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import numpy as np
import h5py
import os
import mercury as mr
import sys
sys.path.append('/plot_scripts/')
from map_packages_colors_all import *
from plot_scripts_all import *
package_str = ['qiskit' , 'cirq', 'qsimcirq', 'pennylane', 'pennylane_l', 'qibo', 'qibojit', 'yao', 'quest', 'qulacs', 'intel_qs_cpp', 'projectq', 'svsim', 'hybridq', 'hiq', 'qcgpu', 'qrack_sch', 'cuquantum_qiskit', 'cuquantum_qsimcirq', 'qpanda', 'qpp', 'myqlm', 'myqlm_cpp', 'braket']
def _build_data_mat(task, cc_1, cc_2, pr, _n_arr):
dir = os.getcwd()
data_mat = np.log(np.zeros((len(package_str), len(_n_arr))))
for p_i, pack in enumerate(package_str):
dat_cc1 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc_1, pr)
dat_cc2 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc_2, pr)
if os.path.isfile(dat_cc1) and os.path.isfile(dat_cc2):
h5f_cc1 = h5py.File(dat_cc1, 'r')
dat_cc1 = h5f_cc1[storage_dict[pack]][:]
h5f_cc1.close()
h5f_cc2 = h5py.File(dat_cc2, 'r')
dat_cc2 = h5f_cc2[storage_dict[pack]][:]
h5f_cc2.close()
ratio_arr = []
if len(dat_cc1) == len(dat_cc2):
for i, elem in enumerate(dat_cc1):
ratio_arr.append(elem/float(dat_cc2[i]))
elif len(dat_cc1) > len(dat_cc2):
for i, elem in enumerate(dat_cc2):
ratio_arr.append(dat_cc1[i]/float(elem))
elif len(dat_cc2) > len(dat_cc1):
for i, elem in enumerate(dat_cc1):
ratio_arr.append(elem/float(dat_cc2[i]))
if len(_n_arr) > len(ratio_arr):
for r_i, rat in enumerate(ratio_arr):
data_mat[p_i, r_i] = rat
elif len(_n_arr) < len(ratio_arr):
for n_i in range(len(_n_arr)):
data_mat[p_i, n_i] = ratio_arr[n_i]
else:
for ri, rat_v in enumerate(ratio_arr):
data_mat[p_i, ri] = rat_v
return data_mat
def abs_time_pack(task, pr, N_end, cc_1, cc_2):
if task == "Heisenberg dynamics":
task = "hdyn"
elif task == "Random Quantum Circuit":
task = "rqc"
elif task == "Quantum Fourier Transform":
task = "qft"
if cc_1 == "Singlethread":
cc_1 = 'singlethread'
elif cc_1 == "Multithread":
cc_1 = 'multithread'
elif cc_1 == "GPU":
cc_1 = 'gpu'
if cc_2 == "Singlethread":
cc_2 = 'singlethread'
elif cc_2 == "Multithread":
cc_2 = 'multithread'
elif cc_2 == "GPU":
cc_2 = 'gpu'
if pr == "Single":
pr = "sp"
elif pr == "Double":
pr = "dp"
fig, ax = plt.subplots()
dir = os.getcwd()
if task == 'hdyn' or task == 'qft':
N_arr = np.arange(6, N_end, 2)
elif task == 'rqc':
N_arr = np.arange(12, N_end, 2)
# if not os.path.isfile(dat_fst) and not os.path.isfile(dat_fmt) and not os.path.isfile(dat_fgpu):
# return mr.Md(f"Precision {pr} possibly not supported")
data_mat = _build_data_mat(task, cc_1, cc_2, pr, N_arr)
# params = {'figure.figsize': (10, 10)}
# plt.rcParams.update(params)
# plt.imshow(data_mat, cmap='OrRd')#, vmin=-16, vmax=0)
if cc_1 == "singlethread" and cc_2 == "multithread":
plt.imshow(data_mat, cmap='gist_heat_r', vmin=-4.5, vmax=30)
#### ST/GPU
elif cc_1 == "singlethread" and cc_2 == "gpu":
# 800 single precision
# 550 double precision
plt.imshow(data_mat, cmap='gist_heat_r', vmin=-50., vmax=550)
### MT/GPU
elif cc_1 == "multithread" and cc_2 == "gpu":
plt.imshow(data_mat, cmap='gist_heat_r', vmin=-10., vmax=100)
