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paulo037
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weather.py
shuiyouren/weather-python
1
43225
<gh_stars>1-10 # -*- coding: utf-8 -*- import requests import sys import os # curent_dir = os.path.dirname(__file__) # print(curent_dir) # sys.path.append(curent_dir) from bs4 import BeautifulSoup from .weather_id import mylist def show_weather(sumht,sumwea): str = None try: l1 = '温度:'+sumht[0] l2 = '天气:'+sumwea[0] str = "{0}; {1}".format(l2, l1) except: print('未查询到天气!!!') else: print(l1) print(l2) return str def get_city_id(name_id): l = mylist() for i in l: if i['name'] == name_id: s = i['id'] return s def get_7dweather(header,id): #最高温 temperatureHigh = [] #天气 wth = [] url = 'http://www.weather.com.cn/weather/%s.shtml'%id req = requests.get(url,headers=header) req.encoding = 'utf-8' html = req.text bs = BeautifulSoup(html,'html.parser') tagToday = bs.select('p[class="tem"]') wth1 = bs.select('p[class="wea"]') for x in tagToday: temperatureHigh.append(x.text.strip()) for z in wth1: wth.append(z.string) return (temperatureHigh, wth) def get_weather_info(city: str): header = { 'Accept':'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'Accept-Encoding':'gzip, deflate, sdch', 'Accept-Language':'zh-CN,zh;q=0.8', 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) \ AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36' } city_id = get_city_id(city) (sumht, sumwea) = get_7dweather(header,city_id) return show_weather(sumht,sumwea) def get_weather_list_str(): text = "上海(%s)\n杭州(%s)\n" % (get_weather_info('上海'), get_weather_info('杭州')) return text if __name__ == '__main__': get_weather_info('上海') print(get_weather_list_str())
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tests/integration/application/test_attribute_server_and_client.py
microprediction/predictionserver
1
24806
<filename>tests/integration/application/test_attribute_server_and_client.py from predictionserver.clientmixins.attributereader import ( AttributeReader, AttributeType, AttributeGranularity ) from predictionserver.set_config import MICRO_TEST_CONFIG from predictionserver.servermixins.attributeserver import AttributeServer BABLOH_CATTLE = MICRO_TEST_CONFIG['BABLOH_CATTLE'] PUBLIC_PROFILE = { AttributeType.homepage: 'https://www.savetrumble.com.au', AttributeType.repository: 'https://pypi.org/project/microfilter/', AttributeType.paper: 'https://arxiv.org/pdf/1512.01389.pdf', AttributeType.topic: 'AutoMl', AttributeType.description: 'Herding cattle using AutoMl' } PRIVATE_PROFILE = { AttributeType.email: '<EMAIL>', AttributeType.description: 'private description' } # def test_attribute_server(localhost_process): # """ Test using local flask app (see testconf.py """ # print('Running localhost_process test') # ar = AttributeReader() # ar.base_url = 'http://127.0.0.1:5000' # server = AttributeServer() # server.connect(**MICRO_TEST_CONFIG) # email = '<EMAIL>' # server.set_attribute( # attribute_type=AttributeType.email, # granularity=AttributeGranularity.write_key, # write_key=BABLOH_CATTLE, # value=email # ) # email_back = server.get_attribute( # attribute_type=AttributeType.email, # granularity=AttributeGranularity.write_key, # write_key=BABLOH_CATTLE # ) # assert email == email_back # email_back_from_client = ar.get_attribute( # attribute_type=AttributeType.email, # granularity=AttributeGranularity.write_key, # write_key=BABLOH_CATTLE # ) # assert email == email_back_from_client
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vis/app/xblock/data/pad.py
ImperialNLP/X-Block
0
162102
#!/usr/bin/env python3 # -*- coding: utf-8 -*- # File : pad.py # Author : <NAME> <<EMAIL>> # Date : 01.11.2020 # Last Modified Date: 09.11.2021 # Last Modified By : <NAME> <<EMAIL>> # # Copyright (c) 2020, Imperial College, London # All rights reserved. # Redistribution and use in source and binary forms, with or without modification, # are permitted provided that the following conditions are met: # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # 3. Neither the name of Imperial College nor the names of its contributors may # be used to endorse or promote products derived from this software without # specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR # TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # pad sequences to maximum length for batch processing # code borrowed from keras_preprocessing (comes with MIT license) import numpy as np def pad_sequences(sequences, maxlen=None, dtype='int32', padding='pre', truncating='pre', value=0.): """Pads sequences to the same length. """ if not hasattr(sequences, '__len__'): raise ValueError('`sequences` must be iterable.') total_samples = len(sequences) lengths = [] sample_shape = () flag = True for x in sequences: try: lengths.append(len(x)) if flag and len(x): sample_shape = np.asarray(x).shape[1:] flag = False except TypeError: raise ValueError('`sequences` must be a list of iterables. ' 'Found non-iterable: ' + str(x)) if maxlen is None: maxlen = np.max(lengths) is_dtype_str = np.issubdtype(dtype, np.str_) or np.issubdtype(dtype, np.unicode_) if isinstance(value, str) and dtype != object and not is_dtype_str: raise ValueError("`dtype` {} is not compatible with `value`'s type: {}\n" "You should set `dtype=object` for variable length strings." .format(dtype, type(value))) x = np.full((total_samples, maxlen) + sample_shape, value, dtype=dtype) for idx, s in enumerate(sequences): if not len(s): continue # empty list/array was found if truncating == 'pre': trunc = s[-maxlen:] elif truncating == 'post': trunc = s[:maxlen] else: raise ValueError('Truncating type "%s" ' 'not understood' % truncating) # check `trunc` has expected shape trunc = np.asarray(trunc, dtype=dtype) if trunc.shape[1:] != sample_shape: raise ValueError('Shape of sample %s of sequence at position %s ' 'is different from expected shape %s' % (trunc.shape[1:], idx, sample_shape)) if padding == 'post': x[idx, :len(trunc)] = trunc elif padding == 'pre': x[idx, -len(trunc):] = trunc else: raise ValueError('Padding type "%s" not understood' % padding) return x
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tools/gen-precalc-tables.py
andrejo/zxmaze3d
4
42110
#! /usr/bin/env python3 import math import decimal N_DIRECTIONS = 256 # If rounded up to 384 and last element has max value, it has the bit # pattern, that prevents bisection from searching past the last element. N_PRECALC_DRAW_DIST = 384 # Python round() uses "banker's rounding", i.e. "round half even" def round_half_up(d): return int(decimal.Decimal(d).to_integral_value(rounding=decimal.ROUND_HALF_UP)) def fixed_from_float(d): if d >= 127.0: return 0x7FFF elif d <= -128.0: return -0x8000 elif d >= 0.0: return round_half_up(d * 256.0) else: return round_half_up(-d * -256.0) def float_from_fixed(f): return f/256.0 def phi_from_direction(i): return i * 2.0 * math.pi / N_DIRECTIONS def generate_array(f, el_type, name, comment, n_el, geterateValue): f.write(f"// {comment}\n") f.write(f"{el_type} {name}[] = {{") for i in range(n_el): if (i > 0): f.write(",") f.write("\n") f.write(str(geterateValue(i))) f.write("};\n") def generate_direction_array(f, el_type, name, func, comment=None): generate_array(f, el_type, name, comment if comment else name, N_DIRECTIONS, lambda i : func(i, phi_from_direction(i), math.sin(phi_from_direction(i)), math.cos(phi_from_direction(i)))) def generate_distance_array(f, el_type, name, func, comment=None): generate_array(f, el_type, name, comment if comment else name, N_PRECALC_DRAW_DIST, lambda i : func(i, 16*i)) f = open("../tables.c", "w") f.write("// Precalculated Look-up tables\n") f.write("// Generated by " + __file__ + "\n") f.write("\n") f.write("#include <stdlib.h>\n") f.write("\n") generate_direction_array(f, "int", "f_dir_sin", \ lambda i, phi, sin_phi, cos_phi : fixed_from_float(sin_phi)) generate_direction_array(f, "int", "f_dir_cos", \ lambda i, phi, sin_phi, cos_phi : fixed_from_float(cos_phi)) generate_direction_array(f, "int", "f_dir_ctan", \ lambda i, phi, sin_phi, cos_phi : fixed_from_float(cos_phi / sin_phi if sin_phi != 0.0 else (127.0 if cos_phi > 0 else -128.0)), comment="ctan of direction, saturated") generate_direction_array(f, "int", "f_dir_tan", \ lambda i, phi, sin_phi, cos_phi : fixed_from_float(sin_phi / cos_phi if cos_phi != 0.0 else (127.0 if sin_phi > 0 else -128.0)), comment="tan of direction, saturated") generate_distance_array(f, "long", "f16_sqrs", \ lambda distidx, f_dist: (f_dist * f_dist) if (distidx < N_PRECALC_DRAW_DIST-1) else 0x7FFFFFFF, comment="Squares of distance, in 16-shifted fixed point, for fast sqrt") def gen_height(distidx, f_dist): if f_dist > 0: height = round_half_up(65.0 / float_from_fixed(f_dist)) result = 95 - height; return max(result, 0); else: return 0 generate_distance_array(f, "uchar", "draw_heigths", gen_height, comment="Heights of given distance index") def gen_height1(distidx, f_dist): if f_dist > 0: height = round_half_up(100.0 / float_from_fixed(f_dist)) result = 97 + height; return min(result, 191); else: return 191 generate_distance_array(f, "uchar", "draw_heigths1", gen_height1, comment="Heights of given distance index") def gen_height(distidx, f_dist): N_INTENSITIES = 17 INTENSITY_WHITE = 16 if f_dist > 0: distance = float_from_fixed(f_dist) intensity = INTENSITY_WHITE - round_half_up((16.0 * (1.0 / ((distance + 2.0) * 0.34)))) return max(0, min(intensity, INTENSITY_WHITE)); else: return 0 generate_distance_array(f, "uchar", "draw_intens", gen_height, comment="Color intensities of given distance index") f.close()
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library/cohesity_agent.py
cohesity/cohesity-ansible-role
10
146876
#!/usr/bin/python # Copyright (c) 2018 Cohesity Inc # Apache License Version 2.0 from __future__ import (absolute_import, division, print_function) __metaclass__ = type import json import os import shutil import time from ansible.module_utils.basic import AnsibleModule from ansible.module_utils._text import to_bytes, to_native from ansible.module_utils.urls import open_url, urllib_error from tempfile import mkstemp, mkdtemp try: # => When unit testing, we need to look in the correct location however, when run via ansible, # => the expectation is that the modules will live under ansible. from module_utils.storage.cohesity.cohesity_utilities import cohesity_common_argument_spec, \ raise__cohesity_exception__handler, REQUEST_TIMEOUT from module_utils.storage.cohesity.cohesity_auth import get__cohesity_auth__token except Exception as e: from ansible.module_utils.storage.cohesity.cohesity_utilities import cohesity_common_argument_spec, \ raise__cohesity_exception__handler, REQUEST_TIMEOUT from ansible.module_utils.storage.cohesity.cohesity_auth import get__cohesity_auth__token ANSIBLE_METADATA = { 'metadata_version': '1.0', 'supported_by': 'community', 'status': ['preview'] } DOCUMENTATION = ''' module: cohesity_agent short_description: Management of Cohesity Physical Agent description: - Ansible Module used to deploy or remove the Cohesity Physical Agent from supported Linux Machines. - When executed in a playbook, the Cohesity Agent installation will be validated and the appropriate - state action will be applied. The most recent version of the Cohesity Agent will be automatically - downloaded to the host. version_added: '2.6.5' author: - <NAME> (github.com/exospheredata) - Cohesity, Inc options: state: description: - Determines if the agent should be C(present) or C(absent) from the host choices: - present - absent default: 'present' download_location: description: - Optional directory path to which the installer will be downloaded. If not selected, then a temporary - directory will be created in the default System Temp Directory. When choosing an alternate directory, - the directory and installer will not be deleted at the end of the execution. service_user: description: - Username underwhich the Cohesity Agent will be installed and run. - This user must exist unless I(create_user=True) is also configured. - This user must be an existing user for native installation. default: 'cohesityagent' for script based installation service_group: description: - Group underwhich permissions will be configured for the Cohesity Agent configuration. - This group must exist unless I(create_user=True) is also configured. - This parameter doesn't apply for native installation default: 'cohesityagent' for script based installation create_user: description: - When enabled, will create a new user and group based on the values of I(service_user) and I(service_group) - This parameter does not apply for native installations type: bool default: True file_based: description: - When enabled, will install the agent in non-LVM mode and support only file based backups type: bool default: False native_package: description: - When enabled, native installer packages are used based on the operating system type: bool default: False download_uri: description: - The download uri from where the installer can be downloaded default: '' operating_system: description: - ansible_distribution from facts, this value is automatically populated. Not given by module user extends_documentation_fragment: - cohesity requirements: [] ''' EXAMPLES = ''' # Install the current version of the agent on Linux - cohesity_agent: server: cohesity.lab cohesity_admin: admin cohesity_password: password state: present # Install the current version of the agent with custom User and Group - cohesity_agent: server: cohesity.lab cohesity_admin: admin cohesity_password: password state: present service_user: cagent service_group: cagent create_user: True # Removes the current installed agent from the host - cohesity_agent: server: cohesity.lab cohesity_admin: admin cohesity_password: password state: absent # Download the agent installer to a custom location. - cohesity_agent: server: cohesity.lab cohesity_admin: admin cohesity_password: password download_location: /software/installers state: present # Install the current version of the agent on Linux using native installers, the service user here should be an # existing user - cohesity_agent: server: cohesity.lab cohesity_admin: admin cohesity_password: password state: present service_user: cagent native_package: True # Install the cohesity agent using native package downloaded from given URI. Here, the Cohesity cluster credentials are not required - cohesity_agent: state: present service_user: cagent native_package: True download_uri: 'http://10.2.145.47/files/bin/installers/el-cohesity-agent-6.3-1.x86_64.rpm' ''' RETURN = ''' ''' SLEEP_TIME_SECONDS = 120 SECONDS_MINUTES_CONVERSION = 60 class InstallError(Exception): pass def verify_dependencies(): # => TODO: Need to add package dependency checks for: # => wget, rsync, lsof, nfs-utils, lvm2 pass def check_agent(module, results): # => Determine if the Cohesity Agent is currently installed aix_agent_path = "/usr/local/cohesity/agent/aix_agent.sh" def_agent_path = "/etc/init.d/cohesity-agent" # Look for default ansible agent path and aix agent path. agent_path = def_agent_path if os.path.exists(def_agent_path) else \ aix_agent_path if os.path.exists(aix_agent_path) else None if agent_path: cmd = "%s version" % agent_path rc, out, err = module.run_command(cmd) split_out = out.split("\n") version = "" for v in split_out: if v.startswith('Version'): version = v.split(" ")[-1] break if version: # => When the agent is installed, we should be able to return # => the version information results['version'] = version else: # => If this didn't return a Version, then we have bigger problems # => and probably should try to re-install or force the uninstall. results['version'] = "unknown" results['check_agent'] = dict( stdout=out, stderr=err ) return results elif os.path.exists("/etc/cohesity-agent"): # => If the file is found then let's return an unknown state # => immediately results['version'] = "unknown" return results else: cmd = "ps -aux | grep crux/bin/linux_agent | grep -v python | awk '{print $2}'" rc, out, err = module.run_command( cmd, check_rc=True, use_unsafe_shell=True) if out: orphaned_agents = out.split("\n") for process in orphaned_agents: if process: try: cmd = "kill -9 {0}".format(process) except BaseException: cmd = "kill -9 %s" % (process) rc, out, err = module.run_command(cmd) if err: pattern = "No such process" if pattern in err: # => Since the kill command returned 'No such process' we will just continue pass else: results['changed'] = False results['Failed'] = True results['check_agent'] = dict( stdout=out, stderr=err ) results['process_id'] = process module.fail_json( msg="Failed to remove an orphaned Cohesity Agent service which is still running", **results) else: pass results['version'] = False return results else: # => If the files are not found then let's return False # => immediately results['version'] = False return results def download_agent(module, path): try: if module.params.get('operating_system') == "AIX": server = module.params.get('cluster') token = get__cohesity_auth__token(module) uri = "https://" + server + \ "/irisservices/api/v1/public/physicalAgents/download?hostType=kAix&agentType=kJava" headers = { "Accept": "application/octet-stream", "Authorization": "Bearer " + token, "user-agent": "cohesity-ansible/v2.3.0"} elif not module.params.get('download_uri'): os_type = "Linux" server = module.params.get('cluster') token = get__cohesity_auth__token(module) package_type = 'kScript' if module.params.get('native_package'): if module.params.get('operating_system') in ('CentOS', 'RedHat'): package_type = 'kRPM' elif module.params.get('operating_system') == 'SLES': package_type = 'kSuseRPM' elif module.params.get('operating_system') == 'Ubuntu': package_type = 'kDEB' uri = "https://" + server + \ "/irisservices/api/v1/public/physicalAgents/download?hostType=k" + os_type + '&pkgType=' + package_type headers = { "Accept": "application/octet-stream", "Authorization": "Bearer " + token, "user-agent": "cohesity-ansible/v2.3.0"} else: uri = module.params.get('download_uri') headers = { "Accept": "application/octet-stream", "user-agent": "cohesity-ansible/v2.3.0"} agent = open_url(url=uri, headers=headers, validate_certs=False, timeout=REQUEST_TIMEOUT) resp_headers = agent.headers if 'content-disposition' in resp_headers.keys(): filename = resp_headers['content-disposition'].split("=")[1] else: filename = 'cohesity-agent-installer' filename = path + "/" + filename try: f = open(filename, "wb") f.write(agent.read()) os.chmod(filename, 0o755) except Exception as e: raise InstallError(e) finally: f.close() except urllib_error.HTTPError as e: error_msg = json.loads(e.read()) if 'message' in error_msg: module.fail_json( msg="Failed to download the Cohesity Agent", reason=error_msg['message']) else: raise__cohesity_exception__handler(e, module) except urllib_error.URLError as e: # => Capture and report any error messages. raise__cohesity_exception__handler(e.read(), module) except Exception as error: raise__cohesity_exception__handler(error, module) return filename def installation_failures(module, stdout, rc, message): # => The way that this installer works, we will not get back messages in stderr # => when a failure occurs. For this reason, we need to jump through some hoops # => to extract the error messages. The install will *Partially* complete even # => if certain dependencies are missing. # => # => This block of code will first split the stdout into a List of strings that # => we will filter for any line which contains *Error:*. Those lines will be # => returned to a new list *stderr* which will be formatted into a \n delimited # => string as the final step, we will raise a module failure to halt progress. stdout_lines = stdout.split("\n") # => Grab any Line that begins with Error: stderr = [k for k in stdout_lines if 'Error:' in k] stderr = "\n".join(stderr) # => Grab any Line that begins with WARNING: stdwarn = [k for k in stdout_lines if 'WARNING:' in k] stdwarn = "\n".join(stdwarn) module.fail_json( changed=False, msg=message, error=stderr, output=stdout, warn=stdwarn, exitcode=rc) def install_agent(module, installer, native): # => This command will run the self-extracting installer for the agent on machine and # => suppress opening a new window (nox11) and not show the extraction (noprogress) results # => which end up in stderr. # # => Note: Python 2.6 doesn't fully support the new string formatters, so this # => try..except will give us a clean backwards compatibility. if not native: install_opts = "--create-user " + \ str(int(module.params.get('create_user'))) + " " if module.params.get('service_user'): install_opts += "--service-user " + \ module.params.get('service_user') + " " if module.params.get('service_group'): install_opts += "--service-group " + \ module.params.get('service_group') + " " if module.params.get('file_based'): install_opts += "--skip-lvm-check " try: cmd = "{0}/setup.sh --install --yes {1}".format( installer, install_opts) except Exception as e: cmd = "%s/setup.sh --install --yes %s" % (installer, install_opts) else: try: if module.params.get('service_user'): user = module.params.get('service_user') if module.params.get('operating_system') == "Ubuntu": cmd = "sudo COHESITYUSER={0} dpkg -i {1}".format(user, installer) elif module.params.get('operating_system') in ("CentOS", "RedHat"): cmd = "sudo COHESITYUSER={0} rpm -i {1}".format(user, installer) elif module.params.get('operating_system') == "AIX": cmd = "sudo COHESITYUSER={0} installp -ad {1} all".format(user, installer) else: installation_failures( module, "", "", str(module.params.get('operating_system')) + " isn't supported by cohesity ansible module") except Exception as e: if module.params.get('operating_system') == "Ubuntu": cmd = "sudo COHESITYUSER=%s dpkg -i %s" % (user, installer) elif module.params.get('operating_system') in ("CentOS", "RedHat"): cmd = "sudo COHESITYUSER=%s rpm -i %s" % (user, installer) rc, stdout, stderr = module.run_command(cmd, cwd=installer) # => Any return code other than 0 is considered a failure. if rc: installation_failures( module, stdout, rc, "Cohesity Agent is partially installed") return (True, "Successfully Installed the Cohesity agent") def extract_agent(module, filename): # => This command will run the self-extracting installer in no execution mode # # => Note: Python 2.6 doesn't fully support the new string formatters, so this # => try..except will give us a clean backwards compatibility. directory = os.path.dirname(os.path.abspath(filename)) target = directory + "/install_files" create_download_dir(module, target) try: cmd = "{0} --nox11 --noexec --target {1} ".format(filename, target) except Exception as e: cmd = "%s --nox11 --noexec --target %s " % (filename, target) rc, stdout, stderr = module.run_command(cmd) # => Any return code other than 0 is considered a failure. if rc: installation_failures( module, stdout, rc, "Cohesity Agent is partially installed") return (True, "Successfully Installed the Cohesity agent", target) def remove_agent(module, installer, native): # => This command will run the self-extracting installer for the agent on machine and # => suppress opening a new window (nox11) and not show the extraction (noprogress) results # => which end up in stderr. # # => Note: Python 2.6 doesn't fully support the new string formatters, so this # => try..except will give us a clean backwards compatibility. if not native: try: cmd = "{0}/setup.sh --full-uninstall --yes".format(installer) except Exception as e: cmd = "%s/setup.sh --full-uninstall --yes" % (installer) rc, out, err = module.run_command(cmd, cwd=installer) # => Any return code other than 0 is considered a failure. if rc: installation_failures( module, out, rc, "Cohesity Agent is partially installed") else: if module.params.get('operating_system') == "AIX": cmd = "installp -u cohesity_agent.rte" rc, out, err = module.run_command(cmd) if rc: installation_failures( module, stdout, rc, "Failed to uninstall cohesity agent") elif module.params.get('operating_system') == "Ubuntu": cmd = "sudo dpkg -P cohesity-agent" rc, stdout, stderr = module.run_command(cmd) if rc: installation_failures( module, stdout, rc, "Failed to uninstall cohesity agent ") elif module.params.get('operating_system') in ("CentOS", "RedHat"): cmd = "sudo rpm -e cohesity-agent" rc, stdout, stderr = module.run_command(cmd) if rc: installation_failures( module, stdout, rc, "Failed to uninstall cohesity agent") cmd = "sudo rm -rf /etc/cohesity-agent" rc, stdout, stderr = module.run_command(cmd) if rc: installation_failures( module, stdout, rc, "The cohesity agent is uninstalled but failed to remove /etc/cohesity-agent") else: installation_failures( module, "", "", str(module.params.get('operating_system')) + " is not supported by cohesity ansible module") return (True, "Successfully Removed the Cohesity agent") def create_download_dir(module, dir_path): # => Note: 2018-12-06 # => Added this method to provide an alternate parameter to download the installer. # => This code was almost entirely pulled out of the Ansible File module. curpath = '' # => Determine if the download directory exists and if not then create it. for dirname in dir_path.strip('/').split('/'): curpath = '/'.join([curpath, dirname]) # Remove leading slash if we're creating a relative path if not os.path.isabs(dir_path): curpath = curpath.lstrip('/') b_curpath = to_bytes(curpath, errors='surrogate_or_strict') if not os.path.exists(b_curpath): try: os.mkdir(b_curpath) except OSError as ex: import errno # Possibly something else created the dir since the os.path.exists # check above. As long as it's a dir, we don't need to error # out. if not (ex.errno == errno.EEXIST and os.path.isdir(b_curpath)): raise def get_source_details(module, source_id): ''' Get protection source details :param module: object that holds parameters passed to the module :param source_id: protection source id :return: ''' server = module.params.get('cluster') validate_certs = module.params.get('validate_certs') token = get__cohesity_auth__token(module) try: if source_id: uri = "https://" + server + \ "/irisservices/api/v1/public/protectionSources?id=" + str(source_id) else: uri = "https://" + server + \ "/irisservices/api/v1/public/protectionSources?environments=kPhysical" headers = {"Accept": "application/json", "Authorization": "Bearer " + token, "user-agent": "cohesity-ansible/v2.3.0"} response = open_url( url=uri, headers=headers, validate_certs=validate_certs, method="GET", timeout=REQUEST_TIMEOUT) response = json.loads(response.read()) if source_id: nodes = response else: nodes = response[0]['nodes'] source_details = dict() for source in nodes: if source['protectionSource']['name'] == module.params.get('host'): source_details['agent'] =\ source['protectionSource']['physicalProtectionSource']['agents'][0] source_details['id'] = source['protectionSource']['id'] if not source_details: module.fail_json( changed=False, msg="Can't find the host on the cluster") return source_details except urllib_error.URLError as e: # => Capture and report any error messages. raise__cohesity_exception__handler(e.read(), module) except Exception as error: raise__cohesity_exception__handler(error, module) def update_agent(module): ''' upgrades the agent on physical servers :param module: object that holds parameters passed to the module :return: ''' server = module.params.get('cluster') validate_certs = module.params.get('validate_certs') token = get__cohesity_auth__token(module) result = dict( changed=False, msg='', version='' ) try: source_details = get_source_details(module, None) if source_details['agent']['upgradability'] == 'kUpgradable': uri = "https://" + server + \ "/irisservices/api/v1/public/physicalAgents/upgrade" headers = {"Accept": "application/json", "Authorization": "Bearer " + token, "user-agent": "cohesity-ansible/v2.3.0"} payload = { "agentIds": [source_details['agent']['id']] } response = open_url( url=uri, data=json.dumps(payload), headers=headers, validate_certs=validate_certs, method="POST", timeout=REQUEST_TIMEOUT) wait_time = module.params.get('wait_minutes') while wait_time > 0: poll_source_details = get_source_details(module, source_details['id']) if not poll_source_details: result['changed'] = True result['msg'] = "Update agent request is accepted but failed to check agent" \ " status during upgrade wait time" result['version'] = source_details['agent']['version'] module.exit_json(**result) elif poll_source_details['agent'].get('upgradeStatusMessage', ''): module.fail_json( changed=False, msg="Failed to upgrade agent. " + poll_source_details['agent']['upgradeStatusMessage']) elif poll_source_details['agent']['upgradeStatus'] == 'kFinished': result['changed'] = True result['msg'] = "Successfully upgraded the agent" result['version'] = poll_source_details['agent']['version'] module.exit_json(**result) time.sleep(SLEEP_TIME_SECONDS) wait_time = wait_time - (SLEEP_TIME_SECONDS/SECONDS_MINUTES_CONVERSION) result['changed'] = True result['msg'] = "The agent upgrade request is accepted." \ " The upgrade is not finished in the wait time" result['version'] = source_details['agent']['version'] module.exit_json(**result) elif source_details['agent']['upgradability'] == 'kCurrent': result['msg'] = "The host has the latest agent version" result['version'] = source_details['agent']['version'] module.exit_json(**result) elif source_details['agent']['upgradability'] == 'kNonUpgradableAgentIsNewer': result['msg'] = "The agent version running on the host is newer" \ " than the agent version on the cluster" result['version'] = source_details['agent']['version'] module.exit_json(**result) elif source_details['agent']['upgradability'] == 'kNonUpgradableAgentIsOld': module.fail_json( changed=False, msg="The agent version running on the host is too old to support upgrades") else: module.fail_json( changed=False, msg="Can't upgrade the agent due to unknown or invalid" " agent version running on the host") except urllib_error.URLError as e: # => Capture and report any error messages. raise__cohesity_exception__handler(e.read(), module) except Exception as error: raise__cohesity_exception__handler(error, module) def main(): # => Load the default arguments including those specific to the Cohesity Agent. argument_spec = cohesity_common_argument_spec() argument_spec.update( dict( state=dict(choices=['present', 'absent'], default='present'), download_location=dict(default=''), service_user=dict(default='cohesityagent'), service_group=dict(default='cohesityagent'), create_user=dict(default=True, type='bool'), file_based=dict(default=False, type='bool'), native_package=dict(default=False, type='bool'), download_uri=dict(defaut=''), operating_system=dict(defalut="", type='str'), host=dict(type='str', default=''), upgrade=dict(type='bool', default=False), wait_minutes=dict(type='int', default=30), ) ) # => Create a new module object module = AnsibleModule(argument_spec=argument_spec, supports_check_mode=True) results = dict( changed=False, version=False, state=module.params.get('state') ) # => Make a temporary directory to house the downloaded installer. if module.params.get('download_location'): tempdir = module.params.get('download_location') create_download_dir(module, tempdir) else: tempdir = mkdtemp( prefix="ansible." ) # Agent installation for AIX operating system is done using native package. if module.params.get('operating_system') == "AIX": module.params['native_package'] = True success = True try: if module.check_mode: results = check_agent(module, results) check_mode_results = dict( changed=False, msg="Check Mode: Agent is Currently not Installed", version="" ) if module.params.get('state') == "present": if results['version']: check_mode_results[ 'msg'] = "Check Mode: Agent is currently installed. No changes" else: check_mode_results[ 'msg'] = "Check Mode: Agent is currently not installed. This action would install the Agent." check_mode_results['version'] = results['version'] else: if results['version']: check_mode_results[ 'msg'] = "Check Mode: Agent is currently installed. This action would uninstall the Agent." check_mode_results['version'] = results['version'] else: check_mode_results[ 'msg'] = "Check Mode: Agent is currently not installed. No changes." module.exit_json(**check_mode_results) elif module.params.get('state') == "present" and not module.params.get('upgrade'): # => Check if the Cohesity Agent is currently installed and only trigger the install # => if the agent does not exist. results = check_agent(module, results) if not results['version']: if not module.params.get('native_package'): results['filename'] = download_agent(module, tempdir) results['changed'], results['message'], results['installer'] = extract_agent( module, results['filename']) results['changed'], results['message'] = install_agent( module, results['installer'], False) results = check_agent(module, results) else: results['filename'] = download_agent(module, tempdir) results['changed'], results['message'] = install_agent(module, results['filename'], True) results = check_agent(module, results) elif results['version'] == "unknown": # => There is a problem that we should invesitgate. module.fail_json( msg="Cohesity Agent is partially installed", **results) else: # => If we received a valid version then the assumption will be # => that the Agent is installed. We should simply pass it foward # => and act like things are normal. pass elif module.params.get('state') == "present" and module.params.get('upgrade'): if not module.params.get('host'): module.fail_json( changed=False, msg="The host parameter is required for agent upgrades") update_agent(module) elif module.params.get('state') == "absent": # => Check if the Cohesity Agent is currently installed and only trigger the uninstall # => if the agent exists. results = check_agent(module, results) # => If anything is returned, we should remove the agent. We also don't care if there # => is any output from the check so we will pop that out of the results to clean up # => our return data. if results['version']: if not module.params.get('native_package'): results.pop('check_agent', None) # => When removing the agent, we will need to download the installer once again, # => and then run the --full-uninstall command. results['filename'] = download_agent(module, tempdir) results['changed'], results['message'], results['installer'] = extract_agent( module, results['filename']) results['changed'], results['message'] = remove_agent( module, results['installer'], False) else: results['changed'], results['message'] = remove_agent(module, "", True) else: # => This error should never happen based on the set assigned to the parameter. # => However, in case, we should raise an appropriate error. module.fail_json(msg="Invalid State selected: {0}".format( module.params.get('state')), changed=False) except Exception as error: # => The exception handler should still trigger but just in case, let's set this # => variable 'success' to be False. success = False # => Call the proper error handler. msg = "Unexpected error caused while managing the Cohesity Linux Agent." raise__cohesity_exception__handler(error, module, msg) finally: # => We should delete the downloaded installer regardless of our success. This could be debated # => either way but seems like a better choice. if module.params.get('download_location'): if 'installer' in results: shutil.rmtree(results['installer']) else: shutil.rmtree(tempdir) if success: # -> Return Ansible JSON module.exit_json(**results) else: module.fail_json(msg="Cohesity Agent Failed", **results) if __name__ == '__main__': main()
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3883, 29892, 2582, 1839, 9507, 11287, 13, 462, 1678, 2582, 1839, 15033, 7464, 2582, 1839, 4906, 2033, 353, 3349, 29918, 14748, 29898, 13, 462, 4706, 3883, 29892, 2582, 1839, 6252, 261, 7464, 7700, 29897, 13, 18884, 1683, 29901, 13, 462, 1678, 2582, 1839, 15033, 7464, 2582, 1839, 4906, 2033, 353, 3349, 29918, 14748, 29898, 5453, 29892, 12633, 5852, 29897, 13, 4706, 1683, 29901, 13, 9651, 396, 1149, 910, 1059, 881, 2360, 3799, 2729, 373, 278, 731, 9859, 304, 278, 3443, 29889, 13, 9651, 396, 1149, 2398, 29892, 297, 1206, 29892, 591, 881, 12020, 385, 8210, 1059, 29889, 13, 9651, 3883, 29889, 14057, 29918, 3126, 29898, 7645, 543, 13919, 4306, 4629, 29901, 426, 29900, 29913, 1642, 4830, 29898, 13, 18884, 3883, 29889, 7529, 29889, 657, 877, 3859, 1495, 511, 3939, 29922, 8824, 29897, 13, 1678, 5174, 8960, 408, 1059, 29901, 13, 4706, 396, 1149, 450, 3682, 7834, 881, 1603, 7135, 541, 925, 297, 1206, 29892, 1235, 29915, 29879, 731, 445, 13, 4706, 396, 1149, 2286, 525, 8698, 29915, 304, 367, 7700, 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source/upload_user_stats.py
CheyenneNS/metrics
0
174989
<reponame>CheyenneNS/metrics<gh_stars>0 import time import methods_upload_user_stats import datetime print("############################################") print("User Stats Upload (UTC): " + str(datetime.datetime.utcnow())) start_time = time.time() user_stats_dict = methods_upload_user_stats.get_user_info_from_auth2() user_stats_dict = methods_upload_user_stats.get_internal_users(user_stats_dict) user_stats_dict = methods_upload_user_stats.get_user_orgs_count(user_stats_dict) user_stats_dict = methods_upload_user_stats.get_user_narrative_stats(user_stats_dict) user_stats_dict = methods_upload_user_stats.get_institution_and_country(user_stats_dict) print("--- gather data %s seconds ---" % (time.time() - start_time)) methods_upload_user_stats.upload_user_data(user_stats_dict) print("--- including user info and user_stats upload %s seconds ---" % (time.time() - start_time))
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subversion/tests/cmdline/svnlook_tests.py
jmckaskill/subversion
1
129021
<reponame>jmckaskill/subversion #!/usr/bin/env python # # svnlook_tests.py: testing the 'svnlook' tool. # # Subversion is a tool for revision control. # See http://subversion.apache.org for more information. # # ==================================================================== # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. ###################################################################### # General modules import re, os, logging logger = logging.getLogger() # Our testing module import svntest # (abbreviation) Skip = svntest.testcase.Skip_deco SkipUnless = svntest.testcase.SkipUnless_deco XFail = svntest.testcase.XFail_deco Issues = svntest.testcase.Issues_deco Issue = svntest.testcase.Issue_deco Wimp = svntest.testcase.Wimp_deco Item = svntest.wc.StateItem #---------------------------------------------------------------------- # Convenience functions to make writing more tests easier def run_svnlook(*varargs): """Run svnlook with VARARGS, returns stdout as list of lines. Raises Failure if any stderr messages.""" exit_code, output, dummy_errput = svntest.main.run_command( svntest.main.svnlook_binary, 0, 0, *varargs) return output def expect(tag, expected, got): if expected != got: logger.warn("When testing: %s", tag) logger.warn("Expected: %s", expected) logger.warn(" Got: %s", got) raise svntest.Failure # Tests def test_misc(sbox): "test miscellaneous svnlook features" sbox.build() wc_dir = sbox.wc_dir repo_dir = sbox.repo_dir # Make a couple of local mods to files mu_path = os.path.join(wc_dir, 'A', 'mu') rho_path = os.path.join(wc_dir, 'A', 'D', 'G', 'rho') svntest.main.file_append(mu_path, 'appended mu text') svntest.main.file_append(rho_path, 'new appended text for rho') # Created expected output tree for 'svn ci' expected_output = svntest.wc.State(wc_dir, { 'A/mu' : Item(verb='Sending'), 'A/D/G/rho' : Item(verb='Sending'), }) # Create expected status tree; all local revisions should be at 1, # but mu and rho should be at revision 2. expected_status = svntest.actions.get_virginal_state(wc_dir, 1) expected_status.tweak('A/mu', 'A/D/G/rho', wc_rev=2) svntest.actions.run_and_verify_commit(wc_dir, expected_output, expected_status, None, wc_dir) # give the repo a new UUID uuid = "01234567-89ab-cdef-89ab-cdef01234567" svntest.main.run_command_stdin(svntest.main.svnadmin_binary, None, 0, 1, ["SVN-fs-dump-format-version: 2\n", "\n", "UUID: ", uuid, "\n", ], 'load', '--force-uuid', repo_dir) expect('youngest', [ '2\n' ], run_svnlook('youngest', repo_dir)) expect('uuid', [ uuid + '\n' ], run_svnlook('uuid', repo_dir)) # it would be nice to test the author too, but the current test framework # does not pull a username when testing over ra_neon or ra_svn, # so the commits have an empty author. expect('log', [ 'log msg\n' ], run_svnlook('log', repo_dir)) # check if the 'svnlook tree' output can be expanded to # the 'svnlook tree --full-paths' output if demanding the whole repository treelist = run_svnlook('tree', repo_dir) treelistfull = run_svnlook('tree', '--full-paths', repo_dir) path = '' treelistexpand = [] for entry in treelist: len1 = len(entry) len2 = len(entry.lstrip()) path = path[0:2*(len1-len2)-1] + entry.strip() + '\n' if path == '/\n': treelistexpand.append(path) else: treelistexpand.append(path[1:]) treelistexpand = svntest.verify.UnorderedOutput(treelistexpand) svntest.verify.compare_and_display_lines('Unexpected result from tree', '', treelistexpand, treelistfull) # check if the 'svnlook tree' output is the ending of # the 'svnlook tree --full-paths' output if demanding # any part of the repository treelist = run_svnlook('tree', repo_dir, '/A/B') treelistfull = run_svnlook('tree', '--full-paths', repo_dir, '/A/B') path = '' treelistexpand = [] for entry in treelist: len1 = len(entry) len2 = len(entry.lstrip()) path = path[0:2*(len1-len2)] + entry.strip() + '\n' treelistexpand.append('/A/' + path) treelistexpand = svntest.verify.UnorderedOutput(treelistexpand) svntest.verify.compare_and_display_lines('Unexpected result from tree', '', treelistexpand, treelistfull) treelist = run_svnlook('tree', repo_dir, '/') if treelist[0] != '/\n': raise svntest.Failure expect('propget svn:log', [ 'log msg' ], run_svnlook('propget', '--revprop', repo_dir, 'svn:log')) proplist = run_svnlook('proplist', '--revprop', repo_dir) proplist = sorted([prop.strip() for prop in proplist]) # We cannot rely on svn:author's presence. ra_svn doesn't set it. if not (proplist == [ 'svn:author', 'svn:date', 'svn:log' ] or proplist == [ 'svn:date', 'svn:log' ]): logger.warn("Unexpected result from proplist: %s", proplist) raise svntest.Failure prop_name = 'foo:bar-baz-quux' exit_code, output, errput = svntest.main.run_svnlook('propget', '--revprop', repo_dir, prop_name) expected_err = "Property '%s' not found on revision " % prop_name for line in errput: if line.find(expected_err) != -1: break else: raise svntest.main.SVNUnmatchedError exit_code, output, errput = svntest.main.run_svnlook('propget', '-r1', repo_dir, prop_name, '/') expected_err = "Property '%s' not found on path '/' in revision " % prop_name for line in errput: if line.find(expected_err) != -1: break else: raise svntest.main.SVNUnmatchedError #---------------------------------------------------------------------- # Issue 1089 @Issue(1089) def delete_file_in_moved_dir(sbox): "delete file in moved dir" sbox.build() wc_dir = sbox.wc_dir repo_dir = sbox.repo_dir # move E to E2 and delete E2/alpha E_path = os.path.join(wc_dir, 'A', 'B', 'E') E2_path = os.path.join(wc_dir, 'A', 'B', 'E2') svntest.actions.run_and_verify_svn(None, None, [], 'mv', E_path, E2_path) alpha_path = os.path.join(E2_path, 'alpha') svntest.actions.run_and_verify_svn(None, None, [], 'rm', alpha_path) # commit expected_output = svntest.wc.State(wc_dir, { 'A/B/E' : Item(verb='Deleting'), 'A/B/E2' : Item(verb='Adding'), 'A/B/E2/alpha' : Item(verb='Deleting'), }) expected_status = svntest.actions.get_virginal_state(wc_dir, 1) expected_status.remove('A/B/E', 'A/B/E/alpha', 'A/B/E/beta') expected_status.add({ 'A/B/E2' : Item(status=' ', wc_rev=2), 'A/B/E2/beta' : Item(status=' ', wc_rev=2), }) ### this commit fails. the 'alpha' node is marked 'not-present' since it ### is a deleted child of a move/copy. this is all well and proper. ### however, during the commit, the parent node is committed down to just ### the BASE node. at that point, 'alpha' has no parent in WORKING which ### is a schema violation. there is a plan for committing in this kind of ### situation, layed out in wc-ng-design. that needs to be implemented ### in order to get this commit working again. svntest.actions.run_and_verify_commit(wc_dir, expected_output, expected_status, None, wc_dir) exit_code, output, errput = svntest.main.run_svnlook("dirs-changed", repo_dir) if errput: raise svntest.Failure # Okay. No failure, but did we get the right output? if len(output) != 2: raise svntest.Failure if not ((output[0].strip() == 'A/B/') and (output[1].strip() == 'A/B/E2/')): raise svntest.Failure #---------------------------------------------------------------------- # Issue 1241 @Issue(1241) def test_print_property_diffs(sbox): "test the printing of property diffs" sbox.build() wc_dir = sbox.wc_dir repo_dir = sbox.repo_dir # Add a bogus property to iota iota_path = os.path.join(wc_dir, 'iota') svntest.actions.run_and_verify_svn(None, None, [], 'propset', 'bogus_prop', 'bogus_val', iota_path) # commit the change svntest.actions.run_and_verify_svn(None, None, [], 'ci', '-m', 'log msg', iota_path) # Grab the diff exit_code, expected_output, err = svntest.actions.run_and_verify_svn( None, None, [], 'diff', '-r', 'PREV', iota_path) exit_code, output, errput = svntest.main.run_svnlook("diff", repo_dir) if errput: raise svntest.Failure # Okay. No failure, but did we get the right output? if len(output) != len(expected_output): raise svntest.Failure canonical_iota_path = iota_path.replace(os.path.sep, '/') # replace wcdir/iota with iota in expected_output for i in range(len(expected_output)): expected_output[i] = expected_output[i].replace(canonical_iota_path, 'iota') # Check that the header filenames match. if expected_output[2].split()[1] != output[2].split()[1]: raise svntest.Failure if expected_output[3].split()[1] != output[3].split()[1]: raise svntest.Failure svntest.verify.compare_and_display_lines('', '', expected_output[4:], output[4:]) #---------------------------------------------------------------------- # Check that svnlook info repairs allows inconsistent line endings in logs. def info_bad_newlines(sbox): "svnlook info must allow inconsistent newlines" dump_str = """SVN-fs-dump-format-version: 2 UUID: dc40867b-38f6-0310-9f5f-f81aa277e06e Revision-number: 0 Prop-content-length: 56 Content-length: 56 K 8 svn:date V 27 2005-05-03T19:09:41.129900Z PROPS-END Revision-number: 1 Prop-content-length: 99 Content-length: 99 K 7 svn:log V 3 \n\r\n K 10 svn:author V 2 pl K 8 svn:date V 27 2005-05-03T19:10:19.975578Z PROPS-END Node-path: file Node-kind: file Node-action: add Prop-content-length: 10 Text-content-length: 5 Text-content-md5: e1cbb0c3879af8347246f12c559a86b5 Content-length: 15 PROPS-END text """ # load dumpfile with inconsistent newlines into repos. svntest.actions.load_repo(sbox, dump_str=dump_str, bypass_prop_validation=True) exit_code, output, errput = svntest.main.run_svnlook("info", sbox.repo_dir, "-r1") if errput: raise svntest.Failure def changed_copy_info(sbox): "test --copy-info flag on the changed command" sbox.build() wc_dir = sbox.wc_dir repo_dir = sbox.repo_dir # Copy alpha to /A/alpha2. E_path = os.path.join(wc_dir, 'A', 'B', 'E') alpha_path = os.path.join(wc_dir, 'A', 'B', 'E', 'alpha') alpha2_path = os.path.join(wc_dir, 'A', 'alpha2') svntest.actions.run_and_verify_svn(None, None, [], 'cp', alpha_path, alpha2_path) # commit expected_output = svntest.wc.State(wc_dir, { 'A/alpha2' : Item(verb='Adding'), }) expected_status = svntest.actions.get_virginal_state(wc_dir, 1) expected_status.add({ 'A/alpha2' : Item(status=' ', wc_rev=2), }) svntest.actions.run_and_verify_commit(wc_dir, expected_output, expected_status, None, wc_dir) exit_code, output, errput = svntest.main.run_svnlook("changed", repo_dir) if errput: raise svntest.Failure expect("changed without --copy-info", ["A A/alpha2\n"], output) exit_code, output, errput = svntest.main.run_svnlook("changed", repo_dir, "--copy-info") if errput: raise svntest.Failure expect("changed with --copy-info", ["A + A/alpha2\n", " (from A/B/E/alpha:r1)\n"], output) #---------------------------------------------------------------------- # Issue 2663 @Issue(2663) def tree_non_recursive(sbox): "test 'svnlook tree --non-recursive'" sbox.build() repo_dir = sbox.repo_dir expected_results_root = ('/', ' iota', ' A/') expected_results_deep = ('B/', ' lambda', ' E/', ' F/') # check the output of svnlook --non-recursive on the # root of the repository treelist = run_svnlook('tree', '--non-recursive', repo_dir) for entry in treelist: if not entry.rstrip() in expected_results_root: logger.warn("Unexpected result from tree with --non-recursive:") logger.warn(" entry : %s", entry.rstrip()) raise svntest.Failure if len(treelist) != len(expected_results_root): logger.warn("Expected %i output entries, found %i", len(expected_results_root), len(treelist)) raise svntest.Failure # check the output of svnlook --non-recursive on a # subdirectory of the repository treelist = run_svnlook('tree', '--non-recursive', repo_dir, '/A/B') for entry in treelist: if not entry.rstrip() in expected_results_deep: logger.warn("Unexpected result from tree with --non-recursive:") logger.warn(" entry : %s", entry.rstrip()) raise svntest.Failure if len(treelist) != len(expected_results_deep): logger.warn("Expected %i output entries, found %i", len(expected_results_deep), len(treelist)) raise svntest.Failure #---------------------------------------------------------------------- def limit_history(sbox): "history --limit" sbox.build(create_wc=False) repo_url = sbox.repo_url svntest.actions.run_and_verify_svn(None, None, [], 'mv', '-m', 'log msg', repo_url + "/iota", repo_url + "/iota2") svntest.actions.run_and_verify_svn(None, None, [], 'mv', '-m', 'log msg', repo_url + "/A/mu", repo_url + "/iota") history = run_svnlook("history", "--limit=1", sbox.repo_dir) # Ignore the two lines of header, and verify expected number of items. if len(history[2:]) != 1: raise svntest.Failure("Output not limited to expected number of items") #---------------------------------------------------------------------- def diff_ignore_whitespace(sbox): "test 'svnlook diff -x -b' and 'svnlook diff -x -w'" sbox.build() repo_dir = sbox.repo_dir wc_dir = sbox.wc_dir # Make whitespace-only changes to mu mu_path = os.path.join(wc_dir, 'A', 'mu') svntest.main.file_write(mu_path, "This is the file 'mu'.\n", "wb") # Created expected output tree for 'svn ci' expected_output = svntest.wc.State(wc_dir, { 'A/mu' : Item(verb='Sending'), }) # Create expected status tree; all local revisions should be at 1, # but mu should be at revision 2. expected_status = svntest.actions.get_virginal_state(wc_dir, 1) expected_status.tweak('A/mu', wc_rev=2) svntest.actions.run_and_verify_commit(wc_dir, expected_output, expected_status, None, wc_dir) # Check the output of 'svnlook diff -x --ignore-space-change' on mu. # It should not print anything. output = run_svnlook('diff', '-r2', '-x', '--ignore-space-change', repo_dir) if output != []: raise svntest.Failure # Check the output of 'svnlook diff -x --ignore-all-space' on mu. # It should not print anything. output = run_svnlook('diff', '-r2', '-x', '--ignore-all-space', repo_dir) if output != []: raise svntest.Failure #---------------------------------------------------------------------- def diff_ignore_eolstyle(sbox): "test 'svnlook diff -x --ignore-eol-style'" sbox.build() repo_dir = sbox.repo_dir wc_dir = sbox.wc_dir if os.name == 'nt': crlf = '\n' else: crlf = '\r\n' mu_path = os.path.join(wc_dir, 'A', 'mu') rev = 1 # do the --ignore-eol-style test for each eol-style for eol, eolchar in zip(['CRLF', 'CR', 'native', 'LF'], [crlf, '\015', '\n', '\012']): # rewrite file mu and set the eol-style property. svntest.main.file_write(mu_path, "This is the file 'mu'." + eolchar, 'wb') svntest.main.run_svn(None, 'propset', 'svn:eol-style', eol, mu_path) # Created expected output tree for 'svn ci' expected_output = svntest.wc.State(wc_dir, { 'A/mu' : Item(verb='Sending'), }) # Create expected status tree; all local revisions should be at # revision 1, but mu should be at revision rev + 1. expected_status = svntest.actions.get_virginal_state(wc_dir, 1) expected_status.tweak('A/mu', wc_rev=rev + 1) svntest.actions.run_and_verify_commit(wc_dir, expected_output, expected_status, None, wc_dir) # Grab the diff exit_code, expected_output, err = svntest.actions.run_and_verify_svn( None, None, [], 'diff', '-r', 'PREV', '-x', '--ignore-eol-style', mu_path) output = run_svnlook('diff', '-r', str(rev + 1), '-x', '--ignore-eol-style', repo_dir) rev += 1 canonical_mu_path = mu_path.replace(os.path.sep, '/') # replace wcdir/A/mu with A/mu in expected_output for i in range(len(expected_output)): expected_output[i] = expected_output[i].replace(canonical_mu_path, 'A/mu') # Check that the header filenames match. if expected_output[2].split()[1] != output[2].split()[1]: raise svntest.Failure if expected_output[3].split()[1] != output[3].split()[1]: raise svntest.Failure svntest.verify.compare_and_display_lines('', '', expected_output[4:], output[4:]) #---------------------------------------------------------------------- def diff_binary(sbox): "test 'svnlook diff' on binary files" sbox.build() repo_dir = sbox.repo_dir wc_dir = sbox.wc_dir # Set A/mu to a binary mime-type, tweak its text, and commit. mu_path = os.path.join(wc_dir, 'A', 'mu') svntest.main.file_append(mu_path, 'new appended text for mu') svntest.main.run_svn(None, 'propset', 'svn:mime-type', 'application/octet-stream', mu_path) svntest.main.run_svn(None, 'ci', '-m', 'log msg', mu_path) # Now run 'svnlook diff' and look for the "Binary files differ" message. output = run_svnlook('diff', repo_dir) if not "(Binary files differ)\n" in output: raise svntest.Failure("No 'Binary files differ' indication in " "'svnlook diff' output.") #---------------------------------------------------------------------- def test_filesize(sbox): "test 'svnlook filesize'" sbox.build() repo_dir = sbox.repo_dir wc_dir = sbox.wc_dir tree_output = run_svnlook('tree', '--full-paths', repo_dir) for line in tree_output: # Drop line endings line = line.rstrip() # Skip directories if line[-1] == '/': continue # Run 'svnlook cat' and measure the size of the output. cat_output = run_svnlook('cat', repo_dir, line) cat_size = len("".join(cat_output)) # Run 'svnlook filesize' and compare the results with the CAT_SIZE. filesize_output = run_svnlook('filesize', repo_dir, line) if len(filesize_output) != 1: raise svntest.Failure("'svnlook filesize' printed something other than " "a single line of output.") filesize = int(filesize_output[0].strip()) if filesize != cat_size: raise svntest.Failure("'svnlook filesize' and the counted length of " "'svnlook cat's output differ for the path " "'%s'." % (line)) #---------------------------------------------------------------------- def verify_logfile(logfilename, expected_data): if os.path.exists(logfilename): fp = open(logfilename) else: raise svntest.verify.SVNUnexpectedOutput("hook logfile %s not found"\ % logfilename) actual_data = fp.readlines() fp.close() os.unlink(logfilename) svntest.verify.compare_and_display_lines('wrong hook logfile content', 'STDOUT', expected_data, actual_data) def test_txn_flag(sbox): "test 'svnlook * -t'" sbox.build() repo_dir = sbox.repo_dir wc_dir = sbox.wc_dir logfilepath = os.path.join(repo_dir, 'hooks.log') # List changed dirs and files in this transaction hook_template = """import sys,os,subprocess svnlook_bin=%s fp = open(os.path.join(sys.argv[1], 'hooks.log'), 'wb') def output_command(fp, cmd, opt): command = [svnlook_bin, cmd, '-t', sys.argv[2], sys.argv[1]] + opt process = subprocess.Popen(command, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=False, bufsize=-1) (output, errors) = process.communicate() status = process.returncode fp.write(output) fp.write(errors) return status for (svnlook_cmd, svnlook_opt) in %s: output_command(fp, svnlook_cmd, svnlook_opt.split()) fp.close()""" pre_commit_hook = svntest.main.get_pre_commit_hook_path(repo_dir) # 1. svnlook 'changed' -t and 'dirs-changed' -t hook_instance = hook_template % (repr(svntest.main.svnlook_binary), repr([('changed', ''), ('dirs-changed', '')])) svntest.main.create_python_hook_script(pre_commit_hook, hook_instance) # Change files mu and rho A_path = os.path.join(wc_dir, 'A') mu_path = os.path.join(wc_dir, 'A', 'mu') rho_path = os.path.join(wc_dir, 'A', 'D', 'G', 'rho') svntest.main.file_append(mu_path, 'appended mu text') svntest.main.file_append(rho_path, 'new appended text for rho') # commit, and check the hook's logfile svntest.actions.run_and_verify_svn(None, None, [], 'ci', '-m', 'log msg', wc_dir) svntest.actions.run_and_verify_svn(None, None, [], 'up', wc_dir) expected_data = [ 'U A/D/G/rho\n', 'U A/mu\n', 'A/\n', 'A/D/G/\n' ] verify_logfile(logfilepath, expected_data) # 2. svnlook 'propget' -t, 'proplist' -t # 2. Change a dir and revision property hook_instance = hook_template % (repr(svntest.main.svnlook_binary), repr([('propget', 'bogus_prop /A'), ('propget', '--revprop bogus_rev_prop'), ('proplist', '/A'), ('proplist', '--revprop')])) svntest.main.create_python_hook_script(pre_commit_hook, hook_instance) svntest.actions.run_and_verify_svn(None, None, [], 'propset', 'bogus_prop', 'bogus_val\n', A_path) svntest.actions.run_and_verify_svn(None, None, [], 'ci', '-m', 'log msg', wc_dir, '--with-revprop', 'bogus_rev_prop=bogus_rev_val\n') # Now check the logfile expected_data = [ 'bogus_val\n', 'bogus_rev_val\n', ' bogus_prop\n', ' svn:log\n', ' svn:author\n', # internal property, not really expected ' svn:check-locks\n', ' bogus_rev_prop\n', ' svn:date\n'] verify_logfile(logfilepath, svntest.verify.UnorderedOutput(expected_data)) def property_delete(sbox): "property delete" sbox.build() repo_dir = sbox.repo_dir sbox.simple_propset('foo', 'bar', 'A/mu') sbox.simple_commit() sbox.simple_propdel('foo', 'A/mu') sbox.simple_commit() # XFail since r1293375, changed and diff produce no output on a # property delete svntest.actions.run_and_verify_svnlook(None, ["_U A/mu\n"], [], 'changed', repo_dir) ######################################################################## # Run the tests # list all tests here, starting with None: test_list = [ None, test_misc, delete_file_in_moved_dir, test_print_property_diffs, info_bad_newlines, changed_copy_info, tree_non_recursive, limit_history, diff_ignore_whitespace, diff_ignore_eolstyle, diff_binary, test_filesize, test_txn_flag, property_delete, ] if __name__ == '__main__': svntest.main.run_tests(test_list) # NOTREACHED ### End of file.
