0.697936 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,786 |
Python
| 36.435443 | 82 | 0.618355 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v1-lama-first-no-ff.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("{index}-lama-first-no-ff-pref-{pref}".format(**locals()), [
"--evaluator",
"hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true), transform=adapt_costs(one), preferred_operators={pref})".format(**locals()),
"--search", "lazy_greedy([hlm],preferred=[hlm],"
"cost_type=one,reopen_closed=false)"])
for index, pref in enumerate(["none", "simple", "all"])
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for rev in REVISIONS
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
#exp.add_comparison_table_step()
exp.run_steps()
| 1,969 |
Python
| 27.970588 | 140 | 0.6968 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v1-bjolp.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("bjolp-pref-{pref}".format(**locals()), [
"--evaluator",
"lmc=lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]),admissible=true, preferred_operators={pref})".format(**locals()),
"--search",
"astar(lmc,lazy_evaluator=lmc)"])
for pref in ["none", "simple"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for rev in REVISIONS
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
#exp.add_comparison_table_step()
exp.run_steps()
| 1,834 |
Python
| 25.985294 | 119 | 0.7012 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue846/v2-bjolp.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue846-base", "issue846-v2"]
BUILDS = ["release32"]
CONFIG_NICKS = [
("bjolp-pref-{pref}".format(**locals()), [
"--evaluator",
"lmc=lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]),admissible=true, pref={pref})".format(**locals()),
"--search",
"astar(lmc,lazy_evaluator=lmc)"])
for pref in ["false"]
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.run_steps()
| 1,802 |
Python
| 25.910447 | 104 | 0.700333 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/version1_v3-version2_v3-base.py
|
#! /usr/bin/env python3
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.environments import FreiburgSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = "/home/drexlerd/benchmarks/downward-benchmarks"
REVISIONS = ["issue348-base", "issue348-version1-v3", "issue348-version2-v3"]
CONFIGS = [
IssueConfig("lama", [], driver_options=["--alias", "lama-first"]),
IssueConfig("ehc-ff", ["--search", "ehc(ff())"]),
IssueConfig("ipdb", ["--search", "astar(ipdb())"]),
#IssueConfig("lmcut", ["--search", "astar(lmcut())"]),
IssueConfig("blind", ["--search", "astar(blind())"]),
#IssueConfig("lazy", [
# "--evaluator",
# "hff=ff()",
# "--evaluator",
# "hcea=cea()",
# "--search",
# "lazy_greedy([hff, hcea], preferred=[hff, hcea])"]),
]
ADL_DOMAINS = [
"assembly",
"miconic-fulladl",
"openstacks",
"openstacks-opt08-adl",
"optical-telegraphs",
"philosophers",
"psr-large",
"psr-middle",
"trucks",
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE + ADL_DOMAINS
#ENVIRONMENT = BaselSlurmEnvironment(
# partition="infai_2",
# email="[email protected]",
# export=["PATH", "DOWNWARD_BENCHMARKS"])
ENVIRONMENT = FreiburgSlurmEnvironment()
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=3)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time", "memory"])
exp.run_steps()
| 2,123 |
Python
| 27.32 | 77 | 0.695714 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".git" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".git")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
#self.add_step(
# 'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
#self.add_step(
# "publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None, additional=[]):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute, config_nick2=None):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
if config_nick2 is not None:
name += "-" + config_nick2
print("Make scatter plot for", name)
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick if config_nick2 is None else config_nick2)
report = ScatterPlotReport(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
relative=relative,
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
for nick1, nick2, rev1, rev2, attribute in additional:
make_scatter_plot(nick1, rev1, rev2, attribute, config_nick2=nick2)
self.add_step(step_name, make_scatter_plots)
| 14,948 |
Python
| 36.84557 | 94 | 0.618076 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/version1_v2-version2_v2-base.py
|
#! /usr/bin/env python3
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.environments import FreiburgSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = "/home/drexlerd/benchmarks/downward-benchmarks"
REVISIONS = ["issue348-base", "issue348-version1-v2", "issue348-version2-v2"]
CONFIGS = [
IssueConfig("lama", [], driver_options=["--alias", "lama-first"]),
IssueConfig("ehc-ff", ["--search", "ehc(ff())"]),
#IssueConfig("ipdb", ["--search", "astar(ipdb())"]),
#IssueConfig("lmcut", ["--search", "astar(lmcut())"]),
IssueConfig("blind", ["--search", "astar(blind())"]),
IssueConfig("lazy", [
"--evaluator",
"hff=ff()",
"--evaluator",
"hcea=cea()",
"--search",
"lazy_greedy([hff, hcea], preferred=[hff, hcea])"]),
]
ADL_DOMAINS = [
"assembly",
"miconic-fulladl",
"openstacks",
"openstacks-opt08-adl",
"optical-telegraphs",
"philosophers",
"psr-large",
"psr-middle",
"trucks",
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE + ADL_DOMAINS
#ENVIRONMENT = BaselSlurmEnvironment(
# partition="infai_2",
# email="[email protected]",
# export=["PATH", "DOWNWARD_BENCHMARKS"])
ENVIRONMENT = FreiburgSlurmEnvironment()
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=3)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time", "memory"])
exp.run_steps()
| 2,117 |
Python
| 27.24 | 77 | 0.697685 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/v24.py
|
#! /usr/bin/env python3
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
#from lab.environments import FreiburgSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue348-base", "issue348-version2-v3", "issue348-v24"]
CONFIGS = [
IssueConfig("lama", [], driver_options=["--alias", "lama-first"]),
IssueConfig("ehc-ff", ["--search", "ehc(ff())"]),
IssueConfig("ipdb", ["--search", "astar(ipdb())"]),
IssueConfig("lmcut", ["--search", "astar(lmcut())"]),
IssueConfig("blind", ["--search", "astar(blind())"]),
IssueConfig("lazy", [
"--evaluator",
"hff=ff()",
"--evaluator",
"hcea=cea()",
"--search",
"lazy_greedy([hff, hcea], preferred=[hff, hcea])"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
#ENVIRONMENT = FreiburgSlurmEnvironment()
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=3)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time", "memory"])
exp.run_steps()
| 1,884 |
Python
| 28.453125 | 77 | 0.708599 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/v14-blind.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue348-v13", "issue348-v14"]
CONFIGS = [
IssueConfig("blind", ["--search", "astar(blind())"]),
]
ADL_DOMAINS = [
"assembly",
"miconic-fulladl",
"openstacks",
"openstacks-opt08-adl",
"optical-telegraphs",
"philosophers",
"psr-large",
"psr-middle",
"trucks",
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE + ADL_DOMAINS
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE + ["openstacks-opt08-adl:p01.pddl"]
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time"], suffix="-strips", filter_domain=common_setup.DEFAULT_OPTIMAL_SUITE)
exp.add_scatter_plot_step(relative=True, attributes=["total_time"], suffix="-adl", filter_domain=ADL_DOMAINS)
exp.run_steps()
| 1,853 |
Python
| 27.523076 | 135 | 0.727469 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue348/v19-blind.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue348-base", "issue348-v19"]
CONFIGS = [
IssueConfig("blind", ["--search", "astar(blind())"]),
]
ADL_DOMAINS = [
"assembly",
"miconic-fulladl",
"openstacks",
"openstacks-opt08-adl",
"optical-telegraphs",
"philosophers",
"psr-large",
"psr-middle",
"trucks",
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE + ADL_DOMAINS
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE + ["openstacks-opt08-adl:p01.pddl"]
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time"], suffix="-strips", filter_domain=common_setup.DEFAULT_OPTIMAL_SUITE)
exp.add_scatter_plot_step(relative=True, attributes=["total_time"], suffix="-adl", filter_domain=ADL_DOMAINS)
exp.run_steps()
| 1,854 |
Python
| 27.538461 | 135 | 0.727616 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue722/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if matplotlib:
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,453 |
Python
| 35.872449 | 81 | 0.609562 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue722/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int)
parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[t=.+s\]', required=False, type=float)
def check_ms_constructed(content, props):
ms_construction_time = props.get('ms_construction_time')
abstraction_constructed = False
if ms_construction_time is not None:
abstraction_constructed = True
props['ms_abstraction_constructed'] = abstraction_constructed
parser.add_function(check_ms_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
def check_proved_unsolvability(content, props):
proved_unsolvability = False
if props['coverage'] == 0:
for line in content.splitlines():
if line == 'Completely explored state space -- no solution!':
proved_unsolvability = True
break
props['proved_unsolvability'] = proved_unsolvability
parser.add_function(check_proved_unsolvability)
parser.parse()
| 2,784 |
Python
| 37.150684 | 135 | 0.665589 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue722/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.reports import Attribute, geometric_mean
from lab.environments import LocalEnvironment, MaiaEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment, get_algo_nick, get_repo_base
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue722-base", "issue722-v1"]
CONFIGS = [
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('sccs-dfp-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
#IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
#IssueConfig('sccs-dfp-ginf', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
#IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
#IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
#IssueConfig('sccs-dfp-f50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000))']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
exp.add_scatter_plot_step()
exp.run_steps()
| 5,364 |
Python
| 68.675324 | 465 | 0.772185 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue722/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue560/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-%s-compare.html" %
(self.name, rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in self.get_supported_attributes(
config_nick, attributes):
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,856 |
Python
| 34.913408 | 79 | 0.612943 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue560/issue560.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from relativescatter import RelativeScatterPlotReport
import common_setup
REVS = ["issue560-base", "issue560-v1"]
SUITE = suites.suite_all()
