From 487bf8840846b5d4d694b38985268c308aadb36e Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Wed, 18 Dec 2019 07:21:35 -0700 Subject: Refactor files --- lj_matrix/__init__.py | 22 ++++ lj_matrix/__main__.py | 238 ++++++++++++++++++++++++++++++++++++++++++++ lj_matrix/c_matrix.py | 179 +++++++++++++++++++++++++++++++++ lj_matrix/cholesky_solve.py | 64 ++++++++++++ lj_matrix/do_ml.py | 108 ++++++++++++++++++++ lj_matrix/frob_norm.py | 51 ++++++++++ lj_matrix/gauss_kernel.py | 49 +++++++++ lj_matrix/lj_matrix.py | 207 ++++++++++++++++++++++++++++++++++++++ lj_matrix/misc.py | 53 ++++++++++ lj_matrix/read_qm7_data.py | 144 +++++++++++++++++++++++++++ 10 files changed, 1115 insertions(+) create mode 100644 lj_matrix/__init__.py create mode 100644 lj_matrix/__main__.py create mode 100644 lj_matrix/c_matrix.py create mode 100644 lj_matrix/cholesky_solve.py create mode 100644 lj_matrix/do_ml.py create mode 100644 lj_matrix/frob_norm.py create mode 100644 lj_matrix/gauss_kernel.py create mode 100644 lj_matrix/lj_matrix.py create mode 100644 lj_matrix/misc.py create mode 100644 lj_matrix/read_qm7_data.py (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py new file mode 100644 index 000000000..48cd14913 --- /dev/null +++ b/lj_matrix/__init__.py @@ -0,0 +1,22 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py new file mode 100644 index 000000000..4e13f4995 --- /dev/null +++ b/lj_matrix/__main__.py @@ -0,0 +1,238 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import time +from multiprocessing import Process, Pipe +# import matplotlib.pyplot as plt +import pandas as pd +from lj_matrix.misc import printc +from lj_matrix.read_qm7_data import read_qm7_data +from lj_matrix.c_matrix import c_matrix_multiple +from lj_matrix.lj_matrix import lj_matrix_multiple +from lj_matrix.do_ml import do_ml + + +# Test +def ml(): + """ + Main function that does the whole ML process. + """ + # Initialization time. + init_time = time.perf_counter() + + # Data reading. + zi_data, molecules, nuclear_charge, energy_pbe0, energy_delta =\ + read_qm7_data() + + # Matrices calculation. + procs = [] + pipes = [] + + # cm_recv, cm_send = Pipe(False) + # p1 = Process(target=c_matrix_multiple, + # args=(molecules, nuclear_charge, cm_send)) + # procs.append(p1) + # pipes.append(cm_recv) + # p1.start() + + ljm_recv, ljm_send = Pipe(False) + p2 = Process(target=lj_matrix_multiple, + args=(molecules, nuclear_charge, ljm_send, 1, 0.25)) + procs.append(p2) + pipes.append(ljm_recv) + p2.start() + + # cm_data = pipes[0].recv() + ljm_data = pipes[0].recv() + + for proc in procs: + proc.join() + + # ML calculation. + procs = [] + # cm_pipes = [] + ljm_pipes = [] + for i in range(1500, 6500 + 1, 500): + # cm_recv, cm_send = Pipe(False) + # p1 = Process(target=do_ml, + # args=(cm_data, energy_pbe0, i, 'CM', cm_send)) + # procs.append(p1) + # cm_pipes.append(cm_recv) + # p1.start() + + ljm_recv, ljm_send = Pipe(False) + p2 = Process(target=do_ml, + args=(ljm_data, energy_pbe0, i, 'L-JM', ljm_send)) + procs.append(p2) + ljm_pipes.append(ljm_recv) + p2.start() + + # cm_bench_results = [] + ljm_bench_results = [] + for ljd_pipe in ljm_pipes: # cd_pipe, ljd_pipe in zip(cm_pipes, ljm_pipes): + # cm_bench_results.append(cd_pipe.recv()) + ljm_bench_results.append(ljd_pipe.recv()) + + for proc in procs: + proc.join() + + with open('data\\benchmarks.csv', 'a') as save_file: + # save_file.write(''.join(['ml_type,tr_size,te_size,kernel_s,', + # 'mae,time,lj_s,lj_e,date_ran\n'])) + date = '/'.join([str(field) for field in time.localtime()[:3][::-1]]) + for ljm in ljm_bench_results: # cm, ljm, in zip(cm_bench_results, ljm_bench_results): + # cm_text = ','.join([str(field) for field in cm])\ + # + ',' + date + '\n' + ljm_text = ','.join([str(field) for field in ljm])\ + + ',1,0.25,' + date + '\n' + # save_file.write(cm_text) + save_file.write(ljm_text) + + # End of program + end_time = time.perf_counter() + printc('Program took {:.4f} seconds.'.format(end_time - init_time), + 'CYAN') + + +def pl(): + """ + Function for plotting the benchmarks. + """ + # Original columns. + or_cols = ['ml_type', + 'tr_size', + 'te_size', + 'kernel_s', + 'mae', + 'time', + 'lj_s', + 'lj_e', + 'date_ran'] + # Drop some original columns. + dor_cols = ['te_size', + 'kernel_s', + 'time', + 'date_ran'] + + # Read benchmarks data and drop some columns. + data_temp = pd.read_csv('data\\benchmarks.csv',) + data = pd.DataFrame(data_temp, columns=or_cols) + data = data.drop(columns=dor_cols) + + # Get the data of the first benchmarks and drop unnecesary columns. + first_data = pd.DataFrame(data, index=range(0, 22)) + first_data = first_data.drop(columns=['lj_s', 'lj_e']) + + # Columns to keep temporarily. + fd_columns = ['ml_type', + 'tr_size', + 'mae'] + + # Create new dataframes for each matrix descriptor and fill them. + first_data_cm = pd.DataFrame(columns=fd_columns) + first_data_ljm = pd.DataFrame(columns=fd_columns) + for i in range(first_data.shape[0]): + temp_df = first_data.iloc[[i]] + if first_data.at[i, 'ml_type'] == 'CM': + first_data_cm = first_data_cm.append(temp_df) + else: + first_data_ljm = first_data_ljm.append(temp_df) + + # Drop unnecesary column and rename 'mae' for later use. + first_data_cm = first_data_cm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'cm_mae'}) + first_data_ljm = first_data_ljm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'ljm_mae'}) + # print(first_data_cm) + # print(first_data_ljm) + + # Get the cm data axis so it can be joined with the ljm data axis. + cm_axis = first_data_cm.plot(x='tr_size', + y='cm_mae', + kind='line') + # Get the ljm data axis and join it with the cm one. + plot_axis = first_data_ljm.plot(ax=cm_axis, + x='tr_size', + y='ljm_mae', + kind='line') + plot_axis.set_xlabel('tr_size') + plot_axis.set_ylabel('mae') + plot_axis.set_title('mae for different tr_sizes') + # Get the figure and save it. + # plot_axis.get_figure().savefig('.figs\\mae_diff_tr_sizes.pdf') + + # Get the rest of the benchmark data and drop unnecesary column. + new_data = data.drop(index=range(0, 22)) + new_data = new_data.drop(columns=['ml_type']) + + # Get the first set and rename it. + nd_first = first_data_ljm.rename(columns={'ljm_mae': '1, 1'}) + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(22, 99, 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(s)') + + last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_s.pdf') + + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(99, data.shape[0], 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(e)') + + last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_e.pdf') + + +if __name__ == '__main__': + # ml() + pl() diff --git a/lj_matrix/c_matrix.py b/lj_matrix/c_matrix.py new file mode 100644 index 000000000..f40a18c68 --- /dev/null +++ b/lj_matrix/c_matrix.py @@ -0,0 +1,179 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import time +from lj_matrix.misc import printc +import math +import numpy as np +from numpy.linalg import eig + + +def c_matrix(mol_data, + nc_data, + max_len=25, + as_eig=True, + bohr_radius_units=False): + """ + Creates the Coulomb Matrix from the molecule data given. + mol_data: molecule data, matrix of atom coordinates. + nc_data: nuclear charge data, array of atom data. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + """ + if bohr_radius_units: + conversion_rate = 0.52917721067 + else: + conversion_rate = 1 + + mol_n = len(mol_data) + mol_nr = range(mol_n) + + if not mol_n == len(nc_data): + print(''.join(['Error. Molecule matrix dimension is different ', + 'than the nuclear charge array dimension.'])) + else: + if max_len < mol_n: + print(''.join(['Error. Molecule matrix dimension (mol_n) is ', + 'greater than max_len. Using mol_n.'])) + max_len = None + + if max_len: + cm = np.zeros((max_len, max_len)) + ml_r = range(max_len) + + # Actual calculation of the coulomb matrix. + for i in ml_r: + if i < mol_n: + x_i = mol_data[i, 0] + y_i = mol_data[i, 1] + z_i = mol_data[i, 2] + Z_i = nc_data[i] + else: + break + + for j in ml_r: + if j < mol_n: + x_j = mol_data[j, 0] + y_j = mol_data[j, 1] + z_j = mol_data[j, 2] + Z_j = nc_data[j] + + x = (x_i-x_j)**2 + y = (y_i-y_j)**2 + z = (z_i-z_j)**2 + + if i == j: + cm[i, j] = (0.5*Z_i**2.4) + else: + cm[i, j] = (conversion_rate*Z_i*Z_j/math.sqrt(x + + y + + z)) + else: + break + + # Now the value will be returned. + if as_eig: + cm_sorted = np.sort(eig(cm)[0])[::-1] + # Thanks to SO for the following lines of code. + # https://stackoverflow.com/a/43011036 + + # Keep zeros at the end. + mask = cm_sorted != 0. + f_mask = mask.sum(0, keepdims=1) >\ + np.arange(cm_sorted.shape[0]-1, -1, -1) + + f_mask = f_mask[::-1] + cm_sorted[f_mask] = cm_sorted[mask] + cm_sorted[~f_mask] = 0. + + return cm_sorted + + else: + return cm + + else: + cm_temp = [] + # Actual calculation of the coulomb matrix. + for i in mol_nr: + x_i = mol_data[i, 0] + y_i = mol_data[i, 1] + z_i = mol_data[i, 2] + Z_i = nc_data[i] + + cm_row = [] + for j in mol_nr: + x_j = mol_data[j, 0] + y_j = mol_data[j, 1] + z_j = mol_data[j, 2] + Z_j = nc_data[j] + + x = (x_i-x_j)**2 + y = (y_i-y_j)**2 + z = (z_i-z_j)**2 + + if i == j: + cm_row.append(0.5*Z_i**2.4) + else: + cm_row.append(conversion_rate*Z_i*Z_j/math.sqrt(x + + y + + z)) + + cm_temp.append(np.array(cm_row)) + + cm = np.array(cm_temp) + # Now the value will be returned. + if as_eig: + return np.sort(eig(cm)[0])[::-1] + else: + return cm + + +def c_matrix_multiple(mol_data, + nc_data, + pipe=None, + max_len=25, + as_eig=True, + bohr_radius_units=False): + """ + Calculates the Coulomb Matrix of multiple molecules. + mol_data: molecule data, matrix of atom coordinates. + nc_data: nuclear charge data, array of atom data. + pipe: for multiprocessing purposes. Sends the data calculated + through a pipe. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + """ + printc('Coulomb Matrices calculation started.', 'CYAN') + tic = time.perf_counter() + + cm_data = np.array([c_matrix(mol, nc, max_len, as_eig, bohr_radius_units) + for mol, nc in zip(mol_data, nc_data)]) + + toc = time.perf_counter() + printc('\tCM calculation took {:.4f} seconds.'.format(toc - tic), 'GREEN') + + if pipe: + pipe.send(cm_data) + + return cm_data diff --git a/lj_matrix/cholesky_solve.py b/lj_matrix/cholesky_solve.py new file mode 100644 index 000000000..bc6a572a3 --- /dev/null +++ b/lj_matrix/cholesky_solve.py @@ -0,0 +1,64 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import numpy as np +from numpy.linalg import cholesky + + +def cholesky_solve(K, y): + """ + Applies Cholesky decomposition to obtain the 'alpha coeficients'. + K: kernel. + y: known parameters. + """ + # The initial mathematical problem is to solve Ka=y. + + # First, add a small lambda value. + K[np.diag_indices_from(K)] += 1e-8 + + # Get the Cholesky decomposition of the kernel. + L = cholesky(K) + size = len(L) + + # Solve Lx=y for x. + x = np.zeros(size) + x[0] = y[0] / L[0, 0] + for i in range(1, size): + temp_sum = 0.0 + for j in range(i): + temp_sum += L[i, j] * x[j] + x[i] = (y[i] - temp_sum) / L[i, i] + + # Now, solve LTa=x for a. + L2 = L.T + a = np.zeros(size) + a_ms = size - 1 + a[a_ms] = x[a_ms] / L2[a_ms, a_ms] + # Because of the form of L2 (upper triangular matriz), an inversion of + # range() needs to be done. + for i in range(0, a_ms)[::-1]: + temp_sum = 0.0 + for j in range(i, size)[::-1]: + temp_sum += L2[i, j] * a[j] + a[i] = (x[i] - temp_sum) / L2[i, i] + + return a diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py new file mode 100644 index 000000000..acf5455f4 --- /dev/null +++ b/lj_matrix/do_ml.py @@ -0,0 +1,108 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import time +from misc import printc +import numpy as np +from lj_matrix.gauss_kernel import gauss_kernel +from lj_matrix.cholesky_solve import cholesky_solve + + +def do_ml(desc_data, + energy_data, + training_size, + desc_type=None, + pipe=None, + test_size=None, + sigma=1000.0, + show_msgs=True): + """ + Does the ML methodology. + desc_data: descriptor (or representation) data. + energy_data: energy data associated with desc_data. + training_size: size of the training set to use. + desc_type: string with the name of the descriptor used. + pipe: for multiprocessing purposes. Sends the data calculated + through a pipe. + test_size: size of the test set to use. If no size is given, + the last remaining molecules are used. + sigma: depth of the kernel. + show_msgs: Show debug messages or not. + NOTE: desc_type is just a string and is only for identification purposes. + Also, training is done with the first part of the data and + testing with the ending part of the data. + """ + # Initial calculations for later use. + d_len = len(desc_data) + e_len = len(energy_data) + + if not desc_type: + desc_type = 'NOT SPECIFIED' + + if d_len != e_len: + printc(''.join(['ERROR. Descriptor data size different ', + 'than energy data size.']), 'RED') + return None + + if training_size >= d_len: + printc('ERROR. Training size greater or equal than data size.', 'RED') + return None + + if not test_size: + test_size = d_len - training_size + if test_size > 1500: + test_size = 1500 + + tic = time.perf_counter() + if show_msgs: + printc('{} ML started.'