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src/EdgelistExtractor.py
centre-for-humanities-computing/ProdigalNetworks
0
58435
#!/usr/bin/env python # coding: utf-8 # import packages import re import pandas as pd from bs4 import BeautifulSoup from collections import defaultdict # Function definitions def extract_all_characters(soup): """ Function to extract characters from XML file of a play. Extracts the value of two tag attributes One relates to Act/Scene divisions and the other is for the name of the speaking character. These should be fairly clear from the code. This function should be modified to deal with different XML schema. """ idList = [] for a in soup.findAll(['div', 'sp']): if 'type' in a.attrs.keys(): idList.append(a.attrs['type']) elif 'who' in a.attrs.keys(): idList.append(a.attrs['who']) df = pd.DataFrame(idList, columns=['names']) return df def character_pairings_in(l): """ Function to create list of tuples of character pairings from extracted data This also (quite crudely) removes any Act or Scene divisions, which have all been tagged using an asterisk. """ # Create list from Pandas DF #l = dataframe[0].tolist() l = [x for x in l if str(x) != 'nan'] # Create pairings from list l2 = [(l[i],l[i+1]) for i in range(len(l)-1)] # Remove all Act and Scene markers #x = [[t for t in a if not '#' in t] for a in l2] # Keep only pairs of characters y = [row for row in l2 if len(row) > 1] # Create list of tuples character_pairings = [tuple(l) for l in y] return character_pairings def create_edgelist_from(pairs): """ Function to create edgelists for "speaking-in-turn" pairs Returns results in a way that will be useful in Gephi """ # Create edgelist using defaultDict edges = defaultdict(int) for people in pairs: for personA in people: for personB in people: if personA < personB: edges[personA + ",undirected," + personB] += 1 # Create a dataframe from the defaultDict df = pd.DataFrame.from_dict(edges, orient='index') df.reset_index(level=0, inplace=True) # Split cell on comma into muliple columns split = (df['index'].str.split(',', expand=True).rename(columns=lambda x: f"col{x+1}")) # Merge these split columns with the 'weights' from the first df merged = split.join(df[0]) # Rename columns for use in Gephi merged.columns = ["Source", "Type", "Target", "Weight"] return merged if __name__=="__main__": # List of filenames targets = ["KL", "ado", "2h4", "wt"] # Read in play and create BeautifulSoup object for target in targets: filename = f"/Users/au564346/Desktop/{target}.xml" with open(filename, 'r') as file: raw = file.read() soup = BeautifulSoup(raw, 'lxml') # Create list using extract function character_list = extract_all_characters(soup) # Cleaning #cleaned = pd.read_csv(f"{target}.csv", header=None) #merged = pd.merge(character_list, cleaned, left_on="names", right_on=0, how="left") #merged = merged[1].dropna() #merged = merged[~merged.str.contains('#')] # Create edgelist edgelist_df = create_edgelist_from(character_pairings_in(character_list)) print(edgelist_df) # Save to csv edgelist_df.to_csv(f"{target}.csv", sep=",", index=False, header=True)
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tests/test_utils/test_pywriting_utils.py
heylohousing/quickbase-client
0
549
import os from tempfile import TemporaryDirectory from quickbase_client.utils.pywriting_utils import BasicPyFileWriter from quickbase_client.utils.pywriting_utils import PyPackageWriter class TestBasicFileWriter: def test_outputs_lines(self): w = BasicPyFileWriter() w.add_line('import abc') w.add_line('import os').space() s = w.get_file_as_string() assert s == 'import abc\nimport os\n' def test_indent_dedent(self): w = BasicPyFileWriter() w.add_line('def foo():').indent().add_line('return 5').dedent().space() s = w.get_file_as_string() assert s == 'def foo():\n return 5\n' def test_use_refs(self): w = BasicPyFileWriter() w.add_line('a = "A"') ref = w.make_ref() w.add_line('d = "D"') ref.add_line('b = "B"').add_line('c = "C"') s = w.get_file_as_string() lns = s.split('\n') assert 'a' in lns[0] assert 'b' in lns[1] assert 'c' in lns[2] assert 'd' in lns[3] class TestPyPackageWriter: def test_includes_init(self): with TemporaryDirectory() as d: w = PyPackageWriter(pkg_name='foo', parent_dir=d) assert '__init__' in w.modules assert w.has_module_name('__init__') assert w.pkg_path == os.path.join(d, 'foo') w.write() assert os.path.exists(d) assert os.path.exists(os.path.join(d, 'foo')) assert os.path.exists(os.path.join(d, 'foo', '__init__.py'))
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runtests.py
luzfcb/django-versioning
0
61228
<gh_stars>0 # -*- coding: utf-8 -*- import os import sys def main(): from django.conf import settings settings.configure( DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': ':memory:' } }, INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'versioning', ], MIDDLEWARE_CLASSES = [ 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', "versioning.middleware.VersioningMiddleware", ], STATIC_URL = '/static/', TEST_RUNNER = 'django.test.simple.DjangoTestSuiteRunner', TEMPLATE_DIRS = [], DEBUG = True, TEMPLATE_DEBUG = True, ROOT_URLCONF = 'runtests', ) from django.conf.urls import patterns, include, url from django.contrib import admin global urlpatterns urlpatterns = patterns( '', url(r'^admin/', include(admin.site.urls)), url(r'^versioning/', include('versioning.urls')), ) admin.autodiscover() # Run the test suite, including the extra validation tests. from django.test.utils import get_runner TestRunner = get_runner(settings) test_runner = TestRunner(verbosity=1, interactive=False, failfast=False) failures = test_runner.run_tests(['versioning']) sys.exit(failures) if __name__ == "__main__": main()
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graph.py
lokkelvin2/dc_tts
25
129291
from data_load import load_vocab from hyperparams import Hyperparams as hp from networks import TextEnc, AudioEnc, AudioDec, Attention, SSRN import tensorflow as tf class Graph: def __init__(self, num=1, mode="train"): ''' Args: num: Either 1 or 2. 1 for Text2Mel 2 for SSRN. mode: Either "train" or "synthesize". ''' # Load vocabulary self.char2idx, self.idx2char = load_vocab() # Set flag training = True if mode=="train" else False # Graph # Data Feeding ## L: Text. (B, N), int32 ## mels: Reduced melspectrogram. (B, T/r, n_mels) float32 ## mags: Magnitude. (B, T, n_fft//2+1) float32 self.L = tf.placeholder(tf.int32, shape=(None, None)) self.mels = tf.placeholder(tf.float32, shape=(None, None, hp.n_mels)) self.prev_max_attentions = tf.placeholder(tf.int32, shape=(None,)) with tf.variable_scope("Text2Mel"): # Get S or decoder inputs. (B, T//r, n_mels) self.S = tf.concat((tf.zeros_like(self.mels[:, :1, :]), self.mels[:, :-1, :]), 1) # Networks with tf.variable_scope("TextEnc"): self.K, self.V = TextEnc(self.L, training=training) # (N, Tx, e) with tf.variable_scope("AudioEnc"): self.Q = AudioEnc(self.S, training=training) with tf.variable_scope("Attention"): # R: (B, T/r, 2d) # alignments: (B, N, T/r) # max_attentions: (B,) self.R, self.alignments, self.max_attentions = Attention(self.Q, self.K, self.V, mononotic_attention=(not training), prev_max_attentions=self.prev_max_attentions) with tf.variable_scope("AudioDec"): self.Y_logits, self.Y = AudioDec(self.R, training=training) # (B, T/r, n_mels) # During inference, the predicted melspectrogram values are fed. with tf.variable_scope("SSRN"): self.Z_logits, self.Z = SSRN(self.Y, training=training) with tf.variable_scope("gs"): self.global_step = tf.Variable(0, name='global_step', trainable=False)
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main.py
DonnC/retail-simulation
0
101951
<filename>main.py import simpy import random import os import datetime from transaction import transaction_from_dict from prettytable import PrettyTable # Specify the Column Names while initializing the Table myTable = PrettyTable( ["Agent", "Date", "Customer Number", "Amount", "Transaction Id"]) ACCOUNT_BALANCE = 10000.0 NUMBER_OF_AGENTS = 7 T_INTER = [30, 300] # Create an egent every [min, max] seconds AGENT_BALANCE = [500, 5500] # create [min, max] balance to allocate to agent SIM_TIME = 1000 # Simulation time in seconds # keep record transactions = [] fname = 'result.txt' if os.path.exists(fname): os.remove(fname) def write_to_file(info): ''' write stats to file ''' # print(info) with open(fname, 'a+') as f: f.write(str(info)) class Agent(): ''' registered agent, manages his own agent_balance allocated by owner ''' def __init__(self, env, name, allocated_balance: float) -> None: self.env = env self.name = name self.allocated_balance = allocated_balance # keep track of this agent allocated balance self.agent_balance = simpy.Container( env, allocated_balance, init=allocated_balance) def perform_sale(self, oab: simpy.Container): ''' agent to peform sale, sell airtime oab: owner actual current balance (actual_balance container instance) ''' while True: # generate random sale amount, with upper threshold to cater for excess sale amount sale_amount = random.randint(50, self.allocated_balance + 30) # first check if agent bal is enough to perform request if (sale_amount < self.agent_balance.level) and (oab.level > sale_amount): # proceed with transaction sale if sale_amount < 0: sale_amount = 0 self.agent_balance.get(amount=sale_amount) # update actual balance also oab.get(amount=sale_amount) write_to_file( f'[Agent: {self.name}] I performed a sale of ${sale_amount} | agent bal now : ${self.agent_balance.level} | owner balance: ${oab.level}\n\n') # add transaction history trans = { "agent": f"Agent {self.name}", "amount": sale_amount, "transaction_id": str(random.randint(0, 9999)), "date": datetime.datetime.now().isoformat(), "phone_number": f'0778{random.randint(1, 9)}72{random.randint(10, 99)}3' } t = transaction_from_dict(trans) transactions.append(t) yield self.env.timeout(random.randint(1, 5)) else: yield self.env.timeout(random.randint(1, 3)) # insufficient balance, request owner to topup write_to_file( f'[Agent: {self.name}] Insufficient balance to perform sale of ${sale_amount}. I have ${self.agent_balance.level}, Please allocate me more funds | owner balance: ${oab.level}\n\n') class Owner(): ''' shop owner, can allocate Y amount to agents manages agents ''' def __init__(self, env, oab: simpy.Container, vcb: simpy.Container) -> None: self.env = env self.oab = oab # owner actual balance self.vcb = vcb # virtual current balance def register_agents(self): ''' register a new agent ''' for i in range(NUMBER_OF_AGENTS): yield env.timeout(random.randint(*T_INTER)) # allocate funds to agent agent = self.allocate_funds_to_agent(agent_name=i) if agent: env.process(agent.perform_sale(self.oab)) def allocate_funds_to_agent(self, agent_name): ''' allocate funds to an agent ''' vb = self.vcb.level to_allocate = random.randint(*AGENT_BALANCE) if to_allocate < vb: # get amount to allocate self.vcb.get(amount=to_allocate) write_to_file( f'[Agent: {agent_name}] Here i am, I have been allocated ${to_allocate}, current virtual balance: ${self.vcb.level}\n\n') # proceed return Agent(name=agent_name, env=self.env, allocated_balance=to_allocate) else: # not enough funds write_to_file( f'[ERROR] Not enough funds to allocate Agent: {agent_name} | virtual balance: ${vb} | to allocate ${to_allocate}\n\n') return None print('-- Simulation Retail System --') env = simpy.Environment() # hold actual account balance actual_balance = simpy.Container(env, ACCOUNT_BALANCE, init=ACCOUNT_BALANCE) # initially hold a copy of the actual balance virtual_balance = simpy.Container(env, ACCOUNT_BALANCE, init=ACCOUNT_BALANCE) owner = Owner(env=env, oab=actual_balance, vcb=virtual_balance) # add process env.process(owner.register_agents()) # Execute! env.run(until=SIM_TIME) print('---- stats ----') total_agent_sales = 0.0 for t in transactions: myTable.add_row([t.agent, t.date, t.phone_number, t.amount, t.transaction_id]) total_agent_sales += t.amount print(myTable) print(f'\n\n[INFO] Total agent sales: ${total_agent_sales}\n\n') print( f'[INFO] Remaing virtual balance: ${virtual_balance.level} | initial balance: ${virtual_balance.capacity}\n\n') print( f'[INFO] Remaing owner balance: ${actual_balance.level} | initial balance: ${actual_balance.capacity}\n\n') write_to_file(str(myTable)) write_to_file(f'\n\n[INFO] Total agent sales: ${total_agent_sales}\n\n') write_to_file( f'[INFO] Remaing virtual balance: ${virtual_balance.level} | initial balance: ${virtual_balance.capacity}\n\n') write_to_file( f'[INFO] Remaing owner balance: ${actual_balance.level} | initial balance: ${actual_balance.capacity}\n\n') print('-- Done! --')
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selfbot/__init__.py
TibebeJS/tg-selfbot
1
117746
from .selfbot import *
[ 1, 515, 869, 1311, 7451, 1053, 334, 2 ]
checking/classes/mocking/doubles.py
igrekus/checking
4
177622
import builtins from typing import Any, List, Tuple from .calls import Call from .interfaces import Observer from .wrapper import AttributeWrapper def fake_builtins(): real_isinstance = builtins.isinstance def fake_isinstance(initial: Any, class_or_tuple: Any) -> bool: if real_isinstance(initial, Spy): return initial.class_ == class_or_tuple return real_isinstance(initial, class_or_tuple) builtins.isinstance = fake_isinstance class Spy(Observer): """ The test-double (spy), which replaces the desired object. His attributes return None, and the methods do not do anything if unless otherwise indicated, but all of the calls are fixed. This class in used due to make sure in the call of respectively functions with arguments. """ first_instance = False def __init__(self, obj: Any = None): super().__init__() if not Spy.first_instance: Spy.first_instance = True fake_builtins() self.chain: List[Call] = [] self._returns = None self._raises = None if obj is not None: for name in dir(obj): if name == '__dict__': continue if callable(getattr(obj, name)): if name != '__class__': setattr(self, name, AttributeWrapper(name, self)) else: setattr(self, name, self.__class__) else: setattr(self, name, None) self.basic = obj self.class_ = obj.__class__ def notify(self, _call: Call): self.chain.append(_call) def __call__(self, *args, **kwargs): if self._raises is not None: raise self._raises self.chain.append(Call('', *args, **kwargs)) return self._returns def __str__(self): if self.basic is None: return f'Empty Test Spy' return f'Test spy of the "{self.basic}" {type(self.basic)}' def all_calls(self) -> List[Call]: """ Returns list of Call objects (all method calls of the spied object) :return: List[Call] """ return self.chain def was_called(self) -> bool: """ Returns True if spy object was called itself :return: bool """ return self.was_function_called('') def was_called_with_argument(self, arg: Any) -> bool: """ Returns True if spy object was called itself with exact argument :param arg: Any argument to look for :return: bool """ return self.was_function_with_argument_called('', arg) def returns(self, result: Any): """ If spy object will be called itself return result :param result: any type to return when call :return: None """ self._returns = result def raises(self, exception_object: Exception): """ Raise an exception if object will be called itself (not its methods!) :param exception_object: exception object to raise :return: None """ self._raises = exception_object def was_function_called(self, name: str) -> bool: """ Returns True if exact function/method was called on spied object :param name: name of the function/method :return: bool """ return any([e for e in self.chain if e.name == name]) def was_function_with_argument_called(self, name: str, arg: Any) -> bool: """ Returns True if exact function/method was called with exact argument on spied object :param name: name of the function/method :param arg: any argument :return: bool """ if not self.was_function_called(name): return False return any([e for e in self.chain if e.name == name and arg in e.args]) def was_exact_function_called(self, name, *args, **kwargs): call = Call(name, *args, **kwargs) return any([e for e in self.chain if e == call]) def all_calls_args(self) -> List[Tuple]: """ Returns all called function/method arguments :return: List[Tuple] """ return [e.args for e in self.chain] def all_calls_args_flatten(self) -> List[Any]: """ Returns flat list of all arguments of all called functions :return: List[Any] """ return [arg for call in self.chain for arg in call.args] class TestDouble(Spy): """ The full test-double (twin of the object), the main difference with Spy is behaviour. Behaviour stays the same as original object has, but all calls fixed and you can change return result of the methods. This class in used due to make sure in the call of respectively functions with arguments. """ def __init__(self, obj: Any = None): super().__init__() if obj is not None: for name in dir(obj): attr = getattr(obj, name) if callable(attr): if name == '__dict__': continue if name != '__class__': wrapper = AttributeWrapper(name, self) wrapper.use_function(attr) setattr(self, name, wrapper) else: setattr(self, name, self.__class__) else: setattr(self, name, attr) wrapper = AttributeWrapper('len', self) setattr(self, 'len', wrapper) wrapper = AttributeWrapper('bool', self) setattr(self, 'bool', wrapper) wrapper = AttributeWrapper('iter', self) setattr(self, 'iter', wrapper) self.basic = obj self.class_ = obj.__class__ def __str__(self): return f'Test Double of the "{self.basic}" {type(self.basic)}' def __len__(self): if self.len._return is not None or self.len._function: return self.len() self.len() return len(self.basic) def __bool__(self): if self.bool._return is not None or self.bool._function: return self.bool() self.bool() return bool(self.basic) def __iter__(self): if self.iter._return is not None or self.iter._function: return self.iter() self.iter() return iter(self.basic)
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bob/bio/base/test/dummy/preprocessor.py
bioidiap/bob.bio.base
16
138809
<gh_stars>10-100 from bob.bio.base.preprocessor import Preprocessor from bob.bio.base.database import BioFile import numpy numpy.random.seed(10) class DummyPreprocessor (Preprocessor): def __init__(self, return_none=False, probability_of_none=1, **kwargs): Preprocessor.__init__(self) self.return_none = return_none self.probability_of_none = probability_of_none def __call__(self, data, annotation): """Does nothing, simply converts the data type of the data, ignoring any annotation.""" if self.return_none: return numpy.random.choice([None, data], p=[self.probability_of_none, 1-self.probability_of_none]) return data preprocessor = DummyPreprocessor() class DummyPreprocessorMetadata (DummyPreprocessor): def __call__(self, data, annotation, metadata=None): """Does nothing, simply converts the data type of the data, ignoring any annotation.""" assert isinstance(metadata, BioFile) return super(DummyPreprocessorMetadata, self).__call__(data, annotation) preprocessor_metadata = DummyPreprocessorMetadata()
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docs/modeling/code/timingExample.py
pramodsu/ILA-Tools
1
83874
<reponame>pramodsu/ILA-Tools Accelerator = ila.Abstraction('ExampleILA') # Define the Abstraction # Define the Interface write_grant = Accelerator.inp('write_grant', 1) # - request grant write_data = Accelerator.reg('write_data' , 32) # - data port write_length= Accelerator.reg('write_len' , 16) # - burst length ... # - possibly more ports writing = Accelerator.reg('writing' , 1) # 1 bit flag indicating if # it is writing to the bus Accerlator.decode_exprs += [ write_grant == 1 ] # The grant operation is considered as an instruction to the accelerator writing_nxt = ila.ite( write_grant == 1, # The effect of the instruction above b1, # This is the complete function writing ) # without holes. However, you can # use synthesis to create this # function #Note: b0 = ila.const(0,1) (1-bit-wide constant 0) #and b1 = ila.const(1,1) (1-bit-wide constant 1) Accelerator.set_next('writing', writing_nxt ) write_fsm = Accelerator.add_microabstraction('WriteFsm', writing == 1 ) # Bus Write logic. counter = write_fsm.reg('counter', 32) # The counter here is used # to count cycles write_fsm.set_init('counter', h0_16 ) # b0_16 = ila.const(0,16) write_fsm.set_next('counter', counter + 1) write_fsm.set_next('writing', ila.ite(counter == write_length-1, b0, writing) ) # turn the flag off, # when necessary write_fsm.set_next('write_data', ?? ) # write some values # each cycle
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Auditor.py
bryanabsmith/Auditor
0
97871
#!/usr/bin/python import ipgetter import os import platform import subprocess import time import wx # TODO Clean up the code. # Licenced under the MIT Licence. See LICENCE for more details. class Auditor(wx.Frame): def __init__(self, parent, title): self.audit = "" self.version = "0.1 (b2)" self.serial = True self.run_allChecked = False self.wildcardSave = "Text document (*.txt)|*.txt" # http://zetcode.com/wxpython/layout/ super(Auditor, self).__init__(parent, title=title, size=(350, 300), style=wx.MINIMIZE_BOX | wx.CLOSE_BOX) self.panelMain = wx.Panel(self) self.vBoxMain = wx.BoxSizer(wx.VERTICAL) self.labelSelect = wx.StaticText(self.panelMain, label="Select the information that you'd like collected:") self.vBoxOptions = wx.BoxSizer(wx.VERTICAL) self.checkBoxOpen = wx.CheckBox(self.panelMain, label="Open report when done") self.checkBoxForumOptimized = wx.CheckBox(self.panelMain, label="Optimize for forums (BBCode)") self.buttonrun_all = wx.Button(self.panelMain, label="All", size=(120, 30)) self.buttonrun_selected = wx.Button(self.panelMain, label="Selected", size=(120, 30)) self.checkListBoxAudits = wx.CheckListBox(self.panelMain, -1, choices=["Basic", "Networking", "Platform", "Power", "Usage"]) self.hBoxButtons = wx.BoxSizer(wx.HORIZONTAL) self.sbOptions = wx.StaticBox(self.panelMain, label="Options") self.sbOptionsBox = wx.StaticBoxSizer(self.sbOptions, wx.VERTICAL) self.menuBarMain = wx.MenuBar() self.menuRun = wx.Menu() self.menuTemplates = wx.Menu() self.menuHelp = wx.Menu() self.dialogSave = wx.FileDialog(None, message="Save report as ...", defaultDir=os.path.expanduser("~") + "/Desktop/", defaultFile="", wildcard=self.wildcardSave, style=wx.SAVE) self.init_ui() self.Centre() self.Show() def init_ui(self): self.vBoxMain.Add(self.labelSelect, proportion=0, flag=wx.LEFT | wx.TOP, border=10) self.vBoxMain.Add(self.checkListBoxAudits, proportion=1, flag=wx.LEFT | wx.RIGHT | wx.TOP | wx.EXPAND, border=10) self.sbOptionsBox.Add(self.checkBoxForumOptimized, proportion=0, flag=wx.LEFT) self.sbOptionsBox.Add(self.checkBoxOpen, proportion=0, flag=wx.LEFT) self.vBoxMain.Add(self.sbOptionsBox, proportion=0, flag=wx.LEFT | wx.RIGHT | wx.TOP | wx.EXPAND, border=10) self.hBoxButtons = wx.BoxSizer(wx.HORIZONTAL) self.hBoxButtons.Add(self.buttonrun_selected, proportion=0, flag=wx.RIGHT, border=10) self.hBoxButtons.Add(self.buttonrun_all, proportion=0, flag=wx.RIGHT, border=10) self.vBoxMain.Add(self.hBoxButtons, flag=wx.ALIGN_RIGHT | wx.BOTTOM, border=10) self.panelMain.SetSizer(self.vBoxMain) self.menuRun.Append(101, "Run all...\tCtrl-A") self.menuRun.Append(102, "Run selected...\tCtrl-S") self.menuTemplates.Append(201, "Mac-Forums essentials\tCtrl-M") self.menuHelp.Append(wx.ID_ABOUT, "&About Auditor") self.menuHelp.Append(301, "About data collected...\tCtrl-H") self.menuBarMain.Append(self.menuRun, "&Run") self.menuBarMain.Append(self.menuTemplates, "&Templates") self.menuBarMain.Append(self.menuHelp, "&Help") self.SetMenuBar(self.menuBarMain) self.Bind(wx.EVT_MENU, self.about_menu_click, id=wx.ID_ABOUT) self.Bind(wx.EVT_MENU, self.run_all, id=101) self.Bind(wx.EVT_MENU, self.run_selected, id=102) self.Bind(wx.EVT_MENU, self.template_mfessentials, id=201) self.Bind(wx.EVT_MENU, self.show_help, id=301) self.Bind(wx.EVT_BUTTON, self.run_all, self.buttonrun_all) self.Bind(wx.EVT_BUTTON, self.run_selected, self.buttonrun_selected) def template_mfessentials(self, event): self.checkListBoxAudits.SetCheckedStrings(["Basic", "Platform", "Usage"]) self.checkBoxForumOptimized.SetValue(True) self.serial = False def show_help(self, event): message = """ Here is a list of all the pieces of information collected: - Basic: - OS X Version - OS X Build - Processor Info - Memory Info - Model Name - Model ID - Serial number - Platform Info - Platform - Node - Release - Version - Machine - Processor - Usage - Memory Usage: Used Memory, Wired Memory, Unused Memory - Hard Disk Usage, Mounted at /: Total Space, Used Space, Available Space - Networking - SSID - Link Auth - IP Addresses: en0, en1 - External IP - External Host - Ethernet DNS - Wi-Fi DNS - Power - Battery Cycle Count - Battery Condition """ dlg = wx.MessageDialog(self.panelMain, message, "Output", wx.OK | wx.ICON_INFORMATION) dlg.ShowModal() dlg.Destroy() def run_all_or_not(self, event): if self.checkBoxAll.GetValue(): self.run_allChecked = True self.checkListBoxAudits.Disable() else: self.run_allChecked = False self.checkListBoxAudits.Enable() def about_menu_click(self, event): about_options = wx.AboutDialogInfo() about_options.SetName("Auditor") about_options.SetVersion(self.version) about_options.SetCopyright("(c) 2015 <NAME>.\n\nIcon courtesy of the Tango Project.\n\nExternal IP library, ipgetter, licenced under the DWTFYWT licence (http://www.wtfpl.net/)") aboutBox = wx.AboutBox(about_options) print(aboutBox) def button_run_audit_click(self, event): check = self.checkListBoxAudits.GetCheckedStrings() if self.run_allChecked == False and len(check) == 0: dialogNoChecks = wx.MessageDialog(self, "No options selected.", "Auditor", wx.OK | wx.ICON_NONE) # | wx.ICON_INFORMATION dialogNoChecks.ShowModal() dialogNoChecks.Destroy() else: if self.run_allChecked: self.run_all() else: self.run_selected() def run_all(self, event): if self.checkBoxForumOptimized.GetValue() == True: self.audit = "[code]\nAuditor Report\n" else: self.audit = "Auditor Report\n" # http://www.cyberciti.biz/faq/howto-get-current-date-time-in-python/ self.audit += time.strftime("%d/%m/%Y, %H:%M:%S") progValue = 1 # java2s.com/Tutorial/Python/0380__wxPython/Aprogressbox.htm dialog = wx.ProgressDialog("Collection Progress", "Starting...", 5, style=wx.PD_CAN_ABORT | wx.PD_AUTO_HIDE | wx.PD_SMOOTH) dialog.Pulse() self.get_basic() dialog.Update(progValue, "Getting basic information...") progValue += 1 self.get_platform() dialog.Update(progValue, "Getting platform information...") progValue += 1 self.get_usage() dialog.Update(progValue, "Getting usage information...") progValue += 1 self.get_networking() dialog.Update(progValue, "Getting networking information...") progValue += 1 self.get_power() dialog.Update(progValue, "Getting power information...") if self.checkBoxForumOptimized.GetValue(): self.audit += "\n[/code]" path = "" self.dialogSave.SetFilename("Auditor-" + time.strftime("%d-%m-%Y-at-%H-%M-%S")) if self.dialogSave.ShowModal() == wx.ID_OK: path = self.dialogSave.GetPath() output = open(path, "w") output.write(self.audit) output.close() if self.checkBoxOpen.GetValue(): subprocess.Popen(('open', path), stdout=subprocess.PIPE) self.checkListBoxAudits.Enable() self.serial = True def run_selected(self, event): check = self.checkListBoxAudits.GetCheckedStrings() checkLen = len(check) progValue = 1 if checkLen == 0: dlg = wx.MessageDialog(self.panelMain, "Please select some options or run all audits.", "Error", wx.OK | wx.ICON_ERROR) dlg.ShowModal() dlg.Destroy() return 0 if self.checkBoxForumOptimized.GetValue() == True: self.audit = "[code]\nAuditor Report\n" else: self.audit = "Auditor Report\n" # http://www.cyberciti.biz/faq/howto-get-current-date-time-in-python/ self.audit += time.strftime("%d/%m/%Y, %H:%M:%S") dialog = wx.ProgressDialog("Collection Progress", "Starting...", checkLen, style=wx.PD_CAN_ABORT | wx.PD_AUTO_HIDE | wx.PD_SMOOTH) dialog.Pulse() for x in check: if x == "Basic": self.get_basic() dialog.Update(progValue, "Getting basic information...") progValue += 1 elif x == "Platform": self.get_platform() dialog.Update(progValue, "Getting platform information...") progValue += 1 elif x == "Usage": self.get_usage() dialog.Update(progValue, "Getting usage information...") progValue += 1 elif x == "Networking": self.get_networking() dialog.Update(progValue, "Getting networking information...") progValue += 1 elif x == "Power": self.get_power() dialog.Update(progValue, "Getting power information...") progValue += 1 if self.checkBoxForumOptimized.GetValue() == True: self.audit += "\n[/code]" dialog.Destroy() path = "" self.dialogSave.SetFilename("Auditor-" + time.strftime("%d-%m-%Y-at-%H-%M-%S")) if self.dialogSave.ShowModal() == wx.ID_OK: path = self.dialogSave.GetPath() output = open(path, "w") output.write(self.audit) output.close() if self.checkBoxOpen.GetValue(): subprocess.Popen(('open', path), stdout=subprocess.PIPE) self.checkListBoxAudits.Enable() self.serial = True def get_basic(self): self.audit += "\n\n:: Basic Info ::\n" # http://stackoverflow.com/a/13332300 sysctlProc = subprocess.Popen(('sysctl', '-a'), stdout=subprocess.PIPE) sysctlProcPipe = subprocess.check_output(('grep', 'machdep.cpu.brand_string'), stdin=sysctlProc.stdout) sysctlMem = subprocess.Popen(('sysctl', '-a'), stdout=subprocess.PIPE) sysctlMemPipe = subprocess.check_output(('grep', 'hw.memsize'), stdin=sysctlMem.stdout) self.audit += " OS X Version: " + subprocess.check_output(["sw_vers", "-productVersion"]) self.audit += " OS X Build: " + subprocess.check_output(["sw_vers", "-buildVersion"]) self.audit += " Processor Info: " + sysctlProcPipe[26:] memMB = (int(sysctlMemPipe[12:]) / 1024) / 1024 memGB = ((int(sysctlMemPipe[12:]) / 1024) / 1024) / 1024 self.audit += " Memory Info: " + str(memGB) + "GB (" + str(memMB) + "MB)" self.audit += "\n Model Name: " modelName = subprocess.Popen(('system_profiler', 'SPHardwareDataType'), stdout=subprocess.PIPE) modelNamePipe = subprocess.check_output(('grep', 'Model Name'), stdin=modelName.stdout) for x in modelNamePipe.split(): if x == "Model" or x == "Name:": pass else: self.audit += x + " " modelID = subprocess.Popen(('system_profiler', 'SPHardwareDataType'), stdout=subprocess.PIPE) modelIDPipe = subprocess.check_output(('grep', 'Identifier'), stdin=modelID.stdout) self.audit += "\n Model ID: " + modelIDPipe.split()[2] if self.serial == True: serialNumber = subprocess.Popen(('system_profiler', 'SPHardwareDataType'), stdout=subprocess.PIPE) serialNumberPipe = subprocess.check_output(('grep', 'Serial'), stdin=serialNumber.stdout) self.audit += "\n Serial number: " + serialNumberPipe.split()[3] # Model name - http://apple.stackexchange.com/a/98089 (curl http://support-sp.apple.com/sp/product?cc=DTY3) def get_power(self): self.audit += "\n\n:: Power Info ::\n" try: cycleCount = subprocess.Popen(('system_profiler', 'SPPowerDataType'), stdout=subprocess.PIPE) cycleCountPipe = subprocess.check_output(('grep', 'Cycle Count'), stdin=cycleCount.stdout) self.audit += " Battery Cycle Count: " + cycleCountPipe.split()[2] except: self.audit += " Battery Cycle Count: N/A" try: condition = subprocess.Popen(('system_profiler', 'SPPowerDataType'), stdout=subprocess.PIPE) conditionPipe = subprocess.check_output(('grep', 'Condition'), stdin=condition.stdout) self.audit += "\n Battery Condition: " + conditionPipe.split()[1] except: self.audit += "\n Battery Condition: N/A" def get_platform(self): self.audit += "\n\n:: Platform Info ::\n" # http://pymotw.com/2/platform/ self.audit += " Platform: " + platform.system() self.audit += "\n Node: " + platform.node() self.audit += "\n Release: " + platform.release() self.audit += "\n Version: " + platform.version() self.audit += "\n Machine: " + platform.machine() self.audit += "\n Processor: " + platform.processor() def get_usage(self): self.audit += "\n\n:: Usage Info ::\n" # http://stackoverflow.com/questions/21162721/how-to-get-physical-memory-from-top-l1-using-awk-in-os-x-mavericks - physical memory usedMem = subprocess.Popen(('top', '-l1'), stdout=subprocess.PIPE) usedMemPipe = subprocess.check_output(('grep', 'PhysMem'), stdin=usedMem.stdout) usedMemUsed = usedMemPipe.split()[1] usedMemWired = usedMemPipe.split()[3] usedMemUnused = usedMemPipe.split()[5] self.audit += " Memory Usage:\n Used Memory: " + usedMemUsed + "\n Wired Memory: " + usedMemWired.replace( "(", "") + "\n Unused Memory: " + usedMemUnused diskSpace = subprocess.Popen(["df", "-H", "/"], stdout=subprocess.PIPE) diskSpaceInfo = diskSpace.communicate()[0] totalSpace = diskSpaceInfo.split()[11] usedSpace = diskSpaceInfo.split()[12] availableSpace = diskSpaceInfo.split()[13] self.audit += "\n Hard Disk Usage, Mounted at /:\n Total Space: " + totalSpace + "\n Used Space: " + usedSpace + "\n Available Space: " + availableSpace def get_networking(self): # Timing: # - 0.1b1: 23s # - 0.1b2: self.audit += "\n\n:: Networking Info ::\n" try: # /System/Library/PrivateFrameworks/Apple80211.framework/Versions/Current/Resources/airport -I | grep SSID ssid = subprocess.Popen( ('/System/Library/PrivateFrameworks/Apple80211.framework/Versions/Current/Resources/airport', '-I'), stdout=subprocess.PIPE) ssidPipe = subprocess.check_output(('grep', 'SSID'), stdin=ssid.stdout) self.audit += " SSID: " + ssidPipe.split()[3] except subprocess.CalledProcessError: self.audit += " SSID: N/A" # try: # linkAuth = subprocess.Popen(('/System/Library/PrivateFrameworks/Apple80211.framework/Versions/Current/Resources/airport', '-I'), stdout=subprocess.PIPE) # linkAuthPipe = subprocess.check_output(('grep', 'link'), stdin=linkAuth.stdout) # self.audit += "\n Link Auth: " + linkAuthPipe.split()[2] # except subprocess.CalledProcessError: # self.audit += "\n Link Auth: N/A" ipEN0 = subprocess.Popen(["ipconfig", "getifaddr", "en0"], stdout=subprocess.PIPE) ipEN0Value = ipEN0.communicate()[0].strip("\n") if ipEN0Value == "": self.audit += "\n IP Addresses:\n en0: N/A" else: self.audit += "\n IP Addresses:\n en0: " + ipEN0Value print(ipEN0Value) ipEN1 = subprocess.Popen(["ipconfig", "getifaddr", "en1"], stdout=subprocess.PIPE) ipEN1Value = ipEN1.communicate()[0].strip("\n") if ipEN1Value == "": self.audit += "\n en1: N/A" else: self.audit += "\n en1: " + ipEN1Value print(ipEN1Value) # extIP = subprocess.Popen(["curl", "ifconfig.me"], stdout=subprocess.PIPE) extIP = ipgetter.myip() self.audit += "\n External IP: " + extIP # extHost = subprocess.Popen(["curl", "ifconfig.me/host"], stdout=subprocess.PIPE) # self.audit += " External Host: " + extHost.communicate()[0] ethernetDNS = subprocess.Popen(["networksetup", "-getdnsservers", "Ethernet"], stdout=subprocess.PIPE) self.audit += "\n Ethernet DNS: " + ethernetDNS.communicate()[0].replace("\n", " ") wifiDNS = subprocess.Popen(["networksetup", "-getdnsservers", "Wi-Fi"], stdout=subprocess.PIPE) self.audit += "\n Wi-Fi DNS: " + wifiDNS.communicate()[0].replace("\n", " ") if __name__ == "__main__": app = wx.App() Auditor(None, title="Auditor") app.MainLoop()
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democracy_bot/utils.py
TheDuckFIN/democracy-bot
0
82354
<gh_stars>0 """Utility functions""" import discord def get_name(member: discord.Member): """Returns nick primarily and falls back to username""" return member.name if member.nick is None else member.nick
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python/ql/test/2/library-tests/PointsTo/imports/test.py
vadi2/codeql
4,036
134900
from package import foo as myfoo
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pipeline/schemas/friend_invite.py
mystic-ai/pipeline
7
183281
from enum import Enum from .base import BaseModel class FriendInviteStatus(Enum): CREATED = "created" #: Friend has accepted the invite ACCEPTED = "accepted" #: The friend is still under trial period TRIAL = "trial" #: Cycle complete, the inviter has been credited COMPLETE = "complete" class FriendInviteBase(BaseModel): #: The ID of the User who sent the invite inviter_id: str #: The email the invite is to be sent to invitee_email: str class FriendInviteCreate(FriendInviteBase): """Create an invitation for a friend to join""" pass class FriendInviteGet(FriendInviteBase): """View of an invitation for a friend to join""" #: The ID of this invite id: str #: The status of the invite status: FriendInviteStatus class FriendInvitePatch(BaseModel): """Patch the status of a friend invitation""" status: FriendInviteStatus
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renewer/smtp.py
cloud-gov/legacy-domain-certificate-renewer
1
145467
<reponame>cloud-gov/legacy-domain-certificate-renewer from email.mime.text import MIMEText import smtplib import ssl from renewer.extensions import config def send_email(email, subject, body): msg = MIMEText(body, "html") msg["Subject"] = subject msg["To"] = email msg["From"] = config.SMTP_FROM s = smtplib.SMTP(config.SMTP_HOST, config.SMTP_PORT) # if we have a cert, then trust it if config.SMTP_TLS: sslcontext = ssl.create_default_context() if config.SMTP_CERT is not None: sslcontext.load_verify_locations(cadata=config.SMTP_CERT) s.starttls(context=sslcontext) # if smtp credentials were provided, login if config.SMTP_USER is not None and config.SMTP_PASS is not None: s.login(config.SMTP_USER, config.SMTP_PASS) s.sendmail(config.SMTP_FROM, [email], msg.as_string()) s.quit() def send_failed_operation_alert(operation): subject = f"[{config.ENV}] - legacy-domain-certificate-renewer pipeline failed" body = f""" <h1>Pipeline failed unexpectedly!</h1> operation id: {operation.id} <br/> service instance id: {operation.route.instance_id} <br/> service instance type: {operation.route.route_type} <br/> """ send_email(config.SMTP_TO, subject, body)
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rtmlparse/templates/simplephotometry.py
thusser/rtml-parse
1
55853
from zope.interface import implementer from rtmlparse.irtml import ITemplate from rtmlparse.elements import * @implementer(ITemplate) class SimplePhotometry(object): name = "SimplePhotometry" type = Setup def __init__(self, element=None, rtml=None): # define our elements self.setup = None self.Camera = None self.Filter = None self.Target = None self.Exposure = None self.ExposureConstraint = None # existing or new? if element is None: # do we have rtml? if rtml is None: raise ValueError('Need RTML instance for creating new template.') # create all necessary elements self.create(rtml) else: # store it, just use the first matching elements found self.setup = element self.Camera = self.setup.find_first(Camera) self.Target = self.setup.find_first(Target) self.Filter = self.setup.find_first(Filter) self.Exposure = self.setup.find_first(Exposure) self.ExposureConstraint = self.setup.find_first(ExposureConstraint) def create(self, rtml): self.setup = Setup(rtml, name='template:SimplePhotometry') self.Camera = Camera(self.setup) self.Filter = Filter(self.setup) self.Target = Target(self.setup) self.Exposure = Exposure(self.setup) self.ExposureConstraint = ExposureConstraint(self.setup)
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designate/backend/impl_infoblox/record_factory.py
infobloxopen/designate
0
27355
<reponame>infobloxopen/designate # Copyright 2014 Infoblox # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import logging from designate.i18n import _LI from designate.backend.impl_infoblox.records import a from designate.backend.impl_infoblox.records import aaaa from designate.backend.impl_infoblox.records import cname from designate.backend.impl_infoblox.records import ptr from designate.backend.impl_infoblox.records import soa from designate.backend.impl_infoblox.records import ns LOG = logging.getLogger(__name__) class RecordFactory(object): @staticmethod def get_record(recordset, infoblox, tenant_name): if recordset.type == "A": return a.ARecord(infoblox, tenant_name) if recordset.type == "CNAME": return cname.CNameRecord(infoblox, tenant_name) if recordset.type == "NS": return ns.NSRecord(infoblox, tenant_name) if recordset.type == "SOA": return soa.SOARecord(infoblox, tenant_name) if recordset.type == "PTR": return ptr.PTRRecord(infoblox, tenant_name) if recordset.type == "AAAA": return aaaa.AAAARecord(infoblox, tenant_name) LOG.error(_LI("Unknown type %s"), recordset.type)
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swiftwind/core/exceptions.py
m-den-i/swiftwind
11
174826
<reponame>m-den-i/swiftwind class CannotCreateMultipleSettingsInstances(Exception): pass
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python/include/wl_oracle.py
bopopescu/Heimdallr
0
177879
#!/bin/env python #-*-coding:utf-8-*- import MySQLdb import string import sys reload(sys) sys.setdefaultencoding('utf8') import ConfigParser def get_item(data_dict,item): try: item_value = data_dict[item] return item_value except: pass def get_parameters(conn): try: curs=conn.cursor() data=curs.execute('select name,value from v$parameter'); data_list=curs.fetchall() parameters={} for item in data_list: parameters[item[0]] = item[1] return parameters except Exception,e: print e finally: curs.close() def get_sysstat(conn): try: curs=conn.cursor() data=curs.execute('select name,value value from v$sysstat'); data_list=curs.fetchall() sysstat={} for item in data_list: sysstat[item[0]] = item[1] return sysstat except Exception,e: print e finally: curs.close() def get_instance(conn,field): try: curs=conn.cursor() curs.execute("select %s from v$instance" %(field) ); result = curs.fetchone()[0] return result except Exception,e: result = '' print e finally: curs.close() def get_database(conn,field): try: curs=conn.cursor() curs.execute("select %s from v$database" %(field) ); result = curs.fetchone()[0] return result except Exception,e: result = '' print e finally: curs.close() def get_version(conn): try: curs=conn.cursor() curs.execute("select product,version from product_component_version where product like '%Database%'"); result = curs.fetchone()[1] return result except Exception,e: print e finally: curs.close() def get_current_snap_id(conn, inst_id): try: curs=conn.cursor() curs.execute("select max(snap_id) from wrm$_snapshot where instance_number = %s" %(inst_id)); result = curs.fetchone()[0] return result except Exception,e: print e finally: curs.close() def get_end_interval_time(conn, inst_id): try: curs=conn.cursor() curs.execute("""select to_char(t.end_interval_time, 'yyyy-mm-dd hh24:mi:ss') from wrm$_snapshot t where t.snap_id in (select max(snap_id) from wrm$_snapshot) and t.instance_number = %s """ %(inst_id)); result = curs.fetchone()[0] return result except Exception,e: print e finally: curs.close() def get_sessions(conn): try: curs=conn.cursor() curs.execute("select count(*) from v$session"); result = curs.fetchone()[0] return result except Exception,e: return null print e finally: curs.close() def get_actives(conn): try: curs=conn.cursor() curs.execute("select count(*) from v$session where STATUS='ACTIVE'"); result = curs.fetchone()[0] return result except Exception,e: return null print e finally: curs.close() def get_waits(conn): try: curs=conn.cursor() curs.execute("select count(*) from v$session where event like 'library%' or event like 'cursor%' or event like 'latch%' or event like 'enq%' or event like 'log file%'"); result = curs.fetchone()[0] return result except Exception,e: return null print e finally: curs.close() def get_dg_stats(conn): try: curs=conn.cursor() curs.execute("SELECT substr((SUBSTR(VALUE,5)),0,2)*3600 + substr((SUBSTR(VALUE,5)),4,2)*60 + substr((SUBSTR(VALUE,5)),7,2) AS seconds,VALUE FROM v$dataguard_stats a WHERE NAME ='apply lag'"); list = curs.fetchone() if list: result = 1 else: result = 0 return result except Exception,e: return null print e finally: curs.close() def get_dg_delay(conn): try: curs=conn.cursor() curs.execute("SELECT substr((SUBSTR(VALUE,5)),0,2)*3600 + substr((SUBSTR(VALUE,5)),4,2)*60 + substr((SUBSTR(VALUE,5)),7,2) AS seconds,VALUE FROM v$dataguard_stats a WHERE NAME ='apply lag'"); list = curs.fetchone() if list: result = list[0] else: result = '---' return result except Exception,e: return null print e finally: curs.close() def get_sysdate(conn): try: curs=conn.cursor() curs.execute("select to_char(sysdate, 'yyyymmddhh24miss') from dual"); result = curs.fetchone()[0] return result except Exception,e: return null print e finally: curs.close() def get_dg_p_info(conn, dest_id): try: curs=conn.cursor() curs.execute("""select * from (select dest_id, thread#, sequence#+1, archived, applied, current_scn, to_char(scn_to_timestamp(current_scn), 'yyyy-mm-dd hh24:mi:ss') curr_db_time, row_number() over(partition by thread# order by sequence# desc) rn from v$archived_log t, v$database d where t.dest_id = %s) where rn = 1 """ %(dest_id)); result = curs.fetchall() return result except Exception,e: return None print e finally: curs.close() def get_dg_p_info_2(conn, dest_id): try: curs=conn.cursor() curs.execute("""select * from (select t.dest_id, transmit_mode, thread#, sequence#+1, archived, applied, current_scn, to_char(scn_to_timestamp(current_scn), 'yyyy-mm-dd hh24:mi:ss') curr_db_time, row_number() over(partition by thread# order by sequence# desc) rn from v$archived_log t, v$archive_dest a, v$database d where t.dest_id = a.dest_id and t.dest_id = %s) where rn = 1 """ %(dest_id)); result = curs.fetchall() return result except Exception,e: return None print e finally: curs.close() def get_log_archived_delay(conn, dest_id, thread_id): try: result = 0 curs=conn.cursor() curs.execute("""select count(1) from v$archived_log where dest_id = %s and thread# = %s and archived= 'NO' group by dest_id """ %(dest_id, thread_id)); list = curs.fetchone() if list: result = list[0] else: result = 0 return result except Exception,e: return None print e finally: curs.close() def get_log_applied_delay(conn, dest_id, thread_id): try: result = 0 curs=conn.cursor() curs.execute("""select count(1) from v$archived_log where dest_id = %s and thread# = %s and applied= 'NO' group by dest_id """ %(dest_id, thread_id)); list = curs.fetchone() if list: result = list[0] else: result = 0 return result except Exception,e: return None print e finally: curs.close() def get_redo_per_hour(conn): try: curs=conn.cursor() curs.execute("""select to_char(first_time, 'yyyy-mm-dd hh24')||':00' key_time, trunc(sum(blocks * block_size) / 1024 / 1024) redo_p_h from v$archived_log where to_char(first_time, 'yyyymmddhh24') = to_char(sysdate, 'yyyymmddhh24') and standby_dest = 'NO' group by to_char(first_time, 'yyyy-mm-dd hh24') """); result = curs.fetchone() return result except Exception,e: print e return None finally: curs.close() def get_db_time(conn, snap_id, inst_id): try: curs=conn.cursor() curs.execute("""select snap_id, end_time, dbtime, elapsed, round(dbtime/elapsed, 2) as rate from ( select n.stat_name as name, e.snap_id, to_char(te.end_interval_time,'yyyy-mm-dd hh24:mi:ss') as end_time, round((case when (e.value - b.value) > 0 then e.value - b.value else e.value end) / 1000 / 1000, 2) as dbtime, (to_date(to_char(te.end_interval_time,'yyyy-mm-dd hh24:mi:ss'),'yyyy-mm-dd hh24:mi:ss') - to_date(to_char(tb.end_interval_time,'yyyy-mm-dd hh24:mi:ss'),'yyyy-mm-dd hh24:mi:ss'))*86400 as elapsed from wrh$_sys_time_model e, wrh$_sys_time_model b, wrh$_stat_name n, wrm$_snapshot tb, wrm$_snapshot te where e.stat_id = n.stat_id and b.stat_id = n.stat_id and b.snap_id = e.snap_id - 1 and e.snap_id = %s and e.snap_id = te.snap_id and e.instance_number = te.instance_number and b.snap_id = tb.snap_id and b.instance_number = tb.instance_number and e.instance_number=b.instance_number and e.instance_number=%s and n.stat_name = 'DB time') tmp """ %(snap_id, inst_id)); result = curs.fetchone() return result except Exception,e: print e return None finally: curs.close() def get_dg_s_ms(conn): try: curs=conn.cursor() curs.execute("""select ms.thread#, ms.sequence#, ms.block#, ms.delay_mins from v$managed_standby ms where ms.process in ('MRP0') and ms.sequence# <> 0 """); result = curs.fetchone() return result except Exception,e: return None print e finally: curs.close() def get_dg_s_al(conn, scn): try: curs=conn.cursor() curs.execute(""" select thread#,sequence# from v$archived_log where first_change#<%s and next_change#>=%s """ %(scn,scn)); result = curs.fetchone() return result except Exception,e: return None print e finally: curs.close() def get_dg_s_rate(conn): try: curs=conn.cursor() curs.execute("""select * from (select rp.sofar avg_apply_rate from v$recovery_progress rp where rp.item = 'Average Apply Rate' order by start_time desc) where rownum < 2 """); result = curs.fetchone() return result except Exception,e: return None print e finally: curs.close() def get_dg_s_mrp(conn): try: curs=conn.cursor() curs.execute("""select status from gv$session where program like '%(MRP0)' """); list = curs.fetchone() if list: result = 1 else: result = 0 return result except Exception,e: return 0 print e finally: curs.close() def get_standby_redo_count(conn): try: curs=conn.cursor() curs.execute("""select count(1) from v$standby_log """); result = curs.fetchone()[0] return result except Exception,e: return 0 print e finally: curs.close() def get_time_by_scn(conn, scn): try: result=None curs=conn.cursor() curs.execute("""select to_char(scn_to_timestamp(%s), 'yyyy-mm-dd hh24:mi:ss') curr_db_time from v$database """ %(scn)); res = curs.fetchone() if res: result = res[0] else: result = None return result except Exception,e: #print e return None finally: curs.close() def get_time_from_restorepoint(conn, scn): try: result=None curs=conn.cursor() curs.execute("""select to_char(time, 'yyyy-mm-dd hh24:mi:ss') curr_db_time from v$restore_point where scn = %s """ %(scn)); res = curs.fetchone() if res: result = res[0] else: result = None return result except Exception,e: print e return None finally: curs.close() def get_pri_id_by_server(conn, id): try: result=None curs=conn.cursor() curs.execute("""select CASE is_switch WHEN 0 THEN standby_db_id ELSE primary_db_id END as sta_id from db_cfg_oracle_dg where primary_db_id = %s or standby_db_id = %s """ %(id, id)); res = curs.fetchone() if res: result = res[0] else: result = None return result except Exception,e: print e return None finally: curs.close() def get_earliest_fbscn(conn): try: curs=conn.cursor() curs.execute("""select min(scn) from v$restore_point """); result = curs.fetchone()[0] return result except Exception,e: return None print e finally: curs.close() def get_earliest_fbtime(conn,flashback_retention): try: curs=conn.cursor() curs.execute("""select to_char(min(time) + 1/48, 'yyyy-mm-dd hh24:mi:ss') mintime from v$restore_point where time > sysdate -%s/24/60 """ %(flashback_retention)); mintime = curs.fetchone() result = 'null' if mintime[0]: result = mintime[0] return result except Exception,e: print e return None finally: curs.close() def get_last_fbtime(conn): try: curs=conn.cursor() curs.execute("""select to_char(max(time), 'yyyymmddhh24miss') maxtime from v$restore_point """); lasttime = curs.fetchone() result = 'null' if lasttime[0]: result = lasttime[0] return result except Exception,e: print e return None finally: curs.close() def get_flashback_space_used(conn): try: curs=conn.cursor() curs.execute("""select sum(percent_space_used) from v$flash_recovery_area_usage """); fb_space = curs.fetchone() result = 0 if fb_space: result = fb_space[0] if result == '' or result is None: result = 0 return result except Exception,e: print e return None finally: curs.close() def get_restorepoint(conn, flashback_retention): try: curs=conn.cursor() curs.execute("select name from v$restore_point where time > sysdate -%s/60/24 order by name desc " %(flashback_retention)); list = curs.fetchall() return list except Exception,e: return None print e finally: curs.close() def get_expire_restore_list(conn, flashback_retention): try: curs=conn.cursor() curs.execute("select name from v$restore_point where time < sysdate - %s/60/24 " %(flashback_retention)); list = curs.fetchall() return list except Exception,e: return None print e finally: curs.close() def get_tablespace(conn): try: curs=conn.cursor() curs.execute("""select tpsname,status,mgr,max_size,curr_size, max_used from (SELECT d.tablespace_name tpsname, d.status status, d.segment_space_management mgr, TO_CHAR(NVL(trunc(A.maxbytes / 1024 / 1024), 0), '99999990') max_size, TO_CHAR(NVL(trunc(a.bytes / 1024 / 1024), 0), '99999990') curr_size, TO_CHAR(NVL((a.bytes - NVL(f.bytes, 0)) / a.bytes * 100, 0), '990D00') c_used, TO_CHAR(NVL((a.bytes - NVL(f.bytes, 0)) / a.maxbytes * 100, 0), '990D00') max_used FROM sys.dba_tablespaces d, (SELECT tablespace_name, sum(bytes) bytes, SUM(case autoextensible when 'NO' then BYTES when 'YES' then MAXBYTES else null end) maxbytes FROM dba_data_files GROUP BY tablespace_name) a, (SELECT tablespace_name, SUM(bytes) bytes, MAX(bytes) largest_free FROM dba_free_space GROUP BY tablespace_name) f WHERE d.tablespace_name = a.tablespace_name AND d.tablespace_name = f.tablespace_name(+)) order by max_used desc """); list = curs.fetchall() return list except Exception,e: return None print e finally: curs.close() def get_diskgroup(conn): try: curs=conn.cursor() curs.execute("""select name, state, type, total_mb, free_mb, trunc(((total_mb - free_mb) / total_mb) * 100, 2) used_rate from v$asm_diskgroup """); list = curs.fetchall() return list except Exception,e: return None print e finally: curs.close() def get_tables(conn): try: curs=conn.cursor() curs.execute("select owner, owner || '.' || table_name from dba_tables "); list = curs.fetchall() return list except Exception,e: return None print e finally: curs.close()