# We are only interested in the preprocessing here and will only run the first steps of the experiment.
CONFIGS = {
"astar_blind": [
"--search",
"astar(blind())"],
}
exp = common_setup.IssueExperiment(
search_revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_report(
RelativeScatterPlotReport(
attributes=["preprocess_wall_clock_time"],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile='issue560_base_v1_preprocess_wall_clock_time.png'
)
exp.add_absolute_report_step(attributes=["preprocess_wall_clock_time"])
exp()
| 824 |
Python
| 21.916666 | 103 | 0.684466 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue560/relativescatter.py
|
# -*- coding: utf-8 -*-
#
# downward uses the lab package to conduct experiments with the
# Fast Downward planning system.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from collections import defaultdict
import os
from lab import tools
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 4,690 |
Python
| 35.937008 | 84 | 0.624947 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/state_size_parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
def calculate_old_state_size(content, props):
if 'bytes_per_state' not in props and 'preprocessor_variables' in props and 'state_var_t_size' in props:
props['bytes_per_state'] = props['preprocessor_variables'] * props['state_var_t_size']
class StateSizeParser(Parser):
def __init__(self):
Parser.__init__(self)
self.add_pattern('bytes_per_state', 'Bytes per state: (\d+)',
required=False, type=int)
self.add_pattern('state_var_t_size', 'Dispatcher selected state size (\d).',
required=False, type=int)
self.add_pattern('variables', 'Variables: (\d+)',
required=False, type=int)
self.add_function(calculate_old_state_size)
if __name__ == '__main__':
parser = StateSizeParser()
print 'Running state size parser'
parser.parse()
| 923 |
Python
| 37.499998 | 109 | 0.608884 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214-v4-ipdb.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v4"]
CONFIGS = {"ipdb": ["--search", "astar(ipdb())"]}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_optimal_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 865 |
Python
| 22.405405 | 120 | 0.695954 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/common_setup.py
|
# -*- coding: utf-8 -*-
import os.path
from lab.environments import MaiaEnvironment
from lab.steps import Step
from downward.checkouts import Translator, Preprocessor, Planner
from downward.experiments import DownwardExperiment
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the filename of the main script, e.g.
"/ham/spam/eggs.py" => "eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Found by searching upwards in the directory tree from the main
script until a directory with a subdirectory named ".hg" is found."""
path = os.path.abspath(get_script_dir())
while True:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
class MyExperiment(DownwardExperiment):
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"total_time",
"search_time",
"memory",
"expansions_until_last_jump",
]
"""Wrapper for DownwardExperiment with a few convenience features."""
def __init__(self, configs=None, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
suite=None, parsers=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
If "configs" is specified, it should be a dict of {nick:
cmdline} pairs that sets the planner configurations to test.
If "grid_priority" is specified and no environment is
specifically requested in **kwargs, use the maia environment
with the specified priority.
If "path" is not specified, the experiment data path is
derived automatically from the main script's filename.
If "repo" is not specified, the repository base is derived
automatically from the main script's path.
If "revisions" is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search.
If "search_revisions" is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All experiments use the
translator and preprocessor component of the first
revision.
If "suite" is specified, it should specify a problem suite.
If "parsers" is specified, it should be a list of paths to
parsers that should be run in addition to search_parser.py.
Options "combinations" (from the base class), "revisions" and
"search_revisions" are mutually exclusive."""
if grid_priority is not None and "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
num_rev_opts_specified = (
int(revisions is not None) +
int(search_revisions is not None) +
int(kwargs.get("combinations") is not None))
if num_rev_opts_specified > 1:
raise ValueError('must specify exactly one of "revisions", '
'"search_revisions" or "combinations"')
# See add_comparison_table_step for more on this variable.
self._HACK_revisions = revisions
if revisions is not None:
if not revisions:
raise ValueError("revisions cannot be empty")
combinations = [(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions]
kwargs["combinations"] = combinations
if search_revisions is not None:
if not search_revisions:
raise ValueError("search_revisions cannot be empty")
base_rev = search_revisions[0]
translator = Translator(repo, base_rev)
preprocessor = Preprocessor(repo, base_rev)
combinations = [(translator, preprocessor, Planner(repo, rev))
for rev in search_revisions]
kwargs["combinations"] = combinations
self._additional_parsers = parsers or []
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
if configs is not None:
for nick, config in configs.items():
self.add_config(nick, config)
if suite is not None:
self.add_suite(suite)
self._report_prefix = get_experiment_name()
def _make_search_runs(self):
DownwardExperiment._make_search_runs(self)
for i, parser in enumerate(self._additional_parsers):
parser_alias = 'ADDITIONALPARSER%d' % i
self.add_resource(parser_alias, parser, os.path.basename(parser))
for run in self.runs:
run.require_resource(parser_alias)
run.add_command('additional-parser-%d' % i, [parser_alias])
def add_comparison_table_step(self, attributes=None):
revisions = self._HACK_revisions
if revisions is None:
# TODO: It's not clear to me what a "revision" in the
# overall context of the code really is, e.g. when keeping
# the translator and preprocessor method fixed and only
# changing the search component. It's also not really
# clear to me how the interface of the Compare... reports
# works and how to use it more generally. Hence the
# present hack.
# Ideally, this method should look at the table columns we
# have (defined by planners and planner configurations),
# pair them up in a suitable way, either controlled by a
# convenience parameter or a more general grouping method,
# and then use this to define which pairs go together.
raise NotImplementedError(
"only supported when specifying revisions in __init__")
if attributes is None:
attributes = self.DEFAULT_TABLE_ATTRIBUTES
report = CompareRevisionsReport(*revisions, attributes=attributes)
self.add_report(report, outfile="%s-compare.html" % self._report_prefix)
def add_scatter_plot_step(self, attributes=None):
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
revisions = self._HACK_revisions
if revisions is None:
# TODO: See add_comparison_table_step.
raise NotImplementedError(
"only supported when specifying revisions in __init__")
if len(revisions) != 2:
# TODO: Should generalize this, too, by offering a general
# grouping function and then comparing any pair of
# settings in the same group.
raise NotImplementedError("need two revisions")
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plots():
configs = [conf[0] for conf in self.configs]
for nick in configs:
config_before = "%s-%s" % (revisions[0], nick)
config_after = "%s-%s" % (revisions[1], nick)
for attribute in attributes:
name = "%s-%s-%s" % (self._report_prefix, attribute, nick)
report = ScatterPlotReport(
filter_config=[config_before, config_after],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 9,190 |
Python
| 37.456067 | 80 | 0.611099 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v2"]
CONFIGS = default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['astar_selmax_lmcut_lmcount']
TEST_RUN = True
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_optimal_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp.add_scatter_plot_step()
exp.add_report(ScatterPlotReport(
attributes=['bytes_per_state'],
filter_config_nick='astar_blind',
),
outfile='issue214_bytes_per_state.png')
for config_nick in ['astar_blind', 'astar_lmcut', 'astar_merge_and_shrink_bisim', 'astar_ipdb']:
for attr in ['memory', 'total_time']:
exp.add_report(ScatterPlotReport(
attributes=[attr],
filter_config_nick=config_nick,
),
outfile='issue214_%s_%s.png' % (attr, config_nick))
exp()
| 1,483 |
Python
| 25.035087 | 120 | 0.673635 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_satisficing_with_ipc11
from downward.configs import default_configs_satisficing
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v2"]
CONFIGS = default_configs_satisficing()
TEST_RUN = True
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_satisficing_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp.add_scatter_plot_step()
exp.add_report(ScatterPlotReport(
attributes=['bytes_per_state'],
filter_config_nick='astar_blind',
),
outfile='issue214_sat_bytes_per_state.png')
for config_nick in ['lazy_greedy_ff', 'eager_greedy_cg', 'seq_sat_lama_2011']:
for attr in ['memory', 'total_time']:
exp.add_report(ScatterPlotReport(
attributes=[attr],
filter_config_nick=config_nick,
),
outfile='issue214_sat_%s_%s.png' % (attr, config_nick))
exp()
| 1,398 |
Python
| 24.907407 | 120 | 0.669528 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214-v5-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v5"]
CONFIGS = {"blind": ["--search", "astar(blind())"]}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = list(sorted(set(suites.suite_all()) - set(suites.suite_optimal_with_ipc11())))
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 894 |
Python
| 23.189189 | 120 | 0.692394 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214-v3-ipdb.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v3"]
CONFIGS = {"ipdb": ["--search", "astar(ipdb())"]}
TEST_RUN = True
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_optimal_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 864 |
Python
| 22.378378 | 120 | 0.695602 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue214/issue214-v5.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v5"]
CONFIGS = {"blind": ["--search", "astar(blind())"]}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_optimal_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 867 |
Python
| 22.459459 | 120 | 0.696655 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_running_on_cluster_login_node():
return platform.node() == "login20.cluster.bc2.ch"
def can_publish():
return is_running_on_cluster_login_node() or not is_running_on_cluster()
def publish(report_file):
if can_publish():
subprocess.call(["publish", report_file])
else:
print "publishing reports is not supported on this node"
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, name="make-absolute-report", outfile=outfile)
self.add_step("publish-absolute-report", publish, outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def get_revision_pairs_and_files():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
yield (rev1, rev2, outfile)
def make_comparison_tables():
for rev1, rev2, outfile in get_revision_pairs_and_files():
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for _, _, outfile in get_revision_pairs_and_files():
publish(outfile)
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step("publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,462 |
Python
| 35.24812 | 79 | 0.618725 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/v4-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-base", "issue731-v4"]
BUILDS = ["release32"]
SEARCHES = [
("blind", "astar(blind())"),
("divpot", "astar(diverse_potentials())"),
("cegar", "astar(cegar())"),
("systematic2", "astar(cpdbs(systematic(2)))"),
("ipdb", "astar(ipdb())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,264 |
Python
| 24.816326 | 68 | 0.674051 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/v5-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-v5-base", "issue731-v5"]
BUILDS = ["release32", "release64"]