plt.yticks(range(len(pkg_str)), package_str)
locs, labels = plt.yticks()
# plt.setp(labels, rotation=90)
plt.xticks(range(len(N_arr)), N_arr)
# locs, labels = plt.xticks()
ax.xaxis.set_major_locator(ticker.AutoLocator())
ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
plt.colorbar()
plt.tight_layout()
# plt.savefig(fn)
plt.show()
# abs_time_pack("Heisenberg dynamics", "Double", 36, "Singlethread", "Multithread")
# abs_time_pack("Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread")
def comp_time_pack(task_1, task_2, pr, N_end, cc_1, cc_2):
if task_1 == "Heisenberg dynamics":
task_1 = "hdyn"
elif task_1 == "Random Quantum Circuit":
task_1 = "rqc"
elif task_1 == "Quantum Fourier Transform":
task_1 = "qft"
if task_2 == "Heisenberg dynamics":
task_2 = "hdyn"
elif task_2 == "Random Quantum Circuit":
task_2 = "rqc"
elif task_2 == "Quantum Fourier Transform":
task_2 = "qft"
if cc_1 == "Singlethread":
cc_1 = 'singlethread'
elif cc_1 == "Multithread":
cc_1 = 'multithread'
elif cc_1 == "GPU":
cc_1 = 'gpu'
if cc_2 == "Singlethread":
cc_2 = 'singlethread'
elif cc_2 == "Multithread":
cc_2 = 'multithread'
elif cc_2 == "GPU":
cc_2 = 'gpu'
if pr == "Single":
pr = "sp"
elif pr == "Double":
pr = "dp"
fig, ax = plt.subplots()
dir = os.getcwd()
if task_1 == 'hdyn' or task_1 == 'qft':
N_arr_1 = np.arange(6, N_end, 2)
elif task_1 == 'rqc':
N_arr_1 = np.arange(12, N_end, 2)
if task_2 == 'hdyn' or task_2 == 'qft':
N_arr_2 = np.arange(6, N_end, 2)
elif task_2 == 'rqc':
N_arr_2 = np.arange(12, N_end, 2)
data_mat_1 = np.matrix(_build_data_mat(task_1, cc_1, cc_2, pr, N_arr_1))
data_mat_2 = np.matrix(_build_data_mat(task_2, cc_1, cc_2, pr, N_arr_2))
if N_arr_1[0] > N_arr_2[0]:
data_mat_2 = data_mat_2[:,3:]
elif N_arr_1[0] < N_arr_2[0]:
data_mat_1 = data_mat_1[:,3:]
# print(data_mat_1.shape)
# print(data_mat_2.shape)
# plt.imshow(data_mat_1, cmap='OrRd')#, vmin=-16, vmax=0)
# plt.show()
# plt.imshow(data_mat_2, cmap='OrRd')#, vmin=-16, vmax=0)
# plt.show()
comp_data_mat = np.zeros(data_mat_1.shape)
for ri in range(comp_data_mat.shape[0]):
for ci in range(comp_data_mat.shape[1]):
comp_data_mat[ri, ci] = data_mat_1[ri, ci]/data_mat_2[ri, ci]
# comp_data_mat = np.matrix(data_mat_1) - np.matrix(data_mat_2)
# params = {'figure.figsize': (10, 10)}
# plt.rcParams.update(params)
# plt.imshow(comp_data_mat, cmap='Spectral')#, vmin=-16, vmax=0)
plt.imshow(comp_data_mat, cmap='gist_heat_r', vmin=-0.5)
plt.yticks(range(len(pkg_str)), package_str)
locs, labels = plt.yticks()
# plt.setp(labels, rotation=90)
if N_arr_1[0] > N_arr_2[0]:
plt.xticks(range(len(N_arr_1)), N_arr_1)
elif N_arr_1[0] < N_arr_2[0]:
plt.xticks(range(len(N_arr_2)), N_arr_2)
else:
plt.xticks(range(len(N_arr_1)), N_arr_1)
# locs, labels = plt.xticks()
ax.xaxis.set_major_locator(ticker.AutoLocator())
ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
plt.colorbar()
plt.tight_layout()
# plt.savefig(fn)
plt.show()
# comp_time_pack("Heisenberg dynamics", "Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread")
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