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sobolev_alignment/krr_approx.py
saroudant/sobolev_alignment
1
1606970
<reponame>saroudant/sobolev_alignment<filename>sobolev_alignment/krr_approx.py """ Encoder approximation by Kernel Ridge Regression @author: <NAME> This modules train a Kernel Ridge Regression (KRR) on a pair of samples (x_hat) and embeddings (z_hat) using two possible implementations: - scikit-learn: deterministic, but limited in memory and time efficiency. - Falkon: stochastic Nyström approximation, faster both in memory and computation time. Optimised for multi GPUs. References ------- [1] Mourragui et al 2022 [2] Meanti et al, Kernel methods through the roof: handling billions of points efficiently, NeurIPS, 2020. [3] Pedregosa et al, Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, 2011. """ import os, sys, torch, gc import numpy as np from pickle import load, dump from sklearn.preprocessing import StandardScaler # Falkon import from falkon import Falkon, kernels from falkon.options import FalkonOptions from falkon.kernels import GaussianKernel, MaternKernel, LaplacianKernel # Scikit-learn import from sklearn.metrics.pairwise import rbf_kernel, laplacian_kernel from sklearn.gaussian_process.kernels import Matern, RBF from sklearn.gaussian_process.kernels import PairwiseKernel from sklearn.kernel_ridge import KernelRidge class KRRApprox: """ Kernel Ridge Regression approximation. This class contains the functions used to approximate the encoding functions of a Variational Auto Encoder (VAE) by a kernel machines by means of Kernel Ridge Regression (KRR). <br/> This class takes as input a training data and executes the learning process. The generation of artificial samples and subsequent computation of embeddings is not part of this class. """ sklearn_kernel = { 'rbf': 'wrapper', 'gaussian': 'wrapper', 'laplacian': 'wrapper', 'matern': Matern, } falkon_kernel = { 'rbf': GaussianKernel, 'gaussian': GaussianKernel, 'laplacian': LaplacianKernel, 'matern': MaternKernel, } default_kernel_params = { 'falkon': { 'rbf': {'sigma': 1}, 'gaussian': {'sigma': 1}, 'laplacian': {'sigma': 1}, 'matern': {'sigma': 1, 'nu': .5}}, 'sklearn': { 'rbf': {}, 'gaussian': {}, 'laplacian': {}, 'matern': {}} } def __init__( self, method: str = 'sklearn', kernel: str = 'rbf', M: int = 100, kernel_params: dict = None, penalization: float = 1e-6, maxiter: int=20, falkon_options: dict = {}, mean_center: bool=False, unit_std: bool=False ): """ Parameters ---------- method: str, default to 'sklearn'. Method used for KRR approximation, 'sklearn' or 'falkon'. kernel: str, default to 'rbf' Name of the kernel to use in the approximation: 'rbf' (Gaussian kernel), 'matern' (Matern kernel), 'laplace' (Laplace). M: int, default to 100 Number of anchors samples for the Nyström approximation. Only used when method='falkon'. Default to 100 corresponds to a very low number of anchors and would lead to a poor approximation. kernel_params: dict, default to None Dictionary containing the kernel hyper-parameters, e.g. nu or sigma parameters for a Matérn kernel. penalization: float, default to 1e-6 Amount of penalization. Higher values induce more penalization. When method='sklearn', it corresponds to alpha (sklearn.kernel_ridge.KernelRidge). maxiter: int, default to 20 Maximum number of iterations in Falkon. falkon_options: dictionary, default to None Additional options to provide to falkon.options.FalkonOptions. More information on Falkon's documentation: https://falkonml.github.io/falkon/api_reference/options.html#falkonoptions mean_center: bool, default to False Whether to mean center features (genes) before regression. unit_std: bool, default to False Whether to standardize features (genes) before regression. """ self.method = method # Set kernel self.kernel = kernel self.kernel_params = kernel_params if kernel_params is not None else self.default_kernel_params[self.method][self.kernel] self._make_kernel() # Set penalization parameters self.penalization = penalization self.M = M self.maxiter = maxiter # Set hardware specifications self.falkon_options = falkon_options # Preprocessing self.mean_center = mean_center self.unit_std = unit_std self.pre_process_ = StandardScaler(with_mean=mean_center, with_std=unit_std, copy=False) def _make_kernel(self): """ Process the kernel parameters and set up the kernel to be used in KRR. Returns ------- True if kernel has successfully been set up. """ # scikit-learn initialization if self.method.lower() == 'sklearn': if self.sklearn_kernel[self.kernel.lower()] != 'wrapper': self.kernel_ = self.sklearn_kernel[self.kernel.lower()](**self.kernel_params) else: self.kernel_ = PairwiseKernel(metric=self.kernel.lower(), **self.kernel_params) # Falkon elif self.method.lower() == 'falkon': self.kernel_ = self.falkon_kernel[self.kernel.lower()](**self.kernel_params) # If not implemented else: raise NotImplementedError('%s not implemented. Choices: sklearn and falkon'%(self.method)) return True def fit(self, X: torch.Tensor, y: torch.Tensor): """ Train a regression model (KRR) between X and all columns of Y. Parameters ---------- X: torch.Tensor Tensor containing the artificial input (x_hat), with samples in the rows. y: torch.Tensor Tensor containing the artificial embedding (z_hat). Called y for compliance with sklearn functions. Returns ------- self: fitted KRRApprox instance. """ self._setup_clf() # Process data if required. No direct use of StandardScaler when mean_center and unit_std # are False as it can have a large memory footprint. if self.mean_center or self.unit_std: self.pre_process_.fit(X) self.training_data_ = torch.Tensor(self.pre_process_.transform(torch.Tensor(X))) else: self.training_data_ = X self.training_label_ = y # Train KRR instances. if self.method == 'sklearn': self.ridge_clf_.fit(self.kernel_(self.training_data_), y) elif self.method == 'falkon': self.ridge_clf_.fit(self.training_data_, y) self._save_coefs() if self.method == 'falkon': self.training_data_ = self.ridge_clf_.ny_points_ gc.collect() return self def _setup_clf(self): if self.method.lower() == 'sklearn': self._setup_sklearn_clf() elif self.method.lower() == 'falkon': self._setup_falkon_clf() def _setup_sklearn_clf(self): """ Set up the regression model using scikit-learn implementation Returns ------- True if set up ran properly. """ self.ridge_clf_ = KernelRidge(kernel='precomputed',alpha=self.penalization) return True def _setup_falkon_clf(self): """ Set up the regression model using Falkon implementation Returns ------- True if set up ran properly. """ self.ridge_clf_ = Falkon( kernel=self.kernel_, penalty=self.penalization, M=self.M, maxiter=self.maxiter, options=FalkonOptions(**self.falkon_options) ) return True def _save_coefs(self): if self.method.lower() == 'sklearn': self._process_coef_ridge_sklearn() elif self.method.lower() == 'falkon': self._process_coef_ridge_falkon() def _process_coef_ridge_sklearn(self): """ Save and process (i.e. transform to torch.Tensor) the coefficients obtained after kernel ridge regression with scikit-learn implementation """ self.sample_weights_ = torch.Tensor(self.ridge_clf_.dual_coef_) self.ridge_samples_idx_ = np.arange(self.training_data_.shape[0]) def _process_coef_ridge_falkon(self): """ Save the coefficients obtained after kernel ridge regression with Falkon implementation. """ self.sample_weights_ = self.ridge_clf_.alpha_ def anchors(self): """ Return anchor points used in KRR. """ return self.training_data_ def transform( self, X: torch.Tensor ): """ Apply the trained KRR models to a given data. This corresponds to the out-of-sample extension. Parameters ---------- X: torch.Tensor Tensor containing gene expression profiles with samples in the rows. <br/> <b>WARNING:</b> genes (features) need to be following the same order as the training data. Returns ------- torch.Tensor with predicted values for each of the encoding functions. Samples are in the rows and encoding functions (embedding) in the columns. """ if self.mean_center or self.unit_std: X = torch.Tensor(self.pre_process_.transform(X)) if self.method == 'sklearn': return self.ridge_clf_.predict(self.kernel_(X, self.training_data_)) elif self.method == 'falkon': return self.ridge_clf_.predict(X) else: raise NotImplementedError('%s not implemented. Choices: sklearn and falkon'%(self.method)) def save(self, folder:str = '.'): """ Save the instance Parameters ---------- folder: str, default to '.' Folder path to use for saving the instance Returns ------- True if the instance was properly saved. """ # Create path should it not exist yet. if not os.path.exists(folder) and not os.path.isdir(folder): os.mkdir(folder) # Save parameters of KRR. params = { 'method': self.method, 'kernel': self.kernel_, 'M': self.M, 'penalization': self.penalization, 'mean_center': self.mean_center, 'unit_std': self.unit_std } params.update(self.kernel_params) dump(params, open('%s/params.pkl'%(folder), 'wb')) # Save important material: # - KRR weights # - Samples used for prediction. torch.save( torch.Tensor(self.anchors()), open('%s/sample_anchors.pt'%(folder), 'wb') ) torch.save( torch.Tensor(self.sample_weights_), open('%s/sample_weights.pt'%(folder), 'wb') ) # Save weights and anchors as csv. Longer to load, but compatible with all platforms. # NOTE: was created to insure higher compatibility than torch saving option. np.savetxt('%s/sample_weights.csv'%(folder), self.sample_weights_.detach().numpy()) np.savetxt('%s/sample_anchors.csv'%(folder), self.anchors().detach().numpy()) return True def load(folder:str = '.'): """ Load a KRRApprox instance. Parameters ---------- folder: str, default to '.' Folder path where the instance is located Returns ------- KRRApprox: instance saved at the folder location. """ # Load and format parameters. params = load(open('%s/params.pkl'%(folder), 'rb')) krr_params = {e:f for e,f in params.items() if e in ['method', 'M', 'penalization', 'mean_center', 'unit_std']} # krr_params['kernel'] = krr_params['kernel'].kernel_name krr_approx_clf = KRRApprox(**krr_params) krr_approx_clf.kernel_ = params['kernel'] # Load sample weights and anchors. # NOTE: we use the torch option. In case of incompatibility, one could use the csv option. krr_approx_clf.sample_weights_ = torch.load(open('%s/sample_weights.pt'%(folder), 'rb')) krr_approx_clf.training_data_ = torch.load(open('%s/sample_anchors.pt'%(folder), 'rb')) # Set up classifiers for out-of-sample application. krr_approx_clf._setup_clf() krr_approx_clf.ridge_clf_.ny_points_ = krr_approx_clf.training_data_ krr_approx_clf.ridge_clf_.alpha_ = krr_approx_clf.sample_weights_ return krr_approx_clf
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docs/conf.py
urm8/django-translations
100
6893
<reponame>urm8/django-translations # -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # import os import sys import json import datetime # `Django setup` below, will add the path to `translations` module # automatically because it's been included in `project.settings`, so no need # to import it here # -- Django setup ------------------------------------------------------------ # generated project settings import django sys.path.insert( 0, os.path.join(os.path.dirname(os.path.abspath('.')), 'project') ) os.environ['DJANGO_SETTINGS_MODULE'] = 'project.settings' django.setup() # -- Project information ----------------------------------------------------- with open( os.path.join( os.path.dirname(os.path.abspath('.')), 'config.json' ), 'r') as fh: info = json.load(fh) # project project = info['project']['name'] # description description = info['project']['desc'] # author author = info['author']['name'] # The short X.Y version version = info['release']['version'] # The full version, including alpha/beta/rc tags release = info['release']['name'] # github github_user = info['github']['user'] github_repo = info['github']['repo'] # donation donate_url = info['urls']['funding'] # logo logo = info['project']['logo'] # documentation documentation = '{} {}'.format(project, 'Documentation') # year year = datetime.datetime.now().year # copyright copyright = '{year}, {author}'.format(year=year, author=author) # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.intersphinx', 'sphinx.ext.viewcode', 'sphinx.ext.githubpages', ] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path . exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'monokai' # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = 'alabaster' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # html_theme_options = { 'note_bg': '#fec', 'note_border': '#ffe2a8', 'show_relbars': True, 'logo': logo, 'touch_icon': logo, 'logo_name': True, 'description': description, 'github_user': github_user, 'github_repo': github_repo, 'github_banner': True, } # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'DjangoTranslationsdoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'DjangoTranslations.tex', documentation, author, 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'djangotranslations', documentation, [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'DjangoTranslations', documentation, author, 'DjangoTranslations', description, 'Miscellaneous'), ] # -- Extension configuration ------------------------------------------------- # -- Options for intersphinx extension --------------------------------------- # Example configuration for intersphinx: refer to the Python standard library. intersphinx_mapping = { 'python': ('https://docs.python.org/', None), 'django': ('http://django.readthedocs.org/en/latest/', None), } # -- Options for doctest extension ------------------------------------------- doctest_global_setup = """ import builtins from django.db import connection from django.test import TestCase from sample.utils import create_samples import beautifier # Turn on the test database for the doctests connection.creation.create_test_db(verbosity=0) TestCase.setUpClass() # Beautify `testoutput` def print(value='', end='\\n'): builtins.print(beautifier.beautify(value, False), end=end) # Sample creation def create_doc_samples(translations=True): if translations: create_samples( continent_names=['europe', 'asia'], country_names=['germany', 'south korea'], city_names=['cologne', 'seoul'], continent_fields=['name', 'denonym'], country_fields=['name', 'denonym'], city_fields=['name', 'denonym'], langs=['de'] ) else: create_samples( continent_names=['europe', 'asia'], country_names=['germany', 'south korea'], city_names=['cologne', 'seoul'], ) """ doctest_global_cleanup = """ import builtins from django.db import connection from django.test import TestCase # Normalize `testoutput` def print(value='', end='\\n'): builtins.print(value, end=end) # Turn off the test database for the doctests TestCase.tearDownClass() connection.creation.destroy_test_db(verbosity=0) """
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example.py
kaplanbr/Adversarial-Predictor
0
96507
# -*- coding: utf-8 -*- from AdversarialPredictor import AdversarialPredictionClassifier #dependencies %matplotlib inline import matplotlib.pyplot as plt import numpy as np from sklearn import datasets from sklearn.linear_model import LogisticRegression from sklearn.gaussian_process import GaussianProcessClassifier from sklearn.gaussian_process.kernels import RBF #download dataset iris_dataset = datasets.load_iris() #limit features to sepal and petal lenght X = iris_dataset["data"][:,[0,2]] y = iris_dataset["target"] #limited sample with virginica and versicolor species Xt = X[y<>0] yt = y[y<>0] Xs = X[y==0] #setosa sample #2 class model fit m_logr = LogisticRegression() m_logr.fit(Xt,yt) #3 class plot plt.title('3-class plot') plt.scatter(X[:,0][y==0],X[:,1][y==0], label="setosa",color="green",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("3-class.pdf") #2 class plot plt.title('2-class plot') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("2-class.pdf") #2 class logistic regression decision boundary xx, yy = np.mgrid[4:8:.01, 0.5:7.5:.01] grid = np.c_[xx.ravel(), yy.ravel()] probs = m_logr.predict_proba(grid)[:, 1].reshape(xx.shape) plt.title('2-class Logistic Regression Decision Boundary') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.contour(xx, yy, probs, levels=[.5], colors="black") plt.savefig("2-class-logr.pdf") #3 class logistic regression probabilistic decision boundary xx, yy = np.mgrid[4:8:0.01, 0.5:7.5:0.01] Z = m_logr.predict_proba(np.vstack((xx.ravel(), yy.ravel())).T)[:, 1] Z = Z.reshape(xx.shape) image = plt.imshow(Z.T, interpolation='nearest', extent=(4, 8, 0.5, 7.5), aspect='auto', origin='lower', cmap=plt.cm.RdBu) plt.colorbar(image) plt.title('2-class Logistic Regression\n Probabilistic Decision Boundary') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==0],X[:,1][y==0], label="setosa",color="green",edgecolors=(0, 0, 0)) plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("2-class-logr-prob.pdf") #gaussian process decision map xx, yy = np.mgrid[4:8:0.05, 0.5:7.5:0.05] kernel = 1.0 * RBF([1.0, 1.0])#rbf_anisotropic m_gpc = GaussianProcessClassifier(kernel=kernel).fit(Xt, yt) Z = m_gpc.predict_proba(np.vstack((xx.ravel(), yy.ravel())).T)[:, 1] Z = Z.reshape(xx.shape) image = plt.imshow(Z.T, interpolation='nearest', extent=(4, 8, 0.5, 7.5), aspect='auto', origin='lower', cmap=plt.cm.RdBu) plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==0],X[:,1][y==0], label="setosa",color="green",edgecolors=(0, 0, 0)) plt.colorbar(image) plt.title("2-class RBF Gaussian Process Classifier\n Decision Map") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("2-class-gpc-prob.pdf") #adversarial predictor classifier m_apc = AdversarialPredictionClassifier() m_apc.fit(Xt,yt) xx, yy = np.mgrid[4:8:0.05, 0.5:7.5:0.05] Z = m_apc.predict_conf(np.vstack((xx.ravel(), yy.ravel())).T) Z_a = [] for i in Z: if i[0][0]>i[0][1]: Z_a.append(0.5-i[1]/2.) else: Z_a.append(0.5+i[1]/2.) Z_a = np.array(Z_a) Z_a = Z_a.reshape(xx.shape) image = plt.imshow(Z_a.T, interpolation='nearest', extent=(4, 8,0.5, 7.5), aspect='auto', origin='lower', cmap=plt.cm.RdBu) plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==0],X[:,1][y==0], label="setosa",color="green",edgecolors=(0, 0, 0)) plt.colorbar(image) plt.title("2-class Adversarial Predictor Classifier\n Confidence Map") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("2-class-apc-prob4.pdf") #visual description of apc pred = m_apc.predict_conf(Xs[1].reshape(1,2)) X_cand = np.array(m_apc.X_cand) plt.title('Predicting new sample x') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X[:,0][y==2],X[:,1][y==2], label="virginica",color="blue",edgecolors=(0, 0, 0)) plt.scatter(Xs[1][0],Xs[1][1], label="new sample to be predicted",color="grey",edgecolors=(0, 0, 0),marker="x") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("new-sample.pdf") plt.title('Base classifier prediction: versicolor') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(Xs[1][0],Xs[1][1], label="new sample to be predicted",color="grey",edgecolors=(0, 0, 0),marker="x") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("versicolor-predicted.pdf") plt.title('Adversarial sample is generated') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X_cand[:,0],X_cand[:,1], label="adversarial sample",color="grey",edgecolors=(0, 0, 0),marker="x") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.legend() plt.savefig("adversarial-sample.pdf") xx, yy = np.mgrid[4:8:.01, 0.5:7.5:.01] grid = np.c_[xx.ravel(), yy.ravel()] probs = m_apc.m_adv.predict_proba(grid)[:, 1].reshape(xx.shape) plt.title('High accuracy means low confidence') plt.scatter(X[:,0][y==1],X[:,1][y==1], label="versicolor",color="red",edgecolors=(0, 0, 0)) plt.scatter(X_cand[:,0],X_cand[:,1], label="adversarial sample",color="grey",edgecolors=(0, 0, 0),marker="x") plt.xlabel("Sepal Length") plt.ylabel("Petal Length") plt.xlim(4,8) plt.ylim(0.5,7.5) plt.contour(xx, yy, probs, levels=[.5], colors="black") plt.legend() plt.savefig("confidence-classifier.pdf")
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Gym/web_athlete/models.py
Ahmadrezasamadi/django-internship
6
83688
from django.db import models from django.contrib.auth.models import User import datetime # Create your models here. class Time_option(models.Model): timee = models.CharField(max_length = 10) def __str__(self): return self.timee class Fields(models.Model): name = models.CharField(max_length = 200) def __str__(self): return self.name class F_t(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE) time = models.DateField(auto_now=datetime.datetime.now()) Field = models.ForeignKey(Fields, on_delete=models.CASCADE) time_options = models.ForeignKey(Time_option, on_delete=models.CASCADE) class Member(models.Model): sexuality = ( ('M','male'), ('F','female'), ('O','other'), ) skills = ( ('‌‌B','beginner'), ('E','elementary'), ('P','professional'), ) name = models.CharField(max_length = 200) user = models.ForeignKey(User,on_delete=models.CASCADE) phone_number = models.CharField(max_length = 11) field = models.ForeignKey(Fields,on_delete=models.CASCADE) birth_date = models.DateTimeField() first_session_date = models.DateTimeField(auto_now=True) sex = models.CharField(max_length =1 ,choices=sexuality) age = models.IntegerField() skill = models.CharField(max_length=1,choices = skills) profile = models.TextField(max_length = 200) class_time = models.ForeignKey(Time_option,on_delete=models.CASCADE) def __str__(self): return self.name
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src/ase2sprkkr/potentials/definitions/potential.py
ase2sprkkr/ase2sprkkr
1
143153
<gh_stars>1-10 """ Here, the format of the potential_file is defined """ from .sections import * def fce(): from ...common.misc import OrderedDict from ...common.grammar_types import \ Keyword, DefKeyword, Table, Array, Sequence, \ integer, Date, boolean, line_string from ..potential_definitions import \ PotSectionDefinition, \ ASEArraySectionDefinition, \ PotValueDefinition as V,\ PotentialDefinition, \ Separator import datetime sections = [] def Section(*args, cls=PotSectionDefinition, **kwargs): x=cls(*args, **kwargs) sections.append(x) return x def ArraySection(array_name): def factory(*args, **kwargs): return ASEArraySectionDefinition(*args, array_name = array_name, **kwargs) return factory Section('HEADER', [ Separator(), V('HEADER', line_string, lambda x: f'SPR-KKR potential file, created at {datetime.datetime.now()}'), Separator(), V('TITLE', line_string, 'Created by ASE-SPR-KKR wrapper'), V('SYSTEM', line_string, lambda x: 'System: {}'.format(x._get_root_container().atoms.symbols) ), V('PACKAGE', line_string, 'SPR-KKR'), V('FORMAT', Sequence(int, Date(prefix='(', postfix=')'), names = ['VERSION', 'DATE']), default_value = [7, datetime.datetime(2007,5,21)]), ], name_in_grammar = False) Section('GLOBAL SYSTEM PARAMETER', cls = GlobalSystemParameterDefinition) Section('SCF-INFO', [ V('INFO', line_string, 'NONE'), V('SCFSTATUS', DefKeyword('START', 'CONVERGED', 'ITR-BULK')), V('FULLPOT', False), V('BREITINT', False), V('NONMAG', False, alternative_names='NOMAG'), V('ORBPOL', str, 'NONE'), V('EXTFIELD', False), V('BLCOUPL', False), V('BEXT', 0.0), V('SEMICORE', False), V('LLOYD', False), V('NE', Array(int), is_optional = True), V('IBZINT', int, is_optional = True), V('NKTAB', int, is_optional = True), # V('XC-POT', str, is_optional = True), V('SCF-ALG', Keyword('BROYDEN', 'BROYDEN2'), is_optional = True), V('SCF-ITER', 0), V('SCF-MIX', 0.2), V('SCF-TOL', 1e-5), V('RMSAVV', 999999.), V('RMSAVB', 999999.), V('EF', 999999.), V('VMTZ', 0.7), ], ) Section('LATTICE', cls = LatticeSectionDefinition) Section('SITES', cls = SitesSectionDefinition) Section('OCCUPATION', cls = OccupationSectionDefinition) Section('REFERENCE SYSTEM', cls = ReferenceSystemSectionDefinition) Section('MAGNETISATION DIRECTION', [ V('KMROT', int, 0), V('QMVEC', Array([0.,0.,0.])), V('DATA', Table({'MTET_Q' : float, 'MPHI_Q' : float }, numbering='IQ', free_header = True)), V('IT_DATA', Table({'IT': int, 'MTET_Q' : float, 'MPHI_T' : float, 'MGAM_T': float}, free_header = lambda x: '*' not in x), is_optional=True), ], cls = ArraySection('magnetisation_direction') ) Section('MESH INFORMATION', cls = MeshInformationSectionDefinition) Section('OCCUPATION', cls = OccupationSectionDefinition) Section('TYPES', cls = TypesSectionDefinition) return PotentialDefinition(sections) potential_definition = fce() """ Potential file format definition """ del fce
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Ch6/iris.py
quietcoolwu/MLCode
0
187161
<gh_stars>0 # Code from Chapter 6 of Machine Learning: An Algorithmic Perspective (2nd Edition) # by <NAME> (http://stephenmonika.net) # You are free to use, change, or redistribute the code in any way you wish for # non-commercial purposes, but please maintain the name of the original author. # This code comes with no warranty of any kind. # <NAME>, 2008, 2014 # Various dimensionality reductions running on the Iris dataset import pylab as pl import numpy as np iris = np.loadtxt('../3 MLP/iris_proc.data', delimiter=',') iris[:, :4] = iris[:, :4] - iris[:, :4].mean(axis=0) imax = np.concatenate((iris.max(axis=0) * np.ones((1, 5)), iris.min(axis=0) * np.ones((1, 5))), axis=0).max(axis=0) iris[:, :4] = iris[:, :4] / imax[:4] labels = iris[:, 4:] iris = iris[:, :4] order = list(range(np.shape(iris)[0])) np.random.shuffle(order) iris = iris[order, :] labels = labels[order, 0] w0 = np.where(labels == 0) w1 = np.where(labels == 1) w2 = np.where(labels == 2) import lda newData, w = lda.lda(iris, labels, 2) print(np.shape(newData)) pl.plot(iris[w0, 0], iris[w0, 1], 'ok') pl.plot(iris[w1, 0], iris[w1, 1], '^k') pl.plot(iris[w2, 0], iris[w2, 1], 'vk') pl.axis([-1.5, 1.8, -1.5, 1.8]) pl.axis('off') pl.figure(2) pl.plot(newData[w0, 0], newData[w0, 1], 'ok') pl.plot(newData[w1, 0], newData[w1, 1], '^k') pl.plot(newData[w2, 0], newData[w2, 1], 'vk') pl.axis([-1.5, 1.8, -1.5, 1.8]) pl.axis('off') import pca x, y, evals, evecs = pca.pca(iris, 2) pl.figure(3) pl.plot(y[w0, 0], y[w0, 1], 'ok') pl.plot(y[w1, 0], y[w1, 1], '^k') pl.plot(y[w2, 0], y[w2, 1], 'vk') pl.axis('off') import kernelpca newData = kernelpca.kernelpca(iris, 'gaussian', 2) pl.figure(4) pl.plot(newData[w0, 0], newData[w0, 1], 'ok') pl.plot(newData[w1, 0], newData[w1, 1], '^k') pl.plot(newData[w2, 0], newData[w2, 1], 'vk') pl.axis('off') import factoranalysis newData = factoranalysis.factoranalysis(iris, 2) # print newData pl.figure(5) pl.plot(newData[w0, 0], newData[w0, 1], 'ok') pl.plot(newData[w1, 0], newData[w1, 1], '^k') pl.plot(newData[w2, 0], newData[w2, 1], 'vk') pl.axis('off') import lle print(np.shape(iris)) a, b, newData = lle.lle(iris, 2, 12) print(np.shape(newData)) print(newData[w0, :]) print("---") print(newData[w1, :]) print("---") print(newData[w2, :]) pl.plot(newData[w0, 0], newData[w0, 1], 'ok') pl.plot(newData[w1, 0], newData[w1, 1], '^k') pl.plot(newData[w2, 0], newData[w2, 1], 'vk') pl.axis('off') import isomap print(labels) newData, newLabels = isomap.isomap(iris, 2, 100) print(np.shape(newData)) print(newLabels) w0 = np.where(newLabels == 0) w1 = np.where(newLabels == 1) w2 = np.where(newLabels == 2) pl.plot(newData[w0, 0], newData[w0, 1], 'ok') pl.plot(newData[w1, 0], newData[w1, 1], '^k') pl.plot(newData[w2, 0], newData[w2, 1], 'vk') pl.axis('off') print("Done") pl.show()
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lastfm.py
Metastruct/hal1320
1
164643
from sopel.module import commands from sopel.config import ConfigurationError from sopel.config.types import StaticSection, ValidatedAttribute import urllib, json class LastFMsection(StaticSection): path = ValidatedAttribute('apikey') def setup(bot): bot.config.define_section('lastfm', LastFMsection) def configure(config): config.define_section('lastfm', LastFMsection, validate=False) config.lastfm.configure_setting('apikey', 'Last.fm API key') @commands('lastfm') def lastfm(bot, trigger): username = trigger.group(2) if not username: bot.say('You need to specify a username.') else: resp = urllib.urlopen("http://ws.audioscrobbler.com/2.0/?method=user.getrecenttracks&user={0}&api_key={1}&format=json".format(username, bot.config.lastfm.apikey)) if not resp: bot.say('Failed to request last.fm data.') else: data = json.loads(resp.read()) if not data: bot.say('Failed to parse last.fm data.') else: if not 'recenttracks' in data or not 'track' in data['recenttracks']: bot.say('Invalid username or no recently played tracks.') else: currenttrack = '' for track in data['recenttracks']['track']: if '@attr' in track and track['@attr']['nowplaying']: currenttrack = '{0} - {1}'.format(track['artist']['#text'], track['name']) break if currenttrack != '': bot.say('{0} is currently listening to: {1} (via last.fm)'.format(username, currenttrack)) else: bot.say('%s is not currently listening to anything.' % username)
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back/color.py
PoCInnovation/AI4UX
0
27906
<filename>back/color.py import extcolors import PIL def new_image(image, x1, y1, x2, y2): area = (x1, y1, x2, y2) tmp = image.crop(area) return tmp def nbColor_daltonisme(image, total): protanopie = [] # Ne voit pas le rouge deutéranopie = [] # Ne voit pas le vert tritanopie = [] # Ne voit pas le bleu color_tab = [] colors, pixel_count = extcolors.extract_from_image(image) above = 0 for color in colors: percentage = color[1] / total * 100 if percentage > 15: above += 1 if percentage > 5 and color[0][2] > 200 and color[0][0] < 200 and color[0][1] < 200: tritanopie.append(color) if percentage > 5 and color[0][1] > 200 and color[0][0] < 200 and color[0][2] < 200: deutéranopie.append(color) if percentage > 5 and color[0][0] > 200 and color[0][1] < 200 and color[0][2] < 200: protanopie.append(color) color_tuple = (color[0][0], color[0][1], color[0][2], percentage) color_tab.append(color_tuple) return above, (len(protanopie) + len(deutéranopie) + len(tritanopie)) / len(colors), color_tab def padding_ratio(image, total): colors, pixel = extcolors.extract_from_image(image) i = 0 total_percent = 0 percentage = 0 for color in colors: percentage = color[1] / total * 100 if i < 3: total_percent += percentage i += 1 return total_percent def dataColor(image): width, height = image.size total = width * height above, score_dalto, color_tab = nbColor_daltonisme(image, total) image_first = new_image(image, 0, 0, width // 4, height) size_first_w, size_first_h = image_first.size total_first = size_first_w * size_first_h percent_first = padding_ratio(image_first, total_first) image_forth = new_image(image, (width // 4) * 3, 0, width, height) size_forth_w, size_forth_h = image_forth.size total_forth = size_forth_w * size_forth_h percent_forth = padding_ratio(image_forth, total_forth) score_color = 1.0 if above > 3: score_color -= 0.15 * (above - 3) if score_color < 0.0: score_color = 0.0 return score_color, 1 - score_dalto, round(percent_first) / 100, round(percent_forth) / 100, color_tab if __name__ == "__main__": ## IMAGE ## image = PIL.Image.open("web_screenshot.png") print(dataColor(image))
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PFERD/crawl/ilias/__init__.py
Toorero/PFERD
74
127196
<filename>PFERD/crawl/ilias/__init__.py from .kit_ilias_web_crawler import KitIliasWebCrawler, KitIliasWebCrawlerSection __all__ = ["KitIliasWebCrawler", "KitIliasWebCrawlerSection"]
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blender/2.79/scripts/addons/add_mesh_extra_objects/geodesic_domes/__init__.py
uzairakbar/bpy2.79
2
66521
# ##### BEGIN GPL LICENSE BLOCK ##### # # 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 2 # 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, write to the Free Software Foundation, # Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # ##### END GPL LICENSE BLOCK ##### bl_info = { "name": "Geodesic Domes2", "author": "Noctumsolis, PKHG, Meta Androcto, <NAME>", "version": (0, 3, 2), "blender": (2, 7, 1), "location": "Toolshelf > Create Tab", "description": "Create geodesic dome type objects.", "warning": "", "wiki_url": "https://wiki.blender.org/index.php/Extensions:2.6/Py/Scripts/Modeling/Geodesic_Domes", "tracker_url": "", "category": "Mesh"} if "bpy" in locals(): import importlib importlib.reload(third_domes_panel_271) else: from . import third_domes_panel_271 import bpy def register(): bpy.utils.register_module(__name__) def unregister(): bpy.utils.unregister_module(__name__) if __name__ == "__main__": register()
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pyaud_plugins/_plugins/action.py
jshwi/pyaud-plugins
0
170014
""" pyaud_plugins._plugins.action ============================= """ import shutil import typing as t from pathlib import Path import pyaud from pyaud_plugins._abc import SphinxBuild from pyaud_plugins._environ import environ as e from pyaud_plugins._parsers import LineSwitch, Md2Rst from pyaud_plugins._utils import colors @pyaud.plugins.register() class Tests(pyaud.plugins.Action): """Run the package unit-tests with ``pytest``.""" pytest = "pytest" cache = True cache_all = True @property def exe(self) -> t.List[str]: return [self.pytest] @property def is_tests(self) -> bool: """Confirm that a test suite exists. :return: Does a test suite exist? True or False. """ return any( f for f in pyaud.files for p in ("test_*.py", "*_test.py") if f.match(p) and str(e.TESTS) in str(f) ) def action(self, *args: str, **kwargs: bool) -> int: if self.is_tests: return self.subprocess[self.pytest].call(*args, **kwargs) print("No tests found") return 0 @pyaud.plugins.register() class Coverage(Tests): """Run package unit-tests with ``pytest`` and ``coverage``.""" coverage = "coverage" @property def exe(self) -> t.List[str]: return [self.pytest, self.coverage] def action(self, *args: str, **kwargs: bool) -> int: returncode = super().action( *[f"--cov={i}" for i in pyaud.files.reduce()], **kwargs ) if self.is_tests and not returncode: kwargs["suppress"] = True return self.subprocess[self.coverage].call("xml", *args, **kwargs) print("No coverage to report") return returncode @pyaud.plugins.register() class Docs(SphinxBuild): """Compile package documentation with ``Sphinx``. This is so the hyperlink isn't exactly the same as the package documentation. Build the ``Sphinx`` html documentation. Return the README's title to what it originally was. """ @property def args(self) -> t.Tuple[t.Union[str, Path], ...]: return "-M", "html", e.DOCS, e.BUILDDIR, "-W" def action(self, *args: str, **kwargs: bool) -> int: returncode = 0 pyaud.plugins.get("toc")(*args, **kwargs) shutil.rmtree(e.BUILDDIR, ignore_errors=True) with Md2Rst(e.README_MD, temp=True): if e.DOCS_CONF.is_file() and e.README_RST.is_file(): with LineSwitch( e.README_RST, {0: e.README_RST.stem, 1: len(e.README_RST.stem) * "="}, ): returncode = self.sphinx_build(*args, **kwargs) return returncode @pyaud.plugins.register() class DoctestReadme(pyaud.plugins.Action): """Run ``doctest`` on Python code-blocks in README.""" python = "python" @property def exe(self) -> t.List[str]: return [self.python] def action(self, *args: str, **kwargs: bool) -> int: returncode = self.subprocess[self.python].call( "-m", "doctest", e.README_RST ) if not returncode: colors.green.bold.print( "Success: No issues found in {}".format( e.README_RST.relative_to(Path.cwd()) ) ) return returncode @pyaud.plugins.register() class DoctestPackage(SphinxBuild): """Run ``doctest`` on package.""" cache = True @property def args(self) -> t.Tuple[t.Union[str, Path], ...]: return "-M", "doctest", e.DOCS, e.BUILDDIR
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powerflow.py
simoncometto/PowerFlow
0
159449
# coding=utf-8 import numpy as np import scipy as sp import scipy.sparse as sparse import scipy.sparse.linalg as sparse_alg from time import time import IEEE_cdf as cdf from jacobian import jacobian from P_Q import P_Q class powerflow: ''' ''' def __init__(self, filename=''): n, mat_admitancia, load, generation, voltage_phase, swing_bus, PV_buses = cdf.read(filename) self.n = n self.Y = sparse.coo_matrix(mat_admitancia) self.swing_bus = swing_bus self.PV_buses = PV_buses delta_PQ = generation-load self.P = delta_PQ.real self.Q = delta_PQ.imag self.P_Q_inj = delta_PQ[1:].real self.P_Q_inj = np.append(self.P_Q_inj, delta_PQ[1:].imag) def J(self, x): '''Computa el jacobiano para un valor de tensión y ángulo dado :parameter x: un vactor de 2*(n-1) donde n es la cantidad de nodos del sistema :returns jacobiano: una matriz de 2(n-1) x 2(n-1) ''' return jacobian(self.Y, x, self.swing_bus, self.last_P_Q) def f(self, x): ''' Computa deltaP y deltaQ para un valor de tensión y ángulo dado :parameter x un vactor de 2*(n-1) donde n es la cantidad de nodos del sistema :returns delta_PQ: una vector de 2(n-1)''' self.last_P_Q = P_Q(self.Y, x) return (self.P_Q_inj - self.last_P_Q) def solve_newton(self, initial_voltage=1, initial_angle=0): theta = initial_angle * np.ones(self.n-1) v = initial_voltage * np.ones(self.n-1) x = np.append(theta, v) #while(delta_x < convergencia): for i in range(1): func = self.f(x) #self.disp_matrix(np.vstack([func, func])) jaco = self.J(x) J_to_disp = jaco.todense() #self.disp_matrix(J_to_disp[:self.n-1,:self.n-1]) #Jacobiano reducido rJ = jaco.todense() #Las filas a eliminar son aquellas que corresponden a la dQ/dtheta de un PV bus filas_a_eliminar = self.PV_buses- 1 + self.n-1 #Las columas a eliminar son aquellas que corresponden a la dP/dV de un PV bus columnas_a_eliminar = filas_a_eliminar rJ = np.delete(rJ, filas_a_eliminar, 0) rJ = np.delete(rJ, columnas_a_eliminar, 1) #self.disp_matrix(rJ) #a = sparse_alg.spsolve(jaco,-func) func_reducido = np.delete(func, columnas_a_eliminar) a = np.linalg.solve(rJ, -func_reducido) xn = a - x x = xn return x def disp_matrix(self, mat): import matplotlib.pyplot as plt if sparse.issparse(mat): mat = mat.todense() mat_plot = mat != 0.0 plt.matshow(mat_plot) plt.show() #--------------------------------------------------------------------------------------------- if __name__ == '__main__': ieee14bus = powerflow('IEEE14cdf.txt') start = time() x = ieee14bus.solve_newton() end = time() #print(x) print('Tiempo: ', end-start, 's')
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tests/test_filters.py
Ryanb58/algoliaqb
4
79598
from algoliaqb import AlgoliaQueryBuilder def test_normal_filters(): aqb = AlgoliaQueryBuilder( search_param="search", filter_map={ "is_reported": "is_reported" } ) flask_request_args = { "is_reported": True } filter_query = aqb.get_filter_query(flask_request_args) assert filter_query == "is_reported:True" def test_object_filters(): aqb = AlgoliaQueryBuilder( search_param="search", filter_map={ "status_id": { "status_id": "statuses.status_id", "group_id": "statuses.group_id" }, "is_reported": "is_reported" } ) flask_request_args = { "is_reported": True, "status_id": 21, "group_id": 4 } filter_query = aqb.get_filter_query(flask_request_args) assert "is_reported:True" in filter_query assert "statuses.status_id:21" in filter_query assert "statuses.group_id:4" in filter_query assert filter_query == "(statuses.status_id:21 AND statuses.group_id:4) AND is_reported:True" def test_date_filter(): aqb = AlgoliaQueryBuilder( search_param="search", filter_map={ "group_id":"group_id", "created_on": { "type": "date", "created_on_start": "created_on", "created_on_end": "created_on" } } ) flask_request_args = { "group_id": 4, "created_on_start": "1538697600", } filter_query = aqb.get_filter_query(flask_request_args) assert "created_on > 1538697600" in filter_query assert filter_query == "group_id:4 AND created_on > 1538697600" flask_request_args = { "group_id": 4, "created_on_start": "1538697600", "created_on_end": "1539697800", } filter_query = aqb.get_filter_query(flask_request_args) assert "created_on:1538697600 TO 1539697800" in filter_query assert filter_query == "group_id:4 AND created_on:1538697600 TO 1539697800" flask_request_args = { "group_id": 4, "created_on_end": "1539697800", } filter_query = aqb.get_filter_query(flask_request_args) assert "created_on < 1539697800" in filter_query assert filter_query == "group_id:4 AND created_on < 1539697800" def test_not_using_normal_string_filters(): aqb = AlgoliaQueryBuilder( search_param="search", filter_map={ "group_id": "group_id", "status_id": { "group_id": "statuses.group_id", "status_id": "statuses.status_id", }, "is_reported": "is_reported", "main_contact_account_id": "main_contact.account_id", "created_on": { "type": "date", "created_on_start": "created_on", "created_on_end": "created_on", }, "updated_on": { "type": "date", "updated_on_start": "updated_on", "updated_on_end": "updated_on", }, "referral_source_id": { "group_id": "referral_sources.group_id", "referral_source_id": "referral_sources.id", }, "tag_id": { "group_id": "tags.group_id", "tag_id": "tags.id", } } ) flask_request_args = { "page": 1, "order_by": "status_custom-position", "group_id": 4, } filter_query = aqb.get_filter_query(flask_request_args) assert "group_id:4" in filter_query assert filter_query == "group_id:4"
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deepx/nn/stats.py
sharadmv/deepx
74
47543
import numpy as np from .. import T from ..layer import ShapedLayer from ..initialization import initialize_weights from .full import Linear from .. import stats __all__ = ['Gaussian', 'Bernoulli', 'IdentityVariance'] class Gaussian(Linear): def __init__(self, *args, **kwargs): self.cov_type = kwargs.pop('cov_type', 'diagonal') self.min_stdev = kwargs.pop('min_stdev', 1e-2) super(Gaussian, self).__init__(*args, **kwargs) assert not self.elementwise def initialize(self): if not self.elementwise: dim_in, dim_out = self.get_dim_in()[-1], self.get_dim_out()[-1] left = initialize_weights(self.initialization, [dim_in, dim_out // 2]) right = T.zeros([dim_in, dim_out // 2]) self.create_parameter('W', [dim_in, dim_out], initial_value=( T.concatenate([ right, left ], -1) )) self.create_parameter('b', [dim_out], initial_value=np.zeros([dim_out])) def get_dim_out(self): return [self.dim_out[0] * 2] def activate(self, X): if self.cov_type == 'diagonal': scale_diag, mu = T.split(X, 2, axis=-1) if hasattr(self, 'min_stdev'): scale_diag = T.softplus(scale_diag) + self.min_stdev else: scale_diag = T.softplus(scale_diag) + 1e-5 return stats.GaussianScaleDiag([scale_diag, mu], parameter_type='regular') raise Exception("Undefined covariance type: %s" % self.cov_type) def __str__(self): return "Gaussian(%s)" % self.dim_out class Bernoulli(Linear): def __init__(self, *args, **kwargs): self.parameter_type = kwargs.pop('parameter_type', 'natural') super(Bernoulli, self).__init__(*args, **kwargs) def activate(self, X): if self.elementwise: return stats.Bernoulli(X, parameter_type=self.parameter_type) return stats.Bernoulli(X, parameter_type=self.parameter_type) def __str__(self): return "Bernoulli(%s)" % self.dim_out class IdentityVariance(ShapedLayer): def __init__(self, variance=1e-4, *args, **kwargs): self.variance = variance super(IdentityVariance, self).__init__(*args, **kwargs) def initialize(self): pass def get_parameters(self): return [] def infer_shape(self, shape): if shape is None: return if self.elementwise: self.dim_in = shape self.dim_out = shape return if self.dim_in is None: self.dim_in = shape def forward(self, X): return stats.GaussianScaleDiag([np.sqrt(self.variance) * T.ones_like(X), X])
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packages/main/tests/python/test_pdf.py
ete99/rpaframework
2
1611911
from pathlib import Path import pytest from RPA.PDF import PDF RESOURCE_DIR = Path(__file__).resolve().parent / ".." / "resources" TEMP_DIR = Path(__file__).resolve().parent / ".." / "temp" imagesandtext_pdf = RESOURCE_DIR / "imagesandtext.pdf" invoice_pdf = RESOURCE_DIR / "invoice.pdf" vero_pdf = RESOURCE_DIR / "vero.pdf" pytest_pdf = RESOURCE_DIR / "18467.pdf" loremipsum_pdf = RESOURCE_DIR / "LoremIpsum.pdf" encrypted_pdf = RESOURCE_DIR / "encrypted.pdf" @pytest.fixture def library(): return PDF() def test_page_count(library): assert library.get_number_of_pages(invoice_pdf) == 1 assert library.get_number_of_pages(vero_pdf) == 2 assert library.get_number_of_pages(pytest_pdf) == 9 def test_page_info(library): info = library.get_info(pytest_pdf) assert info["Pages"] == 9 assert not info["Encrypted"] assert not info["Fields"] info = library.get_info(vero_pdf) assert info["Fields"] assert info["Pages"] == 2 def test_get_text_from_all_pages(library): text = library.get_text_from_pdf(loremipsum_pdf) assert len(text) == 1, "text should be parsed from 1 pages" assert len(text[1]) == 3622 text = library.get_text_from_pdf(vero_pdf) assert len(text) == 2, "text should be parsed from 2 pages" assert "Muualle lomakkeeseen kirjoittamaasi tietoa ei käsitellä." in text[2] def test_get_text_from_specific_page(library): text = library.get_text_from_pdf(pytest_pdf, pages=[7]) assert "Plugins for Web Development" in text[7] def test_set_anchor_to_element(library): library.open_pdf_document(invoice_pdf) result = library.set_anchor_to_element("text:due date") assert result result = library.set_anchor_to_element("text:due to the date") assert not result def test_get_value_from_anchor_by_default_from_right(library): library.open_pdf_document(invoice_pdf) invoice_number = library.get_value_from_anchor("text:invoice number") order_number = library.get_value_from_anchor("text:order number") invoice_date = library.get_value_from_anchor("text:invoice date") due_date = library.get_value_from_anchor("text:due date") total_due = library.get_value_from_anchor("text:total due") assert invoice_number.text == "INV-3337" assert order_number.text == "12345" assert invoice_date.text == "January 25, 2016" assert due_date.text == "January 31, 2016" assert total_due.text == "$93.50" def test_get_value_from_anchor_from_left(library): library.open_pdf_document(invoice_pdf) invoice_label = library.get_value_from_anchor("text:INV-3337", direction="left") assert invoice_label.text == "Invoice Number" def test_get_from_anchor_from_bottom(library): library.open_pdf_document(invoice_pdf) service = library.get_value_from_anchor("text:service", direction="bottom") assert "Web Design" in service.text def test_get_from_anchor_from_top(library): library.open_pdf_document(invoice_pdf) item = library.get_value_from_anchor("text:Tax", direction="top") assert item.text == "Sub Total" def test_extract_pages_from_pdf(library): pages = [7, 8] target_pdf = TEMP_DIR / "extracted.pdf" library.extract_pages_from_pdf(pytest_pdf, target_pdf, pages) assert library.get_number_of_pages(target_pdf) == 2 text = library.get_text_from_pdf(target_pdf) assert "Plugins for Web Development" in text[1] def test_rotating(library): target_pdf = TEMP_DIR / "rotated.pdf" library.page_rotate(1, vero_pdf, target_pdf) # TODO. Assert def test_get_pdf_xml_dump(library): library.open_pdf_document(invoice_pdf) xml = library.dump_pdf_as_xml() assert '<?xml version="1.0" encoding="utf-8" ?>' in xml def test_get_input_fields(library): fields = library.get_input_fields(vero_pdf) assert fields["Puhelinnumero"]["value"] == "" assert isinstance(fields["Puhelinnumero"]["rect"], list) fields = library.get_input_fields(vero_pdf, replace_none_value=True) assert fields["Puhelinnumero"]["value"] == "Puhelinnumero" @pytest.mark.skip(reason="known issue of reading fields of already updated pdf") def test_update_field_values(library): update_fields = {"Puhelinnumero": "10-1231233", "Paivays": "01.01.2020"} target_pdf = TEMP_DIR / "values_updated.pdf" fields = library.get_input_fields(vero_pdf) assert fields["Puhelinnumero"]["value"] == "" library.update_field_values(vero_pdf, target_pdf, update_fields) fields = library.get_input_fields(target_pdf) assert fields["Puhelinnumero"]["value"] == update_fields["Puhelinnumero"] assert fields["Paivays"]["value"] == update_fields["Paivays"] def test_set_field_value(library): target_pdf = TEMP_DIR / "copy_of_vero.pdf" library.open_pdf_document(vero_pdf) library.set_field_value("Puhelinnumero", "+358-55-12322121312") library.set_field_value("Paivays", "31.12.2020") library.save_pdf(vero_pdf, target_pdf) def test_get_texts_matching_regexp(library): pass
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test/test_app.py
dmillington/lunchroulette
1
97595
import pytest from unittest.mock import MagicMock, patch from lunchroulette.models import SlackAccessToken, RouletteMessage # test / (hello world) def test_root(client): resp = client.get('/') assert resp.status_code == 200 assert resp.get_data() == b'Hello World' # test /begin_auth def test_begin_auth(client): CLIENT_ID = 'NOCLIENTID' OAUTH_SCOPE = 'NOBOTSCOPE' resp = client.get('/begin_auth') assert resp.status_code == 200 assert resp.get_data().decode() == f'<a href="https://slack.com/oauth/authorize?scope={ OAUTH_SCOPE }&client_id={ CLIENT_ID }">Add to Slack</a>' # test /finish_auth @patch('slack.WebClient.oauth_access') def test_finish_auth_new_token(mock_oa, client, session): mock_oa.return_value = dict(team_id='a', bot={'bot_access_token': 'b'}) resp = client.get('/finish_auth', query_string=dict(code='thecode')) mock_oa.assert_called_once() assert resp.status_code == 200 assert resp.get_data().decode() == 'Auth complete!' tokens = session.query(SlackAccessToken).all() assert len(tokens) == 1 assert tokens[0].team_id == 'a' assert tokens[0].access_token == 'b' # Test requesting for same team updates existing row mock_oa.return_value = dict(team_id='a', bot={'bot_access_token': 'c'}) resp = client.get('/finish_auth', query_string=dict(code='thecode')) mock_oa.assert_called() assert resp.status_code == 200 assert resp.get_data().decode() == 'Auth complete!' tokens = session.query(SlackAccessToken).all() assert len(tokens) == 1 assert tokens[0].team_id == 'a' assert tokens[0].access_token == 'c' # test /start_roulette @patch('slack.WebClient.chat_postMessage') def test_start_roulette_success(mock_pm, client, session): mock_pm.return_value = dict(channel='C012AB3CD', ts='1234567890.123456') session.add(SlackAccessToken(team_id='T12345', access_token='xoxa-access-token-string')) session.commit() resp = client.post('/start_roulette', data=dict(team_id='T12345', channel_id='C012AB3CD')) mock_pm.assert_called() assert resp.status_code == 200 messages = session.query(RouletteMessage).all() assert len(messages) == 1 assert messages[0].channel == 'C012AB3CD' assert messages[0].timestamp == '1234567890.123456' @patch('slack.WebClient.chat_postMessage') def test_start_roulette_already_started(mock_pm, client, session): session.add(SlackAccessToken(team_id='T12345', access_token='xoxa-access-token-string')) session.add(RouletteMessage(channel='C012AB3CD', timestamp='1234567890.123456')) session.commit() resp = client.post('/start_roulette', data=dict(team_id='T12345', channel_id='C012AB3CD')) mock_pm.assert_not_called() assert resp.status_code == 500 assert resp.headers.get('error') == 'There is already a roulette happening in this channel!' # test /end_roulette @patch('slack.WebClient.chat_postMessage') @patch('slack.WebClient.conversations_open') @patch('slack.WebClient.reactions_get') def test_end_roulette_success(mock_reactions, mock_conversations_open, mock_pm, client, session): mock_reactions.return_value = dict(message=dict(reactions=[dict(users=['ABCD','EFGH'])]), ts='1234567890.123456') mocked_channel_id = 'C012AB3CD' mocked_group_channel_id = 'D012AB3CD' mock_conversations_open.return_value = dict(channel=dict(id=mocked_group_channel_id)) session.add(SlackAccessToken(team_id='T12345', access_token='xoxa-access-token-string')) session.add(RouletteMessage(channel=mocked_channel_id, timestamp='1234567890.123456')) session.commit() resp = client.post('/end_roulette', data=dict(team_id='T12345', channel_id=mocked_channel_id)) mock_pm.assert_called_once_with(channel=mocked_group_channel_id, text="Hi! You all are going to get Lunch! You can use this channel to coordinate logistics.") assert resp.get_data() == b'Roulette ended! Matching people for lunch now. Participants will receive a group DM with their lunch buddies.' @patch('slack.WebClient.chat_postMessage') def test_end_roulette_not_started(mock_pm, client, session): mocked_channel_id = 'C012AB3CD' session.add(SlackAccessToken(team_id='T12345', access_token='xoxa-access-token-string')) session.commit() resp = client.post('/end_roulette', data=dict(team_id='T12345', channel_id=mocked_channel_id)) mock_pm.assert_not_called() assert resp.status_code == 500 assert resp.headers.get('error') == 'No roulette started. Try /lr_start first'