SEARCHES = [
("blind", "astar(blind())"),
("systematic2", "astar(cpdbs(systematic(2)))"),
("ipdb", "astar(ipdb())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
# Compare builds.
for build1, build2 in itertools.combinations(BUILDS, 2):
for rev in REVISIONS:
algorithm_pairs = [
("{rev}-{config_nick}-{build1}".format(**locals()),
"{rev}-{config_nick}-{build2}".format(**locals()),
"Diff ({config_nick}-{rev})".format(**locals()))
for config_nick, search in SEARCHES]
exp.add_report(
ComparativeReport(
algorithm_pairs,
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES),
name="issue731-{build1}-vs-{build2}-{rev}".format(**locals()))
exp.run_steps()
| 1,863 |
Python
| 28.125 | 74 | 0.652174 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/v4-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-base", "issue731-v4"]
BUILDS = ["release32"]
SEARCHES = [
("ff_lazy", ["--heuristic", "h=ff()", "--search", "lazy_greedy([h], preferred=[h])"]),
("cea_lazy", ["--heuristic", "h=cea()", "--search", "lazy_greedy([h], preferred=[h])"]),
("type_based", ["--heuristic", "h=ff()", "--search", "eager(alt([type_based([h, g()])]))"]),
("zhu_givan", [
"--heuristic", "hlm=lmcount(lm_zg())",
"--search", """lazy_greedy([hlm], preferred=[hlm])"""]),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
search,
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
] + [
IssueConfig(
"lama-first-{build}".format(**locals()),
[],
build_options=[build],
driver_options=["--build", build, "--alias", "lama-first"])
for build in BUILDS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,678 |
Python
| 28.45614 | 96 | 0.628129 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/hash-microbenchmark/main.cc
|
#include <algorithm>
#include <ctime>
#include <functional>
#include <iostream>
#include <string>
#include <unordered_set>
#include "hash.h"
using namespace std;
static void benchmark(const string &desc, int num_calls,
const function<void()> &func) {
cout << "Running " << desc << " " << num_calls << " times:" << flush;
clock_t start = clock();
for (int j = 0; j < num_calls; ++j)
func();
clock_t end = clock();
double duration = static_cast<double>(end - start) / CLOCKS_PER_SEC;
cout << " " << duration << "s" << endl;
}
static int scramble(int i) {
return (0xdeadbeef * i) ^ 0xfeedcafe;
}
int main(int, char **) {
const int REPETITIONS = 2;
const int NUM_CALLS = 1;
const int NUM_INSERTIONS = 10000000;
const int NUM_READ_PASSES = 10;
for (int i = 0; i < REPETITIONS; ++i) {
benchmark("nothing", NUM_CALLS, [] () {});
cout << endl;
benchmark("insert sequential int with BoostHash", NUM_CALLS,
[&]() {
unordered_set<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(i);
}
});
benchmark("insert sequential int with BurtleFeed", NUM_CALLS,
[&]() {
utils::HashSet<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(i);
}
});
cout << endl;
benchmark("insert scrambled int with BoostHash", NUM_CALLS,
[&]() {
unordered_set<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(scramble(i));
}
});
benchmark("insert scrambled int with BurtleFeed", NUM_CALLS,
[&]() {
utils::HashSet<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(scramble(i));
}
});
cout << endl;
benchmark("insert, then read sequential int with BoostHash", NUM_CALLS,
[&]() {
unordered_set<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(i);
}
for (int j = 0; j < NUM_READ_PASSES; ++j) {
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.count(i);
}
}
});
benchmark("insert, then read sequential int with BurtleFeed", NUM_CALLS,
[&]() {
utils::HashSet<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(i);
}
for (int j = 0; j < NUM_READ_PASSES; ++j) {
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.count(i);
}
}
});
cout << endl;
benchmark("insert, then read scrambled int with BoostHash", NUM_CALLS,
[&]() {
unordered_set<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(scramble(i));
}
for (int j = 0; j < NUM_READ_PASSES; ++j) {
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.count(i);
}
}
});
benchmark("insert, then read scrambled int with BurtleFeed", NUM_CALLS,
[&]() {
utils::HashSet<int> s;
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.insert(scramble(i));
}
for (int j = 0; j < NUM_READ_PASSES; ++j) {
for (int i = 0; i < NUM_INSERTIONS; ++i) {
s.count(i);
}
}
});
cout << endl;
}
return 0;
}
| 4,371 |
C++
| 33.15625 | 80 | 0.371997 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue731/hash-microbenchmark/hash.h
|
#ifndef UTILS_HASH_H
#define UTILS_HASH_H
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
namespace utils {
/*
We provide a family of hash functions that are supposedly higher
quality than what is guaranteed by the standard library. Changing a
single bit in the input should typically change around half of the
bits in the final hash value. The hash functions we previously used
turned out to cluster when we tried hash tables with open addressing
for state registries.
The low-level hash functions are based on lookup3.c by Bob Jenkins,
May 2006, public domain. See http://www.burtleburtle.net/bob/c/lookup3.c.
To hash an object x, it is represented as a sequence of 32-bit
pieces (called the "code" for x, written code(x) in the following)
that are "fed" to the main hashing function (implemented in class
HashState) one by one. This allows a compositional approach to
hashing. For example, the code for a pair p is the concatenation of
code(x.first) and code(x.second).
A simpler compositional approach to hashing would first hash the
components of an object and then combine the hash values, and this
is what a previous version of our code did. The approach with an
explicit HashState object is stronger because the internal hash
state is larger (96 bits) than the final hash value and hence pairs
<x, y> and <x', y> where x and x' have the same hash value don't
necessarily collide. Another advantage of our approach is that we
can use the same overall hashing approach to generate hash values of
different types (e.g. 32-bit vs. 64-bit unsigned integers).
To extend the hashing mechanism to further classes, provide a
template specialization for the "feed" function. This must satisfy
the following requirements:
A) If x and y are objects of the same type, they should have code(x)
= code(y) iff x = y. That is, the code sequence should uniquely
describe each logically distinct object.
This requirement avoids unnecessary hash collisions. Of course,
there will still be "necessary" hash collisions because different
code sequences can collide in the low-level hash function.
B) To play nicely with composition, we additionally require that feed
implements a prefix code, i.e., for objects x != y of the same
type, code(x) must not be a prefix of code(y).
This requirement makes it much easier to define non-colliding
code sequences for composite objects such as pairs via
concatenation: if <a, b> != <a', b'>, then code(a) != code(a')
and code(b) != code(b') is *not* sufficient for concat(code(a),
code(b)) != concat(code(a'), code(b')). However, if we require a
prefix code, it *is* sufficient and the resulting code will again
be a prefix code.
Note that objects "of the same type" is meant as "logical type"
rather than C++ type.
For example, for objects such as vectors where we expect
different-length vectors to be combined in the same containers (=
have the same logical type), we include the length of the vector as
the first element in the code to ensure the prefix code property.
In contrast, for integer arrays encoding states, we *do not* include
the length as a prefix because states of different sizes are
considered to be different logical types and should not be mixed in
the same container, even though they are represented by the same C++
type.
*/
/*
Circular rotation (http://stackoverflow.com/a/31488147/224132).
*/
inline uint32_t rotate(uint32_t value, uint32_t offset) {
return (value << offset) | (value >> (32 - offset));
}
/*
Store the state of the hashing process.
This class can either be used by specializing the template function
utils::feed() (recommended, see below), or by working with it directly.
*/
class HashState {
std::uint32_t a, b, c;
int pending_values;
/*
Mix the three 32-bit values bijectively.
Any information in (a, b, c) before mix() is still in (a, b, c) after
mix().
*/
void mix() {
a -= c;
a ^= rotate(c, 4);
c += b;
b -= a;
b ^= rotate(a, 6);
a += c;
c -= b;
c ^= rotate(b, 8);
b += a;
a -= c;
a ^= rotate(c, 16);
c += b;
b -= a;
b ^= rotate(a, 19);
a += c;
c -= b;
c ^= rotate(b, 4);
b += a;
}
/*
Final mixing of the three 32-bit values (a, b, c) into c.
Triples of (a, b, c) differing in only a few bits will usually produce
values of c that look totally different.
