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, pr_1, pr_2, _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_pr1 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc, pr_1) dat_pr2 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc, pr_2) if os.path.isfile(dat_pr1) and os.path.isfile(dat_pr2): h5f_pr1 = h5py.File(dat_pr1, 'r') dat_pr1 = h5f_pr1[storage_dict[pack]][:] h5f_pr1.close() h5f_pr2 = h5py.File(dat_pr2, 'r') dat_pr2 = h5f_pr2[storage_dict[pack]][:] h5f_pr2.close() ratio_arr = [] if len(dat_pr1) == len(dat_pr2): for i, elem in enumerate(dat_pr1): ratio_arr.append(elem/float(dat_pr2[i])) elif len(dat_pr1) > len(dat_pr2): for i, elem in enumerate(dat_pr2): ratio_arr.append(dat_pr1[i]/float(elem)) elif len(dat_pr2) > len(dat_pr1): for i, elem in enumerate(dat_pr1): ratio_arr.append(elem/float(dat_pr2[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, cc, N_end, pr_1, pr_2): if task == "Heisenberg dynamics": task = "hdyn" elif task == "Random Quantum Circuit": task = "rqc" elif task == "Quantum Fourier Transform": task = "qft" if cc == "Singlethread": cc = 'singlethread' elif cc == "Multithread": cc = 'multithread' elif cc == "GPU": cc = 'gpu' if pr_1 == "Single": pr_1 = "sp" elif pr_1 == "Double": pr_1 = "dp" if pr_2 == "Single": pr_2 = "sp" elif pr_2 == "Double": pr_2 = "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, pr_1, pr_2, N_arr) # params = {'figure.figsize': (10, 10)} # plt.rcParams.update(params) # plt.imshow(data_mat, cmap='OrRd')#, vmin=-16, vmax=0) plt.imshow(data_mat, cmap='gist_heat_r', vmin=-1., vmax=10) 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", "Singlethread", 36, "Double", "Single") # abs_time_pack("Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread") def comp_time_pack(task_1, task_2, cc, N_end, pr_1, pr_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 == "Singlethread": cc = 'singlethread' elif cc == "Multithread": cc = 'multithread' elif cc == "GPU": cc = 'gpu' if pr_1 == "Single": pr_1 = "sp" elif pr_1 == "Double": pr_1 = "dp" if pr_2 == "Single": pr_2 = "sp" elif pr_2 == "Double": pr_2 = "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, pr_1, pr_2, N_arr_1)) data_mat_2 = np.matrix(_build_data_mat(task_2, cc, pr_1, pr_2, 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")