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environment_data.py
Yacine22/test_dome
0
76110
<gh_stars>0 """ Environment Data ----- """ from tkinter import * class environement_data: global date, place, projectname, object_of_interest def __init__(self): self.envi_wind = Tk() self.envi_wind.attributes('-fullscreen', True) self.envi_wind.title('environment') self.frame_exit = Frame(self.envi_wind) self.frame = Frame(self.envi_wind) keypad_frame = Frame(self.envi_wind) self.environment_list = ["Date", "Place", "Appelation", "Object Of Int"] self.button_exit = Button(self.frame_exit, text="Sortir", width=8, height=3, bg='white', fg='blue', font=('helvetica', 14, 'bold'), command=self.envi_wind.destroy) for i, data in enumerate(self.environment_list): label = Label(self.frame, text=data, width=15) label.grid(row=i, column=0, padx=10, pady=10, sticky='news') self.entries = [Entry(self.frame, width=30, bd=3, font=('helvetica', 10)) for i in range(len(self.environment_list))] self.entry_list = [] for i,e in enumerate(self.entries): e.grid(row=i, column=1, padx=5, pady=5) self.entry_list.append(e) btn_delete = Button(self.frame_exit, text='Del', bd=2, bg='white', fg='blue', font=('helvetica', 12), borderwidth=0, command=self.delete_text).grid(row=0, column=10, padx=5, pady=2, sticky='ne') btn_save = Button(self.frame_exit, text='Save', bd=2, bg='white', fg='blue', font=('helvetica', 12), borderwidth=0, command=self.save_data).grid(row=0, column=11, padx=5, pady=2, sticky='ne') cara = {1: (5, 2), 2: (5, 3), 3: (5, 4), 4: (5, 5), 5: (5, 6), 6: (5, 7), 7: (5, 8), 8: (5, 9), 9: (5, 10), 0: (5, 11), 'A':(6, 2), 'Z':(6, 3), 'E':(6, 4), 'R':(6, 5), 'T': (6, 6), 'Y':(6, 7), 'U':(6, 8), 'I':(6, 9), 'O':(6, 10), 'P':(6, 11), 'Q':(7, 2), 'S':(7, 3), 'D':(7, 4), 'F':(7, 5), 'G':(7, 6), 'H':(7, 7), 'J':(7, 8), 'K':(7, 9), 'L':(7, 10), 'M':(7, 11), 'W':(8, 2), 'X':(8, 3), 'C':(8, 4), 'V':(8, 5), 'B':(8, 6), 'N':(8, 7), ' ':(8, 8), '_':(8, 9), '-':(8, 10)} for car, grid_value in cara.items(): if grid_value[0] == 5: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], padx=1, pady=2, sticky='news') if grid_value[0] == 6: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') if grid_value[0] == 7: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') if grid_value[0] == 8: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') self.envi_wind.rowconfigure(0, weight=1) self.envi_wind.columnconfigure(0, weight=1) self.frame_exit.grid(row=0, column=0, sticky='ne') self.frame.grid(row=0, column=0, sticky='n') keypad_frame.grid(row=0, column=0, sticky='s') self.button_exit.grid(row=0, column=0, sticky='news') def set_text(self, text): widget = self.envi_wind.focus_get() if widget in self.entries: widget.insert("insert", text) def delete_text(self): widget = self.envi_wind.focus_get() widget.delete(0, END) def save_data(self): global data data_dict = {} for s, i in enumerate(self.entry_list): widget = i data = widget.get() data_dict[s] = data data_dict[self.environment_list[s]] = data_dict.pop(s) new_wind = Toplevel() new_wind.title("info") new_wind.attributes('-fullscreen', True) new_lab = Label(new_wind, text="data Saved!").grid(row=0, column=0) btn_quit_ = Button(new_wind, text="OK", command=new_wind.destroy).grid(row=1, column=0) inside_data['WHEN'] = data_dict["Date"] inside_data['WHERE'] = data_dict["Place"] what_keys = ["Appelation", "Object Of Int"] what_subset = {key: data_dict[key] for key in what_keys} inside_data['WHAT'] = what_subset data = data_dict["Date"] place = data_dict["Place"] projectname = data_dict["Appelation"] print(inside_data) return projectname class others: def __init__(self): self.envi_wind = Tk() self.envi_wind.attributes('-fullscreen', True) self.envi_wind.title('environment') self.frame_exit = Frame(self.envi_wind) self.frame = Frame(self.envi_wind) keypad_frame = Frame(self.envi_wind) self.environment_list = ["But de Projet", "Type de Projet", "Technique", "Distance objet"] self.button_exit = Button(self.frame_exit, text="Sortir", width=8, height=3, bg='white', fg='blue', font=('helvetica', 14, 'bold'), command=self.envi_wind.destroy) for i, data in enumerate(self.environment_list): label = Label(self.frame, text=data, width=15) label.grid(row=i, column=0, padx=10, pady=10, sticky='news') self.entries = [Entry(self.frame, width=30, bd=3, font=('helvetica', 10)) for i in range(len(self.environment_list))] self.entry_list = [] for i,e in enumerate(self.entries): e.grid(row=i, column=1, padx=5, pady=5) self.entry_list.append(e) btn_delete = Button(self.frame_exit, text='Del', bd=2, bg='white', fg='blue', font=('helvetica', 12), borderwidth=0, command=self.delete_text).grid(row=0, column=10, padx=5, pady=2, sticky='ne') btn_save = Button(self.frame_exit, text='Save', bd=2, bg='white', fg='blue', font=('helvetica', 12), borderwidth=0, command=self.save_data).grid(row=0, column=11, padx=5, pady=2, sticky='ne') cara = {1: (5, 2), 2: (5, 3), 3: (5, 4), 4: (5, 5), 5: (5, 6), 6: (5, 7), 7: (5, 8), 8: (5, 9), 9: (5, 10), 0: (5, 11), 'A':(6, 2), 'Z':(6, 3), 'E':(6, 4), 'R':(6, 5), 'T': (6, 6), 'Y':(6, 7), 'U':(6, 8), 'I':(6, 9), 'O':(6, 10), 'P':(6, 11), 'Q':(7, 2), 'S':(7, 3), 'D':(7, 4), 'F':(7, 5), 'G':(7, 6), 'H':(7, 7), 'J':(7, 8), 'K':(7, 9), 'L':(7, 10), 'M':(7, 11), 'W':(8, 2), 'X':(8, 3), 'C':(8, 4), 'V':(8, 5), 'B':(8, 6), 'N':(8, 7), ' ':(8, 8), '_':(8, 9), '-':(8, 10)} for car, grid_value in cara.items(): if grid_value[0] == 5: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], padx=1, pady=2, sticky='news') if grid_value[0] == 6: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') if grid_value[0] == 7: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') if grid_value[0] == 8: button = Button(keypad_frame, text=str(car), bg='white', fg='blue', font=('helvetica', 14, 'bold'), borderwidth=0, command=lambda x=car: self.set_text(x)).grid(row=grid_value[0], column=grid_value[1], pady=2, sticky='news') self.envi_wind.rowconfigure(0, weight=1) self.envi_wind.columnconfigure(0, weight=1) self.frame_exit.grid(row=0, column=0, sticky='ne') self.frame.grid(row=0, column=0, sticky='n') keypad_frame.grid(row=0, column=0, sticky='s') self.button_exit.grid(row=0, column=0, sticky='news') def set_text(self, text): widget = self.envi_wind.focus_get() if widget in self.entries: widget.insert("insert", text) def delete_text(self): widget = self.envi_wind.focus_get() widget.delete(0, END) def save_data(self): global data data_dict = {} for s, i in enumerate(self.entry_list): widget = i data = widget.get() data_dict[s] = data data_dict[self.environment_list[s]] = data_dict.pop(s) new_wind = Toplevel() new_wind.title("info") new_wind.attributes('-fullscreen', True) new_lab = Label(new_wind, text="data Saved!").grid(row=0, column=0) btn_quit_ = Button(new_wind, text="OK", command=new_wind.destroy).grid(row=1, column=0) inside_data['WHY'] = data_dict["But de Projet"] inside_data['WHY'] = data_dict["Type de Projet"] what_keys = ["Technique", "Distance objet"] what_subset = {key: data_dict[key] for key in what_keys} inside_data['HOW'] = what_subset print(inside_data)
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venv/lib/python3.6/site-packages/tensorflow/python/framework/cpp_shape_inference_pb2.py
yuxuan1995liu/darkflowyolo_detection
6
194726
# Generated by the protocol buffer compiler. DO NOT EDIT! # source: tensorflow/python/framework/cpp_shape_inference.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='tensorflow/python/framework/cpp_shape_inference.proto', package='tensorflow', syntax='proto3', serialized_options=_b('\370\001\001'), serialized_pb=_b('\n5tensorflow/python/framework/cpp_shape_inference.proto\x12\ntensorflow\x1a%tensorflow/core/framework/types.proto\x1a,tensorflow/core/framework/tensor_shape.proto\"\xed\x02\n\x17\x43ppShapeInferenceResult\x12+\n\x05shape\x18\x01 \x01(\x0b\x32\x1c.tensorflow.TensorShapeProto\x12\x43\n\x0bhandle_data\x18\x04 \x01(\x0b\x32..tensorflow.CppShapeInferenceResult.HandleData\x1a\x66\n\x12HandleShapeAndType\x12+\n\x05shape\x18\x01 \x01(\x0b\x32\x1c.tensorflow.TensorShapeProto\x12#\n\x05\x64type\x18\x02 \x01(\x0e\x32\x14.tensorflow.DataType\x1al\n\nHandleData\x12\x0e\n\x06is_set\x18\x01 \x01(\x08\x12N\n\x0eshape_and_type\x18\x02 \x03(\x0b\x32\x36.tensorflow.CppShapeInferenceResult.HandleShapeAndTypeJ\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04\"e\n\x1d\x43ppShapeInferenceInputsNeeded\x12\x1c\n\x14input_tensors_needed\x18\x01 \x03(\x05\x12&\n\x1einput_tensors_as_shapes_needed\x18\x02 \x03(\x05\x42\x03\xf8\x01\x01\x62\x06proto3') , dependencies=[tensorflow_dot_core_dot_framework_dot_types__pb2.DESCRIPTOR,tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2.DESCRIPTOR,]) _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE = _descriptor.Descriptor( name='HandleShapeAndType', full_name='tensorflow.CppShapeInferenceResult.HandleShapeAndType', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='shape', full_name='tensorflow.CppShapeInferenceResult.HandleShapeAndType.shape', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dtype', full_name='tensorflow.CppShapeInferenceResult.HandleShapeAndType.dtype', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=296, serialized_end=398, ) _CPPSHAPEINFERENCERESULT_HANDLEDATA = _descriptor.Descriptor( name='HandleData', full_name='tensorflow.CppShapeInferenceResult.HandleData', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='is_set', full_name='tensorflow.CppShapeInferenceResult.HandleData.is_set', index=0, number=1, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='shape_and_type', full_name='tensorflow.CppShapeInferenceResult.HandleData.shape_and_type', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=400, serialized_end=508, ) _CPPSHAPEINFERENCERESULT = _descriptor.Descriptor( name='CppShapeInferenceResult', full_name='tensorflow.CppShapeInferenceResult', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='shape', full_name='tensorflow.CppShapeInferenceResult.shape', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='handle_data', full_name='tensorflow.CppShapeInferenceResult.handle_data', index=1, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE, _CPPSHAPEINFERENCERESULT_HANDLEDATA, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=155, serialized_end=520, ) _CPPSHAPEINFERENCEINPUTSNEEDED = _descriptor.Descriptor( name='CppShapeInferenceInputsNeeded', full_name='tensorflow.CppShapeInferenceInputsNeeded', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='input_tensors_needed', full_name='tensorflow.CppShapeInferenceInputsNeeded.input_tensors_needed', index=0, number=1, type=5, cpp_type=1, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='input_tensors_as_shapes_needed', full_name='tensorflow.CppShapeInferenceInputsNeeded.input_tensors_as_shapes_needed', index=1, number=2, type=5, cpp_type=1, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=522, serialized_end=623, ) _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.fields_by_name['shape'].message_type = tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2._TENSORSHAPEPROTO _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.fields_by_name['dtype'].enum_type = tensorflow_dot_core_dot_framework_dot_types__pb2._DATATYPE _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.containing_type = _CPPSHAPEINFERENCERESULT _CPPSHAPEINFERENCERESULT_HANDLEDATA.fields_by_name['shape_and_type'].message_type = _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE _CPPSHAPEINFERENCERESULT_HANDLEDATA.containing_type = _CPPSHAPEINFERENCERESULT _CPPSHAPEINFERENCERESULT.fields_by_name['shape'].message_type = tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2._TENSORSHAPEPROTO _CPPSHAPEINFERENCERESULT.fields_by_name['handle_data'].message_type = _CPPSHAPEINFERENCERESULT_HANDLEDATA DESCRIPTOR.message_types_by_name['CppShapeInferenceResult'] = _CPPSHAPEINFERENCERESULT DESCRIPTOR.message_types_by_name['CppShapeInferenceInputsNeeded'] = _CPPSHAPEINFERENCEINPUTSNEEDED _sym_db.RegisterFileDescriptor(DESCRIPTOR) CppShapeInferenceResult = _reflection.GeneratedProtocolMessageType('CppShapeInferenceResult', (_message.Message,), dict( HandleShapeAndType = _reflection.GeneratedProtocolMessageType('HandleShapeAndType', (_message.Message,), dict( DESCRIPTOR = _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE, __module__ = 'tensorflow.python.framework.cpp_shape_inference_pb2' # @@protoc_insertion_point(class_scope:tensorflow.CppShapeInferenceResult.HandleShapeAndType) )) , HandleData = _reflection.GeneratedProtocolMessageType('HandleData', (_message.Message,), dict( DESCRIPTOR = _CPPSHAPEINFERENCERESULT_HANDLEDATA, __module__ = 'tensorflow.python.framework.cpp_shape_inference_pb2' # @@protoc_insertion_point(class_scope:tensorflow.CppShapeInferenceResult.HandleData) )) , DESCRIPTOR = _CPPSHAPEINFERENCERESULT, __module__ = 'tensorflow.python.framework.cpp_shape_inference_pb2' # @@protoc_insertion_point(class_scope:tensorflow.CppShapeInferenceResult) )) _sym_db.RegisterMessage(CppShapeInferenceResult) _sym_db.RegisterMessage(CppShapeInferenceResult.HandleShapeAndType) _sym_db.RegisterMessage(CppShapeInferenceResult.HandleData) CppShapeInferenceInputsNeeded = _reflection.GeneratedProtocolMessageType('CppShapeInferenceInputsNeeded', (_message.Message,), dict( DESCRIPTOR = _CPPSHAPEINFERENCEINPUTSNEEDED, __module__ = 'tensorflow.python.framework.cpp_shape_inference_pb2' # @@protoc_insertion_point(class_scope:tensorflow.CppShapeInferenceInputsNeeded) )) _sym_db.RegisterMessage(CppShapeInferenceInputsNeeded) DESCRIPTOR._options = None # @@protoc_insertion_point(module_scope)
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Scripts/check_two_strings_are_anagrams.py
alexcamargos/Learning_Python_Programming
2
188866
# #!/usr/bin/env python # encoding: utf-8 # -------------------------------------------------------------------------------------------------------------------- # # Name: check_two_strings_are_anagrams.py # Version: 1.0 # # Summary: Find Whether Two Strings are Anagrams # An interesting application of the Counter class is to find anagrams. # An anagram is a word or phrase formed by rearranging the letters of a different word or phrase. # If the Counter objects of two strings are equal, then they are anagrams. # # Author: <NAME> # Author-email: <EMAIL> # # License: MIT # # -------------------------------------------------------------------------------------------------------------------- """ Find Whether Two Strings are Anagrams An interesting application of the Counter class is to find anagrams. An anagram is a word or phrase formed by rearranging the letters of a different word or phrase. If the Counter objects of two strings are equal, then they are anagrams. """ # A Counter is a dict subclass for counting hashable objects. from collections import Counter string_1 = 'acbde' string_2 = 'abced' string_3 = 'abcda' strings_list = [string_1, string_2, string_3] my_list = [Counter(counter) for counter in strings_list] if my_list[0] == my_list[1]: print(f'{string_1} and {string_2} are anagram.') else: print(f"{string_1} and {string_2} aren't anagram.") if my_list[1] == my_list[2]: print(f"{string_2} and {string_3} are anagram.") else: print(f"{string_2} and {string_3} aren't anagram.")
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lib.py
miami-acm/unit-testing
0
45317
#!/usr/bin/env python3 def sleep_in(weekday, vacation): """ The parameter weekday is True if it is a weekday, and the parameter vacation is True if we are on vacation. We sleep in if it is not a weekday or we're on vacation. Return True if we sleep in. sleep_in(False, False) → True sleep_in(True, False) → False sleep_in(False, True) → True """ return False def monkey_trouble(a_smile, b_smile): """ We have two monkeys, a and b, and the parameters a_smile and b_smile indicate if each is smiling. We are in trouble if they are both smiling or if neither of them is smiling. Return True if we are in trouble. monkey_trouble(True, True) → True monkey_trouble(False, False) → True monkey_trouble(True, False) → False """ return False def sum_double(a, b): """ Given two int values, return their sum. Unless the two values are the same, then return double their sum. sum_double(1, 2) → 3 sum_double(3, 2) → 5 sum_double(2, 2) → 8 """ return 0 def diff21(n): """ Given an int n, return the absolute difference between n and 21, except return double the absolute difference if n is over 21. diff21(19) → 2 diff21(10) → 11 diff21(21) → 0 """ return 0 def count_evens(nums): """ Return the number of even ints in the given array. Note: the % "mod" operator computes the remainder, e.g. 5 % 2 is 1. count_evens([2, 1, 2, 3, 4]) → 3 count_evens([2, 2, 0]) → 3 count_evens([1, 3, 5]) → 0 """ return 0 def xyz_there(s): """ Return True if the given string contains an appearance of "xyz" where the xyz is not directly preceeded by a period (.). So "xxyz" counts but "x.xyz" does not. xyz_there('abcxyz') → True xyz_there('abc.xyz') → False xyz_there('xyz.abc') → True """ return False def is_prime(n): """ Return True if the given number is prime. is_prime(2) → True is_prime(4) → False is_prime(11) → True """ return False
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PlantAnalysis/sharpen_image.py
godzmaru/PlantAnalysis
0
113128
<reponame>godzmaru/PlantAnalysis #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Feb 14 13:06:40 2018 @author: hendrawahyu """ import cv2 import numpy as np # ============================================================================= # This function is used to sharpen the image using a simple kernel # ============================================================================= def sharpen_image(image): kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]]) image = cv2.filter2D(image, -1, kernel) return image
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unwarp_models.py
zgjslc/Film-Recovery-master1
0
6639
import torch import torch.nn as nn import torch.nn.functional as F from models.misc import modules constrain_path = { ('threeD', 'normal'): (True, True, ''), ('threeD', 'depth'): (True, True, ''), ('normal', 'depth'): (True, True, ''), ('depth', 'normal'): (True, True, ''), } class UnwarpNet(nn.Module): def __init__(self, use_simple=False, combine_num=3, use_constrain=True, constrain_configure=None): super(UnwarpNet, self).__init__() self.combine_num = combine_num self.use_simple = use_simple self.use_constrain = use_constrain self.constrain_configure = constrain_configure self.geo_encoder = modules.Encoder(downsample=6, in_channels=3) self.threeD_decoder = modules.Decoder(downsample=6, out_channels=3, combine_num=self.combine_num) self.normal_decoder = modules.Decoder(downsample=6, out_channels=3, combine_num=self.combine_num) self.depth_decoder = modules.Decoder(downsample=6, out_channels=1, combine_num=self.combine_num) self.mask_decoder = modules.Decoder(downsample=6, out_channels=1, combine_num=0) bottle_neck = sum([2 ** (i + 4) for i in range(self.combine_num)]) self.second_encoder = modules.Encoder(downsample=6, in_channels=bottle_neck * 3 + 3) self.uv_decoder = modules.Decoder(downsample=6, out_channels=2, combine_num=0) # self.albedo_decoder = modules.AlbedoDecoder(downsample=6, out_channels=1) self.albedo_decoder = modules.Decoder(downsample=6, out_channels=1, combine_num=0) self.deform_decoder = modules.Decoder(downsample=6, out_channels=2, combine_num=0) self.dep2nor = None self.threeD_to_nor2dep = None self.nor2dep = None def forward(self, x): gxvals, gx_encode = self.geo_encoder(x) threeD_map, threeD_feature = self.threeD_decoder(gxvals, gx_encode) threeD_map = nn.functional.tanh(threeD_map) dep_map, dep_feature = self.depth_decoder(gxvals, gx_encode) dep_map = nn.functional.tanh(dep_map) nor_map, nor_feature = self.normal_decoder(gxvals, gx_encode) nor_map = nn.functional.tanh(nor_map) mask_map, mask_feature = self.mask_decoder(gxvals, gx_encode) mask_map = torch.nn.functional.sigmoid(mask_map) # geo_feature = torch.cat([threeD_feature, nor_feature, dep_feature], dim=1) geo_feature = torch.cat([threeD_feature, nor_feature, dep_feature, x], dim=1) b, c, h, w = geo_feature.size() geo_feature_mask = geo_feature.mul(mask_map.expand(b, c, h, w)) secvals, sec_encode = self.second_encoder(geo_feature_mask) uv_map, _ = self.uv_decoder(secvals, sec_encode) uv_map = nn.functional.tanh(uv_map) alb_map, _ = self.albedo_decoder(secvals, sec_encode) alb_map = nn.functional.tanh(alb_map) deform_map, _ = self.deform_decoder(secvals, sec_encode) deform_map = nn.functional.tanh(deform_map) return uv_map, threeD_map, nor_map, alb_map, dep_map, mask_map, \ None, None, None, None, None, deform_map
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t2/primes.py
Macelai/security
0
71958
import random import time BITS_LENGTH = [40, 56, 80, 128, 168, 224, 256, 512, 1024, 2048, 4096] def lcg(m: int, seed: int = None) -> int: a = 39177369995579819498972128804676596941198511312402174107900118507767888787985319889078498768125726538781142699985438519849879849879867913387985078149715117956575598705232859627482107678765877225323948753141 c = 0 num = seed or 1 while True: num = (a * num + c) % m yield num def xorshift32(seed: int, n: int) -> int: xor_parts = list() while n != 0: x = seed & 0x7fffffff # 32 bits x ^= x << 13 x ^= x >> 17 x ^= x << 5 x = x & 0x7fffffff # 32 bits novamente xor_parts.append(x) n >>= 32 x = 0 for i, part in enumerate(xor_parts): x |= part << (32 * i) return x def miller_rabin(n: int, k: int) -> bool: if n == 2: return True if n % 2 == 0: return False r, s = 0, n - 1 while s % 2 == 0: r += 1 s //= 2 for _ in range(k): a = random.randrange(2, n - 1) x = pow(a, s, n) if x == 1 or x == n - 1: continue for _ in range(r - 1): x = pow(x, 2, n) if x == n - 1: break else: return False return True def fermat_little_theorem(n: int) -> bool: return (2 << (n - 2)) % n == 1 def measure_time(f): n = 100000 start = time.time() for _ in range(n): f() end = time.time() time_ = (end - start) / n print(time_) if __name__ == "__main__": for length in BITS_LENGTH: print(f"LCG {length}") measure_time(lambda: lcg(m=length, seed=2**length-1)) print(f"Xorshift {length}") measure_time(lambda: xorshift32(n=length, seed=1)) x = False generator = lcg(m=2**length, seed=2**length-1) start = time.time() while(not x): x = miller_rabin(next(generator), 40) end = time.time() print(f"{length} : {(end - start)}")
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sherpa_client/models/engine_name.py
kairntech/sherpa-client
0
1610392
<filename>sherpa_client/models/engine_name.py<gh_stars>0 from typing import Any, Dict, Type, TypeVar import attr T = TypeVar("T", bound="EngineName") @attr.s(auto_attribs=True) class EngineName: """ """ name: str def to_dict(self) -> Dict[str, Any]: name = self.name field_dict: Dict[str, Any] = {} field_dict.update( { "name": name, } ) return field_dict @classmethod def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: d = src_dict.copy() name = d.pop("name") engine_name = cls( name=name, ) return engine_name
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code/figures/5.0-plot-fig-S2.py
edunnsigouin/ds21grl
1
84287
""" Plots fig S2: Specifically, zonal-mean root-mean-square of stationary wave meridional wind at 850 hPa for both reanalysis and aquaplanet simulation data for ANNUAL and NDJFM. NOTE: since the reviewer asked for a measure of interannual variability in stationary wave amplitude, here we calculate stationary waves as the annual or seasonal mean for each year and then calculate the rms over all years. """ import numpy as np import xarray as xr from matplotlib import pyplot as plt from ds21grl import dim_aqua,dim_erai from ds21grl.config import data_name,dir_interim,dir_fig # INPUT ----------------------------------------------------------- ilat = 70 write2file = 1 # ----------------------------------------------------------------- # read rms data from experiments L+, 2L+, Lk1 and erai filename1 = dir_interim + data_name[0] + '/zm_rms_V850_stw_pl_70N_' + dim_erai.timestamp + '.nc' filename2 = dir_interim + data_name[2] + '/zm_rms_V850_stw_ml_70N_' + dim_aqua.timestamp + '.nc' filename3 = dir_interim + data_name[6] + '/zm_rms_V850_stw_ml_70N_' + dim_aqua.timestamp + '.nc' filename4 = dir_interim + data_name[7] + '/zm_rms_V850_stw_ml_70N_' + dim_aqua.timestamp + '.nc' ds1 = xr.open_dataset(filename1) ds2 = xr.open_dataset(filename2) ds3 = xr.open_dataset(filename3) ds4 = xr.open_dataset(filename4) rms_erai = ds1['rms_stw'].values rms_L = ds2['rms_stw'].values rms_2L = ds3['rms_stw'].values rms_Lk1 = ds4['rms_stw'].values # plotting positions = np.array([1,2,3,4]) fontsize = 12 figsize = np.array([10,5]) plt.figure(figsize=(figsize[0],figsize[1])) plt.subplots_adjust(hspace=0.3,wspace=0.2,left=0.075,right=0.95,top=0.95,bottom=0.1) plt.plot(positions[0],rms_erai[0],'k',marker='o',markersize=10) plt.plot(positions[1],rms_L[0],'k',marker='o',markersize=10) plt.plot(positions[2],rms_2L[0],'k',marker='o',markersize=10) plt.plot(positions[3],rms_Lk1[0],'k',marker='o',markersize=10) plt.plot(positions[0],rms_erai[1],'tab:blue',marker='o',markersize=10) plt.plot(positions[1],rms_L[1],'tab:blue',marker='o',markersize=10) plt.plot(positions[2],rms_2L[1],'tab:blue',marker='o',markersize=10) plt.plot(positions[3],rms_Lk1[1],'tab:blue',marker='o',markersize=10) plt.plot([],[],'k',marker='o',markersize=10,label='ANN') plt.plot([],[],'tab:blue',marker='o',markersize=10,label='NDJFM') plt.legend(loc='lower right',frameon=False,fontsize=fontsize,labelcolor='linecolor',markerscale=0) plt.xticks(positions,['reanalysis','L+','2L+',r'L$_{k1}$'],fontsize=fontsize) plt.yticks(np.arange(0,3,0.5),np.arange(0,3,0.5),fontsize=fontsize) plt.xlabel('experiment',fontsize=fontsize) plt.ylabel(r'$[\overline{v}^*_{rms}]_{850hPa}$',fontsize=fontsize) plt.ylim([0,2.5]) if write2file == 1: plt.savefig(dir_fig + 'fig_S2.pdf') plt.show()
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fpb/base/dask.py
cloudmercato/python-fpb
3
134244
<reponame>cloudmercato/python-fpb import multiprocessing import dask import dask.array as da import dask.dataframe as dd from fpb.base import common from fpb.base import numpy class BaseDaskRunner(numpy.BaseNumpyRunner): dd = dd da = da extra_data = { 'numpy_version': numpy.np.__version__, 'dask_version': dask.__version__, } scheduler = 'threads' def check_output(self, output): if self.da.isinf(output).any(): raise self.TypeTooSmall() class BaseDask1dRunner(common.Runner1dMixin, BaseDaskRunner): """Helpers for Dask Runners in 1 dimension array""" def prepare(self, size, dtype): chunksize = int(size / multiprocessing.cpu_count()) data = self.da.random.random(size, chunks=chunksize)\ .astype(dtype) return data class BaseDask2dRunner(common.Runner2dMixin, BaseDaskRunner): """Helpers for Dask Runners in 2 dimension array""" def prepare(self, size, size_y, dtype): chunksize = (int(size / multiprocessing.cpu_count()), 1) data = self.da.random\ .random((size, size_y))\ .rechunk(chunksize)\ .astype(dtype) return data class BaseDaskDataframe2dRunner(BaseDask2dRunner): """Helpers for Dask Runners in 2 dataframes""" def check_output(self, output): pass def prepare(self, size, size_y, dtype): chunksize = (int(size / multiprocessing.cpu_count()), 1) da_data = self.da.random\ .random((size, size_y))\ .rechunk(chunksize)\ .astype(dtype) data = da_data.to_dask_dataframe() return data
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examples/periodic2D/plot_diffraction_efficiencies.py
benvial/pytheas
10
99166
# -*- coding: utf-8 -*- """ Simulating diffraction by a 2D metamaterial =========================================== Finite element simulation of the diffraction of a plane wave by a mono-periodic grating and calculation of diffraction efficiencies. """ ############################################################################## # First we import the required modules and class import numpy as np import matplotlib.pyplot as plt from pytheas import genmat from pytheas import Periodic2D ############################################################################## # Then we need to instanciate the class :py:class:`Periodic2D`: fem = Periodic2D() ############################################################################## # The model consist of a single unit cell with quasi-periodic boundary conditions # in the :math:`x` direction enclosed with perfectly matched layers (PMLs) # in the :math:`y` direction to truncate the semi infinite media. From top to bottom: # # - PML top # - superstrate (incident medium) # - layer 1 # - design layer: this is the layer containing the periodic pattern, can be continuous or discrete # - layer 2 # - substrate # - PML bottom # # We define here the opto-geometric parameters: mum = 1e-6 #: flt: the scale of the problem (here micrometers) fem.d = 0.4 * mum #: flt: period fem.h_sup = 1.0 * mum #: flt: "thickness" superstrate fem.h_sub = 1.0 * mum #: flt: "thickness" substrate fem.h_layer1 = 0.1 * mum #: flt: thickness layer 1 fem.h_layer2 = 0.1 * mum #: flt: thickness layer 2 fem.h_des = 0.4 * mum #: flt: thickness layer design fem.h_pmltop = 1.0 * mum #: flt: thickness pml top fem.h_pmlbot = 1.0 * mum #: flt: thickness pml bot fem.a_pml = 1 #: flt: PMLs parameter, real part fem.b_pml = 1 #: flt: PMLs parameter, imaginary part fem.eps_sup = 1 #: flt: permittivity superstrate fem.eps_sub = 3 #: flt: permittivity substrate fem.eps_layer1 = 1 #: flt: permittivity layer 1 fem.eps_layer2 = 1 #: flt: permittivity layer 2 fem.eps_des = 1 #: flt: permittivity layer design fem.lambda0 = 0.6 * mum #: flt: incident wavelength fem.theta_deg = 0.0 #: flt: incident angle fem.pola = "TE" #: str: polarization (TE or TM) fem.lambda_mesh = 0.6 * mum #: flt: incident wavelength #: mesh parameters, correspond to a mesh size of lambda_mesh/(n*parmesh), #: where n is the refractive index of the medium fem.parmesh_des = 15 fem.parmesh = 13 fem.parmesh_pml = fem.parmesh * 2 / 3 fem.type_des = "elements" ############################################################################## # We then initialize the model (copying files, etc...) and mesh the unit # cell using gmsh fem.getdp_verbose = 0 fem.gmsh_verbose = 0 fem.initialize() mesh = fem.make_mesh() ############################################################################## # We use the :py:mod:`genmat` module to generate a material pattern genmat.np.random.seed(100) mat = genmat.MaterialDensity() # instanciate mat.n_x, mat.n_y, mat.n_z = 2 ** 7, 2 ** 7, 1 # sizes mat.xsym = True # symmetric with respect to x? mat.p_seed = mat.mat_rand # fix the pattern random seed mat.nb_threshold = 3 # number of materials mat._threshold_val = np.random.permutation(mat.threshold_val) mat.pattern = mat.discrete_pattern fig, ax = plt.subplots() mat.plot_pattern(fig, ax) ############################################################################## # We now assign the permittivity fem.register_pattern(mat.pattern, mat._threshold_val) fem.matprop_pattern = [1.4, 4 - 0.02 * 1j, 2] # refractive index values ############################################################################## # Now we're ready to compute the solution: fem.compute_solution() ############################################################################## # Finally we compute the diffraction efficiencies, absorption and energy balance effs_TE = fem.diffraction_efficiencies() print("efficiencies TE", effs_TE) ############################################################################## # It is fairly easy to switch to TM polarization: fem.pola = "TM" fem.compute_solution() effs_TM = fem.diffraction_efficiencies() print("efficiencies TM", effs_TM)
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django_cradmin/uicontainer/container.py
appressoas/django_cradmin
11
32117
<reponame>appressoas/django_cradmin from django.conf import settings from django.forms.utils import flatatt from django_cradmin import renderable class NotBootsrappedError(Exception): """ Raised when trying to use features of :class:`.AbstractContainerRenderable` that requires is to have been bootstrapped. """ class AlreadyBootsrappedError(Exception): """ Raised when trying to :meth:`~.AbstractContainerRenderable.bootstrap` and already bootstrapped :class:`.AbstractContainerRenderable`. """ class NotAllowedToAddChildrenError(Exception): """ Raised when trying to add children to a :class:`.AbstractContainerRenderable` where :meth:`~.AbstractContainerRenderable.html_tag_supports_children` returns ``False``. """ class UnsupportedHtmlTagError(ValueError): """ Raised when providing an invalid ``html_tag`` kwarg to :class:`.AbstractContainerRenderable`. See :obj:`.AbstractContainerRenderable.supported_html_tags`. """ class InvalidBemError(ValueError): """ Raised when invalid BEM is supplied. """ class InvalidDomIdError(ValueError): """ Raised when invalid dom_id is supplied. """ class AbstractContainerRenderable(renderable.AbstractRenderableWithCss): """ Base class for all renderables in the uicontainer framework. This can not be used directly. You extend it, and at least override :meth:`.get_default_html_tag`, or use one of the subclasses. The most basic subclass is :class:`django_cradmin.uicontainer.div.Div`. .. attribute:: parent The parent AbstractContainerRenderable. Set in :meth:`.bootstrap`. The attribute does not exist if :meth:`.bootstrap` has not been run. Is ``None`` if this is the root of the container tree. .. attribute:: properties A dict of properties. These properties is copied down to the ``properties`` attribute of children (with the update-method, not full replace) in :meth:`.bootstrap`. This means that you can add properties in ``__init__()``, and make them available to any children recursively. """ template_name = 'django_cradmin/uicontainer/container.django.html' #: You can override this to specify a set of supported HTML tags #: for the ``html_tag`` attribute for :meth:`~.AbstractContainerRenderable.__init__`. #: This is useful to avoid typing errors. It should not be a big problem if you #: forget a tag that should be supported - developers can just create a subclass. #: #: If the value of this field is None, or any other value that is considered False by #: ``bool()``, we do not validate the ``html_tag`` kwarg. supported_html_tags = None def __init__(self, children=None, bem_block=None, bem_element=None, bem_variant_list=None, html_tag=None, css_classes_list=None, extra_css_classes_list=None, test_css_class_suffixes_list=None, role=False, dom_id=False, html_element_attributes=None, **kwargs): """ Args: children: List of children. Children must be objects of subclasses of :class:`.AbstractContainerRenderable`. css_classes_list (list): Override the :meth:`default css classes <.get_default_css_classes_list>` with your own list of css classes. extra_css_classes_list (list): Add extra css classes. This is appended to the css classes in the ``css_classes_list`` kwarg if that is specified, or appended to the css classes returned by :meth:`.get_default_css_classes_list`. role (str): The value of the role attribute. If this is not specified, we fall back on the value returned by :meth:`.get_default_role`. If both is ``False``, we do not render the role attribute. dom_id (str): The value of the id attribute. If this is not specified, we fall back on the value returned by :meth:`.get_default_dom_id`. If both is ``False``, we do not render the id attribute. html_element_attributes (dict): HTML element attributes to add to the HTML element. This adds attributes returned by :meth:`.get_html_element_attributes`. If this dict includes attributes returned by :meth:`.get_html_element_attributes`, the attributes specified in this kwarg takes presedense. The format of the dict is specified in :meth:`.get_html_element_attributes`. """ self.kwargs = kwargs self.validate_dom_id(dom_id=dom_id) self.validate_bem(bem_block=bem_block, bem_element=bem_element) self.validate_html_tag(html_tag=html_tag) self._childrenlist = [] self._virtual_childrenlist = [] self._is_bootstrapped = False self.properties = {} self._overridden_bem_block_or_element = bem_block or bem_element self._overridden_bem_variant_list = bem_variant_list self._overridden_role = role self._overridden_dom_id = dom_id self._overridden_html_tag = html_tag self._html_element_attributes = html_element_attributes self._overridden_css_classes_list = css_classes_list self._overridden_test_css_class_suffixes_list = test_css_class_suffixes_list self._extra_css_classes_list = extra_css_classes_list self.add_children(*self.prepopulate_children_list()) self.add_virtual_children(*self.prepopulate_virtual_children_list()) if children: self.add_children(*children) def should_validate_dom_id(self): """ Should we raise :class:`.InvalidDomIdError` exception when the ``dom_id`` kwarg is malformed. Returns the value of the :setting:`DJANGO_CRADMIN_UICONTAINER_VALIDATE_DOM_ID` setting, falling back to ``True`` if it is not defined. The validator requires the dom_id to start with ``id_``, be lowercase, and not contain ``-``. We recommend to not override this to ensure uniform DOM id naming. You should disable this validation in production using the :setting:`DJANGO_CRADMIN_UICONTAINER_VALIDATE_DOM_ID` setting. """ return getattr(settings, 'DJANGO_CRADMIN_UICONTAINER_VALIDATE_DOM_ID', True) def should_validate_bem(self): """ Should we raise :class:`.InvalidBemIdError` exception when the ``bem_block`` or ``bem_element`` kwarg is malformed? Returns the value of the :setting:`DJANGO_CRADMIN_UICONTAINER_VALIDATE_BEM` setting, falling back to ``True`` if it is not defined. The validator requires the bem_block to not contain ``__`` (double underscore), and the bem_element to comtain ``__`` (double underscore). We recommend to not chanding this to ensure BEM elements and blocks are used correctly. You should disable this validation in production using the :setting:`DJANGO_CRADMIN_UICONTAINER_VALIDATE_BEM` setting. """ return getattr(settings, 'DJANGO_CRADMIN_UICONTAINER_VALIDATE_BEM', True) def validate_dom_id(self, dom_id): if dom_id is False: return if not self.should_validate_dom_id(): return normalized_dom_id = dom_id.replace('-', '').lower() if not dom_id.startswith('id_') or dom_id != normalized_dom_id: raise InvalidDomIdError( 'dom_id must begin with "id_", be all lowercase, and can not contain "-". ' '{dom_id!r} does not match this requirement.'.format( dom_id=dom_id)) def validate_bem(self, bem_block, bem_element): if not self.should_validate_bem(): return if bem_block and bem_element: raise InvalidBemError( 'Can not specify both bem_element or bem_block. An ' 'HTML element is eighter a BEM block or a BEM element.') if bem_block: if '__' in bem_block: raise InvalidBemError( '{bem_block} is not a valid BEM block name. ' 'BEM blocks do not contain "__". Are you sure you ' 'did not mean to use the bem_element kwarg?'.format( bem_block=bem_block )) elif bem_element: if '__' not in bem_element: raise InvalidBemError( '{bem_element} is not a valid BEM element name. ' 'BEM elements must contain "__". Are you sure you ' 'did not mean to use the bem_block kwarg?'.format( bem_element=bem_element )) def get_full_class_path_as_string(self): """ Get full class path as string. Useful for providing some extra information in exceptions. Normally this will be in a traceback, but when dealing with things rendered by a Django template, this information is not always included. """ return '{}.{}'.format(self.__class__.__module__, self.__class__.__name__) def validate_html_tag(self, html_tag): if html_tag and self.supported_html_tags and html_tag not in self.supported_html_tags: raise UnsupportedHtmlTagError('Unsupported HTML tag for {classpath}: {html_tag}'.format( classpath=self.get_full_class_path_as_string(), html_tag=self._overridden_html_tag )) def get_default_html_tag(self): """ Get the default HTML tag to wrap renderable in. Can be overriden by the ``html_tag`` kwarg for :meth:`.__init__`. Returns ``"div"`` by default. """ return 'div' @property def html_tag(self): """ Get the HTML tag for this container. """ return self._overridden_html_tag or self.get_default_html_tag() @property def html_tag_supports_children(self): """ Does the html tag support children? If this returns ``False``, we: - Do not render an end tag for the wrapper element. - Do not allow children to be added to the container. Should be overridden to return ``False`` if the :meth:`.get_default_html_tag` does not allow for children. Examples of this case is if the wrapper html tag i ``input`` or ``hr``. See also :meth:`.can_have_children`, which should be used if the HTML tag should have and end tag, but not children. Returns: boolean: True by default. """ return True @property def can_have_children(self): """ Can this container have children? If this returns ``False``, :meth:`.add_child` will raise :class:`.NotAllowedToAddChildrenError`. Returns: boolean: The return value from :meth:`.html_tag_supports_children` by default. """ return self.html_tag_supports_children def get_default_role(self): """ Get the default value for the role attribute of the html element. Defaults to ``False``. """ return False @property def role(self): """ Get the value for the role attribute of the html element. You should not override this. Override :meth:`.get_default_role` instead. """ return self._overridden_role or self.get_default_role() def get_default_dom_id(self): """ Get the default value for the id attribute of the html element. Defaults to ``False``. """ return False @property def dom_id(self): """ Get the value for the id attribute of the html element. You should not override this. Override :meth:`.get_default_dom_id` instead. """ return self._overridden_dom_id or self.get_default_dom_id() def get_html_element_attributes(self): """ Get HTML element attributes as a dict. The dict is parsed by :func:`django.forms.utils.flatatt`, so: - ``{'myattribute': True}`` results in ``myattribute`` (no value). - ``{'myattribute': False}`` results in the attribute beeing ignored (not included in the output). - ``{'myattribute': 'Some value'}`` results in the ``myattribute="Some value"``. If you override this method, *remember to call super* to get the attributes set in the superclass. """ html_element_attributes = { 'role': self.role, 'id': self.dom_id, 'class': self.css_classes or False, # Fall back to false to avoid class="" } if self._html_element_attributes: html_element_attributes.update(self._html_element_attributes) return html_element_attributes @property def html_element_attributes_string(self): """ Get :meth:`.get_html_element_attributes` + any attributes in the ``html_element_attributes`` kwarg for :meth:`.__init__` encoded as a string using :func:`django.forms.utils.flatatt`. """ return flatatt(self.get_html_element_attributes()) def get_default_css_classes_list(self): """ Override this to provide a default list of css classes. The css classes specified here can be overridden using the ``css_classes_list`` kwarg for :meth:`.__init__`. """ return [] def get_default_bem_block_or_element(self): """ Get the default BEM block or element. A HTML element is eighter a BEM block or a BEM element, so we have joined this into a single method. """ return None def get_bem_block_or_element(self): """ Get the BEM block or element. DO NOT OVERRIDE THIS METHOD. Override :meth:`.get_default_bem_block_or_element` instead. """ return (self._overridden_bem_block_or_element or self.get_default_bem_block_or_element()) def get_default_bem_variant_list(self): """ Get the default BEM variants. The full CSS class of any variant in the list will be :meth:`.get_bem_block_or_element` with ``--`` and the variant appended, so if the bem block/element is ``"menu"``, and the variant is ``"expanded"``, the resulting css class will be ``"menu--expanded"``. """ return [] def get_bem_variant_list(self): """ Get the list of BEM variants. DO NOT OVERRIDE THIS METHOD. Override :meth:`.get_default_bem_variant_list` instead. """ return self._overridden_bem_variant_list or self.get_default_bem_variant_list() def get_bem_css_classes_list(self): """ Get the BEM css classes as list. DO NOT OVERRIDE THIS METHOD. Override :meth:`.get_default_bem_block_or_element` and :meth:`.get_default_bem_variant_list` instead. """ bem_block_or_element = self.get_bem_block_or_element() bem_css_classes = [] if bem_block_or_element: bem_css_classes.append(bem_block_or_element) for variant in self.get_bem_variant_list(): css_class = '{}--{}'.format(bem_block_or_element, variant) bem_css_classes.append(css_class) return bem_css_classes def get_css_classes_list(self): """ DO NOT OVERRIDE THIS METHOD. Unlike with :class:`django_cradmin.renderable.AbstractRenderableWithCss`, you do not override this class to add your own css classes. Override :meth:`.get_default_css_classes_list`. This is because this method respects the ``css_classes_list`` kwarg for :meth:`.__init__`, and just falls back to :meth:`.get_default_css_classes_list`. So if you override this method, the ``css_classes_list`` kwarg will be useless. """ css_classes_list = self.get_bem_css_classes_list() if self._overridden_css_classes_list: css_classes_list.extend(self._overridden_css_classes_list) else: css_classes_list.extend(self.get_default_css_classes_list()) if self._extra_css_classes_list: css_classes_list.extend(self._extra_css_classes_list) return css_classes_list def get_default_test_css_class_suffixes_list(self): """ Override this to provide a default list of css classes for unit tests. The css classes specified here can be overridden using the ``test_css_class_suffixes_list`` kwarg for :meth:`.__init__`. """ return ['uicontainer-{}'.format(self.__class__.__name__.lower())] def get_test_css_class_suffixes_list(self): """ DO NOT OVERRIDE THIS METHOD. Unlike with :class:`django_cradmin.renderable.AbstractRenderableWithCss`, you do not override this class to add your own test css classes. Override :meth:`.get_default_test_css_class_suffixes_list`. This is because this method respects the ``test_css_class_suffixes_list`` kwarg for :meth:`.__init__`, and just falls back to :meth:`.get_default_test_css_class_suffixes_list`. So if you override this method, the ``test_css_class_suffixes_list`` kwarg will be useless. """ if self._overridden_test_css_class_suffixes_list: test_css_class_suffixes_list = self._overridden_test_css_class_suffixes_list else: test_css_class_suffixes_list = self.get_default_test_css_class_suffixes_list() return test_css_class_suffixes_list def bootstrap(self, parent=None): """ Bootstrap the container. Must be called once on the top-level container in the tree of containers. Sets the provided parent as :attr:`.parent`. Updates the properties of all children (using dict update()) with :attr:`.properties`. """ if self._is_bootstrapped: raise AlreadyBootsrappedError('The container is already bootstrapped. Can not bootstrap ' 'the same container twice.') self.parent = parent if self.parent: self.properties.update(self.parent.properties) for child in self._virtual_childrenlist: child.bootstrap(parent=self) for child in self._childrenlist: child.bootstrap(parent=self) self._is_bootstrapped = True return self def prepopulate_children_list(self): """ Pre-polulate the children list. This is called in :meth:`.__init__` before any children from the kwargs is added. Returns: list: An empty list by default, but you can override this in subclasses. """ return [] def prepopulate_virtual_children_list(self): """ Pre-polulate the virtual children list. This is called in :meth:`.__init__` before any children from the kwargs is added, and before any children is :meth:`.prepopulate_children_list` is added. Returns: list: An empty list by default, but you can override this in subclasses. """ return [] def add_child(self, childcontainer): """ Add a child to the container. Args: childcontainer: A :class:`.AbstractContainerRenderable` object. Returns: A reference to self. This means that you can chain calls to this method. """ if self.can_have_children: self._childrenlist.append(childcontainer) if self._is_bootstrapped and not childcontainer._is_bootstrapped: childcontainer.bootstrap(parent=self) else: raise NotAllowedToAddChildrenError('{modulename}.{classname} can not have children'.format( modulename=self.__class__.__module__, classname=self.__class__.__name__ )) return self def add_virtual_child(self, childcontainer): """ Add a "virtual" child to the container. This child is not rendered as a child of the container automatically (that is left to the template rendering the container). But it inherits properties and is automatically bootstrapped just like a regular child. Args: childcontainer: A :class:`.AbstractContainerRenderable` object. Returns: A reference to self. This means that you can chain calls to this method. """ if self.can_have_children: self._virtual_childrenlist.append(childcontainer) if self._is_bootstrapped and not childcontainer._is_bootstrapped: childcontainer.bootstrap(parent=self) return self def add_children(self, *childcontainers): """ Add children to the container. Args: *childcontainers: Zero or more :class:`.AbstractContainerRenderable` objects. Returns: A reference to self. This means that you can chain calls to this method. """ for childcontainer in childcontainers: self.add_child(childcontainer) return self def add_virtual_children(self, *childcontainers): """ Add virtual children to the container. Args: *childcontainers: Zero or more :class:`.AbstractContainerRenderable` objects. Returns: A reference to self. This means that you can chain calls to this method. """ for childcontainer in childcontainers: self.add_virtual_child(childcontainer) return self def iter_children(self): """ Returns an iterator over the children of this container. The yielded children will be objects of :class:`.AbstractContainerRenderable` subclasses. """ return iter(self._childrenlist) def iter_virtual_children(self): """ Returns an iterator over the virtual children of this container. The yielded children will be objects of :class:`.AbstractContainerRenderable` subclasses. """ return iter(self._virtual_childrenlist) def get_childcount(self): """ Get the number of children in the container. """ return len(self._childrenlist) def get_virtual_childcount(self): """ Get the number of virtual children in the container. """ return len(self._virtual_childrenlist) @property def should_render(self): """ Should we render anything? Override this to make the :meth:`.render` to control if the container is rendered. If this returns ``False``, :meth:`.render` returns an empty string instead of rendering the template. Returns: bool: ``True`` by default, but subclasses can override this behavior. """ return True def render(self, **kwargs): """ Overrides :meth:`django_cradmin.renderable.AbstractRenderable.render`. The only change is that we return an empty string if :meth:`.should_render` returns ``False``. If it returns ``True``, we call the overriden method and returns the result. Args: **kwargs: Forwarded to the overridden method if it is called. """ if not self._is_bootstrapped: raise NotBootsrappedError( 'Can not render an AbstractContainerRenderable that has not been bootstrapped. ' 'Ensure you call bootsrap() on the top-level container in the container ' 'hierarchy before rendering. Class causing this issue: {classpath}'.format( classpath=self.get_full_class_path_as_string() )) if self.should_render: return super(AbstractContainerRenderable, self).render(**kwargs) else: return '' class Div(AbstractContainerRenderable): """ Renders a ``<div>``. The only thing this class does is to override :meth:`django_cradmin.uicontainer.container.AbstractContainerRenderable.get_default_html_tag` and return ``"div"``. """ def get_default_html_tag(self): return 'div' class NoWrapperElement(AbstractContainerRenderable): """ Renders children, but no wrapper HTML element. """ template_name = 'django_cradmin/uicontainer/no_wrapper_element.django.html'
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pythonexercicios/ex042-analisandotrianguloV2.py
marroni1103/exercicios-pyton
0
108920
print('\033[34m-=\033[m'*12) print('Analisador de Trianulo') print('\033[34m-=\033[m'*12) a = float(input('Informe a primeira reta: ')) b = float(input('Informe a segunda reta: ')) c = float(input('Informe a terceira reta: ')) if a + b > c and a + c > b and b + c > a: print(f'Com essas retas {a} X {b} X {c} consegeuimos montar um triangulo.') if a == b == c: print(f'Esse é um triangulo Equilátero.') elif a == b and a != c or a == c and a != b: print(f'Esse é um triangulo Isósceles.') elif a != b and a != c and b != c: print(f'Esse é um triangulo Escaleno.') else: print(f'Com essas retas {a} X {b} X {c} NÃO consegeuimos montar um triangulo.')