*/
void final_mix() {
c ^= b;
c -= rotate(b, 14);
a ^= c;
a -= rotate(c, 11);
b ^= a;
b -= rotate(a, 25);
c ^= b;
c -= rotate(b, 16);
a ^= c;
a -= rotate(c, 4);
b ^= a;
b -= rotate(a, 14);
c ^= b;
c -= rotate(b, 24);
}
public:
HashState()
: a(0xdeadbeef),
b(a),
c(a),
pending_values(0) {
}
void feed(std::uint32_t value) {
assert(pending_values != -1);
if (pending_values == 3) {
mix();
pending_values = 0;
}
if (pending_values == 0) {
a += value;
++pending_values;
} else if (pending_values == 1) {
b += value;
++pending_values;
} else if (pending_values == 2) {
c += value;
++pending_values;
}
}
/*
After calling this method, it is illegal to use the HashState object
further, i.e., make further calls to feed, get_hash32 or get_hash64. We
set pending_values = -1 to catch such illegal usage in debug mode.
*/
std::uint32_t get_hash32() {
assert(pending_values != -1);
if (pending_values) {
/*
pending_values == 0 can only hold if we never called
feed(), i.e., if we are hashing an empty sequence.
In this case we don't call final_mix for compatibility
with the original hash function by Jenkins.
*/
final_mix();
}
pending_values = -1;
return c;
}
/*
See comment for get_hash32.
*/
std::uint64_t get_hash64() {
assert(pending_values != -1);
if (pending_values) {
// See comment for get_hash32.
final_mix();
}
pending_values = -1;
return (static_cast<std::uint64_t>(b) << 32) | c;
}
};
/*
These functions add a new object to an existing HashState object.
To add hashing support for a user type X, provide an override
for utils::feed(HashState &hash_state, const X &value).
*/
static_assert(
sizeof(int) == sizeof(std::uint32_t),
"int and uint32_t have different sizes");
inline void feed(HashState &hash_state, int value) {
hash_state.feed(static_cast<std::uint32_t>(value));
}
static_assert(
sizeof(unsigned int) == sizeof(std::uint32_t),
"unsigned int and uint32_t have different sizes");
inline void feed(HashState &hash_state, unsigned int value) {
hash_state.feed(static_cast<std::uint32_t>(value));
}
inline void feed(HashState &hash_state, std::uint64_t value) {
hash_state.feed(static_cast<std::uint32_t>(value));
value >>= 32;
hash_state.feed(static_cast<std::uint32_t>(value));
}
template<typename T>
void feed(HashState &hash_state, const T *p) {
// This is wasteful in 32-bit mode, but we plan to discontinue 32-bit compiles anyway.
feed(hash_state, reinterpret_cast<std::uint64_t>(p));
}
template<typename T1, typename T2>
void feed(HashState &hash_state, const std::pair<T1, T2> &p) {
feed(hash_state, p.first);
feed(hash_state, p.second);
}
template<typename T>
void feed(HashState &hash_state, const std::vector<T> &vec) {
/*
Feed vector size to ensure that no two different vectors of the same type
have the same code prefix.
*/
feed(hash_state, vec.size());
for (const T &item : vec) {
feed(hash_state, item);
}
}
/*
Public hash functions.
get_hash() is used internally by the HashMap and HashSet classes below. In
more exotic use cases, such as implementing a custom hash table, you can also
use `get_hash32()`, `get_hash64()` and `get_hash()` directly.
*/
template<typename T>
std::uint32_t get_hash32(const T &value) {
HashState hash_state;
feed(hash_state, value);
return hash_state.get_hash32();
}
template<typename T>
std::uint64_t get_hash64(const T &value) {
HashState hash_state;
feed(hash_state, value);
return hash_state.get_hash64();
}
template<typename T>
std::size_t get_hash(const T &value) {
return static_cast<std::size_t>(get_hash64(value));
}
// This struct should only be used by HashMap and HashSet below.
template<typename T>
struct Hash {
std::size_t operator()(const T &val) const {
return get_hash(val);
}
};
/*
Aliases for hash sets and hash maps in user code.
Use these aliases for hashing types T that don't have a standard std::hash<T>
specialization.
To hash types that are not supported out of the box, implement utils::feed.
*/
template<typename T1, typename T2>
using HashMap = std::unordered_map<T1, T2, Hash<T1>>;
template<typename T>
using HashSet = std::unordered_set<T, Hash<T>>;
/*
Legacy hash functions.
We plan to remove these legacy hash functions since implementing std::hash<T>
for non-user-defined types T causes undefined behaviour
(http://en.cppreference.com/w/cpp/language/extending_std) and maintaining
only one set of user-defined hash functions is easier.
*/
template<typename T>
inline void hash_combine(size_t &hash, const T &value) {
std::hash<T> hasher;
/*
The combination of hash values is based on issue 6.18 in
http://www.open-std.org/JTC1/SC22/WG21/docs/papers/2005/n1756.pdf.
Boost combines hash values in the same way.
*/
hash ^= hasher(value) + 0x9e3779b9 + (hash << 6) + (hash >> 2);
}
template<typename Sequence>
size_t hash_sequence(const Sequence &data, size_t length) {
size_t hash = 0;
for (size_t i = 0; i < length; ++i) {
hash_combine(hash, data[i]);
}
return hash;
}
}
namespace std {
template<typename T>
struct hash<std::vector<T>> {
size_t operator()(const std::vector<T> &vec) const {
return utils::hash_sequence(vec, vec.size());
}
};
template<typename TA, typename TB>
struct hash<std::pair<TA, TB>> {
size_t operator()(const std::pair<TA, TB> &pair) const {
size_t hash = 0;
utils::hash_combine(hash, pair.first);
utils::hash_combine(hash, pair.second);
return hash;
}
};
}
#endif
| 10,889 |
C
| 29.334262 | 90 | 0.634953 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue742/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
"unsolvable",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if matplotlib:
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,475 |
Python
| 35.834606 | 81 | 0.609326 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue742/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_pattern('ms_atomic_construction_time', 't=(.+)s \(after computation of atomic transition systems\)', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int)
def check_ms_constructed(content, props):
ms_construction_time = props.get('ms_construction_time')
abstraction_constructed = False
if ms_construction_time is not None:
abstraction_constructed = True
props['ms_abstraction_constructed'] = abstraction_constructed
parser.add_function(check_ms_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
parser.parse()
| 2,415 |
Python
| 37.967741 | 139 | 0.672464 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue742/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue742-v1"]
CONFIGS = [
IssueConfig('rl-rnd-noprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-rnd-punr', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=true,prune_irrelevant_states=false))']),
IssueConfig('rl-rnd-pirr', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=true))']),
IssueConfig('rl-rnd-fullprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=true,prune_irrelevant_states=true))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step()
exp.run_steps()
| 3,618 |
Python
| 52.220587 | 332 | 0.767828 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue742/v1-debug.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue742-v1"]
CONFIGS = [
IssueConfig('rl-rnd-noprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))'], driver_options=['--debug'], build_options=['--debug']),
IssueConfig('rl-rnd-punr', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=true,prune_irrelevant_states=false))'], driver_options=['--debug'], build_options=['--debug']),
IssueConfig('rl-rnd-pirr', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=true))'], driver_options=['--debug'], build_options=['--debug']),
IssueConfig('rl-rnd-fullprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_random,merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=true,prune_irrelevant_states=true))'], driver_options=['--debug'], build_options=['--debug']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step()
exp.run_steps()
| 3,838 |
Python
| 55.455882 | 387 | 0.760292 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue529/issue529.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import configs, suites
from downward.reports.scatter import ScatterPlotReport
import common_setup
from relativescatter import RelativeScatterPlotReport
SEARCH_REVS = ["issue529-v1-base", "issue529-v1"]
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
'astar_blind': [
'--search',
'astar(blind())'],
'astar_ipdb': [
'--search',
'astar(ipdb())'],
'astar_cpdbs': [
'--search',
'astar(cpdbs())'],
'astar_gapdb': [
'--search',
'astar(gapdb())'],
'astar_pdb': [
'--search',
'astar(pdb())'],
'astar_zopdbs': [
'--search',
'astar(zopdbs())'],
'eager_greedy_cg': [
'--heuristic',
'h=cg()',
'--search',
'eager_greedy(h, preferred=h)'],
}
exp = common_setup.IssueExperiment(
revisions=SEARCH_REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
for conf in CONFIGS:
for attr in ("memory", "total_time"):
exp.add_report(
RelativeScatterPlotReport(
attributes=[attr],
get_category=lambda run1, run2: run1.get("domain"),
filter_config=["issue529-v1-base-%s" % conf, "issue529-v1-%s" % conf]
),
outfile='issue529_base_v1_%s_%s.png' % (conf, attr)
)
exp()
| 1,439 |
Python
| 22.606557 | 85 | 0.544128 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue529/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.reports import Table
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports import PlanningReport
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" % (rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for attribute in valid_attributes:
name = "-".join([rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
class RegressionReport(PlanningReport):
"""
Compare revisions for tasks on which the first revision performs
better than other revisions.
*revision_nicks* must be a list of revision_nicks, e.g.
["default", "issue123"].
*config_nicks* must be a list of configuration nicknames, e.g.
["eager_greedy_ff", "eager_greedy_add"].
*regression_attribute* is the attribute that we compare between
different revisions. It defaults to "coverage".