.format(desc_type), 'GREEN') + printc('\tTraining size: {}'.format(training_size), 'CYAN') + printc('\tTest size: {}'.format(test_size), 'CYAN') + printc('\tSigma: {}'.format(sigma), 'CYAN') + + Xcm_training = desc_data[:training_size] + Ycm_training = energy_data[:training_size] + Kcm_training = gauss_kernel(Xcm_training, Xcm_training, sigma) + alpha_cm = cholesky_solve(Kcm_training, Ycm_training) + + Xcm_test = desc_data[-test_size:] + Ycm_test = energy_data[-test_size:] + Kcm_test = gauss_kernel(Xcm_test, Xcm_training, sigma) + Ycm_predicted = np.dot(Kcm_test, alpha_cm) + + mae = np.mean(np.abs(Ycm_predicted - Ycm_test)) + if show_msgs: + printc('\tMAE for {}: {:.4f}'.format(desc_type, mae), 'GREEN') + + toc = time.perf_counter() + tictoc = toc - tic + if show_msgs: + printc('\t{} ML took {:.4f} seconds.'.format(desc_type, tictoc), + 'GREEN') + printc('\t\tTraining size: {}'.format(training_size), 'CYAN') + printc('\t\tTest size: {}'.format(test_size), 'CYAN') + printc('\t\tSigma: {}'.format(sigma), 'CYAN') + + if pipe: + pipe.send([desc_type, training_size, test_size, sigma, mae, tictoc]) + + return mae, tictoc diff --git a/lj_matrix/frob_norm.py b/lj_matrix/frob_norm.py new file mode 100644 index 000000000..4c3a2945d --- /dev/null +++ b/lj_matrix/frob_norm.py @@ -0,0 +1,51 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import math + + +def frob_norm(array): + """ + Calculates the frobenius norm of a given array or matrix. + array: array of data. + """ + + arr_sh_len = len(array.shape) + arr_range = range(len(array)) + fn = 0.0 + + # If it is a 'vector'. + if arr_sh_len == 1: + for i in arr_range: + fn += array[i]*array[i] + + return math.sqrt(fn) + + # If it is a matrix. + elif arr_sh_len == 2: + for i in arr_range: + for j in arr_range: + fn += array[i, j]*array[i, j] + + return math.sqrt(fn) + else: + print('Error. Array size greater than 2 ({}).'.format(arr_sh_len)) diff --git a/lj_matrix/gauss_kernel.py b/lj_matrix/gauss_kernel.py new file mode 100644 index 000000000..5dd8e6406 --- /dev/null +++ b/lj_matrix/gauss_kernel.py @@ -0,0 +1,49 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import math +import numpy as np +from lj_matrix.frob_norm import frob_norm + + +def gauss_kernel(X_1, X_2, sigma): + """ + Calculates the Gaussian Kernel. + X_1: first representations. + X_2: second representations. + sigma: kernel width. + """ + x1_l = len(X_1) + x1_range = range(x1_l) + x2_l = len(X_2) + x2_range = range(x2_l) + + inv_sigma = -0.5 / (sigma*sigma) + + K = np.zeros((x1_l, x2_l)) + for i in x1_range: + for j in x2_range: + f_norm = frob_norm(X_1[i] - X_2[j]) + # print(f_norm) + K[i, j] = math.exp(inv_sigma * f_norm) + + return K diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py new file mode 100644 index 000000000..4f63e95ca --- /dev/null +++ b/lj_matrix/lj_matrix.py @@ -0,0 +1,207 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import time +from lj_matrix.misc import printc +import math +import numpy as np +from numpy.linalg import eig + + +def lj_matrix(mol_data, + nc_data, + sigma=1.0, + epsilon=1.0, + max_len=25, + as_eig=True, + bohr_radius_units=False): + """ + Creates the Lennard-Jones Matrix from the molecule data given. + mol_data: molecule data, matrix of atom coordinates. + nc_data: nuclear charge data, array of atom data. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + """ + if bohr_radius_units: + conversion_rate = 0.52917721067 + else: + conversion_rate = 1 + + mol_n = len(mol_data) + mol_nr = range(mol_n) + + if not mol_n == len(nc_data): + print(''.join(['Error. Molecule matrix dimension is different ', + 'than the nuclear charge array dimension.'])) + else: + if max_len < mol_n: + print(''.join(['Error. Molecule matrix dimension (mol_n) is ', + 'greater than max_len. Using mol_n.'])) + max_len = None + + if max_len: + lj = np.zeros((max_len, max_len)) + ml_r = range(max_len) + + # Actual calculation of the coulomb matrix. + for i in ml_r: + if i < mol_n: + x_i = mol_data[i, 0] + y_i = mol_data[i, 1] + z_i = mol_data[i, 2] + Z_i = nc_data[i] + else: + break + + for j in ml_r: + if j < mol_n: + x_j = mol_data[j, 0] + y_j = mol_data[j, 1] + z_j = mol_data[j, 2] + + x = (x_i-x_j)**2 + y = (y_i-y_j)**2 + z = (z_i-z_j)**2 + + if i == j: + lj[i, j] = (0.5*Z_i**2.4) + else: + # Calculations are done after i==j is checked + # so no division by zero is done. + + # A little play with r exponents + # so no square root is calculated. + # Conversion factor is included in r^2. + + # 1/r^2 + r_2 = sigma**2/(conversion_rate**2*(x + y + z)) + + r_6 = math.pow(r_2, 3) + r_12 = math.pow(r_6, 2) + lj[i, j] = (4*epsilon*(r_12 - r_6)) + else: + break + + # Now the value will be returned. + if as_eig: + lj_sorted = np.sort(eig(lj)[0])[::-1] + # Thanks to SO for the following lines of code. + # https://stackoverflow.com/a/43011036 + + # Keep zeros at the end. + mask = lj_sorted != 0. + f_mask = mask.sum(0, keepdims=1) >\ + np.arange(lj_sorted.shape[0]-1, -1, -1) + + f_mask = f_mask[::-1] + lj_sorted[f_mask] = lj_sorted[mask] + lj_sorted[~f_mask] = 0. + + return lj_sorted + + else: + return lj + + else: + lj_temp = [] + # Actual calculation of the coulomb matrix. + for i in mol_nr: + x_i = mol_data[i, 0] + y_i = mol_data[i, 1] + z_i = mol_data[i, 2] + Z_i = nc_data[i] + + lj_row = [] + for j in mol_nr: + x_j = mol_data[j, 0] + y_j = mol_data[j, 1] + z_j = mol_data[j, 2] + + x = (x_i-x_j)**2 + y = (y_i-y_j)**2 + z = (z_i-z_j)**2 + + if i == j: + lj_row.append(0.5*Z_i**2.4) + else: + # Calculations are done after i==j is checked + # so no division by zero is done. + + # A little play with r exponents + # so no square root is calculated. + # Conversion factor is included in r^2. + + # 1/r^2 + r_2 = sigma**2/(conversion_rate**2*(x + y + z)) + + r_6 = math.pow(r_2, 3) + r_12 = math.pow(r_6, 2) + lj_row.append(4*epsilon*(r_12 - r_6)) + + lj_temp.append(np.array(lj_row)) + + lj = np.array(lj_temp) + # Now the value will be returned. + if as_eig: + return np.sort(eig(lj)[0])[::-1] + else: + return lj + + +def lj_matrix_multiple(mol_data, + nc_data, + pipe=None, + sigma=1, + epsilon=1, + max_len=25, + as_eig=True, + bohr_radius_units=False): + """ + Calculates the Lennard-Jones Matrix of multiple molecules. + mol_data: molecule data, matrix of atom coordinates. + nc_data: nuclear charge data, array of atom data. + pipe: for multiprocessing purposes. Sends the data calculated + through a pipe. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + """ + printc('L-J Matrices calculation started.', 'CYAN') + tic = time.perf_counter() + + ljm_data = np.array([lj_matrix(mol, + nc, + sigma, + epsilon, + max_len, + as_eig, + bohr_radius_units) + for mol, nc in zip(mol_data, nc_data)]) + + toc = time.perf_counter() + printc('\tL-JM calculation took {:.4f} seconds.'