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src/quiche/ast_heuristic_cost_model.py
riswords/quiche
0
62851
from typing import Dict, Tuple from quiche.analysis import CostModel from quiche.egraph import ENode, EClassID from quiche.ast_quiche_tree import ASTQuicheTree class ASTHeuristicCostModel(CostModel): """ Cost model for AST nodes, based on "size", i.e., number of children and also a relative weighting for AST nodes. The default weighting may optionally be altered by users. """ def __init__(self, node_weights: Dict[str, int] = None): self.node_weights = { 'Module': 1, 'Interactive': 1, 'Expression': 1, 'Suite': 1, 'FunctionDef': 1, 'AsyncFunctionDef': 1, 'ClassDef': 1, 'Return': 1, 'Delete': 1, 'Assign': 1, 'AugAssign': 1, 'AnnAssign': 1, 'For': 1, 'AsyncFor': 1, 'While': 1, 'If': 1, 'With': 1, 'AsyncWith': 1, 'Raise': 1, 'Try': 1, 'Assert': 1, 'Import': 1, 'ImportFrom': 1, 'Global': 1, 'Nonlocal': 1, 'Expr': 1, 'Pass': 1, 'Break': 1, 'Continue': 1, 'BoolOp': 1, 'BinOp': 1, 'UnaryOp': 1, 'Lambda': 1, 'IfExp': 1, 'Dict': 1, 'Set': 1, 'ListComp': 1, 'SetComp': 1, 'DictComp': 1, 'GeneratorExp': 1, 'Yield': 1, 'YieldFrom': 1, 'Compare': 1, 'Call': 1, 'Num': 1, 'Str': 1, 'FormattedValue': 1, 'JoinedStr': 1, 'Bytes': 1, 'NameConstant': 5, 'Ellipsis': 1, 'Constant': 1, 'Attribute': 1, 'Subscript': 1, 'Starred': 1, 'Name': 1, 'List': 1, 'Tuple': 1, 'Load': 1, 'Store': 1, 'Del': 1, 'AugLoad': 1, 'AugStore': 1, 'Param': 1, 'Slice': 1, 'ExtSlice': 1, 'Index': 1, 'And': 1, 'Or': 1, 'Add': 1, 'Sub': 1, 'Mult': 1, 'MatMult': 1, 'Div': 1, 'Mod': 1, 'Pow': 1, 'LShift': 1, 'RShift': 1, 'BitOr': 1, 'BitXor': 1, 'BitAnd': 1, 'FloorDiv': 1, 'Invert': 1, 'Not': 1, 'UAdd': 1, 'USub': 1, 'Eq': 1, 'NotEq': 1, 'Lt': 1, 'LtE': 1, 'Gt': 1, 'GtE': 1, 'Is': 1, 'IsNot': 1, 'In': 1, 'NotIn': 1, 'ExceptHandler': 1, # special leaf kinds: 'int': 0, 'float': 1, 'bool': 2, 'complex': 3, 'str': 4, } if node_weights: self.node_weights.update(node_weights) def enode_cost(self, node: ENode, costs: Dict[EClassID, Tuple[int, ENode]]) -> int: """ Calculate the cost of a node based solely on its key (not its children) """ key = node.key if hasattr(node.key, '__name__'): key = node.key.__name__ elif isinstance(node.key, tuple): key = node.key[0] if key in self.node_weights: return self.node_weights[key] elif node.key in self.node_weights: return self.node_weights[node.key] return 1 def enode_cost_rec( self, enode: ENode, costs: Dict[EClassID, Tuple[int, ENode]] ) -> int: """ Calculate the cost of a node based on its key and its children :param enode: the node to calculate the cost of :param costs: dictionary containing costs of children """ child_costs = sum(costs[eid][0] for eid in enode.args) return self.enode_cost(enode, costs) + child_costs def lookup( self, eclassid: EClassID, costs: Dict[EClassID, Tuple[int, ENode]] ) -> ASTQuicheTree: enode = costs[eclassid][1] return ASTQuicheTree.make_node(enode.key, [self.lookup(eid, costs) for eid in enode.args])
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src/waldur_openstack/openstack/migrations/0006_router.py
geant-multicloud/MCMS-mastermind
26
162937
# Generated by Django 2.2.13 on 2020-10-09 17:57 import django.db.models.deletion import django.utils.timezone import model_utils.fields from django.db import migrations, models import waldur_core.core.fields import waldur_core.core.models import waldur_core.core.shims import waldur_core.core.validators import waldur_core.structure.models class Migration(migrations.Migration): dependencies = [ ('taggit', '0003_taggeditem_add_unique_index'), ('openstack', '0005_error_traceback'), ] operations = [ migrations.CreateModel( name='Router', fields=[ ( 'id', models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name='ID', ), ), ( 'created', model_utils.fields.AutoCreatedField( default=django.utils.timezone.now, editable=False, verbose_name='created', ), ), ( 'modified', model_utils.fields.AutoLastModifiedField( default=django.utils.timezone.now, editable=False, verbose_name='modified', ), ), ( 'description', models.CharField( blank=True, max_length=2000, verbose_name='description' ), ), ( 'name', models.CharField( max_length=150, validators=[waldur_core.core.validators.validate_name], verbose_name='name', ), ), ('uuid', waldur_core.core.fields.UUIDField()), ('backend_id', models.CharField(blank=True, max_length=255)), ( 'service_project_link', models.ForeignKey( on_delete=django.db.models.deletion.PROTECT, related_name='routers', to='openstack.OpenStackServiceProjectLink', ), ), ( 'tags', waldur_core.core.shims.TaggableManager( blank=True, help_text='A comma-separated list of tags.', related_name='router_router_openstack', through='taggit.TaggedItem', to='taggit.Tag', verbose_name='Tags', ), ), ( 'tenant', models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name='routers', to='openstack.Tenant', ), ), ], options={'abstract': False,}, bases=( waldur_core.core.models.DescendantMixin, waldur_core.core.models.BackendModelMixin, waldur_core.structure.models.StructureLoggableMixin, models.Model, ), ), ]
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cymepy/export_manager/hooks/JSON_writer.py
GMLC-TDC/cymepy
1
36257
<gh_stars>1-10 from cymepy.export_manager.base_definations import ExportManager from cymepy.common import EXPORT_FILENAME import json import os class Writer(ExportManager): def __init__(self, sim_instance, solver, options, logger, **kwargs): super(Writer, self).__init__(sim_instance, solver, options, logger, **kwargs) self.results = [] self.path = os.path.join( self.settings["project"]['project_path'], 'exports', f"{EXPORT_FILENAME}.json" ) pass def update(self): results = super().update() self.results.append(results) return def export(self): with open(self.path, "w") as write_file: json.dump(self.results, write_file, indent=4, sort_keys=True)
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drl_grasping/envs/models/primitives/__init__.py
Tiamat-Tech/drl_grasping
126
103702
from .box import Box from .cylinder import Cylinder from .sphere import Sphere from .random_primitive import RandomPrimitive from .plane import Plane
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blog/models/__init__.py
sharif-42/Personal_Website
0
161530
<reponame>sharif-42/Personal_Website<filename>blog/models/__init__.py from .post import Post from .comments import Comment
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tests/e2e/utils.py
BeryJu/passbook
15
169884
"""authentik e2e testing utilities""" import json import os from functools import lru_cache, wraps from os import environ, makedirs from time import sleep, time from typing import Any, Callable, Optional from django.apps import apps from django.contrib.staticfiles.testing import StaticLiveServerTestCase from django.db import connection from django.db.migrations.loader import MigrationLoader from django.db.migrations.operations.special import RunPython from django.test.testcases import TransactionTestCase from django.urls import reverse from docker import DockerClient, from_env from docker.errors import DockerException from docker.models.containers import Container from selenium import webdriver from selenium.common.exceptions import NoSuchElementException, TimeoutException, WebDriverException from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys from selenium.webdriver.remote.webdriver import WebDriver from selenium.webdriver.remote.webelement import WebElement from selenium.webdriver.support.ui import WebDriverWait from structlog.stdlib import get_logger from authentik.core.api.users import UserSerializer from authentik.core.models import User from authentik.core.tests.utils import create_test_admin_user from authentik.managed.manager import ObjectManager RETRIES = int(environ.get("RETRIES", "3")) def get_docker_tag() -> str: """Get docker-tag based off of CI variables""" env_pr_branch = "GITHUB_HEAD_REF" default_branch = "GITHUB_REF" branch_name = os.environ.get(default_branch, "main") if os.environ.get(env_pr_branch, "") != "": branch_name = os.environ[env_pr_branch] branch_name = branch_name.replace("refs/heads/", "").replace("/", "-") return f"gh-{branch_name}" class SeleniumTestCase(StaticLiveServerTestCase): """StaticLiveServerTestCase which automatically creates a Webdriver instance""" container: Optional[Container] = None wait_timeout: int user: User def setUp(self): super().setUp() # pylint: disable=invalid-name self.maxDiff = None self.wait_timeout = 60 self.driver = self._get_driver() self.driver.maximize_window() self.driver.implicitly_wait(30) self.wait = WebDriverWait(self.driver, self.wait_timeout) self.logger = get_logger() self.user = create_test_admin_user() if specs := self.get_container_specs(): self.container = self._start_container(specs) def get_container_image(self, base: str) -> str: """Try to pull docker image based on git branch, fallback to main if not found.""" client: DockerClient = from_env() image = f"{base}:gh-main" try: branch_image = f"{base}:{get_docker_tag()}" client.images.pull(branch_image) return branch_image except DockerException: client.images.pull(image) return image def _start_container(self, specs: dict[str, Any]) -> Container: client: DockerClient = from_env() container = client.containers.run(**specs) if "healthcheck" not in specs: return container while True: container.reload() status = container.attrs.get("State", {}).get("Health", {}).get("Status") if status == "healthy": return container self.logger.info("Container failed healthcheck") sleep(1) def output_container_logs(self, container: Optional[Container] = None): """Output the container logs to our STDOUT""" _container = container or self.container print(f"--------container logs {_container.image.tags[0]}") for log in _container.logs().decode().split("\n"): print(log) print(f"--------end container logs {_container.image.tags[0]}") def get_container_specs(self) -> Optional[dict[str, Any]]: """Optionally get container specs which will launched on setup, wait for the container to be healthy, and deleted again on tearDown""" return None def _get_driver(self) -> WebDriver: count = 0 while count < RETRIES: try: return webdriver.Remote( command_executor="http://localhost:4444/wd/hub", options=webdriver.ChromeOptions(), ) except WebDriverException: count += 1 raise ValueError(f"Webdriver failed after {RETRIES}.") def tearDown(self): if "TF_BUILD" in environ: makedirs("selenium_screenshots/", exist_ok=True) screenshot_file = f"selenium_screenshots/{self.__class__.__name__}_{time()}.png" self.driver.save_screenshot(screenshot_file) self.logger.warning("Saved screenshot", file=screenshot_file) self.logger.debug("--------browser logs") for line in self.driver.get_log("browser"): self.logger.debug(line["message"], source=line["source"], level=line["level"]) self.logger.debug("--------end browser logs") if self.container: self.output_container_logs() self.container.kill() self.driver.quit() super().tearDown() def wait_for_url(self, desired_url): """Wait until URL is `desired_url`.""" self.wait.until( lambda driver: driver.current_url == desired_url, f"URL {self.driver.current_url} doesn't match expected URL {desired_url}", ) def url(self, view, **kwargs) -> str: """reverse `view` with `**kwargs` into full URL using live_server_url""" return self.live_server_url + reverse(view, kwargs=kwargs) def if_user_url(self, view) -> str: """same as self.url() but show URL in shell""" return f"{self.live_server_url}/if/user/#{view}" def get_shadow_root(self, selector: str, container: Optional[WebElement] = None) -> WebElement: """Get shadow root element's inner shadowRoot""" if not container: container = self.driver shadow_root = container.find_element(By.CSS_SELECTOR, selector) element = self.driver.execute_script("return arguments[0].shadowRoot", shadow_root) return element def login(self): """Do entire login flow and check user afterwards""" flow_executor = self.get_shadow_root("ak-flow-executor") identification_stage = self.get_shadow_root("ak-stage-identification", flow_executor) identification_stage.find_element(By.CSS_SELECTOR, "input[name=uidField]").click() identification_stage.find_element(By.CSS_SELECTOR, "input[name=uidField]").send_keys( self.user.username ) identification_stage.find_element(By.CSS_SELECTOR, "input[name=uidField]").send_keys( Keys.ENTER ) flow_executor = self.get_shadow_root("ak-flow-executor") password_stage = self.get_shadow_root("ak-stage-password", flow_executor) password_stage.find_element(By.CSS_SELECTOR, "input[name=password]").send_keys( self.user.username ) password_stage.find_element(By.CSS_SELECTOR, "input[name=password]").send_keys(Keys.ENTER) sleep(1) def assert_user(self, expected_user: User): """Check users/me API and assert it matches expected_user""" self.driver.get(self.url("authentik_api:user-me") + "?format=json") user_json = self.driver.find_element(By.CSS_SELECTOR, "pre").text user = UserSerializer(data=json.loads(user_json)["user"]) user.is_valid() self.assertEqual(user["username"].value, expected_user.username) self.assertEqual(user["name"].value, expected_user.name) self.assertEqual(user["email"].value, expected_user.email) @lru_cache def get_loader(): """Thin wrapper to lazily get a Migration Loader, only when it's needed and only once""" return MigrationLoader(connection) def apply_migration(app_name: str, migration_name: str): """Re-apply migrations that create objects using RunPython before test cases""" def wrapper_outter(func: Callable): """Retry test multiple times""" @wraps(func) def wrapper(self: TransactionTestCase, *args, **kwargs): migration = get_loader().get_migration(app_name, migration_name) with connection.schema_editor() as schema_editor: for operation in migration.operations: if not isinstance(operation, RunPython): continue operation.code(apps, schema_editor) return func(self, *args, **kwargs) return wrapper return wrapper_outter def object_manager(func: Callable): """Run objectmanager before a test function""" @wraps(func) def wrapper(*args, **kwargs): """Run objectmanager before a test function""" ObjectManager().run() return func(*args, **kwargs) return wrapper def retry(max_retires=RETRIES, exceptions=None): """Retry test multiple times. Default to catching Selenium Timeout Exception""" if not exceptions: exceptions = [WebDriverException, TimeoutException, NoSuchElementException] logger = get_logger() def retry_actual(func: Callable): """Retry test multiple times""" count = 1 @wraps(func) def wrapper(self: TransactionTestCase, *args, **kwargs): """Run test again if we're below max_retries, including tearDown and setUp. Otherwise raise the error""" nonlocal count try: return func(self, *args, **kwargs) # pylint: disable=catching-non-exception except tuple(exceptions) as exc: count += 1 if count > max_retires: logger.debug("Exceeded retry count", exc=exc, test=self) # pylint: disable=raising-non-exception raise exc logger.debug("Retrying on error", exc=exc, test=self) self.tearDown() self._post_teardown() # noqa self.setUp() return wrapper(self, *args, **kwargs) return wrapper return retry_actual
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utils/visualize_tree.py
moyiming1/Retrosynthesis-pathway-ranking
10
10766
<gh_stars>1-10 import os, sys project_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) sys.path.append(project_path) import pickle def construct_tree_for_visual(tree, node_info_key, depth=0): tree_for_visual = {'smiles': 'http://askcos.mit.edu/draw/smiles/' + str(tree['smiles']).replace('#', '%23'), 'depth': depth, 'children': []} if node_info_key in tree.keys(): if type(tree[node_info_key]) is not str: tree_for_visual['score'] = '{:.3f}'.format(tree[node_info_key]) else: tree_for_visual['score'] = tree[node_info_key] else: tree_for_visual['score'] = '' if tree['child']: # tree_for_visual['children'] = [] for child in tree['child']: tree_for_visual['children'].append(construct_tree_for_visual(child, node_info_key, depth+1)) return tree_for_visual def construct_tree_for_d3_visualization(tree, depth, new_tree={}, max_children=0): # if 'is_chemical' in tree.keys(): new_tree['smiles'] = 'http://askcos.mit.edu/draw/smiles/' + str(tree['smiles']).replace('#', '%23') if 'score' in tree.keys(): new_tree['score'] = str(tree['score']) else: new_tree['score'] = '' # new_tree['smiles'] = str(new_tree['smiles']) new_tree['children'] = [] if tree['child']: # print(len(tree['child'])) if max_children < len(tree['child']): max_children = len(tree['child']) for child in tree['child']: new_tree['children'].append({}) _, max_children = construct_tree_for_d3_visualization(child, depth + 1, new_tree['children'][-1], max_children) return new_tree, max_children def count_tree_depth_children(tree, count): count[tree['depth']] += 1 if tree['children']: for child in tree['children']: count = count_tree_depth_children(child, count) return count def create_tree_html(trees, file_name, tree_info=None, node_info_key='score', width_factor=1, max_depth=10): try: outfile = file_name except Exception as e: print(e) print('Need to specify file name to write results to') trees_for_visualization = {'name': 'dummy_root', 'children': []} max_children = 1 for i, tree in enumerate(trees): output = construct_tree_for_visual(tree, node_info_key) trees_for_visualization['children'].append(output) # print() current_children = max(count_tree_depth_children(output, count=[0]*20)) if current_children > max_children: max_children = current_children if tree_info: # print(tree_info[i]) trees_for_visualization['children'][-1]['_id'] = tree_info[i] else: trees_for_visualization['children'][-1]['_id'] = ('T%d' % i) # print(max_children) max_children = max(max_children, 3) height = 300 * len(trees) * max_children / 3 * width_factor page_width = max_depth * 300 fid_out = open(outfile + '.html', 'w') fid_out.write('<!DOCTYPE html>\n') fid_out.write(' <head>\n') fid_out.write(' <meta charset="utf-8">\n') fid_out.write(' <title>{}</title>\n'.format(outfile)) fid_out.write(' <style>\n') fid_out.write(' .node circle {\n') fid_out.write(' fill: #fff;\n') fid_out.write(' stroke: steelblue;\n') fid_out.write(' stroke-width: 3px;\n') fid_out.write(' }\n') fid_out.write(' .node rect {\n') fid_out.write(' fill: #fff;\n') fid_out.write(' stroke: steelblue;\n') fid_out.write(' stroke_width: 3px;\n') fid_out.write(' }\n') fid_out.write(' .node text { font: 12px sans-serif; }\n') fid_out.write(' .link {\n') fid_out.write(' fill: none;\n') fid_out.write(' stroke: #ccc;\n') fid_out.write(' stroke-width: 2px;\n') fid_out.write(' }\n') fid_out.write(' </style>\n') fid_out.write(' </head>\n') fid_out.write(' <body>\n') fid_out.write('<!-- load the d3.js library --> \n') fid_out.write('<script src="http://d3js.org/d3.v3.min.js"></script>\n') fid_out.write('<script>\n') fid_out.write('var treeData = [\n') fid_out.write('{}\n'.format(trees_for_visualization)) fid_out.write('];\n') fid_out.write('var margin = {top: 20, right: 120, bottom: 20, left: 0},\n') fid_out.write(' width = {} - margin.right - margin.left,\n'.format(page_width)) fid_out.write(' height = {} - margin.top - margin.bottom;\n'.format(height)) fid_out.write('var i = 0;\n') fid_out.write('var tree = d3.layout.tree()\n') fid_out.write(' .size([height, width]);\n') fid_out.write('var diagonal = d3.svg.diagonal()\n') fid_out.write(' .projection(function(d) { return [d.y, d.x]; });\n') fid_out.write('var svg = d3.select("body").append("svg")\n') fid_out.write(' .attr("width", width + margin.right + margin.left)\n') fid_out.write(' .attr("height", height + margin.top + margin.bottom)\n') fid_out.write(' .append("g")\n') fid_out.write(' .attr("transform", \n') fid_out.write(' "translate(" + margin.left + "," + margin.top + ")");\n') fid_out.write('root = treeData[0];\n') fid_out.write('update(root);\n') fid_out.write('function update(source) {\n') fid_out.write(' // Compute the new tree layout.\n') fid_out.write(' var nodes = tree.nodes(root).reverse(),\n') fid_out.write(' links = tree.links(nodes);\n') fid_out.write(' // Normalize for fixed-depth.\n') fid_out.write(' nodes.forEach(function(d) { d.y = d.depth * 250; });\n') fid_out.write(' // Declare the nodes…\n') fid_out.write(' var node = svg.selectAll("g.node")\n') fid_out.write(' .data(nodes, function(d) { return d.id || (d.id = ++i); });\n') fid_out.write(' // Enter the nodes.\n') fid_out.write(' var nodeEnter = node.enter().append("g")\n') fid_out.write(' .attr("class", "node")\n') fid_out.write(' .attr("transform", function(d) { \n') fid_out.write(' return "translate(" + d.y + "," + d.x + ")"; });\n') fid_out.write(' nodeEnter.append("image")\n') fid_out.write(' .attr("xlink:href", function(d) { return d.smiles; })\n') fid_out.write(' .attr("x", "-60px")\n') fid_out.write(' .attr("y", "-60px")\n') fid_out.write(' .attr("width", "120px")\n') fid_out.write(' .attr("height", "120px");\n') fid_out.write(' nodeEnter.append("path")\n') fid_out.write(' .style("stroke", "black")\n') fid_out.write(' .style("fill", function(d) { if (d.freq==1) { return "white"; }\n') fid_out.write(' else if (d.freq==2) { return "yellow";}\n') fid_out.write(' else if (d.freq==3) { return "orange"; }\n') fid_out.write(' else if (d.freq>=4) { return "red"; }\n') fid_out.write(' else {return "white";}\n') fid_out.write(' })\n') fid_out.write(' .attr("d", d3.svg.symbol()\n') fid_out.write(' .size(0)\n') fid_out.write(' .type(function(d) {if\n') fid_out.write(' (d.rc_type == "chemical") {return "circle";} else if\n') fid_out.write(' (d.rc_type == "reaction") {return "cross";}\n') fid_out.write(' }));\n') fid_out.write(' nodeEnter.append("text")\n') fid_out.write(' .attr("x", 0)\n') fid_out.write(' .attr("y", 35)\n') fid_out.write(' .attr("text-anchor", function(d) { \n') fid_out.write(' return d.children || d._children ? "end" : "start"; })\n') fid_out.write(' .text(function(d) { return d.names; })\n') fid_out.write(' .style("fill-opacity", 1);\n') fid_out.write(' nodeEnter.append("text")\n') fid_out.write(' .attr("x", 200)\n') fid_out.write(' .attr("y", 120)\n') fid_out.write(' .attr("text-anchor", function(d) { \n') fid_out.write(' return d.children || d._children ? "end" : "start"; })\n') fid_out.write(' .text(function(d) { return d._id; })\n') fid_out.write(' .style("fill-opacity", 1);\n') fid_out.write(' nodeEnter.append("text")\n') fid_out.write(' .attr("x", 0)\n') fid_out.write(' .attr("y", -30)\n') fid_out.write(' .attr("text-anchor", function(d) { \n') fid_out.write(' return d.children || d._children ? "end" : "start"; })\n') fid_out.write(' .text(function(d) { return d.score; })\n') fid_out.write(' .style("fill-opacity", 1);\n') fid_out.write(' // Declare the links…\n') fid_out.write(' var link = svg.selectAll("path.link")\n') fid_out.write(' .data(links, function(d) { return d.target.id; });\n') fid_out.write(' // Enter the links.\n') fid_out.write(' link.enter().insert("path", "g")\n') fid_out.write(' .attr("class", "link")\n') fid_out.write(' .style("stroke", function(d) { return d.target.level; })\n') fid_out.write(' .attr("d", diagonal);\n') fid_out.write(' // remove the first level, leaving the targets as the first level\n') fid_out.write(' node.each(function(d){\n') fid_out.write(' if (d.name == "dummy_root")\n') fid_out.write(' d3.select(this).remove();});\n') fid_out.write(' link.each(function(d){\n') fid_out.write(' if (d.source.name == "dummy_root") \n') fid_out.write(' d3.select(this).remove();});\n') fid_out.write('}\n') fid_out.write('</script>\n') fid_out.write(' </body>\n') fid_out.write('</html>\n') fid_out.close() if __name__ == "__main__": file_name = project_path + '/data/pathway_train_example.pkl' with open(file_name, 'rb') as f: data = pickle.load(f) trees_to_plot = [d['tree'] for d in data['generated_paths'][0:10]] create_tree_html(trees_to_plot, 'plotted_trees')
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cgnal/core/data/model/__init__.py
CGnal/cgnal-core
9
108719
""" Data model module. In this module the data types used in CGnal framework are defined. """
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setup.py
eddo888/perdy
0
11972
#!/usr/bin/env python import codecs from os import path from setuptools import setup pwd = path.abspath(path.dirname(__file__)) with codecs.open(path.join(pwd, 'README.md'), 'r', encoding='utf8') as input: long_description = input.read() version='1.7' setup( name='Perdy', version=version, license='MIT', long_description=long_description, long_description_content_type="text/markdown", url='https://github.com/eddo888/perdy', download_url='https://github.com/eddo888/perdy/archive/%s.tar.gz'%version, author='<NAME>', author_email='<EMAIL>', packages=[ 'Perdy', ], install_requires=[ 'pytz', 'arrow', 'xmltodict', 'PyYAML', 'jsonpath', 'argcomplete', 'Baubles', ], scripts=[ 'bin/parser.py', 'bin/pyson.py', 'bin/colourize.py', ], )
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aslam_offline_calibration/kalibr/python/kalibr_imu_camera_calibration/IccSensors.py
xxiao-1/timeShift
0
65194
<reponame>xxiao-1/timeShift import sm import aslam_cv as acv import aslam_cameras_april as acv_april import aslam_splines as asp import aslam_backend as aopt import bsplines import kalibr_common as kc import kalibr_errorterms as ket import IccCalibrator as ic import cv2 import sys import math import numpy as np import pylab as pl import scipy.optimize def initCameraBagDataset(bagfile, topic, from_to=None, perform_synchronization=False): print "Initializing camera rosbag dataset reader:" print "\tDataset: {0}".format(bagfile) print "\tTopic: {0}".format(topic) reader = kc.BagImageDatasetReader(bagfile, topic, bag_from_to=from_to, \ perform_synchronization=perform_synchronization) print "\tNumber of images: {0}".format(len(reader.index)) return reader def initImuBagDataset(bagfile, topic, from_to=None, perform_synchronization=False): print "Initializing imu rosbag dataset reader:" print "\tDataset: {0}".format(bagfile) print "\tTopic: {0}".format(topic) reader = kc.BagImuDatasetReader(bagfile, topic, bag_from_to=from_to, \ perform_synchronization=perform_synchronization) print "\tNumber of messages: {0}".format(len(reader.index)) return reader #mono camera class IccCamera(): def __init__(self, camConfig, targetConfig, dataset, reprojectionSigma=1.0, showCorners=True, \ showReproj=True, showOneStep=False): #store the configuration self.dataset = dataset self.camConfig = camConfig self.targetConfig = targetConfig # Corner uncertainty self.cornerUncertainty = reprojectionSigma #set the extrinsic prior to default self.T_extrinsic = sm.Transformation() #initialize timeshift prior to zero self.timeshiftCamToImuPrior = 0.0 #initialize the camera data self.camera = kc.AslamCamera.fromParameters( camConfig ) #extract corners self.setupCalibrationTarget( targetConfig, showExtraction=showCorners, showReproj=showReproj, imageStepping=showOneStep ) multithreading = not (showCorners or showReproj or showOneStep) self.targetObservations = kc.extractCornersFromDataset(self.dataset, self.detector, multithreading=multithreading) #an estimate of the gravity in the world coordinate frame self.gravity_w = np.array([9.80655, 0., 0.]) def setupCalibrationTarget(self, targetConfig, showExtraction=False, showReproj=False, imageStepping=False): #load the calibration target configuration targetParams = targetConfig.getTargetParams() targetType = targetConfig.getTargetType() if targetType == 'checkerboard': options = acv.CheckerboardOptions() options.filterQuads = True options.normalizeImage = True options.useAdaptiveThreshold = True options.performFastCheck = False options.windowWidth = 5 options.showExtractionVideo = showExtraction grid = acv.GridCalibrationTargetCheckerboard(targetParams['targetRows'], targetParams['targetCols'], targetParams['rowSpacingMeters'], targetParams['colSpacingMeters'], options) elif targetType == 'circlegrid': options = acv.CirclegridOptions() options.showExtractionVideo = showExtraction options.useAsymmetricCirclegrid = targetParams['asymmetricGrid'] grid = acv.GridCalibrationTargetCirclegrid(targetParams['targetRows'], targetParams['targetCols'], targetParams['spacingMeters'], options) elif targetType == 'aprilgrid': options = acv_april.AprilgridOptions() options.showExtractionVideo = showExtraction options.minTagsForValidObs = int( np.max( [targetParams['tagRows'], targetParams['tagCols']] ) + 1 ) grid = acv_april.GridCalibrationTargetAprilgrid(targetParams['tagRows'], targetParams['tagCols'], targetParams['tagSize'], targetParams['tagSpacing'], options) else: raise RuntimeError( "Unknown calibration target." ) options = acv.GridDetectorOptions() options.imageStepping = imageStepping options.plotCornerReprojection = showReproj options.filterCornerOutliers = True #options.filterCornerSigmaThreshold = 2.0 #options.filterCornerMinReprojError = 0.2 self.detector = acv.GridDetector(self.camera.geometry, grid, options) def findOrientationPriorCameraToImu(self, imu): print print "Estimating imu-camera rotation prior" # build the problem problem = aopt.OptimizationProblem() # Add the rotation as design variable q_i_c_Dv = aopt.RotationQuaternionDv( self.T_extrinsic.q() ) q_i_c_Dv.setActive( True ) problem.addDesignVariable(q_i_c_Dv) # Add the gyro bias as design variable gyroBiasDv = aopt.EuclideanPointDv( np.zeros(3) ) gyroBiasDv.setActive( True ) problem.addDesignVariable(gyroBiasDv) #initialize a pose spline using the camera poses poseSpline = self.initPoseSplineFromCamera( timeOffsetPadding=0.0 ) for im in imu.imuData: tk = im.stamp.toSec() if tk > poseSpline.t_min() and tk < poseSpline.t_max(): #DV expressions R_i_c = q_i_c_Dv.toExpression() bias = gyroBiasDv.toExpression() #get the vision predicted omega and measured omega (IMU) omega_predicted = R_i_c * aopt.EuclideanExpression( np.matrix( poseSpline.angularVelocityBodyFrame( tk ) ).transpose() ) omega_measured = im.omega #error term gerr = ket.GyroscopeError(omega_measured, im.omegaInvR, omega_predicted, bias) problem.addErrorTerm(gerr) if problem.numErrorTerms() == 0: sm.logFatal("Failed to obtain orientation prior. "\ "Please make sure that your sensors are synchronized correctly.") sys.exit(-1) #define the optimization options = aopt.Optimizer2Options() options.verbose = False options.linearSolver = aopt.BlockCholeskyLinearSystemSolver() options.nThreads = 2 options.convergenceDeltaX = 1e-4 options.convergenceDeltaJ = 1 options.maxIterations = 50 #run the optimization optimizer = aopt.Optimizer2(options) optimizer.setProblem(problem) #get the prior try: optimizer.optimize() except: sm.logFatal("Failed to obtain orientation prior!") sys.exit(-1) #overwrite the external rotation prior (keep the external translation prior) R_i_c = q_i_c_Dv.toRotationMatrix().transpose() self.T_extrinsic = sm.Transformation( sm.rt2Transform( R_i_c, self.T_extrinsic.t() ) ) #estimate gravity in the world coordinate frame as the mean specific force a_w = [] for im in imu.imuData: tk = im.stamp.toSec() if tk > poseSpline.t_min() and tk < poseSpline.t_max(): a_w.append(np.dot(poseSpline.orientation(tk), np.dot(R_i_c, - im.alpha))) mean_a_w = np.mean(np.asarray(a_w).T, axis=1) self.gravity_w = mean_a_w / np.linalg.norm(mean_a_w) * 9.80655 print "Gravity was intialized to", self.gravity_w, "[m/s^2]" #set the gyro bias prior (if we have more than 1 cameras use recursive average) b_gyro = bias.toEuclidean() imu.GyroBiasPriorCount += 1 imu.GyroBiasPrior = (imu.GyroBiasPriorCount-1.0)/imu.GyroBiasPriorCount * imu.GyroBiasPrior + 1.0/imu.GyroBiasPriorCount*b_gyro #print result print " Orientation prior camera-imu found as: (T_i_c)" print R_i_c print " Gyro bias prior found as: (b_gyro)" print b_gyro #return an etimate of gravity in the world coordinate frame as perceived by this camera def getEstimatedGravity(self): return self.gravity_w #estimates the timeshift between the camearas and the imu using a crosscorrelation approach # #approach: angular rates are constant on a fixed body independent of location # using only the norm of the gyro outputs and assuming that the biases are small # we can estimate the timeshift between the cameras and the imu by calculating # the angular rates of the cameras by fitting a spline and evaluating the derivatives # then computing the cross correlating between the "predicted" angular rates (camera) # and imu, the maximum corresponds to the timeshift... # in a next step we can use the time shift to estimate the rotation between camera and imu def findTimeshiftCameraImuPrior(self, imu, verbose=False): print "Estimating time shift camera to imu:" #fit a spline to the camera observations poseSpline = self.initPoseSplineFromCamera( timeOffsetPadding=0.0 ) #predict time shift prior t=[] omega_measured_norm = [] omega_predicted_norm = [] for im in imu.imuData: tk = im.stamp.toSec() if tk > poseSpline.t_min() and tk < poseSpline.t_max(): #get imu measurements and spline from camera omega_measured = im.omega omega_predicted = aopt.EuclideanExpression( np.matrix( poseSpline.angularVelocityBodyFrame( tk ) ).transpose() ) #calc norm t = np.hstack( (t, tk) ) omega_measured_norm = np.hstack( (omega_measured_norm, np.linalg.norm( omega_measured ) )) omega_predicted_norm = np.hstack( (omega_predicted_norm, np.linalg.norm( omega_predicted.toEuclidean() )) ) if len(omega_predicted_norm) == 0 or len(omega_measured_norm) == 0: sm.logFatal("The time ranges of the camera and IMU do not overlap. "\ "Please make sure that your sensors are synchronized correctly.") sys.exit(-1) #get the time shift corr = np.correlate(omega_predicted_norm, omega_measured_norm, "full") discrete_shift = corr.argmax() - (np.size(omega_measured_norm) - 1) #get cont. time shift times = [im.stamp.toSec() for im in imu.imuData] dT = np.mean(np.diff( times )) shift = -discrete_shift*dT #Create plots if verbose: pl.plot(t, omega_measured_norm, label="measured_raw") pl.plot(t, omega_predicted_norm, label="predicted") pl.plot(t-shift, omega_measured_norm, label="measured_corrected") pl.legend() pl.title("Time shift prior camera-imu estimation") pl.figure() pl.plot(corr) pl.title("Cross-correlation ||omega_predicted||, ||omega_measured||") pl.show() sm.logDebug("discrete time shift: {0}".format(discrete_shift)) sm.logDebug("cont. time shift: {0}".format(shift)) sm.logDebug("dT: {0}".format(dT)) #store the timeshift (t_imu = t_cam + timeshiftCamToImuPrior) self.timeshiftCamToImuPrior = shift print " Time shift camera to imu (t_imu = t_cam + shift):" print self.timeshiftCamToImuPrior #initialize a pose spline using camera poses (pose spline = T_wb) def initPoseSplineFromCamera(self, splineOrder=6, poseKnotsPerSecond=100, timeOffsetPadding=0.02): T_c_b = self.T_extrinsic.T() pose = bsplines.BSplinePose(splineOrder, sm.RotationVector() ) # Get the checkerboard times. times = np.array([obs.time().toSec()+self.timeshiftCamToImuPrior for obs in self.targetObservations ]) curve = np.matrix([ pose.transformationToCurveValue( np.dot(obs.T_t_c().T(), T_c_b) ) for obs in self.targetObservations]).T if np.isnan(curve).any(): raise RuntimeError("Nans in curve values") sys.exit(0) # Add 2 seconds on either end to allow the spline to slide during optimization times = np.hstack((times[0] - (timeOffsetPadding * 2.0), times, times[-1] + (timeOffsetPadding * 2.0))) curve = np.hstack((curve[:,0], curve, curve[:,-1])) # Make sure the rotation vector doesn't flip for i in range(1,curve.shape[1]): previousRotationVector = curve[3:6,i-1] r = curve[3:6,i] angle = np.linalg.norm(r) axis = r/angle best_r = r best_dist = np.linalg.norm( best_r - previousRotationVector) for s in range(-3,4): aa = axis * (angle + math.pi * 2.0 * s) dist = np.linalg.norm( aa - previousRotationVector ) if dist < best_dist: best_r = aa best_dist = dist curve[3:6,i] = best_r seconds = times[-1] - times[0] knots = int(round(seconds * poseKnotsPerSecond)) print print "Initializing a pose spline with %d knots (%f knots per second over %f seconds)" % ( knots, poseKnotsPerSecond, seconds) pose.initPoseSplineSparse(times, curve, knots, 1e-4) return pose def addDesignVariables(self, problem, noExtrinsics=True, noTimeCalibration=True, baselinedv_group_id=ic.HELPER_GROUP_ID): # Add the calibration design variables. active = not noExtrinsics self.T_c_b_Dv = aopt.TransformationDv(self.T_extrinsic, rotationActive=active, translationActive=active) for i in range(0, self.T_c_b_Dv.numDesignVariables()): problem.addDesignVariable(self.T_c_b_Dv.getDesignVariable(i), baselinedv_group_id) # Add the time delay design variable. self.cameraTimeToImuTimeDv = aopt.Scalar(0.0) self.cameraTimeToImuTimeDv.setActive( not noTimeCalibration ) problem.addDesignVariable(self.cameraTimeToImuTimeDv, ic.CALIBRATION_GROUP_ID) def addCameraErrorTerms(self, problem, poseSplineDv, T_cN_b, blakeZissermanDf=0.0, timeOffsetPadding=0.0): print print "Adding camera error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.targetObservations) ) iProgress.sample() allReprojectionErrors = list() error_t = self.camera.reprojectionErrorType for obs in self.targetObservations: # Build a transformation expression for the time. frameTime = self.cameraTimeToImuTimeDv.toExpression() + obs.time().toSec() + self.timeshiftCamToImuPrior frameTimeScalar = frameTime.toScalar() #as we are applying an initial time shift outside the optimization so #we need to make sure that we dont add data outside the spline definition if frameTimeScalar <= poseSplineDv.spline().t_min() or frameTimeScalar >= poseSplineDv.spline().t_max(): continue T_w_b = poseSplineDv.transformationAtTime(frameTime, timeOffsetPadding, timeOffsetPadding) T_b_w = T_w_b.inverse() #calibration target coords to camera N coords #T_b_w: from world to imu coords #T_cN_b: from imu to camera N coords T_c_w = T_cN_b * T_b_w #get the image and target points corresponding to the frame imageCornerPoints = np.array( obs.getCornersImageFrame() ).T targetCornerPoints = np.array( obs.getCornersTargetFrame() ).T #setup an aslam frame (handles the distortion) frame = self.camera.frameType() frame.setGeometry(self.camera.geometry) #corner uncertainty R = np.eye(2) * self.cornerUncertainty * self.cornerUncertainty invR = np.linalg.inv(R) for pidx in range(0,imageCornerPoints.shape[1]): #add all image points k = self.camera.keypointType() k.setMeasurement( imageCornerPoints[:,pidx] ) k.setInverseMeasurementCovariance(invR) frame.addKeypoint(k) reprojectionErrors=list() for pidx in range(0,imageCornerPoints.shape[1]): #add all target points targetPoint = np.insert( targetCornerPoints.transpose()[pidx], 3, 1) p = T_c_w * aopt.HomogeneousExpression( targetPoint ) #build and append the error term rerr = error_t(frame, pidx, p) #add blake-zisserman m-estimator if blakeZissermanDf>0.0: mest = aopt.BlakeZissermanMEstimator( blakeZissermanDf ) rerr.setMEstimatorPolicy(mest) problem.addErrorTerm(rerr) reprojectionErrors.append(rerr) allReprojectionErrors.append(reprojectionErrors) #update progress bar iProgress.sample() print "\r Added {0} camera error terms ".format( len(self.targetObservations) ) self.allReprojectionErrors = allReprojectionErrors #pair of cameras with overlapping field of view (perfectly synced cams required!!) # # Sensor "chain" R_C1C0 source: *fixed as input from stereo calib # *optimized using stereo error terms # R_C1C0(R,t) C1 R_C2C1(R,t) C2 Cn # C0 o------------------o------------------o ... o # | # | R_C0I (R,t) # | # o (IMU) # #imu is need to initialize an orientation prior between imu and camera chain class IccCameraChain(): def __init__(self, chainConfig, targetConfig, parsed): #create all camera in the chain self.camList = [] for camNr in range(0, chainConfig.numCameras()): camConfig = chainConfig.getCameraParameters(camNr) dataset = initCameraBagDataset(parsed.bagfile[0], camConfig.getRosTopic(), \ parsed.bag_from_to, parsed.perform_synchronization) #create the camera self.camList.append( IccCamera( camConfig, targetConfig, dataset, #Ultimately, this should come from the camera yaml. reprojectionSigma=parsed.reprojection_sigma, showCorners=parsed.showextraction, showReproj=parsed.showextraction, showOneStep=parsed.extractionstepping) ) self.chainConfig = chainConfig #find and store time between first and last image over all cameras self.findCameraTimespan() #use stereo calibration guess if no baselines are provided self.initializeBaselines() def initializeBaselines(self): #estimate baseline prior if no external guess is provided for camNr in range(1, len(self.camList)): self.camList[camNr].T_extrinsic = self.chainConfig.getExtrinsicsLastCamToHere(camNr) print "Baseline between cam{0} and cam{1} set to:".format(camNr-1,camNr) print "T= ", self.camList[camNr].T_extrinsic.T() print "Baseline: ", np.linalg.norm(self.camList[camNr].T_extrinsic.t()), " [m]" #initialize a pose spline for the chain def initializePoseSplineFromCameraChain(self, splineOrder=6, poseKnotsPerSecond=100, timeOffsetPadding=0.02): #use the main camera for the spline to initialize the poses return self.camList[0].initPoseSplineFromCamera(splineOrder, poseKnotsPerSecond, timeOffsetPadding) #find the timestamp for the first and last image considering all cameras in the chain def findCameraTimespan(self): tStart = acv.Time( 0.0 ) tEnd = acv.Time( 0.0 ) for cam in self.camList: if len(cam.targetObservations)>0: tStartCam = cam.targetObservations[0].time() tEndCam = cam.targetObservations[-1].time() if tStart.toSec() > tStartCam.toSec(): tStart = tStartCam if tEndCam.toSec() > tEnd.toSec(): tEnd = tEndCam self.timeStart = tStart self.timeStart = tEnd #find/set orientation prior between first camera in chain and main IMU (imu0) def findOrientationPriorCameraChainToImu(self, imu): self.camList[0].findOrientationPriorCameraToImu( imu ) #get an initial estimate of gravity in the world coordinate frame def getEstimatedGravity(self): return self.camList[0].getEstimatedGravity() #return the baseline transformation from camA to camB def getResultBaseline(self, fromCamANr, toCamBNr): #transformation from cam a to b is always stored in the higer ID cam idx = np.max([fromCamANr, toCamBNr]) #get the transform from camNrmin to camNrmax T_cB_cA = sm.Transformation( self.camList[idx].T_c_b_Dv.T() ) #get the transformation direction right if fromCamANr > toCamBNr: T_cB_cA = T_cB_cA.inverse() #calculate the metric baseline baseline = np.linalg.norm( T_cB_cA.t() ) return T_cB_cA, baseline def getResultTrafoImuToCam(self, camNr): #trafo from imu to cam0 in the chain T_c0_i = sm.Transformation( self.camList[0].T_c_b_Dv.T() ) #add all the baselines along the chain up to our camera N T_cN_imu = T_c0_i #now add all baselines starting from the second camera up to the desired one for cam in self.camList[1:camNr+1]: T_cNplus1_cN = sm.Transformation( cam.T_c_b_Dv.T() ) T_cN_imu = T_cNplus1_cN*T_cN_imu return T_cN_imu def getResultTimeShift(self, camNr): return self.camList[camNr].cameraTimeToImuTimeDv.toScalar() + self.camList[camNr].timeshiftCamToImuPrior def addDesignVariables(self, problem, noTimeCalibration = True, noChainExtrinsics = True): #add the design variables (T(R,t) & time) for all induvidual cameras for camNr, cam in enumerate( self.camList ): #the first "baseline" dv is between the imu and cam0 if camNr == 0: noExtrinsics = False baselinedv_group_id = ic.CALIBRATION_GROUP_ID else: noExtrinsics = noChainExtrinsics baselinedv_group_id = ic.HELPER_GROUP_ID cam.addDesignVariables(problem, noExtrinsics, noTimeCalibration, baselinedv_group_id=baselinedv_group_id) #add the reprojection error terms for all cameras in the chain def addCameraChainErrorTerms(self, problem, poseSplineDv, blakeZissermanDf=-1, timeOffsetPadding=0.0): #add the induviduak error terms for all cameras for camNr, cam in enumerate(self.camList): #add error terms for the first chain element if camNr == 0: #initialize the chain with first camerea ( imu to cam0) T_chain = cam.T_c_b_Dv.toExpression() else: T_chain = cam.T_c_b_Dv.toExpression() * T_chain #from imu coords to camerea N coords (as DVs) T_cN_b = T_chain #add the error terms cam.addCameraErrorTerms( problem, poseSplineDv, T_cN_b, blakeZissermanDf, timeOffsetPadding ) #IMU class IccImu(object): class ImuParameters(kc.ImuParameters): def __init__(self, imuConfig): kc.ImuParameters.