Example comparing search_time for tasks were we lose coverage::
exp.add_report(RegressionReport(revision_nicks=["default", "issue123"],
config_nicks=["eager_greedy_ff"],
regression_attribute="coverage",
attributes="search_time"))
"""
def __init__(self, revision_nicks, config_nicks,
regression_attribute="coverage", **kwargs):
PlanningReport.__init__(self, **kwargs)
assert revision_nicks
self.revision_nicks = revision_nicks
assert config_nicks
self.config_nicks = config_nicks
self.regression_attribute = regression_attribute
def get_markup(self):
tables = []
for (domain, problem) in self.problems:
for config_nick in self.config_nicks:
runs = [self.runs[(domain, problem, rev + "-" + config_nick)]
for rev in self.revision_nicks]
if any(runs[0][self.regression_attribute] >
runs[i][self.regression_attribute]
for i in range(1, len(self.revision_nicks))):
print "\"%s:%s\"," % (domain, problem)
table = Table()
for rev, run in zip(self.revision_nicks, runs):
for attr in self.attributes:
table.add_cell(rev, attr, run.get(attr))
table_name = ":".join((domain, problem, config_nick))
tables.append((table_name, table))
return "\n".join(name + "\n" + str(table) for name, table in tables)
| 14,920 |
Python
| 36.3025 | 79 | 0.601475 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue529/relativescatter.py
|
# -*- coding: utf-8 -*-
#
# downward uses the lab package to conduct experiments with the
# Fast Downward planning system.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from collections import defaultdict
import os
from lab import tools
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 4,690 |
Python
| 35.937008 | 84 | 0.624947 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue420/issue420-v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
import common_setup
REVS = ["issue420-base", "issue420-v1"]
CONFIGS = {
"blind": ["--search", "astar(blind())"],
"lmcut": ["--search", "astar(lmcut())"],
}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_optimal_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES
)
exp()
| 718 |
Python
| 18.432432 | 65 | 0.655989 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue420/common_setup.py
|
# -*- coding: utf-8 -*-
import os.path
from lab.environments import MaiaEnvironment
from lab.steps import Step
from downward.checkouts import Translator, Preprocessor, Planner
from downward.experiments import DownwardExperiment
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the filename of the main script, e.g.
"/ham/spam/eggs.py" => "eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Found by searching upwards in the directory tree from the main
script until a directory with a subdirectory named ".hg" is found."""
path = os.path.abspath(get_script_dir())
while True:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
class MyExperiment(DownwardExperiment):
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"total_time",
"search_time",
"memory",
"expansions_until_last_jump",
]
"""Wrapper for DownwardExperiment with a few convenience features."""
def __init__(self, configs=None, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
suite=None, parsers=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
If "configs" is specified, it should be a dict of {nick:
cmdline} pairs that sets the planner configurations to test.
If "grid_priority" is specified and no environment is
specifically requested in **kwargs, use the maia environment
with the specified priority.
If "path" is not specified, the experiment data path is
derived automatically from the main script's filename.
If "repo" is not specified, the repository base is derived
automatically from the main script's path.
If "revisions" is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search.
If "search_revisions" is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All experiments use the
translator and preprocessor component of the first
revision.
If "suite" is specified, it should specify a problem suite.
If "parsers" is specified, it should be a list of paths to
parsers that should be run in addition to search_parser.py.
Options "combinations" (from the base class), "revisions" and
"search_revisions" are mutually exclusive."""
if grid_priority is not None and "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
num_rev_opts_specified = (
int(revisions is not None) +
int(search_revisions is not None) +
int(kwargs.get("combinations") is not None))
if num_rev_opts_specified > 1:
raise ValueError('must specify exactly one of "revisions", '
'"search_revisions" or "combinations"')
# See add_comparison_table_step for more on this variable.
self._HACK_revisions = revisions
if revisions is not None:
if not revisions:
raise ValueError("revisions cannot be empty")
combinations = [(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions]
kwargs["combinations"] = combinations
if search_revisions is not None:
if not search_revisions:
raise ValueError("search_revisions cannot be empty")
base_rev = search_revisions[0]
translator = Translator(repo, base_rev)
preprocessor = Preprocessor(repo, base_rev)
combinations = [(translator, preprocessor, Planner(repo, rev))
for rev in search_revisions]
kwargs["combinations"] = combinations
self._additional_parsers = parsers or []
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
if configs is not None:
for nick, config in configs.items():
self.add_config(nick, config)
if suite is not None:
self.add_suite(suite)
self._report_prefix = get_experiment_name()
def _make_search_runs(self):
DownwardExperiment._make_search_runs(self)
for i, parser in enumerate(self._additional_parsers):
parser_alias = 'ADDITIONALPARSER%d' % i
self.add_resource(parser_alias, parser, os.path.basename(parser))
for run in self.runs:
run.require_resource(parser_alias)
run.add_command('additional-parser-%d' % i, [parser_alias])
def add_comparison_table_step(self, attributes=None):
revisions = self._HACK_revisions
if revisions is None:
# TODO: It's not clear to me what a "revision" in the
# overall context of the code really is, e.g. when keeping
# the translator and preprocessor method fixed and only
# changing the search component. It's also not really
# clear to me how the interface of the Compare... reports
# works and how to use it more generally. Hence the
# present hack.
# Ideally, this method should look at the table columns we
# have (defined by planners and planner configurations),
# pair them up in a suitable way, either controlled by a
# convenience parameter or a more general grouping method,
# and then use this to define which pairs go together.
raise NotImplementedError(
"only supported when specifying revisions in __init__")
if attributes is None:
attributes = self.DEFAULT_TABLE_ATTRIBUTES
report = CompareRevisionsReport(*revisions, attributes=attributes)
self.add_report(report, outfile="%s-compare.html" % self._report_prefix)
def add_scatter_plot_step(self, attributes=None):
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
revisions = self._HACK_revisions
if revisions is None:
# TODO: See add_comparison_table_step.
raise NotImplementedError(
"only supported when specifying revisions in __init__")
if len(revisions) != 2:
# TODO: Should generalize this, too, by offering a general
# grouping function and then comparing any pair of
# settings in the same group.
raise NotImplementedError("need two revisions")
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plots():
configs = [conf[0] for conf in self.configs]
for nick in configs:
config_before = "%s-%s" % (revisions[0], nick)
config_after = "%s-%s" % (revisions[1], nick)
for attribute in attributes:
name = "%s-%s-%s" % (self._report_prefix, attribute, nick)
report = ScatterPlotReport(
filter_config=[config_before, config_after],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 9,190 |
Python
| 37.456067 | 80 | 0.611099 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue420/issue420-v1-regressions.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Before you can run the experiment you need to create duplicates of the
two tasks we want to test:
cd ../benchmarks/tidybot-opt11-strips
for i in {00..49}; do cp p14.pddl p14-$i.pddl; done
cd ../parking-opt11-strips
for i in {00..49}; do cp pfile04-015.pddl pfile04-015-$i.pddl; done
Don't forget to remove the duplicate tasks afterwards. Otherwise they
will be included in subsequent experiments.
"""
import common_setup
REVS = ["issue420-base", "issue420-v1"]
CONFIGS = {
"blind": ["--search", "astar(blind())"],
"lmcut": ["--search", "astar(lmcut())"],
}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = (["tidybot-opt11-strips:p14-%02d.pddl" % i for i in range(50)] +
["parking-opt11-strips:pfile04-015-%02d.pddl" % i for i in range(50)])
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES
)
exp()
| 1,194 |
Python
| 23.387755 | 83 | 0.669179 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue479/issue479-5min.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute
import common_setup
import os
exp = common_setup.IssueExperiment(
search_revisions=["issue479-v2"],
configs={
'dfp-b-50k': ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(max_states=100000,threshold=1,greedy=false),merge_strategy=merge_dfp(),label_reduction=label_reduction(before_shrinking=true, before_merging=false)))'],
'blind': ['--search', 'astar(blind())'],
},
suite=['airport'],
limits={"search_time": 300},
)
exp.add_absolute_report_step(attributes=['coverage', 'error', 'run_dir'])
exp()
| 679 |
Python
| 26.199999 | 246 | 0.674521 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue479/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (node.endswith("cluster.bc2.ch") or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