__init__(self, '', True) self.data = imuConfig.data self.data["model"] = "calibrated" def setImuPose(self, T_i_b): self.data["T_i_b"] = T_i_b.tolist() def setTimeOffset(self, time_offset): self.data["time_offset"] = time_offset def formatIndented(self, indent, np_array): return indent + str(np.array_str(np_array)).replace('\n',"\n"+indent) def printDetails(self, dest=sys.stdout): print >> dest, " Model: {0}".format(self.data["model"]) kc.ImuParameters.printDetails(self, dest) print >> dest, " T_i_b" print >> dest, self.formatIndented(" ", np.array(self.data["T_i_b"])) print >> dest, " time offset with respect to IMU0: {0} [s]".format(self.data["time_offset"]) def getImuConfig(self): self.updateImuConfig() return self.imuConfig def updateImuConfig(self): self.imuConfig.setImuPose(sm.Transformation(sm.r2quat(self.q_i_b_Dv.toRotationMatrix()), \ self.r_b_Dv.toEuclidean()).T()) self.imuConfig.setTimeOffset(self.timeOffset) def __init__(self, imuConfig, parsed, isReferenceImu=True, estimateTimedelay=True): #determine whether IMU coincides with body frame (for multi-IMU setups) self.isReferenceImu = isReferenceImu self.estimateTimedelay = estimateTimedelay #store input self.imuConfig = self.ImuParameters(imuConfig) #load dataset self.dataset = initImuBagDataset(parsed.bagfile[0], imuConfig.getRosTopic(), \ parsed.bag_from_to, parsed.perform_synchronization) #statistics self.accelUncertaintyDiscrete, self.accelRandomWalk, self.accelUncertainty = self.imuConfig.getAccelerometerStatistics() self.gyroUncertaintyDiscrete, self.gyroRandomWalk, self.gyroUncertainty = self.imuConfig.getGyroStatistics() #init GyroBiasPrior (+ count for recursive averaging if we have more than 1 measurement = >1 cameras) self.GyroBiasPrior = np.array([0,0,0]) self.GyroBiasPriorCount = 0 #load the imu dataset self.loadImuData() #initial estimates for multi IMU calibration self.q_i_b_prior = np.array([0., 0., 0., 1.]) self.timeOffset = 0.0 class ImuMeasurement(object): def __init__(self, stamp, omega, alpha, Rgyro, Raccel): self.omega = omega self.alpha = alpha self.omegaR = Rgyro self.omegaInvR = np.linalg.inv(Rgyro) self.alphaR = Raccel self.alphaInvR = np.linalg.inv(Raccel) self.stamp = stamp def loadImuData(self): print "Reading IMU data ({0})".format(self.dataset.topic) # print(self.dataset) # prepare progess bar iProgress = sm.Progress2( self.dataset.numMessages() ) iProgress.sample() Rgyro = np.eye(3) * self.gyroUncertaintyDiscrete * self.gyroUncertaintyDiscrete Raccel = np.eye(3) * self.accelUncertaintyDiscrete * self.accelUncertaintyDiscrete # Now read the imu measurements. imu = [] for timestamp, omega, alpha in self.dataset: timestamp = acv.Time( timestamp.toSec() ) imu.append( self.ImuMeasurement(timestamp, omega, alpha, Rgyro, Raccel) ) iProgress.sample() self.imuData = imu if len(self.imuData)>1: print "\r Read %d imu readings over %.1f seconds " \ % (len(imu), imu[-1].stamp.toSec() - imu[0].stamp.toSec()) else: sm.logFatal("Could not find any IMU messages. Please check the dataset.") sys.exit(-1) def addDesignVariables(self, problem): #create design variables self.gyroBiasDv = asp.EuclideanBSplineDesignVariable( self.gyroBias ) self.accelBiasDv = asp.EuclideanBSplineDesignVariable( self.accelBias ) ic.addSplineDesignVariables(problem, self.gyroBiasDv, setActive=True, \ group_id=ic.HELPER_GROUP_ID) ic.addSplineDesignVariables(problem, self.accelBiasDv, setActive=True, \ group_id=ic.HELPER_GROUP_ID) self.q_i_b_Dv = aopt.RotationQuaternionDv(self.q_i_b_prior) problem.addDesignVariable(self.q_i_b_Dv, ic.HELPER_GROUP_ID) self.q_i_b_Dv.setActive(False) self.r_b_Dv = aopt.EuclideanPointDv(np.array([0., 0., 0.])) problem.addDesignVariable(self.r_b_Dv, ic.HELPER_GROUP_ID) self.r_b_Dv.setActive(False) if not self.isReferenceImu: self.q_i_b_Dv.setActive(True) self.r_b_Dv.setActive(True) def addAccelerometerErrorTerms(self, problem, poseSplineDv, g_w, mSigma=0.0, \ accelNoiseScale=1.0): print print "Adding accelerometer error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.imuData) ) iProgress.sample() # AccelerometerError(measurement, invR, C_b_w, acceleration_w, bias, g_w) weight = 1.0/accelNoiseScale accelErrors = [] num_skipped = 0 if mSigma > 0.0: mest = aopt.HuberMEstimator(mSigma) else: mest = aopt.NoMEstimator() for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > poseSplineDv.spline().t_min() and tk < poseSplineDv.spline().t_max(): C_b_w = poseSplineDv.orientation(tk).inverse() a_w = poseSplineDv.linearAcceleration(tk) b_i = self.accelBiasDv.toEuclideanExpression(tk,0) w_b = poseSplineDv.angularVelocityBodyFrame(tk) w_dot_b = poseSplineDv.angularAccelerationBodyFrame(tk) C_i_b = self.q_i_b_Dv.toExpression() r_b = self.r_b_Dv.toExpression() a = C_i_b * (C_b_w * (a_w - g_w) + \ w_dot_b.cross(r_b) + w_b.cross(w_b.cross(r_b))) aerr = ket.EuclideanError(im.alpha, im.alphaInvR * weight, a + b_i) aerr.setMEstimatorPolicy(mest) accelErrors.append(aerr) problem.addErrorTerm(aerr) else: num_skipped = num_skipped + 1 #update progress bar iProgress.sample() print "\r Added {0} of {1} accelerometer error terms (skipped {2} out-of-bounds measurements)".format( len(self.imuData)-num_skipped, len(self.imuData), num_skipped ) self.accelErrors = accelErrors def addGyroscopeErrorTerms(self, problem, poseSplineDv, mSigma=0.0, gyroNoiseScale=1.0, \ g_w=None): print print "Adding gyroscope error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.imuData) ) iProgress.sample() num_skipped = 0 gyroErrors = [] weight = 1.0/gyroNoiseScale if mSigma > 0.0: mest = aopt.HuberMEstimator(mSigma) else: mest = aopt.NoMEstimator() for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > poseSplineDv.spline().t_min() and tk < poseSplineDv.spline().t_max(): # GyroscopeError(measurement, invR, angularVelocity, bias) w_b = poseSplineDv.angularVelocityBodyFrame(tk) b_i = self.gyroBiasDv.toEuclideanExpression(tk,0) C_i_b = self.q_i_b_Dv.toExpression() w = C_i_b * w_b gerr = ket.EuclideanError(im.omega, im.omegaInvR * weight, w + b_i) gerr.setMEstimatorPolicy(mest) gyroErrors.append(gerr) problem.addErrorTerm(gerr) else: num_skipped = num_skipped + 1 #update progress bar iProgress.sample() print "\r Added {0} of {1} gyroscope error terms (skipped {2} out-of-bounds measurements)".format( len(self.imuData)-num_skipped, len(self.imuData), num_skipped ) self.gyroErrors = gyroErrors def initBiasSplines(self, poseSpline, splineOrder, biasKnotsPerSecond): start = poseSpline.t_min(); end = poseSpline.t_max(); seconds = end - start; knots = int(round(seconds * biasKnotsPerSecond)) print print "Initializing the bias splines with %d knots" % (knots) #initialize the bias splines self.gyroBias = bsplines.BSpline(splineOrder) self.gyroBias.initConstantSpline(start,end,knots, self.GyroBiasPrior ) self.accelBias = bsplines.BSpline(splineOrder) self.accelBias.initConstantSpline(start,end,knots, np.zeros(3)) def addBiasMotionTerms(self, problem): Wgyro = np.eye(3) / (self.gyroRandomWalk * self.gyroRandomWalk) Waccel = np.eye(3) / (self.accelRandomWalk * self.accelRandomWalk) gyroBiasMotionErr = asp.BSplineEuclideanMotionError(self.gyroBiasDv, Wgyro, 1) problem.addErrorTerm(gyroBiasMotionErr) accelBiasMotionErr = asp.BSplineEuclideanMotionError(self.accelBiasDv, Waccel, 1) problem.addErrorTerm(accelBiasMotionErr) def getTransformationFromBodyToImu(self): if self.isReferenceImu: return sm.Transformation() return sm.Transformation(sm.r2quat(self.q_i_b_Dv.toRotationMatrix()) , \ np.dot(self.q_i_b_Dv.toRotationMatrix(), \ self.r_b_Dv.toEuclidean())) def findOrientationPrior(self, referenceImu): print print "Estimating imu-imu rotation initial guess." # build the problem problem = aopt.OptimizationProblem() # Add the rotation as design variable q_i_b_Dv = aopt.RotationQuaternionDv( np.array([0.0, 0.0, 0.0, 1.0]) ) q_i_b_Dv.setActive(True) problem.addDesignVariable(q_i_b_Dv) # Add spline representing rotational velocity of in body frame startTime = self.imuData[0].stamp.toSec() endTime = self.imuData[-1].stamp.toSec() knotsPerSecond = 50 knots = int( round( (endTime - startTime) * knotsPerSecond) ) angularVelocity = bsplines.BSpline(3) angularVelocity.initConstantSpline(startTime, endTime, knots, np.array([0., 0., 0.]) ) angularVelocityDv = asp.EuclideanBSplineDesignVariable(angularVelocity) for i in range(0,angularVelocityDv.numDesignVariables()): dv = angularVelocityDv.designVariable(i) dv.setActive(True) problem.addDesignVariable(dv) # Add constant reference gyro bias as design variable referenceGyroBiasDv = aopt.EuclideanPointDv( np.zeros(3) ) referenceGyroBiasDv.setActive(True) problem.addDesignVariable(referenceGyroBiasDv) for im in referenceImu.imuData: tk = im.stamp.toSec() if tk > angularVelocity.t_min() and tk < angularVelocity.t_max(): #DV expressions bias = referenceGyroBiasDv.toExpression() omega_predicted = angularVelocityDv.toEuclideanExpression(tk, 0) omega_measured = im.omega #error term gerr = ket.GyroscopeError(im.omega, im.omegaInvR, omega_predicted, bias) problem.addErrorTerm(gerr) #define the optimization options = aopt.Optimizer2Options() options.verbose = False options.linearSolver = aopt.BlockCholeskyLinearSystemSolver() options.nThreads = 2 options.convergenceDeltaX = 1e-4 options.convergenceDeltaJ = 1 options.maxIterations = 50 #run the optimization optimizer = aopt.Optimizer2(options) optimizer.setProblem(problem) try: optimizer.optimize() except: sm.logFatal("Failed to obtain initial guess for the relative orientation!") sys.exit(-1) referenceAbsoluteOmega = lambda dt = np.array([0.]): \ np.asarray([np.linalg.norm(angularVelocityDv.toEuclidean(im.stamp.toSec() + dt[0], 0)) \ for im in self.imuData \ if (im.stamp.toSec() + dt[0] > angularVelocity.t_min() \ and im.stamp.toSec() + dt[0] < angularVelocity.t_max())]) absoluteOmega = lambda dt = np.array([0.]): \ np.asarray([np.linalg.norm(im.omega) for im in self.imuData \ if (im.stamp.toSec() + dt[0] > angularVelocity.t_min() \ and im.stamp.toSec() + dt[0] < angularVelocity.t_max())]) if len(referenceAbsoluteOmega()) == 0 or len(absoluteOmega()) == 0: sm.logFatal("The time ranges of the IMUs published as topics {0} and {1} do not overlap. "\ "Please make sure that the sensors are synchronized correctly." \ .format(referenceImu.imuConfig.getRosTopic(), self.imuConfig.getRosTopic())) sys.exit(-1) #get the time shift corr = np.correlate(referenceAbsoluteOmega(), absoluteOmega(), "full") discrete_shift = corr.argmax() - (np.size(absoluteOmega()) - 1) #get cont. time shift times = [im.stamp.toSec() for im in self.imuData] dT = np.mean(np.diff( times )) shift = discrete_shift*dT if self.estimateTimedelay and not self.isReferenceImu: #refine temporal offset only when used. objectiveFunction = lambda dt: np.linalg.norm(referenceAbsoluteOmega(dt) - absoluteOmega(dt))**2 refined_shift = scipy.optimize.fmin(objectiveFunction, np.array([shift]), maxiter=100)[0] self.timeOffset = float(refined_shift) print "Temporal correction with respect to reference IMU " print self.timeOffset, "[s]", ("" if self.estimateTimedelay else \ " (this offset is not accounted for in the calibration)") # Add constant gyro bias as design variable gyroBiasDv = aopt.EuclideanPointDv( np.zeros(3) ) gyroBiasDv.setActive(True) problem.addDesignVariable(gyroBiasDv) for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > angularVelocity.t_min() and tk < angularVelocity.t_max(): #DV expressions C_i_b = q_i_b_Dv.toExpression() bias = gyroBiasDv.toExpression() omega_predicted = C_i_b * angularVelocityDv.toEuclideanExpression(tk, 0) omega_measured = im.omega #error term gerr = ket.GyroscopeError(im.omega, im.omegaInvR, omega_predicted, bias) problem.addErrorTerm(gerr) #get the prior try: optimizer.optimize() except: sm.logFatal("Failed to obtain initial guess for the relative orientation!") sys.exit(-1) print "Estimated imu to reference imu Rotation: " print q_i_b_Dv.toRotationMatrix() self.q_i_b_prior = sm.r2quat(q_i_b_Dv.toRotationMatrix()) #Lidar class IccLidar(object): def __init__(self): self.loadLidarData() self.targetObservations = [] self.timeshiftLidarToImuPrior = 0.0 class LidarMeasurement(object): def __init__(self, stamp, vec): self.vec = vec self.stamp = stamp def loadLidarData(self): # print "Reading Lidar data ({0})".format(self.dataset.topic) Lidar = [] with open("/home/xxiao/kalibr/poseLidar.txt", "r") as f: for line in f.readlines(): line = line.strip('\n') line = line.split(' ') v=np.array([float(line[1]),float(line[2]),float(line[3]),float(line[4]),float(line[5]),float(line[6])]) # print(v) Lidar.append(self.LidarMeasurement(line[0], v) ) self.LidarData = Lidar if len(self.LidarData)>1: print "\r Read %d Lidar readings over %.1f seconds " \ % (len(Lidar), float(Lidar[-1].stamp) - float(Lidar[0].stamp)) else: sm.logFatal("Could not find any Lidar messages. Please check the dataset.") sys.exit(-1) #estimates the timeshift between the camearas and the imu using a crosscorrelation approach # #approach: angular rates are constant on a fixed body independent of location # using only the norm of the gyro outputs and assuming that the biases are small # we can estimate the timeshift between the cameras and the imu by calculating # the angular rates of the cameras by fitting a spline and evaluating the derivatives # then computing the cross correlating between the "predicted" angular rates (camera) # and imu, the maximum corresponds to the timeshift... # in a next step we can use the time shift to estimate the rotation between camera and imu def findTimeshiftCameraImuPrior(self, imu, verbose=False): print "Estimating time shift lidar to imu:" #fit a spline to the camera observations poseSpline = self.initPoseSplineFromLidar( timeOffsetPadding=0.0 ) #predict time shift prior t=[] omega_measured_norm = [] omega_predicted_norm = [] for im in imu.imuData: tk = im.stamp.toSec() if tk > poseSpline.t_min() and tk < poseSpline.t_max(): #get imu measurements and spline from camera omega_measured = im.omega # lidar omega_predicted = aopt.EuclideanExpression( np.matrix( poseSpline.angularVelocityBodyFrame( tk ) ).transpose() ) #calc norm t = np.hstack( (t, tk) ) omega_measured_norm = np.hstack( (omega_measured_norm, np.linalg.norm( omega_measured ) )) omega_predicted_norm = np.hstack( (omega_predicted_norm, np.linalg.norm( omega_predicted.toEuclidean() )) ) print(len(omega_predicted_norm)) print(len(omega_measured_norm)) if len(omega_predicted_norm) == 0 or len(omega_measured_norm) == 0: sm.logFatal("The time ranges of the Lidar and IMU do not overlap. "\ "Please make sure that your sensors are synchronized correctly.") sys.exit(-1) #get the time shift corr = np.correlate(omega_predicted_norm, omega_measured_norm, "full") discrete_shift = corr.argmax() - (np.size(omega_measured_norm) - 1) #get cont. time shift times = [im.stamp.toSec() for im in imu.imuData] dT = np.mean(np.diff( times )) shift = -discrete_shift*dT #Create plots Isplot = True if Isplot: pl.plot(t, omega_measured_norm, label="measured_raw") pl.plot(t, omega_predicted_norm, label="predicted") pl.plot(t-shift, omega_measured_norm, label="measured_corrected") pl.legend() pl.title("Time shift prior camera-imu estimation") pl.figure() pl.plot(corr) pl.title("Cross-correlation ||omega_predicted||, ||omega_measured||") pl.show() sm.logDebug("discrete time shift: {0}".format(discrete_shift)) sm.logDebug("cont. time shift: {0}".format(shift)) sm.logDebug("dT: {0}".format(dT)) #store the timeshift (t_imu = t_cam + timeshiftLidarToImuPrior) self.timeshiftLidarToImuPrior = shift print " Time shift Lidar to imu (t_imu = t_lidar + shift):" print self.timeshiftLidarToImuPrior #initialize a pose spline using camera poses (pose spline = T_wb) def initPoseSplineFromLidar(self, splineOrder=6, poseKnotsPerSecond=100, timeOffsetPadding=0.02): # T_c_b = self.T_extrinsic.T() pose = bsplines.BSplinePose(splineOrder, sm.RotationVector()) self.targetObservations = self.LidarData # Get the checkerboard times. times = np.array([float(obs.stamp)+self.timeshiftLidarToImuPrior for obs in self.targetObservations ]) # ??? whether use t_c_b # curve = np.matrix([ pose.timeshiftLidarToImuPrior( np.dot(obs[1], T_c_b) ) for obs in self.targetObservations]).T curve = np.matrix([ obs.vec for obs in self.targetObservations]).T if np.isnan(curve).any(): raise RuntimeError("Nans in curve values") sys.exit(0) # Add 2 seconds on either end to allow the spline to slide during optimization times = np.hstack((times[0] - (timeOffsetPadding * 2.0), times, times[-1] + (timeOffsetPadding * 2.0))) curve = np.hstack((curve[:,0], curve, curve[:,-1])) # print(curve) # Make sure the rotation vector doesn't flip for i in range(2,curve.shape[1]): # print(i) previousRotationVector = curve[3:6,i-1] r = curve[3:6,i] angle = np.linalg.norm(r) # print(r) # print(angle) axis = r/angle best_r = r best_dist = np.linalg.norm( best_r - previousRotationVector) for s in range(-3,4): aa = axis * (angle + math.pi * 2.0 * s) dist = np.linalg.norm( aa - previousRotationVector ) if dist < best_dist: best_r = aa best_dist = dist curve[3:6,i] = best_r seconds = times[-1] - times[0] knots = int(round(seconds * poseKnotsPerSecond)) print print "Initializing a pose spline with %d knots (%f knots per second over %f seconds)" % ( knots, poseKnotsPerSecond, seconds) pose.initPoseSplineSparse(times, curve, knots, 1e-4) return pose class IccScaledMisalignedImu(IccImu): class ImuParameters(IccImu.ImuParameters): def __init__(self, imuConfig): IccImu.ImuParameters.__init__(self, imuConfig) self.data = imuConfig.data self.data["model"] = "scale-misalignment" def printDetails(self, dest=sys.stdout): IccImu.ImuParameters.printDetails(self, dest) print >> dest, " Gyroscope: " print >> dest, " M:" print >> dest, self.formatIndented(" ", np.array(self.data["gyroscopes"]["M"])) print >> dest, " A [(rad/s)/(m/s^2)]:" print >> dest, self.formatIndented(" ", np.array(self.data["gyroscopes"]["A"])) print >> dest, " C_gyro_i:" print >> dest, self.formatIndented(" ", np.array(self.data["gyroscopes"]["C_gyro_i"])) print >> dest, " Accelerometer: " print >> dest, " M:" print >> dest, self.formatIndented(" ", np.array(self.data["accelerometers"]["M"])) def setIntrisicsMatrices(self, M_accel, C_gyro_i, M_gyro, Ma_gyro): self.data["accelerometers"] = dict() self.data["accelerometers"]["M"] = M_accel.tolist() self.data["gyroscopes"] = dict() self.data["gyroscopes"]["M"] = M_gyro.tolist() self.data["gyroscopes"]["A"] = Ma_gyro.tolist() self.data["gyroscopes"]["C_gyro_i"] = C_gyro_i.tolist() def updateImuConfig(self): IccImu.updateImuConfig(self) self.imuConfig.setIntrisicsMatrices(self.M_accel_Dv.toMatrix3x3(), \ self.q_gyro_i_Dv.toRotationMatrix(), \ self.M_gyro_Dv.toMatrix3x3(), \ self.M_accel_gyro_Dv.toMatrix3x3()) def addDesignVariables(self, problem): IccImu.addDesignVariables(self, problem) self.q_gyro_i_Dv = aopt.RotationQuaternionDv(np.array([0., 0., 0., 1.])) problem.addDesignVariable(self.q_gyro_i_Dv, ic.HELPER_GROUP_ID) self.q_gyro_i_Dv.setActive(True) self.M_accel_Dv = aopt.MatrixBasicDv(np.eye(3), np.array([[1, 0, 0],[1, 1, 0],[1, 1, 1]], \ dtype=int)) problem.addDesignVariable(self.M_accel_Dv, ic.HELPER_GROUP_ID) self.M_accel_Dv.setActive(True) self.M_gyro_Dv = aopt.MatrixBasicDv(np.eye(3), np.array([[1, 0, 0],[1, 1, 0],[1, 1, 1]], \ dtype=int)) problem.addDesignVariable(self.M_gyro_Dv, ic.HELPER_GROUP_ID) self.M_gyro_Dv.setActive(True) self.M_accel_gyro_Dv = aopt.MatrixBasicDv(np.zeros((3,3)),np.ones((3,3),dtype=int)) problem.addDesignVariable(self.M_accel_gyro_Dv, ic.HELPER_GROUP_ID) self.M_accel_gyro_Dv.setActive(True) def addAccelerometerErrorTerms(self, problem, poseSplineDv, g_w, mSigma=0.0, \ accelNoiseScale=1.0): print print "Adding accelerometer error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.imuData) ) iProgress.sample() # AccelerometerError(measurement, invR, C_b_w, acceleration_w, bias, g_w) weight = 1.0/accelNoiseScale accelErrors = [] num_skipped = 0 if mSigma > 0.0: mest = aopt.HuberMEstimator(mSigma) else: mest = aopt.NoMEstimator() for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > poseSplineDv.spline().t_min() and tk < poseSplineDv.spline().t_max(): C_b_w = poseSplineDv.orientation(tk).inverse() a_w = poseSplineDv.linearAcceleration(tk) b_i = self.accelBiasDv.toEuclideanExpression(tk,0) M = self.M_accel_Dv.toExpression() w_b = poseSplineDv.angularVelocityBodyFrame(tk) w_dot_b = poseSplineDv.angularAccelerationBodyFrame(tk) C_i_b = self.q_i_b_Dv.toExpression() r_b = self.r_b_Dv.toExpression() a = M * (C_i_b * (C_b_w * (a_w - g_w) + \ w_dot_b.cross(r_b) + w_b.cross(w_b.cross(r_b)))) aerr = ket.EuclideanError(im.alpha, im.alphaInvR * weight, a + b_i) aerr.setMEstimatorPolicy(mest) accelErrors.append(aerr) problem.addErrorTerm(aerr) else: num_skipped = num_skipped + 1 #update progress bar iProgress.sample() print "\r Added {0} of {1} accelerometer error terms (skipped {2} out-of-bounds measurements)".format( len(self.imuData)-num_skipped, len(self.imuData), num_skipped ) self.accelErrors = accelErrors def addGyroscopeErrorTerms(self, problem, poseSplineDv, mSigma=0.0, gyroNoiseScale=1.0, g_w=None): print print "Adding gyroscope error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.imuData) ) iProgress.sample() num_skipped = 0 gyroErrors = [] weight = 1.0/gyroNoiseScale if mSigma > 0.0: mest = aopt.HuberMEstimator(mSigma) else: mest = aopt.NoMEstimator() for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > poseSplineDv.spline().t_min() and tk < poseSplineDv.spline().t_max(): # GyroscopeError(measurement, invR, angularVelocity, bias) w_b = poseSplineDv.angularVelocityBodyFrame(tk) w_dot_b = poseSplineDv.angularAccelerationBodyFrame(tk) b_i = self.gyroBiasDv.toEuclideanExpression(tk,0) C_b_w = poseSplineDv.orientation(tk).inverse() a_w = poseSplineDv.linearAcceleration(tk) r_b = self.r_b_Dv.toExpression() a_b = C_b_w * (a_w - g_w) + w_dot_b.cross(r_b) + w_b.cross(w_b.cross(r_b)) C_i_b = self.q_i_b_Dv.toExpression() C_gyro_i = self.q_gyro_i_Dv.toExpression() C_gyro_b = C_gyro_i * C_i_b M = self.M_gyro_Dv.toExpression() Ma = self.M_accel_gyro_Dv.toExpression() w = M * (C_gyro_b * w_b) + Ma * (C_gyro_b * a_b) gerr = ket.EuclideanError(im.omega, im.omegaInvR * weight, w + b_i) gerr.setMEstimatorPolicy(mest) gyroErrors.append(gerr) problem.addErrorTerm(gerr) else: num_skipped = num_skipped + 1 #update progress bar iProgress.sample() print "\r Added {0} of {1} gyroscope error terms (skipped {2} out-of-bounds measurements)".format( len(self.imuData)-num_skipped, len(self.imuData), num_skipped ) self.gyroErrors = gyroErrors class IccScaledMisalignedSizeEffectImu(IccScaledMisalignedImu): class ImuParameters(IccScaledMisalignedImu.ImuParameters): def __init__(self, imuConfig): IccScaledMisalignedImu.ImuParameters.__init__(self, imuConfig) self.data = imuConfig.data self.data["model"] = "scale-misalignment-size-effect" def printDetails(self, dest=sys.stdout): IccScaledMisalignedImu.ImuParameters.printDetails(self, dest) print >> dest, " rx_i [m]:" print >> dest, self.formatIndented(" ", \ np.array(self.data["accelerometers"]["rx_i"])) print >> dest, " ry_i [m]:" print >> dest, self.formatIndented(" ", \ np.array(self.data["accelerometers"]["ry_i"])) print >> dest, " rz_i [m]:" print >> dest, self.formatIndented(" ", \ np.array(self.data["accelerometers"]["rz_i"])) def setAccelerometerLeverArms(self, rx_i, ry_i, rz_i): self.data["accelerometers"]["rx_i"] = rx_i.tolist() self.data["accelerometers"]["ry_i"] = ry_i.tolist() self.data["accelerometers"]["rz_i"] = rz_i.tolist() def updateImuConfig(self): IccScaledMisalignedImu.updateImuConfig(self) self.imuConfig.setAccelerometerLeverArms(self.rx_i_Dv.toEuclidean(), \ self.ry_i_Dv.toEuclidean(), \ self.rz_i_Dv.toEuclidean()) def addDesignVariables(self, problem): IccScaledMisalignedImu.addDesignVariables(self, problem) self.rx_i_Dv = aopt.EuclideanPointDv(np.array([0., 0., 0.])) problem.addDesignVariable(self.rx_i_Dv, ic.HELPER_GROUP_ID) self.rx_i_Dv.setActive(False) self.ry_i_Dv = aopt.EuclideanPointDv(np.array([0., 0., 0.])) problem.addDesignVariable(self.ry_i_Dv, ic.HELPER_GROUP_ID) self.ry_i_Dv.setActive(True) self.rz_i_Dv = aopt.EuclideanPointDv(np.array([0., 0., 0.])) problem.addDesignVariable(self.rz_i_Dv, ic.HELPER_GROUP_ID) self.rz_i_Dv.setActive(True) self.Ix_Dv = aopt.MatrixBasicDv(np.diag([1.,0.,0.]), np.zeros((3,3),dtype=int)) problem.addDesignVariable(self.Ix_Dv, ic.HELPER_GROUP_ID) self.Ix_Dv.setActive(False) self.Iy_Dv = aopt.MatrixBasicDv(np.diag([0.,1.,0.]), np.zeros((3,3),dtype=int)) problem.addDesignVariable(self.Iy_Dv, ic.HELPER_GROUP_ID) self.Iy_Dv.setActive(False) self.Iz_Dv = aopt.MatrixBasicDv(np.diag([0.,0.,1.]), np.zeros((3,3),dtype=int)) problem.addDesignVariable(self.Iz_Dv, ic.HELPER_GROUP_ID) self.Iz_Dv.setActive(False) def addAccelerometerErrorTerms(self, problem, poseSplineDv, g_w, mSigma=0.0, \ accelNoiseScale=1.0): print print "Adding accelerometer error terms ({0})".format(self.dataset.topic) #progress bar iProgress = sm.Progress2( len(self.imuData) ) iProgress.sample() # AccelerometerError(measurement, invR, C_b_w, acceleration_w, bias, g_w) weight = 1.0/accelNoiseScale accelErrors = [] num_skipped = 0 if mSigma > 0.0: mest = aopt.HuberMEstimator(mSigma) else: mest = aopt.NoMEstimator() for im in self.imuData: tk = im.stamp.toSec() + self.timeOffset if tk > poseSplineDv.spline().t_min() and tk < poseSplineDv.spline().t_max(): C_b_w = poseSplineDv.orientation(tk).inverse() a_w = poseSplineDv.linearAcceleration(tk) b_i = self.accelBiasDv.toEuclideanExpression(tk,0) M = self.M_accel_Dv.toExpression() w_b = poseSplineDv.angularVelocityBodyFrame(tk) w_dot_b = poseSplineDv.angularAccelerationBodyFrame(tk) C_i_b = self.q_i_b_Dv.toExpression() rx_b = self.r_b_Dv.toExpression() + C_i_b.inverse() * self.rx_i_Dv.toExpression() ry_b = self.r_b_Dv.toExpression() + C_i_b.inverse() * self.ry_i_Dv.toExpression() rz_b = self.r_b_Dv.toExpression() + C_i_b.inverse() * self.rz_i_Dv.toExpression() Ix = self.Ix_Dv.toExpression() Iy = self.Iy_Dv.toExpression() Iz = self.Iz_Dv.toExpression() a = M * (C_i_b * (C_b_w * (a_w - g_w)) + \ Ix * (C_i_b * (w_dot_b.cross(rx_b) + w_b.cross(w_b.cross(rx_b)))) + \ Iy * (C_i_b * (w_dot_b.cross(ry_b) + w_b.cross(w_b.cross(ry_b)))) + \ Iz * (C_i_b * (w_dot_b.cross(rz_b) + w_b.cross(w_b.cross(rz_b)))) ) aerr = ket.EuclideanError(im.alpha, im.alphaInvR * weight, a + b_i) aerr.setMEstimatorPolicy(mest) accelErrors.append(aerr) problem.addErrorTerm(aerr) else: num_skipped = num_skipped + 1 #update progress bar iProgress.sample() print "\r Added {0} of {1} accelerometer error terms (skipped {2} out-of-bounds measurements)".format( len(self.imuData)-num_skipped, len(self.imuData), num_skipped ) self.accelErrors = accelErrors
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module3/itcc_test.py
jdahhan/Stem-Away-group-5
1
146337
import unittest from itcc import ITCC import pandas as pd class TestITCC(unittest.TestCase): def test_itcc_ingest(self): i = ITCC() df = i.get_path_matrix() self.assertEqual(type(df), pd.DataFrame) print(df.describe()) print("=" * 80) def test_getCXY(self): i = ITCC() df = i.getCXY() print(df.head()) print(f"Shape: {df.shape}") print("=" * 80) def test_generate_artifact(self): i = ITCC() druggene_mappings = pd.read_csv( "/Users/mtaruno/Documents/DevZone/Stem-Away-group-5/data/artifacts/druggene_mappings.csv", index_col=0, ) path_mappings = pd.read_csv( "/Users/mtaruno/Documents/DevZone/Stem-Away-group-5/data/artifacts/path_mappings.csv", index_col=0, ) df = i.generate_artifact( druggene_mappings=druggene_mappings, path_mappings=path_mappings ) print(df.head()) df.to_csv( "/Users/mtaruno/Documents/DevZone/Stem-Away-group-5/data/artifacts/ebc_artifact.csv" ) print("=" * 80) unittest.main()
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mechlib/amech_io/parser/models.py
kevinmooreiii/mechdriver
1
71824
""" Parses the `models.dat` input file for MechDriver that specifies all of the parameters used to construct the partition functions and master equations for the calculation of rate constants and thermochemistry. """ import automol import ioformat from mechanalyzer.inf import thy as tinfo from mechlib.amech_io.parser._keywrd import defaults_with_dcts # DCTS MODKIN_REQ_LST = ('pressures', 'rate_temps', 'thermo_temps') MODKIN_VAL_DCT = { 'pressures': ((tuple,), (), None), 'rate_temps': ((tuple,), (), None), 'thermo_temps': ((tuple,), (), None), 'temp_unit': ((str,), (), 'K'), 'pressure_unit': ((str,), (), 'atm'), 'rate_fit': { 'fit_method': ((str,), ('arrhenius', 'chebyshev'), 'arrhenius'), 'pdep_temps': (((tuple,),), (), (500, 100)), 'pdep_tol': ((float,), (), 20.0), 'pdep_pval': ((float,), (), 1.0), 'pdep_low': ((float,), (), None), 'pdep_high': ((float,), (), None), 'arrfit_dbltol': ((float,), (), 15.0), 'arrfit_dblcheck': ((str,), ('max', 'avg'), 'max'), 'troefit_params': ((tuple,), (), ('ts1', 'ts2', 'ts3', 'alpha')), 'chebfit_tdeg': (int, (), 6), 'chebfit_pdeg': (int, (), 4), 'chebfit_tol': ((float,), (), 20.0) }, 'thermo_fit': { 'ref_scheme': ((str,), ('basic', 'cbh0'), 'basic'), 'ref_enes': ((str,), ('ANL0',), 'ANL0') }, 'glob_etransfer': { 'lj': (None, (), 'estimate'), 'edown': (None, (), 'estimate'), 'mass': ((tuple,), (), None) } } MODPF_REQ_LST = ('pressures', 'rate_temps', 'thermo_temps') MODPF_VAL_DCT = { 'ene': { 'lvl1': ((tuple,), (), None), 'lvl2': ((tuple,), (), None) }, 'rot': { 'mod': ((str,), ('rigid', 'vpt2'), 'rigid'), 'vpt2lvl': ((str,), (), None) }, 'vib': { 'mod': ((str,), ('harm', 'vpt2', 'tau'), 'harm'), 'geolvl': ((str,), (), None), 'vpt2lvl': ((str,), (), None), }, 'tors': { 'mod': ( (str,), ('rigid', '1dhr', '1dhrf', '1dhrfa', 'mdhr', 'mdhrv', 'tau'), 'rigid'), 'enelvl': ((str,), (), None), 'geolvl': ((str,), (), None), }, 'symm': { 'mod': ((str,), ('none', 'sampling', '1dhr'), 'none'), 'geolvl': ((str,), (), None), }, 'rpath': { 'enelvl': ((str,), (), None), 'geolvl': ((str,), (), None), }, 'ts': { 'nobar': ((str,), ('pst', 'rpvtst', 'vrctst'), 'pst'), 'sadpt': ((str,), ('fixed', 'pst', 'rpvtst', 'vrctst'), 'fixed'), 'rwells': ((str,), ('fake', 'find', 'none'), 'fake'), 'pwells': ((str,), ('fake', 'find', 'none'), 'fake'), 'tunnel': ((str,), ('none', 'eckart', 'sct'), 'eckart'), 'etrans': ((str,), ('none', 'estimate', 'read'), 'estimate') } } # Build Basic Objects def models_dictionary(mod_str, thy_dct): """ Parse the models.dat file string and construct the corresponding model dictionaries that are used by other parts of the code. :param mod_str: models.dat input file string :type mod_str: str :param thy_dct: :type: dict[str:dict[str:str/float]] """ # Format the models input to the kin and spc model dcts kin_blocks = ioformat.ptt.named_end_blocks( mod_str, 'kin', footer='kin') spc_blocks = ioformat.ptt.named_end_blocks( mod_str, 'spc', footer='spc') kin_mod_dct = automol.util.dict_.merge_subdct( ioformat.ptt.keyword_dcts_from_blocks(kin_blocks), keep_subdct=True) spc_mod_dct = automol.util.dict_.merge_subdct( ioformat.ptt.keyword_dcts_from_blocks(spc_blocks), keep_subdct=True) # Add defaults, check key-vals, and format each model dicts for mod, dct in kin_mod_dct.items(): if dct: # if statement for empty global dcts from above fxn kin_mod_dct[mod] = _kin_model_build(dct) for mod, dct in spc_mod_dct.items(): if dct: # if statement for empty global dcts from above fxn spc_mod_dct[mod] = _spc_model_build(dct, thy_dct) return kin_mod_dct, spc_mod_dct # Convert objects def _spc_model_build(spc_model_dct_i, thy_dct): """ Set the PF model list based on the input Combine with es {'vib': {'model': '', 'geolvl_info': (), ...}} Take all of the spc model dcts or just one? """ # Expand the wells keyword if it has been set if 'wells' in spc_model_dct_i['ts']: spc_model_dct_i['ts']['rwells'] = spc_model_dct_i['ts']['wells'] spc_model_dct_i['ts']['pwells'] = spc_model_dct_i['ts']['wells'] spc_model_dct_i['ts'].pop('wells') # Set the defaults for the dct new_dct = automol.util.dict_.right_update( defaults_with_dcts(MODPF_VAL_DCT), spc_model_dct_i) # Have to check the dictionary to see if levels # in mod are in thy dct or it breaks # Format the keys that are thy levels into info objects for later use def _format_lvl(lvl_val): """ format weird energy calls """ if isinstance(lvl_val, str): val_inf = (1.00, tinfo.from_dct(thy_dct.get(lvl_val))) else: val_inf = (lvl_val[0], tinfo.from_dct(thy_dct.get(lvl_val))) return val_inf new_dct2 = {} for key1, val1 in new_dct.items(): _new_dct = {} for key2, val2 in val1.items(): if 'lvl' in key2 and val2 is not None: thy_info = _format_lvl(val2) _new_dct[key2] = (val2, thy_info) else: _new_dct[key2] = val2 new_dct2[key1] = _new_dct return new_dct2 def _kin_model_build(kin_mod_dct_i): """ set kin """ # Set defaults new_kin_dct = automol.util.dict_.right_update( defaults_with_dcts(MODKIN_VAL_DCT), kin_mod_dct_i) # Check for correct input # Repartition ratefit key word into dcts for `ratefit` code old_ratefit = new_kin_dct['rate_fit'] new_ratefit = {} for key, val in old_ratefit.items(): if not any(x in key for x in ('pdep', 'arr', 'cheb', 'troe')): new_ratefit[key] = val new_ratefit.update({ 'pdep_fit': {key.replace('pdep_', ''): val for key, val in old_ratefit.items() if 'pdep' in key}, 'arrfit_fit': {key.replace('arrfit_', ''): val for key, val in old_ratefit.items() if 'arrfit' in key}, 'chebfit_fit': {key.replace('chebfit_', ''): val for key, val in old_ratefit.items() if 'chebfit' in key}, 'troefit_fit': {key.replace('troefit_', ''): val for key, val in old_ratefit.items() if 'troefit' in key} }) new_kin_dct.update({'rate_fit': new_ratefit}) return new_kin_dct # Handle model tasks def extract_models(tsk): """ pull modesl from tasks """ key_dct = tsk[-1] pes_mod = key_dct['kin_model'] spc_mods = tuple(key_dct[key] for key in key_dct.keys() if 'spc_mod' in key) return spc_mods, pes_mod def split_model(mod): """ Take a model given by a set of operations and split it into a set of models and operators model = 3*pf1-pf2 -> model = (models, coefs, operators) model = ((pf1, pf2), (3, 1), (multiple, subtract)) """ # Dictionary to map symbols to strings used later in the code op_dct = {'*': 'multiply', '+': 'add', '/': 'divide', '-': 'substract'} # Break the down the model string into # constituent models, coefficients, and operators coeffs, operators, models = [], [], [] coeff, model = '', '' for char in mod: if char == '.' or char.isdigit(): coeff += char elif char.isalpha(): model += char elif char in op_dct: operators.append(op_dct[char]) if coeff: coeffs.append(float(coeff)) else: coeffs.append(1.0) models.append(model) coeff = '' model = '' if coeff: coeffs.append(float(coeff)) else: coeffs.append(1.0) models.append(model) return (tuple(models), tuple(coeffs), tuple(operators)) # def get_model(comp, spc_mod_dct_i): # """ get model for spc dct compoenent # """ # return spc_mod_dct_i[comp]['mod'] # def thy_method_name(mod_lvl): # """ get the electronic strucure method # """ # return mod_lvl[0] # ? # def thy_info_coeff(mod_lvl): # """ get the coefficient from the model # """ # return mod_lvl[1][0] # def thy_info_obj(mod_lvl): # """ get the name of the mod lvl # """ # return mod_lvl[1][1]
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utils/csv_response_.py
baixuexue123/djmo
1
107926
<filename>utils/csv_response_.py<gh_stars>1-10 # -*- coding: utf-8 -*- from __future__ import unicode_literals, absolute_import import csv import codecs import cStringIO from django.http import StreamingHttpResponse from django.views.generic import View """ 流式响应StreamingHttpResponse可以快速,节省内存地产生一个大型文件 """ class Echo(object): """An object that implements just the write method of the file-like interface.""" def write(self, value): """Write the value by returning it, instead of storing in a buffer.""" return value class UnicodeWriter(object): """ A CSV writer which will write rows to CSV file "f", which is encoded in the given encoding. """ def __init__(self, f, dialect=csv.excel, encoding='utf-8', **kwargs): # Redirect output to a queue self.queue = cStringIO.StringIO() self.writer = csv.writer(self.queue, dialect=dialect, **kwargs) self.stream = f self.encoder = codecs.getincrementalencoder(encoding)() def writerow(self, row): self.writer.writerow([handle_column(s) for s in row]) # Fetch UTF-8 output from the queue ... data = self.queue.getvalue() data = data.decode("utf-8") # ... and reencode it into the target encoding data = self.encoder.encode(data) # write to the target stream value = self.stream.write(data) # empty queue self.queue.truncate(0) return value def writerows(self, rows): for row in rows: self.writerow(row) class ExampleView(View): headers = ('一些', '表头') def get(self, request): result = ( ('第一行', '数据1'), ('第二行', '数据2') ) echoer = Echo() writer = UnicodeWriter(echoer) def csv_iterator(): yield codecs.BOM_UTF8 yield writer.writerow(self.headers) for column in result: yield writer.writerow(column) response = StreamingHttpResponse( (row for row in csv_iterator()), content_type="text/csv;charset=utf-8" ) response['Content-Disposition'] = 'attachment;filename="example.csv"' return response
[ 1, 529, 9507, 29958, 13239, 29914, 7638, 29918, 5327, 5396, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 3166, 4770, 29888, 9130, 1649, 1053, 29104, 29918, 20889, 1338, 29892, 8380, 29918, 5215, 13, 5215, 11799, 13, 5215, 775, 2395, 13, 5215, 274, 1231, 5971, 13, 13, 3166, 9557, 29889, 1124, 1053, 13763, 292, 5506, 5103, 13, 3166, 9557, 29889, 7406, 29889, 19206, 1053, 4533, 13, 13, 13, 15945, 29908, 13, 31151, 30607, 232, 150, 144, 31370, 3835, 292, 5506, 5103, 30682, 30651, 232, 194, 174, 31859, 29892, 31669, 31600, 30728, 30946, 30533, 231, 189, 170, 30486, 30287, 30502, 30257, 30883, 30333, 30631, 13, 15945, 29908, 13, 13, 13, 1990, 382, 1859, 29898, 3318, 1125, 13, 1678, 9995, 2744, 1203, 393, 10703, 925, 278, 2436, 1158, 310, 278, 934, 29899, 4561, 5067, 1213, 15945, 13, 1678, 822, 2436, 29898, 1311, 29892, 995, 1125, 13, 4706, 9995, 6113, 278, 995, 491, 7863, 372, 29892, 2012, 310, 15446, 297, 263, 6835, 1213, 15945, 13, 4706, 736, 995, 13, 13, 13, 1990, 23862, 10507, 29898, 3318, 1125, 13, 13, 1678, 9995, 13, 1678, 319, 16874, 9227, 607, 674, 2436, 4206, 304, 16874, 934, 376, 29888, 613, 13, 1678, 607, 338, 18511, 297, 278, 2183, 8025, 29889, 13, 1678, 9995, 13, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 285, 29892, 23725, 29922, 7638, 29889, 24633, 29892, 8025, 2433, 9420, 29899, 29947, 742, 3579, 19290, 1125, 13, 4706, 396, 4367, 1088, 1962, 304, 263, 9521, 13, 4706, 1583, 29889, 9990, 353, 274, 1231, 5971, 29889, 1231, 5971, 580, 13, 4706, 1583, 29889, 13236, 353, 11799, 29889, 13236, 29898, 1311, 29889, 9990, 29892, 23725, 29922, 15321, 781, 29892, 3579, 19290, 29897, 13, 4706, 1583, 29889, 5461, 353, 285, 13, 4706, 1583, 29889, 3977, 6119, 353, 775, 2395, 29889, 657, 25629, 284, 3977, 6119, 29898, 22331, 29897, 580, 13, 13, 1678, 822, 9227, 340, 29898, 1311, 29892, 1948, 1125, 13, 4706, 1583, 29889, 13236, 29889, 13236, 340, 4197, 8411, 29918, 4914, 29898, 29879, 29897, 363, 269, 297, 1948, 2314, 13, 4706, 396, 383, 3486, 18351, 29899, 29947, 1962, 515, 278, 9521, 2023, 13, 4706, 848, 353, 1583, 29889, 9990, 29889, 657, 1767, 580, 13, 4706, 848, 353, 848, 29889, 13808, 703, 9420, 29899, 29947, 1159, 13, 4706, 396, 2023, 322, 337, 12508, 372, 964, 278, 3646, 8025, 13, 4706, 848, 353, 1583, 29889, 3977, 6119, 29889, 12508, 29898, 1272, 29897, 13, 4706, 396, 2436, 304, 278, 3646, 4840, 13, 4706, 995, 353, 1583, 29889, 5461, 29889, 3539, 29898, 1272, 29897, 13, 4706, 396, 4069, 9521, 13, 4706, 1583, 29889, 9990, 29889, 509, 4661, 403, 29898, 29900, 29897, 13, 4706, 736, 995, 13, 13, 1678, 822, 9227, 1242, 29898, 1311, 29892, 4206, 1125, 13, 4706, 363, 1948, 297, 4206, 29901, 13, 9651, 1583, 29889, 13236, 340, 29898, 798, 29897, 13, 13, 13, 1990, 8741, 1043, 29898, 1043, 1125, 13, 13, 1678, 9066, 353, 6702, 30287, 31959, 742, 525, 30746, 31584, 1495, 13, 13, 1678, 822, 679, 29898, 1311, 29892, 2009, 1125, 13, 4706, 1121, 353, 313, 13, 9651, 6702, 30622, 30287, 30448, 742, 525, 30354, 30763, 29896, 5477, 13, 9651, 6702, 30622, 30685, 30448, 742, 525, 30354, 30763, 29906, 1495, 13, 4706, 1723, 13, 4706, 2916, 261, 353, 382, 1859, 580, 13, 4706, 9227, 353, 23862, 10507, 29898, 8057, 261, 29897, 13, 13, 4706, 822, 11799, 29918, 17609, 7295, 13, 18884, 7709, 775, 2395, 29889, 29933, 6488, 29918, 10496, 29947, 13, 18884, 7709, 9227, 29889, 13236, 340, 29898, 1311, 29889, 13662, 29897, 13, 18884, 363, 1897, 297, 1121, 29901, 13, 462, 1678, 7709, 9227, 29889, 13236, 340, 29898, 4914, 29897, 13, 13, 4706, 2933, 353, 13763, 292, 5506, 5103, 29898, 13, 18884, 313, 798, 363, 1948, 297, 11799, 29918, 17609, 25739, 13, 18884, 2793, 29918, 1853, 543, 726, 29914, 7638, 29936, 3090, 842, 29922, 9420, 29899, 29947, 29908, 13, 4706, 1723, 13, 4706, 2933, 1839, 3916, 29899, 4205, 3283, 2033, 353, 525, 14930, 358, 29936, 9507, 543, 4773, 29889, 7638, 29908, 29915, 13, 4706, 736, 2933, 13, 2 ]
Scripts/TypeRig GUI/Panel/Metrics.py
twardoch/TypeRig
1
67479
<reponame>twardoch/TypeRig<gh_stars>1-10 #FLM: Glyph: Metrics # ---------------------------------------- # (C) <NAME>, 2018 (http://www.kateliev.com) # (C) Karandash Type Foundry (http://www.karandash.eu) #----------------------------------------- # No warranties. By using this you agree # that you use it at your own risk! # - Init global pLayers global pMode pLayers = None pMode = 0 app_name, app_version = 'TypeRig | Metrics', '0.22' # - Dependencies ----------------- import fontlab as fl6 import fontgate as fgt from PythonQt import QtCore from typerig import QtGui from typerig.glyph import eGlyph from typerig.gui import getProcessGlyphs # - Sub widgets ------------------------ class MLineEdit(QtGui.QLineEdit): # - Custom QLine Edit extending the contextual menu with FL6 metric expressions def __init__(self, *args, **kwargs): super(MLineEdit, self).__init__(*args, **kwargs) self.setContextMenuPolicy(QtCore.Qt.CustomContextMenu) self.customContextMenuRequested.connect(self.__contextMenu) def __contextMenu(self): self._normalMenu = self.createStandardContextMenu() self._addCustomMenuItems(self._normalMenu) self._normalMenu.exec_(QtGui.QCursor.pos()) def _addCustomMenuItems(self, menu): menu.addSeparator() menu.addAction(u'EQ', lambda: self.setText('=%s' %self.text)) menu.addAction(u'LSB', lambda: self.setText('=lsb("%s")' %self.text)) menu.addAction(u'RSB', lambda: self.setText('=rsb("%s")' %self.text)) menu.addAction(u'ADV', lambda: self.setText('=width("%s")' %self.text)) menu.addAction(u'L', lambda: self.setText('=l("%s")' %self.text)) menu.addAction(u'R', lambda: self.setText('=r("%s")' %self.text)) menu.addAction(u'W', lambda: self.setText('=w("%s")' %self.text)) menu.addAction(u'G', lambda: self.setText('=g("%s")' %self.text)) class metrics_adjust(QtGui.QGridLayout): # - Copy Metric properties from other glyph def __init__(self): super(metrics_adjust, self).__init__() # - Spin Boxes self.spb_lsb_percent = QtGui.QSpinBox() self.spb_adv_percent = QtGui.QSpinBox() self.spb_rsb_percent = QtGui.QSpinBox() self.spb_lsb_units = QtGui.QSpinBox() self.spb_adv_units = QtGui.QSpinBox() self.spb_rsb_units = QtGui.QSpinBox() self.spb_lsb_percent.setMaximum(200) self.spb_adv_percent.setMaximum(200) self.spb_rsb_percent.setMaximum(200) self.spb_lsb_units.setMaximum(200) self.spb_adv_units.setMaximum(200) self.spb_rsb_units.setMaximum(200) self.spb_lsb_units.setMinimum(-200) self.spb_adv_units.setMinimum(-200) self.spb_rsb_units.setMinimum(-200) self.spb_lsb_percent.setSuffix('%') self.spb_adv_percent.setSuffix('%') self.spb_rsb_percent.setSuffix('%') self.spb_lsb_units.setSuffix(' u') self.spb_adv_units.setSuffix(' u') self.spb_rsb_units.setSuffix(' u') self.resetSpinBox() # - Buttons self.btn_adjMetrics = QtGui.QPushButton('&Adjust Metrics') self.btn_resetSpinBox = QtGui.QPushButton('&Reset') self.btn_adjMetrics.clicked.connect(self.adjMetrics) self.btn_resetSpinBox.clicked.connect(self.resetSpinBox) self.addWidget(QtGui.QLabel('LSB adjust:'), 0, 0, 1, 1) self.addWidget(QtGui.QLabel('RSB adjust:'), 0, 1, 1, 1) self.addWidget(QtGui.QLabel('ADV adjust:'), 0, 2, 1, 1) self.addWidget(self.spb_lsb_percent, 1, 0, 1, 1) self.addWidget(self.spb_rsb_percent, 1, 1, 1, 1) self.addWidget(self.spb_adv_percent, 1, 2, 1, 1) self.addWidget(self.spb_lsb_units, 2, 0, 1, 1) self.addWidget(self.spb_rsb_units, 2, 1, 1, 1) self.addWidget(self.spb_adv_units, 2, 2, 1, 1) self.addWidget(self.btn_resetSpinBox, 3, 0, 1, 1) self.addWidget(self.btn_adjMetrics, 3, 1, 1, 2) def resetSpinBox(self): # - Reset spin-box values self.spb_lsb_percent.setValue(100) self.spb_adv_percent.setValue(100) self.spb_rsb_percent.setValue(100) self.spb_lsb_units.setValue(0) self.spb_adv_units.setValue(0) self.spb_rsb_units.setValue(0) def adjMetrics(self): process_glyphs = getProcessGlyphs(pMode) for glyph in process_glyphs: wLayers = glyph._prepareLayers(pLayers) copyOrder = [False]*3 srcGlyphs = [glyph.name]*3 adjPercents = (self.spb_lsb_percent.value, self.spb_rsb_percent.value, self.spb_adv_percent.value) adjUnits = (self.spb_lsb_units.value, self.spb_rsb_units.value, self.spb_adv_units.value) for layer in wLayers: glyph.setLSB(glyph.getLSB(layer)*adjPercents[0]/100 + adjUnits[0], layer) glyph.setRSB(glyph.getRSB(layer)*adjPercents[1]/100 + adjUnits[1], layer) glyph.setAdvance(glyph.getAdvance(layer)*adjPercents[2]/100 + adjUnits[2], layer) glyph.updateObject(glyph.fl, 'Adjust Metrics @ %s | %s' %('; '.join(wLayers), zip(('LSB','RSB','ADV'), adjPercents, adjUnits))) glyph.update() class metrics_copy(QtGui.QGridLayout): # - Copy Metric properties from other glyph def __init__(self): super(metrics_copy, self).__init__() # - Edit Fields self.edt_lsb = QtGui.QLineEdit() self.edt_adv = QtGui.QLineEdit() self.edt_rsb = QtGui.QLineEdit() self.edt_lsb.setPlaceholderText('Glyph Name') self.edt_adv.setPlaceholderText('Glyph Name') self.edt_rsb.setPlaceholderText('Glyph Name') # - Spin Box self.spb_lsb_percent = QtGui.QSpinBox() self.spb_adv_percent = QtGui.QSpinBox() self.spb_rsb_percent = QtGui.QSpinBox() self.spb_lsb_units = QtGui.QSpinBox() self.spb_adv_units = QtGui.QSpinBox() self.spb_rsb_units = QtGui.QSpinBox() self.spb_lsb_percent.setMaximum(200) self.spb_adv_percent.setMaximum(200) self.spb_rsb_percent.setMaximum(200) self.spb_lsb_units.setMaximum(200) self.spb_adv_units.setMaximum(200) self.spb_rsb_units.setMaximum(200) self.spb_lsb_units.setMinimum(-200) self.spb_adv_units.setMinimum(-200) self.spb_rsb_units.setMinimum(-200) self.spb_lsb_percent.setSuffix('%') self.spb_adv_percent.setSuffix('%') self.spb_rsb_percent.setSuffix('%') self.spb_lsb_units.setSuffix(' u') self.spb_adv_units.setSuffix(' u') self.spb_rsb_units.setSuffix(' u') self.spb_lsb_percent.setMaximumWidth(50) self.spb_adv_percent.setMaximumWidth(50) self.spb_rsb_percent.setMaximumWidth(50) self.spb_lsb_units.setMaximumWidth(50) self.spb_adv_units.setMaximumWidth(50) self.spb_rsb_units.setMaximumWidth(50) self.reset_fileds() # - Buttons self.btn_copyMetrics = QtGui.QPushButton('&Copy Metrics') self.btn_copyMetrics.clicked.connect(self.copyMetrics) # - Build self.addWidget(QtGui.QLabel('LSB:'), 0, 0, 1, 1) self.addWidget(self.edt_lsb, 0, 1, 1, 3) self.addWidget(QtGui.QLabel('@'), 0, 4, 1, 1) self.addWidget(self.spb_lsb_percent, 0, 5, 1, 1) self.addWidget(QtGui.QLabel('+'), 0, 6, 1, 1) self.addWidget(self.spb_lsb_units, 0, 7, 1, 1) self.addWidget(QtGui.QLabel('RSB:'), 1, 0, 1, 1) self.addWidget(self.edt_rsb, 1, 1, 1, 3) self.addWidget(QtGui.QLabel('@'), 1, 4, 1, 1) self.addWidget(self.spb_rsb_percent, 1, 5, 1, 1) self.addWidget(QtGui.QLabel('+'), 1, 6, 1, 1) self.addWidget(self.spb_rsb_units, 1, 7, 1, 1) self.addWidget(QtGui.QLabel('ADV:'), 2, 0, 1, 1) self.addWidget(self.edt_adv, 2, 1, 1, 3) self.addWidget(QtGui.QLabel('@'), 2, 4, 1, 1) self.addWidget(self.spb_adv_percent, 2, 5, 1, 1) self.addWidget(QtGui.QLabel('+'), 2, 6, 1, 1) self.addWidget(self.spb_adv_units, 2, 7, 1, 1) self.addWidget(self.btn_copyMetrics, 3, 1, 1, 8) def reset_fileds(self): # - Reset text fields self.edt_lsb.setText('') self.edt_adv.setText('') self.edt_rsb.setText('') # - Reset spin-box self.spb_lsb_percent.setValue(100) self.spb_adv_percent.setValue(100) self.spb_rsb_percent.setValue(100) self.spb_lsb_units.setValue(0) self.spb_adv_units.setValue(0) self.spb_rsb_units.setValue(0) def copyMetrics(self): process_glyphs = getProcessGlyphs(pMode) for glyph in process_glyphs: copyOrder = ['--' in name for name in (self.edt_lsb.text, self.edt_rsb.text, self.edt_adv.text)] srcGlyphs = [str(name).replace('--', '') if len(name) else None for name in (self.edt_lsb.text, self.edt_rsb.text, self.edt_adv.text)] adjPercents = (self.spb_lsb_percent.value, self.spb_rsb_percent.value, self.spb_adv_percent.value) adjUnits = (self.spb_lsb_units.value, self.spb_rsb_units.value, self.spb_adv_units.value) glyph.copyMetricsbyName(srcGlyphs, pLayers, copyOrder, adjPercents, adjUnits) glyph.updateObject(glyph.fl, 'Copy Metrics | LSB: %s; RSB: %s; ADV:%s.' %(srcGlyphs[0], srcGlyphs[1], srcGlyphs[2])) glyph.update() self.reset_fileds() class metrics_expr(QtGui.QGridLayout): # - Copy Metric properties from other glyph def __init__(self): super(metrics_expr, self).__init__() self.edt_lsb = MLineEdit() self.edt_adv = MLineEdit() self.edt_rsb = MLineEdit() self.edt_lsb.setPlaceholderText('Metric expression') self.edt_adv.setPlaceholderText('Metric expression') self.edt_rsb.setPlaceholderText('Metric expression') self.btn_setMetrics = QtGui.QPushButton('&Set expressions') self.btn_getShapeParent = QtGui.QPushButton('&Get reference') self.btn_delMetrics = QtGui.QPushButton('&Unlink') self.btn_autoBind = QtGui.QPushButton('&Auto bind Metric expressions') self.btn_autoBind.setToolTip('Automatically bind metric expressions from available element references.') self.btn_setMetrics.clicked.connect(lambda: self.setMetricEquations(False)) self.btn_delMetrics.clicked.connect(lambda: self.setMetricEquations(True)) self.btn_getShapeParent.clicked.connect(self.bindShapeParent) self.btn_autoBind.clicked.connect(self.autoMetricEquations) self.spb_shapeIndex = QtGui.QSpinBox() self.addWidget(QtGui.QLabel('LSB:'), 0, 0, 1, 1) self.addWidget(self.edt_lsb, 0, 1, 1, 5) self.addWidget(QtGui.QLabel('RSB:'), 1, 0, 1, 1) self.addWidget(self.edt_rsb, 1, 1, 1, 5) self.addWidget(QtGui.QLabel('ADV:'), 2, 0, 1, 1) self.addWidget(self.edt_adv, 2, 1, 1, 5) self.addWidget(self.btn_setMetrics, 3, 1, 1, 3) self.addWidget(self.btn_delMetrics, 3, 4, 1, 2) self.addWidget(QtGui.QLabel('E:'), 4, 0, 1, 1) self.addWidget(self.btn_getShapeParent, 4, 1, 1, 3) self.addWidget(self.spb_shapeIndex, 4, 4, 1, 2) self.addWidget(QtGui.QLabel('Composite Glyph: Metric expressions'), 5, 0, 1, 5) self.addWidget(self.btn_autoBind, 6, 0, 1, 6) self.setColumnStretch(0, 0) self.setColumnStretch(1, 5) def reset_fileds(self): self.edt_lsb.clear() self.edt_adv.clear() self.edt_rsb.clear() def bindShapeParent(self): glyph = eGlyph() layer = None # Static! Make it smart, so it detects on all layers, dough unnecessary shapeIndex = self.spb_shapeIndex.value # Static! Make it smart, so it detects... namedShapes = [shape for shape in glyph.shapes() + glyph.components() if len(shape.shapeData.name)] try: wShape = namedShapes[shapeIndex] transform = wShape.transform if len(wShape.shapeData.name): if transform.m11() > 0: self.edt_lsb.setText('=%s' %wShape.shapeData.name) self.edt_rsb.setText('=%s' %wShape.shapeData.name) else: self.edt_lsb.setText('=rsb("%s")' %wShape.shapeData.name) self.edt_rsb.setText('=lsb("%s")' %wShape.shapeData.name) except IndexError: print 'ERROR: Glyph /%s - No NAMED SHAPE with INDEX [%s] found!' %(glyph.name, shapeIndex) def setMetricEquations(self, clear=False): process_glyphs = getProcessGlyphs(pMode) for glyph in process_glyphs: wLayers = glyph._prepareLayers(pLayers) for layer in wLayers: if not clear: if len(self.edt_lsb.text): glyph.setLSBeq(self.edt_lsb.text, layer) if len(self.edt_rsb.text): glyph.setRSBeq(self.edt_rsb.text, layer) if len(self.edt_adv.text): glyph.setADVeq(self.edt_adv.text, layer) else: glyph.setLSBeq('', layer) glyph.setRSBeq('', layer) glyph.setADVeq('', layer) glyph.update() glyph.updateObject(glyph.fl, 'Set Metrics Equations @ %s.' %'; '.join(wLayers)) self.reset_fileds() def autoMetricEquations(self): process_glyphs = getProcessGlyphs(pMode) for glyph in process_glyphs: wLayers = glyph._prepareLayers(pLayers) glyph_stat = [] for layer in wLayers: status = glyph.bindCompMetrics(layer) glyph_stat.append(status) glyph.update() glyph.updateObject(glyph.fl, 'Glyph: %s;\tAuto Metrics Equations @ %s.' %(glyph.name, '; '.join('%s: %s' %item for item in zip(wLayers, glyph_stat)))) class metrics_font(QtGui.QGridLayout): # - Copy Metric properties from other glyph def __init__(self): super(metrics_font, self).__init__() self.btn_setAscender = QtGui.QPushButton('Asc.') self.btn_setCapsHeight = QtGui.QPushButton('Caps') self.btn_setDescender = QtGui.QPushButton('Desc.') self.btn_setXHeight = QtGui.QPushButton('X Hgt.') self.btn_togSelection = QtGui.QPushButton('Selection') self.btn_togBBOX = QtGui.QPushButton('Glyph BBOX') self.btn_togSelection.setCheckable(True) self.btn_togBBOX.setCheckable(True) #self.btn_togBBOX.setEnabled(False) self.btn_setAscender.setToolTip('Set Ascender height ') self.btn_setCapsHeight.setToolTip('Set Caps Height') self.btn_setDescender.setToolTip('Set Descender height') self.btn_setXHeight.setToolTip('Set X Height') self.btn_togSelection.setToolTip('Set Font metrics using the selected node') self.btn_togBBOX.setToolTip('Set Font metrics using the active glyph bounding box') self.btn_setAscender.setMinimumWidth(40) self.btn_setCapsHeight.setMinimumWidth(40) self.btn_setDescender.setMinimumWidth(40) self.btn_setXHeight.setMinimumWidth(40) self.btn_setAscender.clicked.connect(lambda: self.setFontMetrics('ascender')) self.btn_setCapsHeight.clicked.connect(lambda: self.setFontMetrics('capsHeight')) self.btn_setDescender .clicked.connect(lambda: self.setFontMetrics('descender')) self.btn_setXHeight.clicked.connect(lambda: self.setFontMetrics('xHeight')) self.addWidget(self.btn_togSelection, 0,0,1,2) self.addWidget(self.btn_togBBOX, 0,2,1,2) self.addWidget(self.btn_setAscender, 1,0,1,1) self.addWidget(self.btn_setCapsHeight, 1,1,1,1) self.addWidget(self.btn_setDescender, 1,2,1,1) self.addWidget(self.btn_setXHeight, 1,3,1,1) def setFontMetrics(self, metricName): glyph = eGlyph() wLayers = glyph._prepareLayers(pLayers) for layer in wLayers: if self.btn_togSelection.isChecked(): selection = glyph.selectedNodes(layer) if len(selection): glyph.package.setMaster(layer) exec('glyph.package.%s_value = selection[0].y' %metricName) if self.btn_togBBOX.isChecked(): glyph.package.setMaster(layer) bbox_layer = glyph.layer(layer).boundingBox if metricName in ['ascender', 'capsHeight', 'xHeight']: exec('glyph.package.%s_value = int(bbox_layer.y() + bbox_layer.height())' %metricName) elif metricName == 'descender': glyph.package.descender_value = int(bbox_layer.y()) self.btn_togSelection.setChecked(False) self.btn_togBBOX.setChecked(False) glyph.update() glyph.updateObject(glyph.package, 'Set Font Metrics: %s @ %s.' %(metricName, '; '.join(wLayers))) # - Tabs ------------------------------- class tool_tab(QtGui.QWidget): def __init__(self): super(tool_tab, self).__init__() # - Init layoutV = QtGui.QVBoxLayout() # - Build #layoutV.addWidget(QtGui.QLabel('Glyph: Adjust Metric data')) layoutV.addLayout(metrics_adjust()) layoutV.addSpacing(10) layoutV.addWidget(QtGui.QLabel('Glyph: Copy Metric data')) layoutV.addLayout(metrics_copy()) layoutV.addSpacing(10) layoutV.addWidget(QtGui.QLabel('Glyph: Set metric expressions')) layoutV.addLayout(metrics_expr()) layoutV.addSpacing(10) layoutV.addWidget(QtGui.QLabel('\nFont: Set Font Metrics')) layoutV.addLayout(metrics_font()) # - Build --------------------------- layoutV.addStretch() self.setLayout(layoutV) # - Test ---------------------- if __name__ == '__main__': test = tool_tab() test.setWindowTitle('%s %s' %(app_name, app_version)) test.setGeometry(300, 300, 280, 400) test.setWindowFlags(QtCore.Qt.WindowStaysOnTopHint) # Always on top!! test.show()
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application/create-application.py
superdiana/nexmo-python-code-snippets
0
95870
<filename>application/create-application.py #!/usr/bin/env python3 import nexmo from pprint import pprint client = nexmo.Client( key=NEXMO_API_KEY, secret=NEXMO_API_SECRET ) response = client.application_v2.create_application({ "name": "Code Example App", "capabilities": { "messages": { "webhooks": { "inbound_url": { "address": "https://example.com/webhooks/inbound", "http_method": "POST" }, "status_url": { "address": "https://example.com/webhooks/status", "http_method": "POST" } } } } }) pprint(response)
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python/ql/src/Classes/ConflictingAttributesInBaseClasses_Fixed.py
vadi2/codeql
4,036
172010
#Fixed by overriding. This does not change behavior, but makes it explicit and comprehensible. class ThreadingTCPServerOverriding(ThreadingMixIn, TCPServer): def process_request(self, request, client_address): #process_request forwards to do_work, so it is OK to call ThreadingMixIn.process_request directly ThreadingMixIn.process_request(self, request, client_address) #Fixed by separating threading functionality from request handling. class ThreadingMixIn: """Mix-in class to help with threads.""" def do_job_in_thread(self, job, args): """Start a new thread to do the job""" t = threading.Thread(target = job, args = args) t.start() class ThreadingTCPServerChangedHierarchy(ThreadingMixIn, TCPServer): def process_request(self, request, client_address): """Start a new thread to process the request.""" self.do_job_in_thread(self.do_work, (request, client_address))
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cogandmem/text.py
aemacdermid/cogandmem
0
44270
""" Functions for displaying text to the screen. Text rendering in pygame does not allow for line breaks. This can lead to issues when attempting to render text, particularly if one is unsure of the width and height of a to-be-rendered string in a given font. The functions here handle these difficulties. This module includes the following functions (see the docstrings for more information): tallest_letter: returns the height in pixels of the tallest letter when rendered in a given font. text_to_sentences: convert a string into a list of sentences. screen_dimensions: returns the dimensions of the active display surface. longest_string_to_render: return the string in a list that will take up the most horizontal space in pixels (this will usually, but not necessarily, be the string with the most characters). height_of_strings: return the height of a list of strings when rendered in a given font. wrap_text: break a string into lines on a screen. string_to_screens_and_lines: break a string into screens and lines. render_string: get pygame.Surface and pygame.Rect objects for a string. render_lines: return pygame.Surface and pygame.Rect objects for a list of strings. string_to_surface_and_rect: return pygame.Surface and pygame.Rect objects for a string, given constraints on the pixel dimensions of the screen. display_text_until_keypress: present text to the screen until the user presses a specific key (or any specific key from a list). ask_question: display a question to the screen and return the response. """ from __future__ import division import sys import pygame from pygame.locals import * from cogandmem import experiment from cogandmem import generic LETTERS = ( K_a, K_b, K_c, K_d, K_e, K_f, K_g, K_h, K_i, K_j, K_k, K_l, K_m, K_n, K_o, K_p, K_q, K_r, K_s, K_t, K_u, K_v, K_w, K_x, K_y, K_z ) ALPHABET = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" NUMBERS = ( K_0, K_1, K_2, K_3, K_4, K_5, K_6, K_7, K_8, K_9 ) PUNCTUATION = ( K_PERIOD, K_COMMA, K_QUESTION, K_QUOTE, K_EXCLAIM, K_COLON, K_SEMICOLON ) def tallest_letter(font): """ Get the height, in pixels, of the tallest letter in the alphabet when rendered with a given font. """ return font.size(ALPHABET)[1] def text_to_sentences(text, terminators = (".", "?", "!", '."', '?"', '!"'), exclude = ("Mr.", "Ms.", "Mrs.", "Dr.", "e.g.", "i.e.")): """ Break text into a list of sentences. This is a highly imperfect function that takes a passage of text and breaks it into a list of sentences. The main stumbling block for the function is that there are numerous words that could indicate either the end of a sentence or the end of an abbreviation. I do not know of an effective solution to this problem. NB: The assumption is made that line breaks always denote the end of a sentence, regardless of the preceding character. Parameters: text: the passage to break into sentences. Keyword Parameters: terminators: strings that denote the end of a sentence. exclude: exceptions to the terminators. Returns: sentences: a list of sentences in text. """ sentences = [] text_as_paragraphs = text.split("\n") paragraphs_as_words = [] for paragraph in text_as_paragraphs: paragraph = paragraph.strip() if not paragraph: # This is a blank line. paragraphs_as_words.append([]) # Go to the next paragraph: continue words = paragraph.split(" ") paragraphs_as_words.append(words) for paragraph in paragraphs_as_words: if not paragraph: # This is a blank line. sentences.append("") continue sentence = "" for word in paragraph: # Add word to sentence, along with a leading space if necessary: if sentence: sentence = sentence+" "+word else: sentence = word # Check whether word ends with a terminator: try: ends_with_terminator = word.endswith(terminators) except TypeError: # terminators is probably a list rather than a tuple. # str.endswith() requires a tuple. terminators = tuple(terminators) ends_with_terminator = word.endswith(terminators) if ends_with_terminator and word not in exclude: # This ends the sentence. sentences.append(sentence) sentence = "" # Check for a dangling sentence: if sentence: sentences.append(sentence) return sentences def screen_dimensions(): """ Get the width and height of the active display surface. If no display surface has been set, get the first element in pygame.display.list_modes(). """ screen_surface = pygame.display.get_surface() try: w, h = screen_surface.get_size() except AttributeError: w, h = pygame.display.list_modes()[0] return w, h def longest_string_to_render(strings, f): """ Get the longest string to render from a list. Parameters: strings: a list or tuple of strings. f: the pygame.font.Font object used for rendering. Returns: s: the longest string to render with f; if there is a tie, s is set to the string occurring earlier in the strings list. n: the number of pixel columns needed to render s. """ s = "" n = 0 for string in strings: # Get the width of string: w = f.size(string)[0] if w > n: n = w s = string return s, n def height_of_strings(strings, f, line_size): """ Compute the height of a list of strings when rendered with a given font, taking into account the line size (i.e., the number of pixel rows interpolated between the bottom of one line of text and the top of the next). Parameters: strings: the list of strings whose height is measured; assumes that each string is a separate line. f: the pygame.font.Font object in which text is to be rendered. line_size: the number of pixel rows between lines; must be positive. Returns: h: the height of strings when rendered. """ h = 0 # Ignore line_size gaps to start: for string in strings: # Get current height: line_height = f.size(string)[1] h = h+line_height # Line gaps are added now. h = h+line_size*(len(strings)-1) return h def wrap_text(new_text, width, f, old_text = [], start_new_line = False, return_height = False, line_height = None): """ Break a string into lines on a screen. Parameters: new_text: words to convert to lines; if list or tuple, each element is a list of words from a paragraph, with line breaks automatically following an element; if str, split() is used to make into paragraphs and then individual words; if new_text evaluates to False in a Boolean context, a blank line is returned width: maximum pixels per line (width > 0). f: the font object to use. Keyword Parameters: return_height: whether the height of the rendered lines is returned; defaults to False. old_text: optional list of lines to which new_text is added; each element in old_text is assumed to be a single line; its legality given width is not checked; defaults to an empty list. start_new_line: only applies if old_text evaluates to True in a Boolean context; indicates whether a new line should start (i.e., whether new_text should begin a new line); defaults to False. line_size: only applies if return_height is True; enotes the pixels interpolated between lines of text; if not set but line_size is needed, it is obtained from f. Returns: lines: old_text with new_text added. optionally: height: the height of lines when rendered with f. """ # Branch depending on whether additional text or a blank line is being # added: if new_text: # If new_text is a string, it needs to be converted to a list. try: # Get paragraphs: new_text_as_paragraphs = new_text.split("\n") # Overwrite new_text: new_text = [] for paragraph in new_text_as_paragraphs: paragraph_list = paragraph.split(" ") new_text.append(paragraph_list) except AttributeError: # new_text is already a list. pass new_lines = list(old_text) # Check if a last line from old_text is needed: if old_text and not start_new_line: line = old_text[-1] # Delete line from new_lines: del new_lines[-1] else: line = "" # Set line width: line_width = f.size(line)[0] # Fill new_lines paragraph by paragraph: for paragraph in new_text: # Fill each line word by word: for word in paragraph: # Unless line is currently empty, a leading space is needed # when calculating word's width. if line: word_width = f.size(" "+word)[0] else: word_width = f.size(word)[0] line_width = line_width+word_width if line_width < width: # word fits on this line. if line: line = line+" "+word else: line = word elif line_width == width: # word fits, but no more words will. line = line+" "+word new_lines.append(line) line= "" line_width = 0 else: # word doesn't fit. new_lines.append(line) line = word word_width = f.size(word)[0] line_width = word_width # Some part of a line might be left. if line: new_lines.append(line) line = "" line_width = 0 else: # A blank line is being added to old_text. new_lines = list(old_text) new_lines.append("") # Check if height is calculated: if return_height: # Check if line_height needs to be set: if not line_height: line_height = f.get_linesize() height = height_of_strings(new_lines, f, line_height) return new_lines, height return new_lines def string_to_screens_and_lines(source, allowed_width, allowed_height, f, pixels_between_lines = None, end_screens_with = (), do_not_include = ()): """ Convert a string to screens and lines. Pygame does not allow line breaks ("\n") when rendering text. The purpose of this function is to break a string into lines and screens given a font and screen dimensions. The following two assumptions are made: 1. Line breaks ("\n") in source denote the start of a new paragraph. Therefore, to have an actual blank line (i.e., an empty string) appear in the returned array, add another "\n" immediately following the first. 2. Spaces denote the end of a word. Parameters: source: the string to divide into screens and lines. allowed_width: the width, in pixels, permitted for lines; can be a number of pixels or a proportion of the active screen's width. allowed_height: same as allowed_width but for the height of a single screen. f: the font with which source is measured. Keyword Parameters: pixels_between_lines: blank pixel rows between lines of text; defaults to None, in which case it is obtained from f. end_screens_with: a restricted set of characters that may end a screen; defaults to an empty tuple, in which case any character ending a word can end a screen. do_not_include: words that are exceptions to the end_screens_with words (e.g., "Mrs." ends in a period but should not end a screen) Returns: screens: a multidimensional list of screens and lines. """ # Check if allowed_height and allowed_width need to be set: if 0 < allowed_width <= 1 and 0 < allowed_height <= 1: allowed_width, allowed_height = screen_dimensions() elif 0 < allowed_width <= 1 or 0 < allowed_height <= 1: raise ValueError("Both or neither of allowed_width and \ allowed_height can be between 0 and 1.") # Check if pixels_between_lines needs to be set: if not pixels_between_lines: pixels_between_lines = f.get_linesize() else: assert pixels_between_lines > 0, "pixels_between_lines must be \ positive." # Make sure that allowed_height can accommodate the tallest word in # source: assert f.size(source)[1] <= allowed_height, "allowed_height cannot \ accommodate source." screens = [] # Break source into paragraphs and paragraphs into single words: paragraphs = source.split("\n") single_words = [] for paragraph in paragraphs: individual_words = paragraph.split(" ") # While here, verify that the longest word fits: widest_word, pixels = longest_string_to_render(individual_words, f) assert pixels < allowed_width, "{:s} in source is too long for \ allowed_width.".format(widest_word) single_words.append(individual_words) # The function branches next, depending on whether restrictions have been # placed on where screen breaks can occur. if not end_screens_with: # Screen breaks can occur following any word. # Break single_words into lines without regard to screens: lines_of_text, total_height = wrap_text( single_words, allowed_width, f, return_height = True, line_height = pixels_between_lines ) if total_height <= allowed_height: # Everything fits on one screen. screens.append(lines_of_text) else: # There will be at least two screens. # Initialize the first screen and a height counter: screen = [] screen_height = 0 for line in lines_of_text: line_height = f.size(line)[1] screen_height = screen_height+line_height+pixels_between_lines if screen_height < allowed_height: # line fits on the current screen. screen.append(line) elif screen_height == allowed_height or screen_height-pixels_between_lines < allowed_height: # line fits, but no more will. screen.append(line) screens.append(screen) screen = [] screen_height = 0 else: # line doesn't fit. screens.append(screen) screen = [line] screen_height = line_height+pixels_between_lines # Check for a remaining screen: if screen: screens.append(screen)\ else: # Screens can only end following specific strings. # These strings do not need to be end-of-sentence characters, but it # is difficult to imagine what else they would be. Therefore, I refer # to the resulting strings as sentences, acknowledging that this may # be incorrect terminology. # Break paragraphs into sentences: sentences = [] for paragraph in paragraphs: if sentences: # This is not the first line, so start the paragraph on a new # line: sentences.append("") if paragraph: # paragraph is not a blank line. # Break it into sentences: paragraph_as_sentences = text_to_sentences( paragraph, terminators = end_screens_with, exclude = do_not_include ) sentences = sentences+paragraph_as_sentences else: # paragraph is a blank line. sentences.append("") # Initialize the first screen: screen = [] for sentence in sentences: # Determine whether sentence starts on a new line or continues # from the current line: if screen: # If the last line in screen is blank, then sentence starts on # a new line. last_line = screen[-1] if last_line: next_line = False else: next_line = True else: # This screen is blank. # Arbitrarily set next_line to False: next_line = False # Try adding sentence to the current screen: possible_screen, screen_height = wrap_text( sentence, allowed_width, f, old_text = screen, start_new_line = next_line, return_height = True, line_height = pixels_between_lines ) if screen_height <= allowed_height: # Update the current screen: screen = possible_screen else: # This sentence does not fit. # If screen is currently blank, it means that sentence needs # to be broken across screens (i.e., it will not fit on a # single screen). if screen: # This is not an issue. # Save screen: screens.append(screen) # Initialize the next screen with sentence: screen, current_height = wrap_text( sentence, allowed_width, f, return_height = True, line_height = pixels_between_lines ) if current_height > allowed_height: # sentence needs to be broken across screens. # This can be accomplished by calling the present # function without restrictions on screen endings. # However, the text currently on screen is needed too. text_to_add = "" for line in screen: text_to_add = text_to_add+line+"" text_to_add = text_to_add+sentence multiple_screens = string_to_screens_and_lines( text_to_add, allowed_width, allowed_height, f, pixels_between_lines = pixels_between_lines ) for s in multiple_screens: screens.append(s) else: # screen is empty, but sentence will not fit. # Call the present function to get this sentence's # screens: multiple_screens = string_to_screens_and_lines( sentence, allowed_width, allowed_height, f, pixels_between_lines = pixels_between_lines ) for s in multiple_screens: screens.append(s) # Check if a final screen needs to be added: if screen: screens.append(screen) return screens def render_string(s, f, colour, background, antialiasing = True): """ Create pygame.Surface and pygame.Rect objects for a string, using a given font (f) and colour. Parameters: s: the string to render. f: the font in which to render s. colour: the colour of text to use, expressed as an RGB list or tuple. background: the background colour. Keyword Parameters: antialiasing: indicates whether text is rendered with antialiasing; defaults to True. Returns: s: the pygame.Surface object. r: the pygame.Rect object. """ s = f.render(s, antialiasing, colour, background) r = s.get_rect() return s, r def render_lines(lines, f, text_colour, background_colour, line_size = None, use_antialiasing = True): """ Create pygame.Surface and pygame.Rect objects for a list of strings. Parameters: lines: the lines to render; "" is treated as a blank line. f: the font in which to render text. text_colour: an RGB list or tuple for the colour of the text. background_colour: RGB for background. Keyword Parameters: line_size: the number of pixel rows between lines; defaults to None, in which case it is set from f. use_antialiasing: indicates whether lines are rendered with antialiasing; defaults to True. Returns: surf: the pygame.Surface object. rect: the pygame.Rect object. """ height = 0 surfaces = [] rects = [] for line in lines: s, r = render_string( line, f, text_colour, background_colour, antialiasing = use_antialiasing ) surfaces.append(s) rects.append(r) height = height+r.height try: height = height+line_size*(len(surfaces)-1) except TypeError: line_size = f.get_linesize() height = height+line_size*(len(surfaces)-1) # height will be the height of the returned surface and rect. # The width will be equal to the widest rect in rects. width = rects[0].width for rect in rects[1:]: if rect.width > width: width = rect.width # Initialize the returned surface: surf = pygame.Surface((width, height)) surf.fill(background_colour) # Keep track of the pixel row at which to blit each surface in surfaces: top = 0 for i in range(len(surfaces)): s = surfaces[i] r = rects[i] r.topleft = (0, top) surf.blit(s, r) top = top+r.height+line_size rect = surf.get_rect() return surf, rect def string_to_surface_and_rect(s, f, colour, background, max_width, max_height, max_screens = 1, line_size = None, antialiasing = True): """ Create a surface and rect from a string given a maximum pixel width for each line and a maximum pixel height for each screen. Parameters: s: the string. f: the font to use. colour: RGB for the text colour. background: RGB for the background colour. max_width: the maximum pixel width for each line. max_height: the maximum pixel height for each screen. Keyword Parameters: line_size: pixels between lines of text; defaults to None, in which case it is obtained from f. antialiasing: Boolean indicating whether antialiasing is used. Returns: surfaces: list of the pygame.Surface objects. rects: the list of pygame.Rect objects. """ surfaces = [] rects = [] lines = string_to_screens_and_lines( s, max_width, max_height, f, line_size ) assert len(lines) <= max_screens, "s is too long." for screen in lines: surf, rect = render_lines( screen, f, colour, background, line_size = line_size, use_antialiasing = antialiasing ) surfaces.append(surf) rects.append(rect) return surfaces, rects def display_text_until_keypress(main_text, main_font, text_colour, background, antialias = True, proportion_width = 0.95, proportion_height = 0.95, main_line = None, break_sentences = False, sentence_terminators = (".", "!", "?"), terminator_exceptions = (), gap = 1, bottom_message = "Press the space bar to continue.", bottom_font = None, bottom_line = None, advance_keys = (K_SPACE,), reverse_keys = (K_LEFT, K_BACKSPACE,), quit_keys = (K_ESCAPE,), ticker = None, frame_rate = 30, files = ()): """ Display text to the screen and wait for the user to advance. If the text exceeds a single screen, users can move back and forth between the screens. Parameters: main_text: the text to be displayed, excluding the advance message. main_font: the font used for main_text. text_colour: RGB list/tuple for the colour of text. background: RGB list/tuple for main_text's background. Keyword Parameters: antialias: Boolean indicating whether antialiasing is used in text rendering; defaults to True. proportion_width: proportion of the main display surface's width used for text rendering (default = 0.95). proportion_height: proportion of the main display surface's height used for text rendering (default = 0.95). main_line: pixel rows between lines of text; taken from main_font if not set. break_sentences: Boolean indicating whether sentences can be broken across screens; defaults to False. NB: Sentences may be broken across screens even if False if they cannot fit on a single screen. sentence_terminators: strings that end a sentence. terminator_exceptions: exceptions to the strings in sentence_terminators. gap: the number of line breaks between the bottom of the main text and the top of bottom_message (default = 1). bottom_message: text at the end of each screen; defaults to "Press the space bar to continue.", but should be changed if advance_keys does not include K_SPACE. bottom_font: font to use for bottom_message; if left as None, main_font is used. bottom_line: same as main_line for bottom_line; taken from bottom_font if not set. advance_keys: keys to move through the screens; defaults to (K_SPACE,). reverse_keys: keys to move backward through the screens; defaults to (K_LEFT, K_BACKSPACE); to disable the user's ability to move backward, pass an empty tuple. quit_keys: keys to exit the program; set as an empty tuple to disable. ticker: a pygame.time.Clock object for controlling frame rate; one is created if one is not passed. frame_rate: the maximum frames per second; defaults to 30. files: an optional list/tuple of open files to close in case the user quits. """ if not main_line: main_line = main_font.get_linesize() if not bottom_font: bottom_font = main_font if not bottom_line: bottom_line = bottom_font.get_linesize() window_surface = pygame.display.get_surface() try: window_rect = window_surface.get_rect() except AttributeError: window_surface = pygame.display.set_mode(pygame.display.list_modes()[0]) window_rect = window_surface.get_rect() window_surface.fill(background) window_width, window_height = window_surface.get_size() pixel_columns = int(proportion_width*window_width) pixel_rows = int(proportion_height*window_height) # Initialize lists to hold the generated surfaces and rects: surfaces = [] rects = [] # Get a surface and rect for bottom_message: bottom_lines = string_to_screens_and_lines( bottom_message, pixel_columns, pixel_rows, f = bottom_font, pixels_between_lines = bottom_line ) assert len(bottom_lines) == 1, "The bottom_message parameter cannot \ exceed a single screen." bottom_lines = bottom_lines[0] bottom_surface, bottom_rect = render_lines( bottom_lines, bottom_font, text_colour, background, line_size = bottom_line, use_antialiasing = antialias ) # Get the height for main_text: main_height = pixel_rows-bottom_rect.height-gap*main_line if break_sentences: main_lines = string_to_screens_and_lines( main_text, pixel_columns, main_height, main_font, pixels_between_lines = main_line, end_screens_with = sentence_terminators, do_not_include = terminator_exceptions ) else: main_lines = string_to_screens_and_lines( main_text, pixel_columns, main_height, main_font, pixels_between_lines = main_line ) for screen in main_lines: main_surface, main_rect = render_lines( screen, main_font, text_colour, background, line_size = main_line, use_antialiasing = antialias ) bottom_rect_copy = pygame.Rect(bottom_rect) # Create a surface to hold both main_surface and bottom_surface: surfaces_combined = pygame.Surface((pixel_columns, pixel_rows)) rects_combined = surfaces_combined.get_rect() surfaces_combined.fill(background) # Centre text with reference to the longer of the main_rect and # bottom_rect: if main_rect.width >= bottom_rect.width: left_coordinate = (pixel_columns-main_rect.width)//2 else: left_coordinate = (pixel_columns-bottom_rect.width)//2 main_rect.topleft = (left_coordinate, 0) bottom_rect_copy.topleft = (left_coordinate, main_rect.bottom+gap*main_line) surfaces_combined.blit(main_surface, main_rect) surfaces_combined.blit(bottom_surface, bottom_rect_copy) rects_combined.center = window_rect.center surfaces.append(surfaces_combined) rects.append(rects_combined) i = 0 surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) keep_looping = True pygame.display.update() while keep_looping: for event in pygame.event.get(): if (event.type == KEYUP and event.key in quit_keys) or event.type == QUIT: generic.terminate(files) elif event.type == KEYUP and event.key in reverse_keys and i > 0: # Move back a screen: i = i-1 surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) pygame.display.update(rect_i) elif event.type == KEYUP and event.key in advance_keys and i < len(surfaces)-1: # Moving forward a screen. i = i+1 surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) pygame.display.update(rect_i) elif event.type == KEYUP and event.key in advance_keys and i == len(surfaces)-1: keep_looping= False else: pass try: ticker.tick(frame_rate) except AttributeError: ticker = pygame.time.Clock() ticker.tick(frame_rate) def ask_question(question, f, text_colour, background, antialiasing = True, w = 0.95, h = 0.95, line_size = None, gap = 1, continue_message = "Press the down arrow key to advance.", continue_font = None, continue_line_size = None, min_response = 1, max_response = None, allowed_keys = LETTERS+NUMBERS+PUNCTUATION+(K_SPACE,), move_ahead = (K_DOWN,), move_back = (K_UP,), finished = (K_RETURN,), quit_keys = (K_ESCAPE,), allow_changes = True, ticker = None, frame_rate = 30, files = ()): """ Display a question and return the user's typed response. Parameters: question: the question to which the user responds. f: the font used. text_colour: RGB list/tuple for text. background: RGB list/tuple for background. Keyword Parameters: antialiasing: Boolean indicating whether antialiasing is used in text rendering; defaults to True. w: the proportion of the active display surface's width allowed for text rendering (default = 0.95). h: the proportion of the active display surface's height allowed for text rendering (default = 0.95). line_size: pixel rows between lines of text; if not set, obtained from f. gap: line breaks between question and continue_message or the user's response (default = 1). continue_message: applies only if question exceeds a single screen; the message prompting the user to press a key to advance (default = "Press the down arrow key to advance.") continue_font: font used instead of f for continue_message; f used if not set. continue_line_size: same as line_size but for continue_message. min_response: the minimum length of the user's response (default = 1). max_response: the maximum length of the user's response; (default = None). allowed_keys: keys that can be used for responding. move_ahead: keys that move to the next screen; only applicable if question takes up more than one screen. move_back: keys that move to the previous screen. finished: keys to press when the response is finished; defaults to return, but can be empty if min_response and max_response are equal. quit_keys: keys for closing the program. allow_changes: Boolean guiding whether input can be deleted once typed; defaults to True. ticker: pygame.time.Clock object; one is created if none is passed. frame_rate: the maximum frames per second (default = 30). files: files to close if terminate() is called. Returns: r: the user's response. """ if not line_size: line_size = f.get_linesize() r = "" window_surface = pygame.display.get_surface() try: window_rect = window_surface.get_rect() except AttributeError: window_surface = pygame.display.set_mode(pygame.display.list_modes()[0]) window_surface.fill(background) window_width, window_height = window_rect.size # Set pixel columns and rows allowed: pixel_columns = int(w*window_width) pixel_rows = int(h*window_height) surfaces = [] rects = [] # Get pixel rows available for question after accounting for the user's # response and gap: question_height = pixel_rows-(gap+1)*line_size # Break question into screens and lines: question_screens = string_to_screens_and_lines( question, pixel_columns, question_height, f, pixels_between_lines = line_size ) if len(question_screens) == 1: # question fits on one screen. # Extract question_screens from its outter list: question_screens = question_screens[0] question_surface, question_rect = render_lines( question_screens, f, text_colour, background, line_size = line_size, use_antialiasing = antialiasing ) # Initialize the surface for question: main_surface = pygame.Surface((pixel_columns, pixel_rows)) main_rect = main_surface.get_rect() # Centre question_rect within a pixel_columns by question_height # rectangle with a top-left coordinate of (0, 0): question_rect.center = (pixel_columns//2, question_height//2) # Get the response position: response_position = ( question_rect.left+(window_width-pixel_columns)//2, question_rect.bottom+gap*line_size+(window_height-pixel_rows)//2 ) main_surface.fill(background) main_surface.blit(question_surface, question_rect) # Centre main_rect with respect to window_surface: main_rect.center = window_rect.center surfaces.append(main_surface) rects.append(main_rect) else: # question doesn't fit on one screen, so continue_message needs to be # created. if not continue_font: continue_font = f if not continue_line_size: continue_line_size = continue_font.get_linesize() continue_lines = string_to_screens_and_lines( continue_message, pixel_columns, pixel_rows, continue_font, pixels_between_lines = continue_line_size ) assert len(continue_lines) == 1, "continue_message is too long; it \ takes up multiple screens." continue_lines = continue_lines[0] continue_surface, continue_rect = render_lines( continue_lines, continue_font, text_colour, background, line_size = continue_line_size, use_antialiasing = antialiasing ) # Unless continue_message takes up the same number of pixel rows as # given for the user's typed response, question_text will need to be # reconverted to question_screens. if continue_rect.height != line_size: # It is possible that continue_message is so much smaller than # line_size that question_text now fits on a single screen. # This causes problems because of the different keypresses # accepted on the last screen. # Prevent it: for i in range(question_height, 0, -1): question_screens = string_to_screens_and_lines( question, pixel_columns, i, f, pixels_between_lines = line_size ) if len(question_screens) > 1: break last_screen = question_screens[-1] last_screen_height = height_of_strings(last_screen, f, line_size) # Because last_screen was just fit with continue_message, ensure # that it fits with line_size. # If it doesn't, it's split into two screens. if last_screen_height+(gap+1)*line_size > pixel_rows: final_line = last_screen[-1] del last_screen[-1] new_last_screen = [final_line] question_screens.append(new_last_screen) for i in range(len(question_screens)): question_screen = question_screens[i] question_surface, question_rect = render_lines( question_screen, f, text_colour, background, line_size = line_size, use_antialiasing = antialiasing ) current_surface = pygame.Surface((pixel_columns, pixel_rows)) current_surface.fill(background) current_rect = current_surface.get_rect() if i == len(question_screens)-1: # continue_message is not on this screen. question_rect.topleft = ((pixel_columns-question_rect.width)//2, 0) response_position = ( question_rect.left+(window_width-pixel_columns), question_rect.bottom+gap*line_size+(window_height-pixel_rows)//2 ) current_surface.blit(question_surface, question_rect) else: # continue_message appears on this screen. # The left coordinate depends on which is wider. if question_rect.width >= continue_rect.width: left_coordinate = (pixel_columns-question_rect.width)//2 else: left_coordinate = (pixel_columns-continue_rect.width)//2 question_rect.topleft = (left_coordinate, 0) continue_rect.topleft = ( left_coordinate, question_rect.bottom+gap*line_size ) current_surface.blit(question_surface, question_rect) current_surface.blit(continue_surface, continue_rect) current_rect.center = window_rect.center surfaces.append(current_surface) rects.append(current_rect) # Create a screen tracker and show the first screen: i = 0 surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) answer_obtained = False pygame.display.update() while not answer_obtained: for event in pygame.event.get(): if event.type == QUIT or (event.type == KEYUP and event.key in quit_keys): generic.terminate(files) elif i < len(surfaces)-1 and event.type == KEYUP and event.key in move_ahead: # The user is moving to the next screen. i = i+1 window_surface.fill(background, rect_i) surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) pygame.display.update(rect_i) elif i > 0 and event.type == KEYUP and event.key in move_back: # The user is moving back one screen. i = i-1 window_surface.fill(background, rect_i) surface_i = surfaces[i] rect_i = rects[i] window_surface.blit(surface_i, rect_i) pygame.display.update(rect_i) elif event.type == KEYUP and event.key in allowed_keys and (len(r) < max_response or not max_response): # A character has been added to r. character = pygame.key.name(event.key) r = r+character if not finished and len(r) == max_response: answer_obtained = True else: surface_r, rect_r = render_string( r, f, text_colour, background, antialiasing ) rect_r.topleft = response_position window_surface.fill(background, rect_r) window_surface.blit(surface_r, rect_r) pygame.display.update(rect_r) elif event.type == KEYUP and event.key == K_BACKSPACE and allow_changes and r and i == len(surfaces)-1: # The last character has been deleted. r = r[:len(r)-1] update_rect = rect_r surface_r, rect_r = render_string( r, f, text_colour, background, antialiasing ) rect_r.topleft = response_position window_surface.fill(background, update_rect) window_surface.blit(surface_r, rect_r) pygame.display.update(update_rect) elif event.type == KEYUP and event.key in finished and i == len(surfaces)-1 and len(r) >= min_response: # The user has finished r. answer_obtained = True else: pass try: ticker.tick(frame_rate) except AttributeError: # No clock was passed to the function. ticker = pygame.time.Clock() ticker.tick(frame_rate) return r
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src/python/shared/BAData.py
dsyme/ADBench
58
98601
# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from dataclasses import dataclass, field import numpy as np from shared.BASparseMat import BASparseMat from shared.output_utils import save_errors_to_file, objective_file_name,\ save_sparse_j_to_file, jacobian_file_name @dataclass class BAInput: cams: np.ndarray = field(default = np.empty(0, dtype = np.float64)) x: np.ndarray = field(default = np.empty(0, dtype = np.float64)) w: np.ndarray = field(default = np.empty(0, dtype = np.float64)) obs: np.ndarray = field(default = np.empty(0, dtype = np.int32)) feats: np.ndarray = field(default = np.empty(0, dtype = np.float64)) @dataclass class BAOutput: reproj_err: np.ndarray = field(default = np.empty(0, dtype = np.float64)) w_err: np.ndarray = field(default = np.empty(0, dtype = np.float64)) J: BASparseMat = field(default = BASparseMat()) def save_output_to_file( self, output_prefix, input_basename, module_basename ): save_errors_to_file( objective_file_name(output_prefix, input_basename, module_basename), self.reproj_err, self.w_err ) save_sparse_j_to_file( jacobian_file_name(output_prefix, input_basename, module_basename), self.J )
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api/server/swagger_server/code_templates/serve_kubernetes.TEMPLATE.py
krishnakumar27/mlx
98
162275
# Copyright 2021 The MLX Contributors # # SPDX-License-Identifier: Apache-2.0 from kfp import dsl from kfp_tekton.compiler import TektonCompiler from kfp_tekton import TektonClient from os import path from tempfile import gettempdir ############################################################ # Define the pipeline method ############################################################ @dsl.pipeline( name='Model Deployment pipeline', description='A pipeline for ML/DL model deployment on Kubernetes.' ) def model_pipeline(model_id='${model_identifier}'): """A pipeline for ML/DL model deployment.""" from kfp import dsl from ai_pipeline_params import use_ai_pipeline_params secret_name = 'e2e-creds' model_config = dsl.ContainerOp( name='model_config', image='aipipeline/model-config', command=['python'], arguments=[ '-u', 'model-config.py', '--secret_name', secret_name, '--model_id', model_id ], file_outputs={ 'model-serving-image': '/tmp/model_serving_image', 'deployment-name': '/tmp/deployment_name' } ) model_deployment = dsl.ContainerOp( name='k8s_model_deployment', image='aipipeline/deployment-k8s-remote', command=['python'], arguments=[ '-u', 'kube_deployment.py', '--model_serving_image', model_config.outputs['model-serving-image'], '--deployment_name', model_config.outputs['deployment-name'] ], file_outputs={ 'output': '/tmp/log.txt' } ) model_deployment.apply(use_ai_pipeline_params(secret_name)) ############################################################ # Compile the pipeline ############################################################ pipeline_function = model_pipeline pipeline_filename = path.join(gettempdir(), pipeline_function.__name__ + '.tar.gz') TektonCompiler().compile(pipeline_function, pipeline_filename) ############################################################ # Run the pipeline ############################################################ client = TektonClient(${pipeline_server}) # Get or create an experiment and submit a pipeline run experiment = client.create_experiment('MODEL_RUNS') # Submit the experiment to run in a pipeline run_name = '${run_name}' run_result = client.run_pipeline(experiment.id, run_name, pipeline_filename)
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is_core/config.py
cedel1/django-is-core
0
195925
from django.conf import settings as django_settings def _get_auth_login_view(): if ('auth_token' in django_settings.INSTALLED_APPS and getattr(django_settings, 'AUTH_TOKEN_TWO_FACTOR_ENABLED', False)): return 'auth_token.contrib.is_core_auth.views.TwoFactorLoginView' elif 'auth_token' in django_settings.INSTALLED_APPS: return 'auth_token.contrib.is_core_auth.views.LoginView' else: return 'is_core.views.auth.LoginView' DEFAULTS = { 'AUTH_LOGIN_CODE_VERIFICATION_VIEW': ( 'auth_token.contrib.is_core_auth.views.LoginCodeVerificationView' if ('auth_token' in django_settings.INSTALLED_APPS and getattr(django_settings, 'AUTH_TOKEN_TWO_FACTOR_ENABLED', False)) else None ), 'AUTH_FORM_CLASS': ( 'auth_token.contrib.is_core_auth.forms.TokenAuthenticationSmartForm' if 'auth_token' in django_settings.INSTALLED_APPS else 'django.contrib.auth.forms.AuthenticationForm' ), 'AUTH_RESOURCE_CLASS': None, 'AUTH_LOGIN_VIEW': _get_auth_login_view(), 'AUTH_LOGOUT_VIEW': ( 'auth_token.contrib.is_core_auth.views.LogoutView' if 'auth_token' in django_settings.INSTALLED_APPS else 'is_core.views.auth.LogoutView' ), 'CODE_VERIFICATION_URL': '/login/login-code-verification/', 'HOME_CORE': 'is_core.main.HomeUiCore', 'HOME_VIEW': 'is_core.generic_views.base.HomeView', 'MENU_GENERATOR': 'is_core.menu.MenuGenerator', 'USERNAME': 'username', 'PASSWORD': 'password', 'LOGIN_URL': '/login/', 'LOGOUT_URL': '/logout/', 'LOGIN_API_URL': lambda s: '/api{}'.format(s.LOGIN_URL), 'EXPORT_TYPES': '', 'FOREIGN_KEY_MAX_SELECTBOX_ENTRIES': 500, 'LIST_PER_PAGE': 20, 'REST_PAGINATOR_MAX_TOTAL': 10000, 'RESPONSE_EXCEPTION_FACTORY': 'is_core.exceptions.response.ui_rest_response_exception_factory', 'DEFAULT_FIELDSET_TEMPLATE': 'is_core/forms/default_fieldset.html', 'HEADER_IMAGE': None, 'ENVIRONMENT': None, 'BACKGROUND_EXPORT_TASK_TIME_LIMIT': 60*60, 'BACKGROUND_EXPORT_TASK_SOFT_TIME_LIMIT': (60*60) - 5, 'BACKGROUND_EXPORT_TASK_UPDATE_REQUEST_FUNCTION': None, 'BACKGROUND_EXPORT_TASK_QUEUE': None, 'BACKGROUND_EXPORT_SERIALIZATION_LIMIT': 2000, 'BACKGROUND_EXPORT_STORAGE_CLASS': 'django.core.files.storage.DefaultStorage', 'BACKGROUND_EXPORT_EXPIRATION_DAYS': 30, } class Settings: def __getattr__(self, attr): if attr not in DEFAULTS: raise AttributeError('Invalid IS_CORE setting: "{}"'.format(attr)) default = DEFAULTS[attr] return getattr(django_settings, 'IS_CORE_{}'.format(attr), default(self) if callable(default) else default) settings = Settings()
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contrib/grok-to-regex.py
bossjones/docker-compose-prometheus
0
151375
<reponame>bossjones/docker-compose-prometheus<filename>contrib/grok-to-regex.py<gh_stars>0 #!/usr/bin/env python import argparse import re from os import walk from os.path import join def get_patterns(patterns_dir): patterns = {} for (dirpath, _, filenames) in walk(patterns_dir): for name in filenames: with open(join(dirpath, name)) as f: for line in f.readlines(): if not line.startswith('#') and not line.strip() == "": k, v = line.split(' ', 1) patterns[k] = v.rstrip('\n') return patterns def convert(expression, patterns): groks = re.compile('%{[^}]*}') failed_matches = set() matches_prev_len = 0 while True: matches = groks.findall(expression) matches_cur_len = len(matches) if matches_cur_len == 0 or matches_cur_len == matches_prev_len: break for m in matches: inner = m.strip('%{}') if ':' in inner: patt, name = inner.split(':') replacement = '(?<{}>{{}})'.format(name) else: patt = inner replacement = '{}' if not patt in list(patterns.keys()): failed_matches.add(patt) continue expression = expression.replace(m, replacement.format(patterns[patt])) matches_prev_len = matches_cur_len print(expression) if failed_matches: global args print('\nWarning! Unable to match the following expressions:') print(' {}'.format(', '.join(failed_matches))) print('This could be a typo or a missing grok pattern file. Double check your grok patterns directory: {}'.format( args.patterns_dir )) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('expression', metavar='expr', help='A grok expression.') parser.add_argument('-d', '--patterns-dir', dest='patterns_dir', default='patterns', help='Directory to find grok patterns.') args = parser.parse_args() patterns = get_patterns(args.patterns_dir) convert(args.expression, patterns)
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gap/src/util/data_iterator.py
cosmozhang/autoencoding_parsing
0
13396
<gh_stars>0 from collections import OrderedDict, defaultdict import numpy as np ''' generate a id to length dic ''' def gen_sid_len(sentences): sid2len = OrderedDict() for i, sent in enumerate(sentences): sid2len[i] = len(sent) return sid2len def batch_slice(data, batch_size): # data is a list of sentences of the same length batch_num = int(np.ceil(len(data) / float(batch_size))) for i in xrange(batch_num): cur_batch_size = batch_size if i < batch_num - 1 else len(data) - batch_size * i # cur_batch_size is the end-point of the batch sents = data[i * batch_size: i * batch_size + cur_batch_size] yield sents def data_iter(sents_id2length_dic, batch_size, shuffle=True): """ randomly permute data, then sort by source length, and partition into batches ensure that the length of source sentences in each batch is decreasing """ buckets = defaultdict(list) for (sent_id, sent_len) in sents_id2length_dic.iteritems(): buckets[sent_len].append(sent_id) batched_data = [] for (sent_len, sent_ids_smlen) in buckets.iteritems(): # sent_ids_smlen is a list of sentences of the same length if shuffle: np.random.shuffle(sent_ids_smlen) # pdb.set_trace() ''' 'extend' expecting a iterable finishes the iteration ''' batched_data.extend(list(batch_slice(sent_ids_smlen, batch_size))) if shuffle: np.random.shuffle(batched_data) for batch in batched_data: """ sent_ids in the same batch are of the same length """ yield batch
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tensorflow_decision_forests/keras/test_runner.py
Saduf2019/decision-forests
1
171322