# TODO: Once we have reference results, we should add "quality".
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" % (rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for attribute in valid_attributes:
name = "-".join([rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,741 |
Python
| 35.614942 | 79 | 0.608743 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue479/issue479.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute
import common_setup
import os
exp = common_setup.IssueExperiment(
search_revisions=["issue479-v2"],
configs={
'dfp-b-50k': ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(max_states=100000,threshold=1,greedy=false),merge_strategy=merge_dfp(),label_reduction=label_reduction(before_shrinking=true, before_merging=false)))'],
'blind': ['--search', 'astar(blind())'],
},
suite=['airport'],
)
exp.add_absolute_report_step(attributes=['coverage', 'error', 'run_dir'])
exp()
| 646 |
Python
| 25.958332 | 246 | 0.679567 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue891/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".git" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".git")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None, additional=[]):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute, config_nick2=None):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
if config_nick2 is not None:
name += "-" + config_nick2
print("Make scatter plot for", name)
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick if config_nick2 is None else config_nick2)
report = ScatterPlotReport(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
relative=relative,
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
for nick1, nick2, rev1, rev2, attribute in additional:
make_scatter_plot(nick1, rev1, rev2, attribute, config_nick2=nick2)
self.add_step(step_name, make_scatter_plots)
| 14,944 |
Python
| 36.835443 | 94 | 0.618241 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue891/v1.py
|
#! /usr/bin/env python3
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue891-base", "issue891-v1"]
CONFIGS = [
IssueConfig("opcount-seq-lmcut-cplex", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()], lpsolver=cplex))"]),
IssueConfig("diverse-potentials-cplex", ["--search", "astar(diverse_potentials(lpsolver=cplex,random_seed=1729))"]),
IssueConfig("optimal-lmcount-cplex", ["--search", "astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]), admissible=true, optimal=true, lpsolver=cplex))"]),
IssueConfig("opcount-seq-lmcut-soplex", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()], lpsolver=soplex))"]),
IssueConfig("diverse-potentials-soplex", ["--search", "astar(diverse_potentials(lpsolver=soplex,random_seed=1729))"]),
IssueConfig("optimal-lmcount-soplex", ["--search", "astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]), admissible=true, optimal=true, lpsolver=soplex))"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=3)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(relative=True, attributes=["total_time", "memory"])
exp.run_steps()
| 2,174 |
Python
| 37.839285 | 156 | 0.735511 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue891/v1-mips.py
|
#! /usr/bin/env python3
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue891-v1"]
CONFIGS = [
IssueConfig("opcount-lp", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()], lpsolver=cplex, use_integer_operator_counts=false))"]),
IssueConfig("opcount-mip", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()], lpsolver=cplex, use_integer_operator_counts=true))"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=3)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_report(ComparativeReport(
[("issue891-v1-opcount-lp", "issue891-v1-opcount-mip", "Diff (LP/MIP)")],
attributes=exp.DEFAULT_TABLE_ATTRIBUTES + ["initial_h_value"]))
exp.add_scatter_plot_step(relative=False, attributes=["total_time", "memory"],
additional=[
("opcount-lp", "opcount-mip", "issue891-v1", "issue891-v1", "total_time"),
("opcount-lp", "opcount-mip", "issue891-v1", "issue891-v1", "memory"),
])
def interesting_h_value(run):
if "initial_h_value" in run and run["initial_h_value"] > 50:
run["initial_h_value"] = 51
return run
exp.add_report(ScatterPlotReport(
attributes=["initial_h_value"],
filter=interesting_h_value,
get_category=lambda run1, run2: run1["domain"],
))
exp.run_steps()
| 2,308 |
Python
| 31.985714 | 176 | 0.719671 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue925/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 |
Python
| 35.955613 | 82 | 0.615205 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue925/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
from itertools import combinations
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
# These revisions are all tag experimental branches off the same revision.
# we only need different tags so lab creates separate build directories in the build cache.
# We then manually recompile the code in the build cache with the correct settings.
REVISIONS = ["issue925-cplex12.8-static", "issue925-cplex12.8-dynamic", "issue925-cplex12.9-static", "issue925-cplex12.9-dynamic"]
CONFIGS = [
IssueConfig("opcount-seq-lmcut", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()]))"]),
IssueConfig("diverse-potentials", ["--search", "astar(diverse_potentials())"]),
IssueConfig("optimal-lmcount", ["--search", "astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]), admissible=true, optimal=true))"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
for r1, r2 in combinations(REVISIONS, 2):
for nick in ["opcount-seq-lmcut", "diverse-potentials", "optimal-lmcount"]:
exp.add_report(RelativeScatterPlotReport(
attributes=["total_time"],
filter_algorithm=["%s-%s" % (r, nick) for r in [r1, r2]],
get_category=lambda run1, run2: run1["domain"]),
outfile="issue925-v1-total-time-%s-%s-%s.png" % (r1, r2, nick))
exp.run_steps()
| 2,243 |
Python
| 37.689655 | 132 | 0.726259 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue925/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue791/v1-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue791-base", "issue791-v1"]
CONFIGS = [
IssueConfig(
'blind-debug', ['--search', 'astar(blind())'],
build_options=["debug32"],
driver_options=["--build", "debug32", "--overall-time-limit", "5m"]
),
IssueConfig(
'blind-release', ['--search', 'astar(blind())'],
build_options=["release32"],
driver_options=["--build", "release32", "--overall-time-limit", "5m"]
),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,509 |
Python
| 26.454545 | 77 | 0.689198 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue791/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 |
Python
| 35.955613 | 82 | 0.615205 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue791/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 |
Python
| 35.566037 | 78 | 0.59871 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue791/v2-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue791-base", "issue791-v2"]
CONFIGS = [
IssueConfig(
'blind-debug', ['--search', 'astar(blind())'],
build_options=["debug32"],
driver_options=["--build", "debug32", "--overall-time-limit", "5m"]
),
IssueConfig(
'blind-release', ['--search', 'astar(blind())'],
build_options=["release32"],
driver_options=["--build", "release32", "--overall-time-limit", "5m"]
),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,509 |
Python
| 26.454545 | 77 | 0.689198 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v2-dfp-tiebreaking-abp-report.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_fetcher('data/issue644-v2-dfp-tiebreaking-eval',
filter_config=[
'issue644-v1-dfp-reg-otn-abp-b50k',
'issue644-v1-dfp-reg-nto-abp-b50k',
'issue644-v1-dfp-reg-rnd-abp-b50k',
'issue644-v1-dfp-inv-otn-abp-b50k',
'issue644-v1-dfp-inv-nto-abp-b50k',
'issue644-v1-dfp-inv-rnd-abp-b50k',
'issue644-v1-dfp-rnd-otn-abp-b50k',
'issue644-v1-dfp-rnd-nto-abp-b50k',
'issue644-v1-dfp-rnd-rnd-abp-b50k',
'issue644-v2-dfp-reg-otn-abp-b50k',
'issue644-v2-dfp-reg-nto-abp-b50k',
'issue644-v2-dfp-reg-rnd-abp-b50k',
'issue644-v2-dfp-inv-otn-abp-b50k',
'issue644-v2-dfp-inv-nto-abp-b50k',
'issue644-v2-dfp-inv-rnd-abp-b50k',
'issue644-v2-dfp-rnd-otn-abp-b50k',
'issue644-v2-dfp-rnd-nto-abp-b50k',
'issue644-v2-dfp-rnd-rnd-abp-b50k',
])
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-v1', 'issue644-v2'])
| 10,140 |
Python
| 82.12295 | 351 | 0.715878 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, benchmarks_dir, suite, revisions=[], configs={},
grid_priority=None, path=None, test_suite=None,
email=None, processes=None,
**kwargs):
"""
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
*configs* must be a non-empty list of IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(..., suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(..., suite=suites.suite_all())
IssueExperiment(..., suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(..., suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(..., grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(..., test_suite=["depot:pfile1", "tpp:p01.pddl"])
If *email* is specified, it should be an email address. This
email address will be notified upon completion of the experiments
if it is run on the cluster.
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment(processes=processes)
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(
priority=grid_priority, email=email)
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
repo = get_repo_base()
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
repo,
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self.add_suite(benchmarks_dir, suite)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(self.eval_dir,
get_experiment_name() + "." +
report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step('publish-absolute-report',
subprocess.call,
['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ "." + report.output_format)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ ".html")
subprocess.call(['publish', outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step("publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,496 |
Python
| 33.907821 | 83 | 0.59435 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/suites.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import textwrap
HELP = "Convert suite name to list of domains or tasks."
def suite_alternative_formulations():
return ['airport-adl', 'no-mprime', 'no-mystery']
def suite_ipc98_to_ipc04_adl():
return [
'assembly', 'miconic-fulladl', 'miconic-simpleadl',
'optical-telegraphs', 'philosophers', 'psr-large',
'psr-middle', 'schedule',
]
def suite_ipc98_to_ipc04_strips():
return [
'airport', 'blocks', 'depot', 'driverlog', 'freecell', 'grid',
'gripper', 'logistics00', 'logistics98', 'miconic', 'movie',
'mprime', 'mystery', 'pipesworld-notankage', 'psr-small',
'satellite', 'zenotravel',
]
def suite_ipc98_to_ipc04():
# All IPC1-4 domains, including the trivial Movie.
return sorted(suite_ipc98_to_ipc04_adl() + suite_ipc98_to_ipc04_strips())
def suite_ipc06_adl():
return [
'openstacks',
'pathways',
'trucks',
]
def suite_ipc06_strips_compilations():
return [
'openstacks-strips',
'pathways-noneg',
'trucks-strips',
]
def suite_ipc06_strips():
return [
'pipesworld-tankage',
'rovers',
'storage',
'tpp',
]
def suite_ipc06():
return sorted(suite_ipc06_adl() + suite_ipc06_strips())
def suite_ipc08_common_strips():
return [
'parcprinter-08-strips',
'pegsol-08-strips',
'scanalyzer-08-strips',
]
def suite_ipc08_opt_adl():
return ['openstacks-opt08-adl']
def suite_ipc08_opt_strips():
return sorted(suite_ipc08_common_strips() + [
'elevators-opt08-strips',
'openstacks-opt08-strips',
'sokoban-opt08-strips',
'transport-opt08-strips',
'woodworking-opt08-strips',
])
def suite_ipc08_opt():
return sorted(suite_ipc08_opt_strips() + suite_ipc08_opt_adl())
def suite_ipc08_sat_adl():
return ['openstacks-sat08-adl']
def suite_ipc08_sat_strips():