<filename>tensorflow_decision_forests/keras/test_runner.py # Copyright 2021 Google LLC. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Loads and runs a SavedModel generated by :keras_test on the Adult dataset. This binary tests the model in a clean tensorflow instance (without pre-loaded functions and resources) and does not require non-canonical tf ops. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import enum from typing import Dict from absl import app from absl import flags from absl import logging import numpy as np import pandas as pd import tensorflow as tf flags.DEFINE_string("model_path", "", "Path to the SavedModel model to load.") flags.DEFINE_string("dataset_path", "", "Path to adult dataset.") FLAGS = flags.FLAGS def main(argv): del argv logging.info("Load model") model = tf.keras.models.load_model(FLAGS.model_path) logging.info("Load dataset") pd_dataset = load_dataset() tf_dataset = dataframe_to_tf_dataset(pd_dataset, "income") logging.info("Evaluate model") evaluation = model.evaluate(tf_dataset) logging.info("evaluation: %s", evaluation) logging.info("Done (unload model)") # The following code is similar to the simple_ml_keras_test. class Semantic(enum.Enum): NUMERICAL = 1 CATEGORICAL = 2 def dataframe_to_tf_dataset(dataframe: pd.DataFrame, label: str) -> tf.data.Dataset: dataset = tf.data.Dataset.from_tensor_slices( (dict(dataframe.drop(label, 1)), dataframe[label].values)) return dataset.batch(64) def load_dataset() -> pd.DataFrame: """Loads the dataset in a pandas dataframe.""" dataset = pd.read_csv(flags.FLAGS.dataset_path) label = "income" def clean(ds): ds[label] = np.where(ds[label] == ">50K", 1, 0) return ds dataset = clean(dataset) return auto_dataset(dataset, label) def infer_semantic_from_dataframe(dataset: pd.DataFrame) -> Dict[str, Semantic]: """Infers the semantic of the columns in a pandas dataframe.""" semantics = {} for col in dataset.columns: dtype = dataset[col].dtype if dtype in [float, np.float, np.int16, np.int32, np.int64, int]: semantics[col] = Semantic.NUMERICAL elif dtype in [str, object]: semantics[col] = Semantic.CATEGORICAL else: raise Exception( "Cannot infer semantic for column \"{}\" with dtype={}".format( col, dtype)) return semantics def auto_dataset(dataset, label) -> pd.DataFrame: """Prepares a dataset object.""" semantics = infer_semantic_from_dataframe(dataset) def extract_by_semantic(semantic): return [k for k, s in semantics.items() if s == semantic and k != label] categorical_features = extract_by_semantic(Semantic.CATEGORICAL) numerical_features = extract_by_semantic(Semantic.NUMERICAL) def clean(dataset): for key in categorical_features: dataset[key] = dataset[key].fillna("") return dataset[categorical_features + numerical_features + [label]] return clean(dataset) if __name__ == "__main__": app.run(main)
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pypika/tests/dialects/test_mssql.py
uhrm/pypika
0
10045
<gh_stars>0 import unittest from pypika import Table from pypika.analytics import Count from pypika.dialects import MSSQLQuery from pypika.utils import QueryException class SelectTests(unittest.TestCase): def test_normal_select(self): q = MSSQLQuery.from_("abc").select("def") self.assertEqual('SELECT "def" FROM "abc"', str(q)) def test_distinct_select(self): q = MSSQLQuery.from_("abc").select("def").distinct() self.assertEqual('SELECT DISTINCT "def" FROM "abc"', str(q)) def test_top_distinct_select(self): q = MSSQLQuery.from_("abc").select("def").top(10).distinct() self.assertEqual('SELECT DISTINCT TOP (10) "def" FROM "abc"', str(q)) def test_top_select(self): q = MSSQLQuery.from_("abc").select("def").top(10) self.assertEqual('SELECT TOP (10) "def" FROM "abc"', str(q)) def test_top_select_non_int(self): with self.assertRaisesRegex(QueryException, "TOP value must be an integer"): MSSQLQuery.from_("abc").select("def").top("a") def test_limit(self): q = MSSQLQuery.from_("abc").select("def").orderby("def").limit(10) self.assertEqual('SELECT "def" FROM "abc" ORDER BY "def" OFFSET 0 ROWS FETCH NEXT 10 ROWS ONLY', str(q)) def test_fetch_next(self): q = MSSQLQuery.from_("abc").select("def").orderby("def").fetch_next(10) self.assertEqual('SELECT "def" FROM "abc" ORDER BY "def" OFFSET 0 ROWS FETCH NEXT 10 ROWS ONLY', str(q)) def test_offset(self): q = MSSQLQuery.from_("abc").select("def").orderby("def").offset(10) self.assertEqual('SELECT "def" FROM "abc" ORDER BY "def" OFFSET 10 ROWS', str(q)) def test_fetch_next_with_offset(self): q = MSSQLQuery.from_("abc").select("def").orderby("def").fetch_next(10).offset(10) self.assertEqual('SELECT "def" FROM "abc" ORDER BY "def" OFFSET 10 ROWS FETCH NEXT 10 ROWS ONLY', str(q)) def test_groupby_alias_False_does_not_group_by_alias_with_standard_query(self): t = Table('table1') col = t.abc.as_('a') q = MSSQLQuery.from_(t).select(col, Count('*')).groupby(col) self.assertEqual('SELECT "abc" "a",COUNT(\'*\') FROM "table1" GROUP BY "abc"', str(q)) def test_groupby_alias_False_does_not_group_by_alias_when_subqueries_are_present(self): t = Table('table1') subquery = MSSQLQuery.from_(t).select(t.abc) col = subquery.abc.as_('a') q = MSSQLQuery.from_(subquery).select(col, Count('*')).groupby(col) self.assertEqual( 'SELECT "sq0"."abc" "a",COUNT(\'*\') FROM (SELECT "abc" FROM "table1") "sq0" GROUP BY "sq0"."abc"', str(q) )
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src/main.py
Quin-Darcy/Crawler
0
38249
<reponame>Quin-Darcy/Crawler import crawler import os def main(): root = crawler.Crawler() root.set_start() root.burrow() root.show() os.system('killall firefox') if __name__ == '__main__': main()
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Exercicios em Python/ex080.py
Raphael-Azevedo/Exercicios_Python
0
12412
<gh_stars>0 n = [] i = 0 for c in range(0, 5): n1 = int(input('Digite um valor: ')) if c == 0 or n1 > n[-1]: n.append(n1) print(f'Adicionado na posição {c} da lista...') else: pos = 0 while pos < len(n): if n1 <= n[pos]: n.insert(pos, n1) print(f'Adicionado na posição {pos} da lista...') break pos += 1 print(f'Os valores digitados em ordem foram {n}')
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dataplotting.py
Shivams9/pythoncodecamp
6
186281
import matplotlib.pyplot as plt x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] y = [7, 8, 11, 1.3, 16, 15, -1, -.2, 0, 3.3] # plt.figure(figsize=(0,1000)) # plt.xlim(0,100) # plt.ylim(-10,100) # fig=plt.figure() plt.scatter(x, y, color='green', marker='o') plt.plot(x, y, color='yellow', linewidth=10, alpha=0.5) plt.xlabel("Time ") plt.ylabel("Income") # plt.bar(x,y,color='green') plt.title("Time Vs Income") plt.show()
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Project-Euler-Solutions/020.py
KartikKannapur/HackerRank
0
167319
<reponame>KartikKannapur/HackerRank #Problem 20: #n! means n × (n − 1) × ... × 3 × 2 × 1 #For example, 10! = 10 × 9 × ... × 3 × 2 × 1 = 3628800, #and the sum of the digits in the number 10! is 3 + 6 + 2 + 8 + 8 + 0 + 0 = 27. #Find the sum of the digits in the number 100! import sympy as sp def main(num): val = sp.factorial(num) summa = 0 val_list = list(str(val)) for i in val_list: summa += int(i) print summa main(100)
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backend/user/permissions.py
HarsimratBhundar/gym-buddy
0
155292
<filename>backend/user/permissions.py from rest_framework import permissions from django.contrib.auth.models import User from rest_framework.authtoken.models import Token class UserAccessPermission(permissions.BasePermission): message = 'Invalid permission' def has_permission(self, request, view): if (request.path == '/user'): token_recieved = request.headers.get('Authorization') username = request.headers.get('username') if token_recieved and username: if (request.method == 'GET' or request.method == 'POST'): user = User.objects.get(username=username) token, _ = Token.objects.get_or_create(user=user) if (token_recieved.split(' ')[1] == token.key): return True return False
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apns_proxy_client/core.py
hagino3000/apns-proxy-client-py
0
7442
<reponame>hagino3000/apns-proxy-client-py # -*- coding: utf-8 -*- """ APNS Proxy Serverのクライアント """ import time import zmq import simplejson as json READ_TIMEOUT = 1500 # msec FLUSH_TIMEOUT = 5000 # msec COMMAND_ASK_ADDRESS = b'\1' COMMAND_SEND = b'\2' COMMAND_FEEDBACK = b'\3' DEVICE_TOKEN_LENGTH = 64 JSON_ALERT_KEY_SET = set(['body', 'action_loc_key', 'loc_key', 'loc_args', 'launch_image']) class APNSProxyClient(object): def __init__(self, host, port, application_id): """ ZMQコンテキストとソケットの初期化 """ if host is None or not isinstance(host, str): raise ValueError("host must be string") if port is None or not isinstance(port, int): raise ValueError("host must be int type") self.host = host self.port = port self.context = zmq.Context() self.context.setsockopt(zmq.LINGER, FLUSH_TIMEOUT) self.communicator = self.context.socket(zmq.REQ) self.publisher = self.context.socket(zmq.PUSH) self.connected = False if not isinstance(application_id, str): raise ValueError("application_id must be string type") self.application_id = application_id def __enter__(self): self.connect() def connect(self): """リモートサーバーへ接続""" if self.connected is False: self.communicator.connect(self.build_address(self.port)) push_port = self.get_push_port() self.publisher.connect(self.build_address(push_port)) self.connected = True def build_address(self, port): return "tcp://%s:%s" % (self.host, port) def get_push_port(self): """ PUSH-PULL接続用のポートを取得する """ self.communicator.send(COMMAND_ASK_ADDRESS) poller = zmq.Poller() poller.register(self.communicator, zmq.POLLIN) if poller.poll(READ_TIMEOUT): return self.communicator.recv() else: self.close() raise IOError("Cannot connect to APNs Proxy Server. Timeout!!") def send(self, token, alert, sound='default', badge=None, content_available=False, custom=None, expiry=None, priority=None, test=False): """ デバイストークンの送信 """ self._check_token(token) self._check_alert(alert) self._check_custom(custom) self.publisher.send(self._serialize( COMMAND_SEND, token, alert, sound, badge, content_available, custom, expiry, priority, test )) def get_feedback(self): data = { 'appid': self.application_id, } command = COMMAND_FEEDBACK + json.dumps(data, ensure_ascii=True) self.communicator.send(command) return json.loads(self.communicator.recv()) @staticmethod def _check_token(token): if len(token) != DEVICE_TOKEN_LENGTH: raise ValueError('Invalid token length %s' % token) @staticmethod def _check_alert(alert): if (alert is None or isinstance(alert, basestring)): return elif isinstance(alert, dict): if len(set(alert.keys()) - JSON_ALERT_KEY_SET) > 0: raise ValueError('JSON Alert allows only' 'body, action_loc_key, loc_key, loc_args, launch_image') else: raise ValueError('alert must be string, unicode or dict type') @staticmethod def _check_custom(custom): if custom is None or isinstance(custom, dict): return raise ValueError('custom must be dict type') def _serialize(self, command, token, alert, sound, badge, content_available, custom, expiry, priority, test): """ 送信データのフォーマット """ aps = {} if alert is not None: aps['alert'] = alert if sound is not None: aps['sound'] = sound if badge is not None: aps['badge'] = badge if content_available is True: aps['content_available'] = True if custom is not None: aps['custom'] = custom data = { 'appid': self.application_id, 'token': token, 'aps': aps, 'test': test } if expiry is not None: data['expiry'] = expiry if priority is not None: data['priority'] = priority return command + json.dumps(data, ensure_ascii=True) def __exit__(self, exc_type, exc_value, traceback): if exc_type: self._close() return False self.close() def close(self): start_time = time.time() self._close() end_time = time.time() if (end_time - start_time) > (FLUSH_TIMEOUT - 20)/1000.0: raise IOError('Timeout close operation. Some messages may not reached to server.') return True def _close(self): self.publisher.close() self.communicator.close() self.context.term()
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deep_ner/udpipe_data.py
bond005/elmo_ner
80
57974
<reponame>bond005/elmo_ner import re from typing import Set import spacy_udpipe from spacy_udpipe import UDPipeLanguage UNIVERSAL_POS_TAGS = ['ADJ', 'ADP', 'ADV', 'AUX', 'CCONJ', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X'] UNIVERSAL_DEPENDENCIES = ['acl', 'advcl', 'advmod', 'amod', 'appos', 'aux', 'auxpass', 'case', 'cc', 'ccomp', 'compound', 'conj', 'cop', 'csubj', 'csubjpass', 'dep', 'det', 'discourse', 'dislocated', 'dobj', 'expl', 'fixed', 'flat', 'foreign', 'goeswith', 'gov', 'iobj', 'list', 'mark', 'mwe', 'name', 'neg', 'nmod', 'nsubj', 'nsubjpass', 'nummod', 'obj', 'obl', 'orphan', 'parataxis', 'pass', 'punct', 'relcl', 'remnant', 'reparandum', 'root', 'vocative', 'xcomp'] def create_udpipe_pipeline(lang: str) -> UDPipeLanguage: try: pipeline = spacy_udpipe.load(lang) except: spacy_udpipe.download(lang) pipeline = spacy_udpipe.load(lang) if pipeline is None: del pipeline raise ValueError('The `{0}` language cannot be loaded for the UDPipe!') return pipeline def prepare_dependency_tag(source_tag: str) -> Set[str]: re_for_splitting = re.compile('[:\-]+') tags = {source_tag.lower().replace(':', '').replace('-', '')} for cur in filter(lambda it2: len(it2) > 0, map(lambda it1: it1.strip().lower(), re_for_splitting.split(source_tag))): tags.add(cur) return tags
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telegram_bot/bot.py
HikkaV/Neural-conversational-bot
1
93084
from model.seq2seq import Seq2Seq from model.decoding_techniques import BeamSearchDecoder, GreedyDecoder, NucleusDecoder from utils.model_utils import predict_beam, predict_greedy, predict_nucleus, process_sentence import telebot from telebot import types import logging logger = telebot.logger telebot.logger.setLevel(logging.DEBUG) class TelegramBot: BOT = telebot.TeleBot("1716865383:AAGR9GxP_cOefogxRgqN-b1NbXAQcgt-GDE") def __init__(self, model: Seq2Seq, token_mapping: dict, start_token: int, end_token: int, max_len: int = 10 ): self.decoder = model.decoder self.encoder = model.encoder self.token_mapping = token_mapping self.inverse_token_mapping = dict((v, k) for k, v in token_mapping.items()) self.max_len = max_len self.greedy_decoder = GreedyDecoder(self.encoder, self.decoder, start_token, end_token, max_len) self.beam_decoder = BeamSearchDecoder(self.encoder, self.decoder, start_token, end_token, max_len) self.nucleus_decoder = NucleusDecoder(self.encoder, self.decoder, start_token, end_token, max_len) self.keys_decoding = self.set_keys_decoding() self.predict = predict_greedy self.decoding_strategy = self.greedy_decoder self.dict_params = {"beam": {"beam_size": 7}, "nucleus": {"top_p": 0.95, "temperature": 1}, } self.setting_message = False self.setting_to_change = None self.decoding_type = "greedy" @self.BOT.callback_query_handler(func=lambda call: True) def callback_worker(call): if call.data in ['beam', 'nucleus', 'greedy']: if call.data == 'beam': self.predict = predict_beam self.decoding_strategy = self.beam_decoder elif call.data == 'nucleus': self.predict = predict_nucleus self.decoding_strategy = self.nucleus_decoder elif call.data == 'greedy': self.predict = predict_greedy self.decoding_strategy = self.greedy_decoder self.decoding_type = call.data else: self.setting_to_change = call.data @self.BOT.message_handler(content_types=['text'], ) def reply(message): if message.text == "/help": self.BOT.send_message(message.from_user.id, "Hello. In order to start the bot please write /start.") elif message.text == "/start" or message.text == "/choose": self.BOT.send_message(message.from_user.id, "Please choose type of decoding and then start the conversation.", reply_markup=self.keys_decoding) elif message.text == "/show_default": if self.decoding_type != 'greedy': self.BOT.send_message(message.from_user.id, "Default settings for used decoding strategy ({0}) are the following : {1}" \ .format(self.decoding_type, self.dict_params[self.decoding_type])) else: self.BOT.send_message(message.from_user.id, "No settings for greedy decoding") elif message.text == '/change_default': if self.decoding_type != 'greedy': keyboard = self.set_keys_options() self.BOT.send_message(message.from_user.id, "Please choose the parameter to change and write the new value.", reply_markup=keyboard) self.setting_message = True else: self.BOT.send_message(message.from_user.id, "No settings for greedy decoding.") elif self.setting_message: try: param = float(message.text) except Exception as e: param = None if param: initial_param = param param = max(param, 0) if self.decoding_type == 'nucleus': param = min(param, 1.0) param = max(param, 0.1) else: param = max(int(param), 2) self.dict_params[self.decoding_type][self.setting_to_change] = param if initial_param != param: self.BOT.send_message(message.from_user.id, "Successfully set value of {0} " "for param {1}. " "Initial param passed by user ({1}={2}) " "was changed to fir constraints. ".format(param, self.setting_to_change, initial_param)) else: self.BOT.send_message(message.from_user.id, "Successfully set value of {0} " "for param {1}".format(param, self.setting_to_change)) else: self.BOT.send_message(message.from_user.id, "The error occurred, please try again with " "command /change_default. ") self.setting_message = False else: processed_sentence = process_sentence(message.text, self.token_mapping, max_len=self.max_len) if self.decoding_type == 'beam': result = self.predict(self.decoding_strategy, processed_sentence, self.inverse_token_mapping, beam_size=self.dict_params[self.decoding_type]['beam_size']) elif self.decoding_type == 'nucleus': result = self.predict(self.decoding_strategy, processed_sentence, self.inverse_token_mapping, top_p=self.dict_params[self.decoding_type]['top_p'], temperature=self.dict_params[self.decoding_type]['temperature']) else: result = self.predict(self.decoding_strategy, processed_sentence, self.inverse_token_mapping) self.BOT.send_message(message.from_user.id, result) def set_keys_decoding(self): keyboard = types.InlineKeyboardMarkup() key_beam = types.InlineKeyboardButton(text='Beam search decoder', callback_data='beam') keyboard.add(key_beam) key_nucleus = types.InlineKeyboardButton(text='Nucleus decoder', callback_data='nucleus') keyboard.add(key_nucleus) key_greedy = types.InlineKeyboardButton(text='Greedy decoder', callback_data='greedy') keyboard.add(key_greedy) return keyboard def set_keys_options(self): keyboard = types.InlineKeyboardMarkup() possible_keys = self.dict_params[self.decoding_type] for key in possible_keys.keys(): keyboard.add(types.InlineKeyboardButton(text=key, callback_data=key)) return keyboard def start(self): self.BOT.polling(none_stop=True, interval=0)
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01_aat-ebook-full-source-code-20160430/chapter4/bayes-binomial-mcmc.py
UpSea/midProjects
1
101134
import matplotlib.pyplot as plt import numpy as np import pymc3 import scipy.stats as stats plt.style.use("ggplot") # Parameter values for prior and analytic posterior n = 50 z = 10 alpha = 12 beta = 12 alpha_post = 22 beta_post = 52 # How many samples to carry out for MCMC iterations = 100000 # Use PyMC3 to construct a model context basic_model = pymc3.Model() with basic_model: # Define our prior belief about the fairness # of the coin using a Beta distribution theta = pymc3.Beta("theta", alpha=alpha, beta=beta) # Define the Bernoulli likelihood function y = pymc3.Binomial("y", n=n, p=theta, observed=z) # Carry out the MCMC analysis using the Metropolis algorithm # Use Maximum A Posteriori (MAP) optimisation as initial value for MCMC start = pymc3.find_MAP() # Use the Metropolis algorithm (as opposed to NUTS or HMC, etc.) step = pymc3.Metropolis() # Calculate the trace trace = pymc3.sample(iterations, step, start, random_seed=1, progressbar=True) # Plot the posterior histogram from MCMC analysis bins=50 plt.hist( trace["theta"], bins, histtype="step", normed=True, label="Posterior (MCMC)", color="red" ) # Plot the analytic prior and posterior beta distributions x = np.linspace(0, 1, 100) plt.plot( x, stats.beta.pdf(x, alpha, beta), "--", label="Prior", color="blue" ) plt.plot( x, stats.beta.pdf(x, alpha_post, beta_post), label='Posterior (Analytic)', color="green" ) # Update the graph labels plt.legend(title="Parameters", loc="best") plt.xlabel("$\\theta$, Fairness") plt.ylabel("Density") plt.show() # Show the trace plot pymc3.traceplot(trace) plt.show()
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utils/files.py
sno2/Payment-Processor
80
171124
<filename>utils/files.py import csv import json def read_csv(*, file): """ Read CSV file as list of dictionaries """ results = [] with open(file) as f: f_csv = csv.DictReader(f) for row in f_csv: results.append(row) return results def write_json(*, file, data): """ Write JSON file """ with open(file, 'w') as f: json.dump(data, f, indent=2)
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src/rogerthat/utils/base65.py
goubertbrent/oca-backend
0
78559
# -*- coding: utf-8 -*- # Copyright 2020 Green Valley Belgium NV # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # @@license_version:1.7@@ # Outcome of this encoding is url-friendly and does not have to be url-encoded # resulting in shorter urls in sms messages from mcfw.rpc import arguments, returns try: from cStringIO import StringIO except ImportError: from StringIO import StringIO _BASE65_MAPPING = "-.1032547698ACBEDGFIHKJMLONQPSRUTWVYXZ_acbedgfihkjmlonqpsrutwvyxz" def _init_reverse_mapping(): rm = [None for _ in xrange(256)] i = 0 for c in _BASE65_MAPPING: rm[ord(c)] = i i += 1 return rm _BASE65_REVERSE_MAPPING = _init_reverse_mapping() del _init_reverse_mapping @returns(str) @arguments(val=int) def encode_int(val): res = StringIO() while val > 0: res.write(_BASE65_MAPPING[val % 65]) val /= 65 return res.getvalue() @returns(int) @arguments(val=str) def decode_int(val): res = 0 val = list(val) val.reverse() for c in val: res = _BASE65_REVERSE_MAPPING[ord(c)] + res * 65 return res
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slaid/classifiers/__init__.py
mdrio/slaid
0
94829
from slaid.classifiers.base import *
[ 1, 515, 8370, 333, 29889, 1990, 14903, 29889, 3188, 1053, 334, 13, 2 ]
ArtGAN/data/ingest_stl10.py
rh01/caffe-model-for-category-artgan
304
29815
from configargparse import ArgParser from PIL import Image import logging import numpy as np import os def transform_and_save(img_arr, output_filename): """ Takes an image and optionally transforms it and then writes it out to output_filename """ img = Image.fromarray(img_arr) img.save(output_filename) class Ingest(object): def __init__(self, input_dir, out_dir, target_size=96, skipimg=False): np.random.seed(0) self.skipimg = skipimg self.out_dir = out_dir self.input_dir = input_dir self.manifests = dict() for setn in ('train', 'val'): self.manifests[setn] = os.path.join(self.out_dir, '{}-index.csv'.format(setn)) self.target_size = target_size self.trainpairlist = {} self.valpairlist = {} self.labels = range(10) if not os.path.exists(self.out_dir): os.mkdir(self.out_dir) self.outimgdir = os.path.join(self.out_dir, 'images') if not os.path.exists(self.outimgdir): os.mkdir(self.outimgdir) os.mkdir(os.path.join(self.outimgdir, 'train')) os.mkdir(os.path.join(self.outimgdir, 'val')) self.outlabeldir = os.path.join(self.out_dir, 'labels') if not os.path.exists(self.outlabeldir): os.mkdir(self.outlabeldir) def collectdata(self,): print 'Start Collect Data...' train_x_path = os.path.join(self.input_dir, 'train_X.bin') train_y_path = os.path.join(self.input_dir, 'train_y.bin') test_x_path = os.path.join(self.input_dir, 'test_X.bin') test_y_path = os.path.join(self.input_dir, 'test_y.bin') train_xf = open(train_x_path, 'rb') train_x = np.fromfile(train_xf, dtype=np.uint8) train_x = np.reshape(train_x, (-1, 3, 96, 96)) train_x = np.transpose(train_x, (0, 3, 2, 1)) train_yf = open(train_y_path, 'rb') train_y = np.fromfile(train_yf, dtype=np.uint8) test_xf = open(test_x_path, 'rb') test_x = np.fromfile(test_xf, dtype=np.uint8) test_x = np.reshape(test_x, (-1, 3, 96, 96)) test_x = np.transpose(test_x, (0, 3, 2, 1)) test_yf = open(test_y_path, 'rb') test_y = np.fromfile(test_yf, dtype=np.uint8) idx = np.zeros(10, dtype=np.int) for i in xrange(train_x.shape[0]): outdir = os.path.join(self.outimgdir, 'train', str(train_y[i]-1)) if not os.path.exists(outdir): os.mkdir(outdir) if not self.skipimg: transform_and_save(img_arr=train_x[i], output_filename=os.path.join(outdir, str(idx[train_y[i]-1]) + '.jpg')) self.trainpairlist[os.path.join('images', 'train', str(train_y[i]-1), str(idx[train_y[i]-1]) + '.jpg')] = \ os.path.join('labels', str(train_y[i] - 1) + '.txt') idx[train_y[i]-1] += 1 idx = np.zeros(10, dtype=np.int) for i in xrange(test_x.shape[0]): outdir = os.path.join(self.outimgdir, 'val', str(test_y[i]-1)) if not os.path.exists(outdir): os.mkdir(outdir) if not self.skipimg: transform_and_save(img_arr=test_x[i], output_filename=os.path.join(outdir, str(idx[test_y[i]-1]) + '.jpg')) self.valpairlist[os.path.join('images', 'val', str(test_y[i]-1), str(idx[test_y[i]-1]) + '.jpg')] = \ os.path.join('labels', str(test_y[i] - 1) + '.txt') idx[test_y[i]-1] += 1 print 'Finished Collect Data...' def write_label(self, ): for i, l in enumerate(self.labels): sdir = os.path.join(self.outlabeldir, str(i) + '.txt') np.savetxt(sdir, [l], '%d') def run(self): """ resize images then write manifest files to disk. """ self.write_label() self.collectdata() records = [(fname, tgt) for fname, tgt in self.trainpairlist.items()] np.savetxt(self.manifests['train'], records, fmt='%s,%s') records = [(fname, tgt) for fname, tgt in self.valpairlist.items()] np.savetxt(self.manifests['val'], records, fmt='%s,%s') class IngestUnlabeled(object): def __init__(self, input_dir, out_dir, target_size=96, skipimg=False): np.random.seed(0) self.skipimg = skipimg self.out_dir = out_dir self.input_dir = input_dir self.manifests = dict() self.manifests = os.path.join(self.out_dir, 'unlabeled-index.csv') self.target_size = target_size self.trainpairlist = {} if not os.path.exists(self.out_dir): os.mkdir(self.out_dir) self.outimgdir = os.path.join(self.out_dir, 'images') if not os.path.exists(self.outimgdir): os.mkdir(self.outimgdir) self.unlabeldir = os.path.join(self.outimgdir, 'unlabeled') if not os.path.exists(self.unlabeldir): os.mkdir(self.unlabeldir) def collectdata(self,): print 'Start Collect Data...' train_x_path = os.path.join(self.input_dir, 'unlabeled_X.bin') train_xf = open(train_x_path, 'rb') train_x = np.fromfile(train_xf, dtype=np.uint8) train_x = np.reshape(train_x, (-1, 3, 96, 96)) train_x = np.transpose(train_x, (0, 3, 2, 1)) idx = 0 for i in xrange(train_x.shape[0]): if not self.skipimg: transform_and_save(img_arr=train_x[i], output_filename=os.path.join(self.unlabeldir, str(idx) + '.jpg')) self.trainpairlist[os.path.join('images', 'unlabeled', str(idx) + '.jpg')] = 'labels/11.txt' idx += 1 print 'Finished Collect Data...' def write_label(self, ): sdir = os.path.join(self.out_dir, 'labels', '11.txt') np.savetxt(sdir, [11], '%d') def run(self): """ resize images then write manifest files to disk. """ self.write_label() self.collectdata() records = [(fname, tgt) for fname, tgt in self.trainpairlist.items()] np.savetxt(self.manifests, records, fmt='%s,%s') if __name__ == "__main__": parser = ArgParser() parser.add_argument('--input_dir', help='Directory to find input', default='/hdd/Dataset/STL10') parser.add_argument('--out_dir', help='Directory to write ingested files', default='/home/william/PyProjects/TFcodes/dataset/stl10') parser.add_argument('--target_size', type=int, default=96, help='Size in pixels to scale shortest side DOWN to (0 means no scaling)') parser.add_argument('--skipImg', type=bool, default=False, help='True to skip processing and copying images') args = parser.parse_args() logger = logging.getLogger(__name__) bw = Ingest(input_dir=args.input_dir, out_dir=args.out_dir, target_size=args.target_size, skipimg=args.skipImg) # bw = IngestUnlabeled(input_dir=args.input_dir, out_dir=args.out_dir, target_size=args.target_size, skipimg=args.skipImg) bw.run()
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stripe/version.py
jameshageman-stripe/stripe-python
7
163348
VERSION = '2.17.0'
[ 1, 478, 1001, 13381, 353, 525, 29906, 29889, 29896, 29955, 29889, 29900, 29915, 13, 2 ]
video/management/commands/loadvideos.py
chandojo/climbbeta
1
148267
<reponame>chandojo/climbbeta<filename>video/management/commands/loadvideos.py from django.core import management from django.core.management.base import BaseCommand, CommandError from django.core.management.commands import loaddata from datetime import date class Command(BaseCommand): help = "Uploads video fixtures to database" def handle(self, *args, **options): today = str(date.today()) return management.call_command('loaddata', today + '.json')
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density-based/train.py
ramonpeter/UnbinnedMeasurements
0
13154
import tensorflow as tf import pandas as pd import numpy as np import sys import time from cflow import ConditionalFlow from MoINN.modules.subnetworks import DenseSubNet from utils import train_density_estimation, plot_loss, plot_tau_ratio # import data tau1_gen = np.reshape(np.load("../data/tau1s_Pythia_gen.npy"), (-1,1)) tau2_gen = np.reshape(np.load("../data/tau2s_Pythia_gen.npy"), (-1,1)) tau1_sim = np.reshape(np.load("../data/tau1s_Pythia_sim.npy"), (-1,1)) tau2_sim = np.reshape(np.load("../data/tau2s_Pythia_sim.npy"), (-1,1)) data_gen = tf.convert_to_tensor(np.concatenate([tau1_gen,tau2_gen], axis=-1), dtype=tf.float32) data_sim = tf.convert_to_tensor(np.concatenate([tau1_sim,tau2_sim], axis=-1), dtype=tf.float32) train_gen, test_gen = np.split(data_gen, 2) train_sim, test_sim = np.split(data_sim, 2) # Get the flow meta = { "units": 16, "layers": 4, "initializer": "glorot_uniform", "activation": "leakyrelu", } cflow = ConditionalFlow(dims_in=[2], dims_c=[[2]], n_blocks=12, subnet_meta=meta, subnet_constructor=DenseSubNet) # train the network EPOCHS = 50 BATCH_SIZE = 1000 LR = 5e-3 DECAY_RATE=0.1 ITERS = len(train_gen)//BATCH_SIZE DECAY_STEP=ITERS #Prepare the tf.dataset train_dataset = tf.data.Dataset.from_tensor_slices((train_gen, train_sim)) train_dataset = train_dataset.shuffle(buffer_size=500000).batch(BATCH_SIZE).prefetch(tf.data.AUTOTUNE) lr_schedule = tf.keras.optimizers.schedules.InverseTimeDecay(LR, DECAY_STEP, DECAY_RATE) opt = tf.keras.optimizers.Adam(lr_schedule) train_losses = [] #train_all = np.concatenate([train_gen, train_sim], axis=-1) start_time = time.time() for e in range(EPOCHS): batch_train_losses = [] # Iterate over the batches of the dataset. for step, (batch_gen, batch_sim) in enumerate(train_dataset): batch_loss = train_density_estimation(cflow, opt, batch_gen, [batch_sim]) batch_train_losses.append(batch_loss) train_loss = tf.reduce_mean(batch_train_losses) train_losses.append(train_loss) if (e + 1) % 1 == 0: # Print metrics print( "Epoch #{}: Loss: {}, Learning_Rate: {}".format( e + 1, train_losses[-1], opt._decayed_lr(tf.float32) ) ) end_time = time.time() print("--- Run time: %s hour ---" % ((end_time - start_time)/60/60)) print("--- Run time: %s mins ---" % ((end_time - start_time)/60)) print("--- Run time: %s secs ---" % ((end_time - start_time))) # Make plots and sample plot_loss(train_losses, name="Log-likelihood", log_axis=False) detector = tf.constant(test_sim, dtype=tf.float32) unfold_gen = cflow.sample(int(5e5),[detector]) plot_tau_ratio(test_gen, unfold_gen, detector, name="tau_ratio") unfold_gen = {} for i in range(10): unfold_gen[i] = cflow.sample(int(5e5),[detector]) unfold_pythia = np.stack([unfold_gen[i] for i in range(10)]) np.save("inn_pythia",unfold_pythia)
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lesson_7/Pro.py
windn19/Python_Developer
1
112778
<reponame>windn19/Python_Developer from docx.shared import Cm # импорт из библиотеки класса для обработки изображений from docxtpl import DocxTemplate, InlineImage # импорт из библиотеки классов генерации doc документов из шаблонов и включения в них изображений import csv # подключение библиотеки для работы с csv import json # подключение библиотеки для работы с json from time import time # импорт метода для работы со временем def get_context(result): """ возвращает словарь значений, которые будут отправлены в шаблон result: данные для отправки в документ """ return { 'dates': result } def from_template(result, template, signature, outfile): """ Создание документа и включение в него рисунка result_sku_list: данные для передачи в документ template: файл шаблона doc-документа signature: файл рисунка для документа outfile: файл для сохранения готового документа """ template = DocxTemplate(template) # создание шаблона документа context = get_context(result) # получение данных в виде словаря img_size = Cm(8) # преобразование изображения к нужному размеру acc = InlineImage(template, signature, img_size) # создания объекта класса для вставки в документ context['acc'] = acc # добавление объекта с рисунком в словарь данных template.render(context) # создание шаблона на основе словаря данных template.save(outfile) # сохранение его в файле. def generate_report(result, outfile): """ Создание doc-документа для данных result: данные для передачи в документ outfile: файл для сохранения готового документа """ template = 'repor1.docx' # шаблон документа signature = 'IiGd2vv6-Cc.jpg' # изображение для вставки в шаблон from_template(result, template, signature, outfile) # вызов метода для генератора документа def create_csv(data, file): """ Создание csv файла data: данные, которые нужно записать file: файл, куда нужно записать данные """ t = time() # запоминание момента начала работы метода with open(file, mode='w') as f: # открытие файла для записи writer = csv.writer(f, delimiter=';') # создание объекта для записи данных с разделителем ";" writer.writerows(data) # запись данных в файл print(f'Writing complete from {round((time() - t) * 100, 2)} миллисекунд') # вывод времени работы метода в миллисекундах def create_json(csv_file, json_file): """ создание json файла из cvs файла csv_file: файл источник данных json_file: файл получатель данных """ t = time() # запоминание момента начала работы метода with open(csv_file, mode='r') as f: # открытие файла для чтения data = csv.DictReader(f, delimiter=';') # объявление объекта для чтения файла как словарь с разделителем ";" data = list(data) # превращение прочитанных данных в словарь. with open('example.json', mode='w') as f: # открытия файла для чтения json.dump(data, f) # загрузка данных в открытый файл print(f'Json done! {round((time() - t) * 100, 2)} миллисекунд') def gen_report(file, outfile): t = time() with open(file, mode='r') as f: data = json.load(f) generate_report(data, outfile) print(f'Report generated from {round((time() - t) * 100, 2)} милисекунд') # вывод времени работы метода в миллисекундах car_data = [['brand', 'sup', 'year', 'price'], # исходные данные ['Volvo', 1.5, 2017, 2345], ['Lada', 0.5, 2018, 5675], ['Audi', 2.0, 2018, 9877]] infile = 'example.csv' # файл для сохранения csv out_file = 'example.json' # файл для сохранения json create_csv(car_data, infile) # вызов метода для создания csv create_json(infile, out_file) # вызов метода для создания json gen_report(out_file, 'rep12.docx') # создание doc документа
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project_underhill/core/security.py
ErikSeguinte/project_underhill
0
67651
from passlib.context import CryptContext import secrets pwd_context = CryptContext(schemes=["argon2"], deprecated="auto") def get_random_string(): return secrets.token_urlsafe(5)
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EDScoutCore/JournalInterface.py
bal6765/ed-scout
0
5394
<gh_stars>0 from inspect import signature import json import time import os import glob import logging from pathlib import Path from watchdog.observers import Observer from watchdog.observers.polling import PollingObserver from watchdog.events import PatternMatchingEventHandler from EDScoutCore.FileSystemUpdatePrompter import FileSystemUpdatePrompter default_journal_path = os.path.join(str(Path.home()), "Saved Games\\Frontier Developments\\Elite Dangerous") journal_file_pattern = "journal.*.log" logger = logging.getLogger('JournalInterface') class JournalChangeIdentifier: def __init__(self, journal_path=default_journal_path): pass self.journals = {} self.journal_path = journal_path logger.debug(f"watching for journal changes in {self.journal_path}") self._init_journal_lists() self._new_journal_entry_callback = None self.latest_journal = self.identify_latest_journal() # Prompter is required to force the file system to do updates on some systems so we get regular updates from the # journal watcher. self.prompter = FileSystemUpdatePrompter(self.latest_journal) def identify_latest_journal(self): if len(self.journals.keys()) == 0: return None keys = sorted(self.journals.keys()) return keys[-1] def process_journal_change(self, changed_file): if changed_file != self.latest_journal: self.latest_journal = changed_file self.prompter.set_watch_file(self.latest_journal) new_size = os.stat(changed_file).st_size new_data = None # If the game was loaded after the scout it will start a new journal which we need to treat as unscanned. if changed_file not in self.journals: self.journals[changed_file] = 0 logger.debug(f'{changed_file} - Size change: {self.journals[changed_file]} to {new_size}') if new_size > 0: # Don't try and read it if this is the first notification (we seem to get two; one from the file being cleared). # Check how much it has grown and read the excess size_diff = new_size - self.journals[changed_file] if size_diff > 0: with open(changed_file, 'rb') as f: f.seek(-size_diff, os.SEEK_END) # Note minus sign new_data = f.read() entries = [] if new_data: new_journal_lines = JournalChangeIdentifier.binary_file_data_to_lines(new_data) try: for line in new_journal_lines: logger.debug(f'New journal entry detected: {line}') entry = json.loads(line) entry['type'] = "JournalEntry" # Add an identifier that's common to everything we shove down the outgoing pipe so the receiver can distiguish. entries.append(entry) logger.debug(f'Found {len(entries)} new entries') for entry in entries: yield entry self.journals[changed_file] = new_size except json.decoder.JSONDecodeError as e: logger.exception(e) @staticmethod def binary_file_data_to_lines(binary_data): as_ascii = binary_data.decode('UTF-8') all_lines = as_ascii.split("\r\n") all_lines.pop() # Drop the last empty line return all_lines def _init_journal_lists(self): journal_files = glob.glob(os.path.join(self.journal_path, journal_file_pattern)) for journal_file in journal_files: self.journals[journal_file] = os.stat(journal_file).st_size class JournalWatcher: def __init__(self, path=default_journal_path, force_polling=False): self.path = path self.force_polling = force_polling self._configure_watchers() def set_callback(self, on_journal_change): self.event_handler.set_callback(on_journal_change) def stop(self): self.observer.stop() self.observer.join() class _EntriesChangeHandler(PatternMatchingEventHandler): def __init__(self): super(JournalWatcher._EntriesChangeHandler, self).__init__( patterns=['*Journal*.log'], ignore_patterns=[], ignore_directories=True) self.on_journal_change = None def set_callback(self, on_new_journal_entry): self.on_journal_change = on_new_journal_entry def on_modified(self, event): changed_file = str(event.src_path) logger.debug("Journal change: " + changed_file) self.on_journal_change(changed_file) def on_created(self, event): file = str(event.src_path) logger.debug("Journal created: " + file) def on_deleted(self, event): file = str(event.src_path) logger.debug("Journal deleted: " + file) def on_moved(self, event): file = str(event.src_path) logger.debug("Journal moved: " + file) def _configure_watchers(self): self.event_handler = JournalWatcher._EntriesChangeHandler() if self.force_polling: self.observer = PollingObserver(0.25) # Poll every quarter of a second else: self.observer = Observer() self.observer.schedule(self.event_handler, self.path, recursive=False) self.observer.start() if __name__ == '__main__': def ReportJournalChange(journal_hange): print('New route detected:' + str(journal_hange)) journalWatcher = JournalWatcher() journalWatcher.set_callback(ReportJournalChange) print('running') try: while True: time.sleep(1) except KeyboardInterrupt: print('done') journalWatcher.stop()
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wisdem/test/test_optimization_drivers/test_dakota_driver.py
johnjasa/WISDEM
81
10791
import unittest import numpy as np from openmdao.utils.assert_utils import assert_near_equal from wisdem.optimization_drivers.dakota_driver import DakotaOptimizer try: import dakota except ImportError: dakota = None @unittest.skipIf(dakota is None, "only run if Dakota is installed.") class TestDakotaOptimization(unittest.TestCase): def test_2D_opt_max_iterations(self): bounds = {"x": np.array([[0.0, 1.0], [0.0, 1.0]])} desvars = {"x": np.array([0.0, 0.25])} outputs = ["y"] template_dir = "template_dir/" model_string = "from weis.multifidelity.models.testbed_components import simple_2D_high_model as model" output_scalers = [1.0] options = {"method": "coliny_cobyla", "max_function_evaluations": 3} opt = DakotaOptimizer(template_dir) results = opt.optimize(desvars, outputs, bounds, model_string, output_scalers, options) assert_near_equal(np.min(np.array(results["y"])), -9.5) def test_2D_opt_EGO(self): bounds = {"x": np.array([[0.0, 1.0], [0.0, 1.0]])} desvars = {"x": np.array([0.0, 0.25])} outputs = ["y"] template_dir = "template_dir/" model_string = "from weis.multifidelity.models.testbed_components import simple_2D_high_model as model" output_scalers = [1.0] options = {"initial_samples": 5, "method": "efficient_global", "seed": 123456} opt = DakotaOptimizer(template_dir) results = opt.optimize(desvars, outputs, bounds, model_string, output_scalers, options) assert_near_equal(np.min(np.array(results["y"])), -9.999996864) def test_two_variables(self): bounds = {"x": np.array([[0.0, 1.0], [0.0, 1.0]]), "z": [1.0, 2.0]} desvars = {"x": np.array([0.0, 0.25]), "z": 1.5} outputs = ["y"] template_dir = "template_dir/" model_string = "from weis.multifidelity.models.testbed_components import simple_two_variable as model" output_scalers = [1.0] options = {"method": "coliny_cobyla", "max_function_evaluations": 3} opt = DakotaOptimizer(template_dir) results = opt.optimize(desvars, outputs, bounds, model_string, output_scalers, options) assert_near_equal(np.min(np.array(results["y"])), 1.0) def test_constraint(self): bounds = {"x": np.array([[0.0, 1.0], [0.0, 1.0]])} desvars = {"x": np.array([0.0, 0.25])} outputs = ["y", "con"] template_dir = "template_dir/" model_string = "from weis.multifidelity.models.testbed_components import simple_2D_low_model as model" output_scalers = [1.0, 1.0] options = {"method": "coliny_cobyla", "max_function_evaluations": 3} opt = DakotaOptimizer(template_dir) results = opt.optimize(desvars, outputs, bounds, model_string, output_scalers, options) assert_near_equal(np.min(np.array(results["y"])), 0.5) assert_near_equal(np.min(np.array(results["con"])), 0.0) if __name__ == "__main__": unittest.main()
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main.py
jonodrew/matchex
0
458
from __future__ import division from timeit import default_timer as timer import csv import numpy as np import itertools from munkres import Munkres, print_matrix, make_cost_matrix import sys from classes import * from functions import * from math import sqrt import Tkinter as tk import tkFileDialog as filedialog root = tk.Tk() root.withdraw() p_file = filedialog.askopenfilename(title='Please select the posting file') c_file = filedialog.askopenfilename(title='Please select the candidate file') """for use with /users/java_jonathan/postings_lge.csv and /Users/java_jonathan/candidates_lge.csv""" # p_file = raw_input("Please enter the path for the postings file: ") # p_file = p_file.strip() # c_file = raw_input("Please enter the path for the candidate file: ") # c_file = c_file.strip() start = timer() with open(p_file,'r') as f: #with open('/Users/Jonathan/Google Drive/CPD/Python/postings.csv','r') as f: reader = csv.reader(f) postingsAll = list(reader) with open(c_file,'r') as f: reader = csv.reader(f) candidatesAll = list(reader) """create empty lists to fill with lists of lists output by iterating function below""" names = [] totalMatrix = [] for list in candidatesAll: candidate = Candidate(*list) names.append(candidate.name) n = 0 for list in postingsAll: posting = Posting(*list) totalMatrix.append(matchDept(posting,candidate) + matchAnchor(posting,candidate) +matchLocation(posting,candidate) + matchCompetency(posting,candidate) + matchSkill(posting,candidate)+matchCohort(posting,candidate)) n += 1 l = len(names) names.extend([0] * (n-l)) totalMatrix.extend([0] * (n**2 - len(totalMatrix))) totalMatrix = np.asarray(totalMatrix) totalMatrix = np.reshape(totalMatrix,(n,-1)) #at this point the matrix is structured as candidates down and jobs across totalMatrix = np.transpose(totalMatrix) #now it's switched! totalMatrix = np.subtract(np.amax(totalMatrix),totalMatrix) totalMatrix = np.array(totalMatrix) minSuitability = 18 check = [] result = [] m = Munkres() indexes = m.compute(totalMatrix) #print_matrix(totalMatrix, msg='Lowest cost through this matrix:') total = 0.0 unhappy_candidates = 0 medium_candidates = 0 tenpc_candidates = 0 qs_candidates = 0 vs_candidates = 0 f = open('output.txt', 'w') for row, column in indexes: if column < l: value = totalMatrix[row][column] if value > minSuitability*0.9: tenpc_candidates += 1 elif value > minSuitability*0.75: medium_candidates += 1 elif value > minSuitability/2: unhappy_candidates += 1 elif value > minSuitability*0.25: qs_candidates += 1 elif value > minSuitability*0.1: vs_candidates += 1 total += value check.append(column+1) result.append((row,column)) f.write('For candidate %s: \nOptimal position: %d (score %s)\n' % (names[column], column+1, value)) else: pass globalSatisfaction = 100*(1-(total/(l*minSuitability))) print('Global satisfaction: %.2f%%' % globalSatisfaction) print('Candidates who are more than 90%% suitable: %d' % vs_candidates) print('Candidates who are more than 75%% suitable: %d' % qs_candidates) print('Candidates who are more than 50%% suitable: %d' % (l-unhappy_candidates)) print('Candidates who are more than 75%% unsuitable: %d' % medium_candidates) print('Candidates who are more than 90%% unsuitable: %d' % tenpc_candidates) #output from excel: correct = [1,3,5,9,10,2,4,8,6,7] #this function tests output above against Excel: #test(correct,check) topMatrix = topFive(names,totalMatrix) #print(topMatrix) np.savetxt('/Users/java_jonathan/test.csv',topMatrix, fmt='%s', delimiter=',', newline='\n', header='', footer='', comments='# ') np.savetxt('/Users/java_jonathan/test2.csv',totalMatrix, fmt='%s', delimiter=',', newline='\n', header='', footer='', comments='# ') end = timer() print(end-start) """ #posting = [Posting(*postingsAll)] #print(posting[0].anchor) #print(posting) #print(candidatesAll) #print(postingsAll) #print(postingsAll[0].name) #print(preferences) #print(postings) #split up files into relative blocks postCode = [lists[0] for lists in postings] postDept = [lists[1] for lists in postings] postAnchor = [lists[2] for lists in postings] postSkills = [lists[3:5] for lists in postings] postLocation = [lists[5] for lists in postings] postCompetencies = [lists[7:10] for lists in postings] postSecurity = [lists[10] for lists in postings] #with open('/Users/Jonathan/Google Drive/CPD/Python/candidates.csv','r') as f: #gives first column ie candidate a a=totalMatrix[:,[0]] #b = totalMatrix[:,[0]] #print(a) #converts 1D matrix to list for ease a = np.array(a).tolist() #print(a) #creates list called output containing rank of score output = [0] * len(a) for i, x in enumerate(sorted(range(len(a)), key=lambda y: a[y])): output[x] = i print(output) #creates tuples of rank, job and appends to list jobRank = [] # for rank, b in zip(output, postCode): # jobScore = (rank,b) # list(jobScore) # jobRank.append(jobScore) # print(jobRank) output = [0] * len(a) for i, x in enumerate(sorted(range(len(a)), key=lambda y: a[y])): output[x] = i print(output) # #print(a) # jobRank = sorted(jobRank, reverse=False) # print(jobRank) # print('For candidate a, the best position is %s') % (jobRank[0][1]) # print(candidate[0].skills) """
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day3/p1.py
pwicks86/adventofcode2015
0
5223
from collections import defaultdict f = open("input.txt") d = f.read() houses = defaultdict(int,{(0,0):1}) cur = [0,0] for c in d: if c == "<": cur[0] -= 1 if c == ">": cur[0] += 1 if c == "v": cur[1] += 1 if c == "^": cur[1] -= 1 houses[tuple(cur)]+=1 print(len(houses.keys()))
[ 1, 515, 16250, 1053, 2322, 8977, 13, 29888, 353, 1722, 703, 2080, 29889, 3945, 1159, 13, 29881, 353, 285, 29889, 949, 580, 13, 29882, 23676, 353, 2322, 8977, 29898, 524, 29892, 8001, 29900, 29892, 29900, 1125, 29896, 1800, 13, 2764, 353, 29871, 518, 29900, 29892, 29900, 29962, 13, 1454, 274, 297, 270, 29901, 13, 1678, 565, 274, 1275, 9872, 1115, 13, 4706, 3151, 29961, 29900, 29962, 22361, 29871, 29896, 13, 1678, 565, 274, 1275, 376, 29958, 1115, 13, 4706, 3151, 29961, 29900, 29962, 4619, 29871, 29896, 13, 1678, 565, 274, 1275, 376, 29894, 1115, 13, 4706, 3151, 29961, 29896, 29962, 4619, 29871, 29896, 13, 1678, 565, 274, 1275, 13898, 1115, 13, 4706, 3151, 29961, 29896, 29962, 22361, 29871, 29896, 13, 1678, 12955, 29961, 23583, 29898, 2764, 4638, 23661, 29896, 13, 13, 2158, 29898, 2435, 29898, 29882, 23676, 29889, 8149, 22130, 13, 2 ]