return sorted(suite_ipc08_common_strips() + [
# Note: cyber-security is missing.
'elevators-sat08-strips',
'openstacks-sat08-strips',
'sokoban-sat08-strips',
'transport-sat08-strips',
'woodworking-sat08-strips',
])
def suite_ipc08_sat():
return sorted(suite_ipc08_sat_strips() + suite_ipc08_sat_adl())
def suite_ipc08():
return sorted(set(suite_ipc08_opt() + suite_ipc08_sat()))
def suite_ipc11_opt():
return [
'barman-opt11-strips',
'elevators-opt11-strips',
'floortile-opt11-strips',
'nomystery-opt11-strips',
'openstacks-opt11-strips',
'parcprinter-opt11-strips',
'parking-opt11-strips',
'pegsol-opt11-strips',
'scanalyzer-opt11-strips',
'sokoban-opt11-strips',
'tidybot-opt11-strips',
'transport-opt11-strips',
'visitall-opt11-strips',
'woodworking-opt11-strips',
]
def suite_ipc11_sat():
return [
'barman-sat11-strips',
'elevators-sat11-strips',
'floortile-sat11-strips',
'nomystery-sat11-strips',
'openstacks-sat11-strips',
'parcprinter-sat11-strips',
'parking-sat11-strips',
'pegsol-sat11-strips',
'scanalyzer-sat11-strips',
'sokoban-sat11-strips',
'tidybot-sat11-strips',
'transport-sat11-strips',
'visitall-sat11-strips',
'woodworking-sat11-strips',
]
def suite_ipc11():
return sorted(suite_ipc11_opt() + suite_ipc11_sat())
def suite_ipc14_agl_adl():
return [
'cavediving-14-adl',
'citycar-sat14-adl',
'maintenance-sat14-adl',
]
def suite_ipc14_agl_strips():
return [
'barman-sat14-strips',
'childsnack-sat14-strips',
'floortile-sat14-strips',
'ged-sat14-strips',
'hiking-agl14-strips',
'openstacks-agl14-strips',
'parking-sat14-strips',
'tetris-sat14-strips',
'thoughtful-sat14-strips',
'transport-sat14-strips',
'visitall-sat14-strips',
]
def suite_ipc14_agl():
return sorted(suite_ipc14_agl_adl() + suite_ipc14_agl_strips())
def suite_ipc14_mco_adl():
return [
'cavediving-14-adl',
'citycar-sat14-adl',
'maintenance-sat14-adl',
]
def suite_ipc14_mco_strips():
return [
'barman-mco14-strips',
'childsnack-sat14-strips',
'floortile-sat14-strips',
'ged-sat14-strips',
'hiking-sat14-strips',
'openstacks-sat14-strips',
'parking-sat14-strips',
'tetris-sat14-strips',
'thoughtful-mco14-strips',
'transport-sat14-strips',
'visitall-sat14-strips',
]
def suite_ipc14_mco():
return sorted(suite_ipc14_mco_adl() + suite_ipc14_mco_strips())
def suite_ipc14_opt_adl():
return [
'cavediving-14-adl',
'citycar-opt14-adl',
'maintenance-opt14-adl',
]
def suite_ipc14_opt_strips():
return [
'barman-opt14-strips',
'childsnack-opt14-strips',
'floortile-opt14-strips',
'ged-opt14-strips',
'hiking-opt14-strips',
'openstacks-opt14-strips',
'parking-opt14-strips',
'tetris-opt14-strips',
'tidybot-opt14-strips',
'transport-opt14-strips',
'visitall-opt14-strips',
]
def suite_ipc14_opt():
return sorted(suite_ipc14_opt_adl() + suite_ipc14_opt_strips())
def suite_ipc14_sat_adl():
return [
'cavediving-14-adl',
'citycar-sat14-adl',
'maintenance-sat14-adl',
]
def suite_ipc14_sat_strips():
return [
'barman-sat14-strips',
'childsnack-sat14-strips',
'floortile-sat14-strips',
'ged-sat14-strips',
'hiking-sat14-strips',
'openstacks-sat14-strips',
'parking-sat14-strips',
'tetris-sat14-strips',
'thoughtful-sat14-strips',
'transport-sat14-strips',
'visitall-sat14-strips',
]
def suite_ipc14_sat():
return sorted(suite_ipc14_sat_adl() + suite_ipc14_sat_strips())
def suite_ipc14():
return sorted(set(
suite_ipc14_agl() + suite_ipc14_mco() +
suite_ipc14_opt() + suite_ipc14_sat()))
def suite_unsolvable():
return sorted(
['mystery:prob%02d.pddl' % index
for index in [4, 5, 7, 8, 12, 16, 18, 21, 22, 23, 24]] +
['miconic-fulladl:f21-3.pddl', 'miconic-fulladl:f30-2.pddl'])
def suite_optimal_adl():
return sorted(
suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() +
suite_ipc08_opt_adl() + suite_ipc14_opt_adl())
def suite_optimal_strips():
return sorted(
suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() +
suite_ipc06_strips_compilations() + suite_ipc08_opt_strips() +
suite_ipc11_opt() + suite_ipc14_opt_strips())
def suite_optimal():
return sorted(suite_optimal_adl() + suite_optimal_strips())
def suite_satisficing_adl():
return sorted(
suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() +
suite_ipc08_sat_adl() + suite_ipc14_sat_adl())
def suite_satisficing_strips():
return sorted(
suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() +
suite_ipc06_strips_compilations() + suite_ipc08_sat_strips() +
suite_ipc11_sat() + suite_ipc14_sat_strips())
def suite_satisficing():
return sorted(suite_satisficing_adl() + suite_satisficing_strips())
def suite_all():
return sorted(
suite_ipc98_to_ipc04() + suite_ipc06() +
suite_ipc06_strips_compilations() + suite_ipc08() +
suite_ipc11() + suite_ipc14() + suite_alternative_formulations())
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("suite", help="suite name")
return parser.parse_args()
def main():
prefix = "suite_"
suite_names = [
name[len(prefix):] for name in sorted(globals().keys())
if name.startswith(prefix)]
parser = argparse.ArgumentParser(description=HELP)
parser.add_argument("suite", choices=suite_names, help="suite name")
parser.add_argument(
"--width", default=72, type=int,
help="output line width (default: %(default)s). Use 1 for single "
"column.")
args = parser.parse_args()
suite_func = globals()[prefix + args.suite]
print(textwrap.fill(
str(suite_func()),
width=args.width,
break_long_words=False,
break_on_hyphens=False))
if __name__ == "__main__":
main()
| 8,551 |
Python
| 23.364672 | 77 | 0.595954 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v1-dfp-tiebreaking-abp-report.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_fetcher('data/issue644-v1-dfp-tiebreaking-eval',
filter_config=[
'issue644-base-dfp-reg-otn-abp-b50k',
'issue644-base-dfp-reg-nto-abp-b50k',
'issue644-base-dfp-reg-rnd-abp-b50k',
'issue644-base-dfp-inv-otn-abp-b50k',
'issue644-base-dfp-inv-nto-abp-b50k',
'issue644-base-dfp-inv-rnd-abp-b50k',
'issue644-base-dfp-rnd-otn-abp-b50k',
'issue644-base-dfp-rnd-nto-abp-b50k',
'issue644-base-dfp-rnd-rnd-abp-b50k',
'issue644-v1-dfp-reg-otn-abp-b50k',
'issue644-v1-dfp-reg-nto-abp-b50k',
'issue644-v1-dfp-reg-rnd-abp-b50k',
'issue644-v1-dfp-inv-otn-abp-b50k',
'issue644-v1-dfp-inv-nto-abp-b50k',
'issue644-v1-dfp-inv-rnd-abp-b50k',
'issue644-v1-dfp-rnd-otn-abp-b50k',
'issue644-v1-dfp-rnd-nto-abp-b50k',
'issue644-v1-dfp-rnd-rnd-abp-b50k',
])
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-base', 'issue644-v1'])
| 10,160 |
Python
| 82.286885 | 351 | 0.716437 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v1-dfp-tiebreaking-pba-report.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
#IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_fetcher('data/issue644-v1-dfp-tiebreaking-eval',
filter_config=[
'issue644-base-dfp-reg-otn-pba-b50k',
'issue644-base-dfp-reg-nto-pba-b50k',
'issue644-base-dfp-reg-rnd-pba-b50k',
'issue644-base-dfp-inv-otn-pba-b50k',
'issue644-base-dfp-inv-nto-pba-b50k',
'issue644-base-dfp-inv-rnd-pba-b50k',
'issue644-base-dfp-rnd-otn-pba-b50k',
'issue644-base-dfp-rnd-nto-pba-b50k',
'issue644-base-dfp-rnd-rnd-pba-b50k',
'issue644-v1-dfp-reg-otn-pba-b50k',
'issue644-v1-dfp-reg-nto-pba-b50k',
'issue644-v1-dfp-reg-rnd-pba-b50k',
'issue644-v1-dfp-inv-otn-pba-b50k',
'issue644-v1-dfp-inv-nto-pba-b50k',
'issue644-v1-dfp-inv-rnd-pba-b50k',
'issue644-v1-dfp-rnd-otn-pba-b50k',
'issue644-v1-dfp-rnd-nto-pba-b50k',
'issue644-v1-dfp-rnd-rnd-pba-b50k',
])
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-base', 'issue644-v1'])
| 10,160 |
Python
| 82.286885 | 350 | 0.716437 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v2-dfp-tiebreaking-pba-report.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
#IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
#IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_fetcher('data/issue644-v2-dfp-tiebreaking-eval',
filter_config=[
'issue644-v1-dfp-reg-otn-pba-b50k',
'issue644-v1-dfp-reg-nto-pba-b50k',
'issue644-v1-dfp-reg-rnd-pba-b50k',
'issue644-v1-dfp-inv-otn-pba-b50k',
'issue644-v1-dfp-inv-nto-pba-b50k',
'issue644-v1-dfp-inv-rnd-pba-b50k',
'issue644-v1-dfp-rnd-otn-pba-b50k',
'issue644-v1-dfp-rnd-nto-pba-b50k',
'issue644-v1-dfp-rnd-rnd-pba-b50k',
'issue644-v2-dfp-reg-otn-pba-b50k',
'issue644-v2-dfp-reg-nto-pba-b50k',
'issue644-v2-dfp-reg-rnd-pba-b50k',
'issue644-v2-dfp-inv-otn-pba-b50k',
'issue644-v2-dfp-inv-nto-pba-b50k',
'issue644-v2-dfp-inv-rnd-pba-b50k',
'issue644-v2-dfp-rnd-otn-pba-b50k',
'issue644-v2-dfp-rnd-nto-pba-b50k',
'issue644-v2-dfp-rnd-rnd-pba-b50k',
])
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-v1', 'issue644-v2'])
| 10,140 |
Python
| 82.12295 | 350 | 0.715878 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int)
parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[t=.+s\]', required=False, type=float)
def check_ms_constructed(content, props):
ms_construction_time = props.get('ms_construction_time')
abstraction_constructed = False
if ms_construction_time is not None:
abstraction_constructed = True
props['ms_abstraction_constructed'] = abstraction_constructed
parser.add_function(check_ms_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
def check_proved_unsolvability(content, props):
proved_unsolvability = False
if props['coverage'] == 0:
for line in content.splitlines():
if line == 'Completely explored state space -- no solution!':
proved_unsolvability = True
break
props['proved_unsolvability'] = proved_unsolvability
parser.add_function(check_proved_unsolvability)
parser.parse()
| 2,784 |
Python
| 37.150684 | 135 | 0.665589 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v1-dfp-tiebreaking.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-base', 'issue644-v1'])
| 9,172 |
Python
| 90.729999 | 350 | 0.734409 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-base', 'issue644-v1'])
| 5,278 |
Python
| 57.010988 | 293 | 0.696476 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 3,921 |
Python
| 35.654205 | 84 | 0.597042 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v2-dfp-tiebreaking.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('dfp-reg-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-abp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=true),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-reg-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=regular,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-inv-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=inverse,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-otn-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=old_to_new,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-nto-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=new_to_old,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-rnd-rnd-pba-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp(atomic_ts_order=random,product_ts_order=random,atomic_before_product=false),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-v1', 'issue644-v2'])
| 9,170 |
Python
| 90.709999 | 350 | 0.734351 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-v3-base', 'issue644-v3'])
| 5,281 |
Python
| 57.043955 | 293 | 0.696459 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue644/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks')
suite=suites.suite_optimal_strips()
configs = {
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
}
exp = IssueExperiment(
benchmarks_dir=benchmarks_dir,
suite=suite,
revisions=revisions,
configs=configs,
test_suite=['depot:p01.pddl'],
processes=4,
email='[email protected]',
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['ms_parser'])
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False)
actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm])
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
proved_unsolvability,
actual_search_time,
ms_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step()
#if matplotlib:
#for attribute in ["memory", "total_time"]:
#for config in configs:
#exp.add_report(
#RelativeScatterPlotReport(
#attributes=[attribute],
#filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
#get_category=lambda run1, run2: run1.get("domain"),
#),
#outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
#)
exp()
main(revisions=['issue644-v1', 'issue644-v2'])
| 5,276 |
Python
| 56.98901 | 293 | 0.696361 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v7.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v1-base", "issue637-v6", "issue637-v7"]
DRIVER_OPTIONS = []
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_memory", "init_time"]
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,206 |
Python
| 30.528571 | 98 | 0.68087 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v3", "issue637-v4"]
#REVISIONS = ["issue637-v4"]
DRIVER_OPTIONS = ["--overall-time-limit", "30m"]
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_fetcher(os.path.join(DIR, 'data/issue637-v3-eval'))
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_time", "search_start_memory", "init_time", "cartesian_states"]
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,343 |
Python
| 32.014084 | 98 | 0.682885 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v5.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v1-base", "issue637-v5"]
#REVISIONS = ["issue637-v5"]
DRIVER_OPTIONS = ["--overall-time-limit", "30m"]
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_fetcher(os.path.join(DIR, "data/issue637-v1-eval"))
exp.add_fetcher(os.path.join(DIR, "data/issue637-v4-eval"))
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_time", "search_start_memory", "init_time", "cartesian_states"]
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,409 |
Python
| 32.013698 | 98 | 0.684101 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v8.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v8-base", "issue637-v8"]
DRIVER_OPTIONS = []
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_memory", "init_time"]
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,191 |
Python
| 30.314285 | 98 | 0.680968 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/parser.py
|
#! /usr/bin/env python
import logging
import re
from lab.parser import Parser
class CommonParser(Parser):
def add_difference(self, diff, val1, val2):
def diff_func(content, props):
if props.get(val1) is None or props.get(val2) is None:
diff_val = None
else:
diff_val = props.get(val1) - props.get(val2)
props[diff] = diff_val
self.add_function(diff_func)
def _get_flags(self, flags_string):
flags = 0
for char in flags_string:
flags |= getattr(re, char)
return flags
def add_repeated_pattern(
self, name, regex, file="run.log", required=True, type=int,
flags=""):
flags += "M"
def find_all_occurences(content, props):
matches = re.findall(regex, content, flags=self._get_flags(flags))
if required and not matches:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
props[name] = [type(m) for m in matches]
self.add_function(find_all_occurences, file=file)
def add_pattern(self, name, regex, file="run.log", required=False, type=int, flags="M"):
Parser.add_pattern(self, name, regex, file=file, required=required, type=type, flags=flags)
def add_bottom_up_pattern(self, name, regex, file="run.log", required=True, type=int, flags=""):
def search_from_bottom(content, props):
reversed_content = "\n".join(reversed(content.splitlines()))
match = re.search(regex, reversed_content, flags=self._get_flags(flags))
if required and not match:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
if match:
props[name] = type(match.group(1))
self.add_function(search_from_bottom, file=file)
def no_search(content, props):
if "search_start_time" not in props:
error = props.get("error")
if error is not None and error != "incomplete-search-found-no-plan":
props["error"] = "no-search-due-to-" + error
def main():
parser = CommonParser()
parser.add_pattern("search_start_time", r"\[g=0, 1 evaluated, 0 expanded, t=(.+)s, \d+ KB\]", type=float, required=False)
parser.add_pattern("search_start_memory", r"\[g=0, 1 evaluated, 0 expanded, t=.+s, (\d+) KB\]", type=int, required=False)
parser.add_pattern("init_time", r"^Time for initializing additive Cartesian heuristic: (.+)s$", type=float, required=False)
parser.add_pattern("cartesian_states", r"^Cartesian states: (\d+)$", type=int, required=False)
parser.add_function(no_search)
parser.parse()
if __name__ == "__main__":
main()
| 2,736 |
Python
| 35.493333 | 127 | 0.605629 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,203 |
Python
| 35.893506 | 82 | 0.614729 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v6.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v1-base", "issue637-v6"]
DRIVER_OPTIONS = ["--overall-time-limit", "30m"]
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_memory", "init_time"]
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,220 |
Python
| 30.728571 | 98 | 0.680631 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v1-base", "issue637-v1"]
DRIVER_OPTIONS = ["--overall-time-limit", "30m"]
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_parse_again_step()
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,031 |
Python
| 29.328358 | 94 | 0.683407 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if not val1 or not val2:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,867 |
Python
| 35.490566 | 78 | 0.598397 |
makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue637/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue637-v1", "issue637-v2", "issue637-v3"]
REVISIONS = ["issue637-v1", "issue637-v3"]
DRIVER_OPTIONS = ["--overall-time-limit", "30m"]
CONFIGS = [
IssueConfig(
"cegar-landmarks-goals",
["--search", "astar(cegar())"],
driver_options=DRIVER_OPTIONS),
IssueConfig(
"cegar-original",
["--search", "astar(cegar(subtasks=[original()]))"],
driver_options=DRIVER_OPTIONS),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_fetcher(os.path.join(DIR, 'data/issue637-v2-eval'))
attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [
"search_start_time", "search_start_memory", "init_time", "cartesian_states"]
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,372 |
Python
| 32.422535 | 98 | 0.682968 |
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