.format(toc-tic), 'GREEN') + + if pipe: + pipe.send(ljm_data) + + return ljm_data diff --git a/lj_matrix/misc.py b/lj_matrix/misc.py new file mode 100644 index 000000000..c50653a5c --- /dev/null +++ b/lj_matrix/misc.py @@ -0,0 +1,53 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +from colorama import init, Fore, Style + +init() + + +def printc(text, color): + """ + Prints texts normaly, but in color. Using colorama. + text: string with the text to print. + color: color to be used, same as available in colorama. + """ + color_dic = {'BLACK': Fore.BLACK, + 'RED': Fore.RED, + 'GREEN': Fore.GREEN, + 'YELLOW': Fore.YELLOW, + 'BLUE': Fore.BLUE, + 'MAGENTA': Fore.MAGENTA, + 'CYAN': Fore.CYAN, + 'WHITE': Fore.WHITE, + 'RESET': Fore.RESET} + + color_dic_keys = color_dic.keys() + if color not in color_dic_keys: + print(Fore.RED + + '\'{}\' not found, using default color.'.format(color) + + Style.RESET_ALL) + actual_color = Fore.RESET + else: + actual_color = color_dic[color] + + print(actual_color + text + Style.RESET_ALL) diff --git a/lj_matrix/read_qm7_data.py b/lj_matrix/read_qm7_data.py new file mode 100644 index 000000000..b54691fb0 --- /dev/null +++ b/lj_matrix/read_qm7_data.py @@ -0,0 +1,144 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import os +import time +import numpy as np +import random +from lj_matrix.misc import printc + + +# 'periodic_table_of_elements.txt' retrieved from +# https://gist.github.com/GoodmanSciences/c2dd862cd38f21b0ad36b8f96b4bf1ee +def read_nc_data(data_path): + """ + Reads nuclear charge data from file and returns a dictionary. + data_path: path to the data directory. + """ + fname = 'periodic_table_of_elements.txt' + with open(''.join([data_path, '\\', fname]), 'r') as infile: + temp_lines = infile.readlines() + + del temp_lines[0] + + lines = [] + for temp_line in temp_lines: + new_line = temp_line.split(sep=',') + lines.append(new_line) + + # Dictionary of nuclear charge. + return {line[2]: int(line[0]) for line in lines} + + +# 'hof_qm7.txt.txt' retrieved from +# https://github.com/qmlcode/tutorial +def reas_db_data(zi_data, + data_path, + r_seed=111): + """ + Reads molecule database and extracts + its contents as usable variables. + zi_data: dictionary containing nuclear charge data. + data_path: path to the data directory. + r_seed: random seed. + """ + os.chdir(data_path) + + fname = 'hof_qm7.txt' + with open(fname, 'r') as infile: + lines = infile.readlines() + + # Temporary energy dictionary. + energy_temp = dict() + + for line in lines: + xyz_data = line.split() + + xyz_name = xyz_data[0] + hof = float(xyz_data[1]) + dftb = float(xyz_data[2]) + # print(xyz_name, hof, dftb) + + energy_temp[xyz_name] = np.array([hof, hof - dftb]) + + # Use a random seed. + random.seed(r_seed) + + et_keys = list(energy_temp.keys()) + random.shuffle(et_keys) + + # Temporary energy dictionary, shuffled. + energy_temp_shuffled = dict() + for key in et_keys: + energy_temp_shuffled.update({key: energy_temp[key]}) + + mol_data = [] + mol_nc_data = [] + # Actual reading of the xyz files. + for i, k in enumerate(energy_temp_shuffled.keys()): + with open(k, 'r') as xyz_file: + lines = xyz_file.readlines() + + len_lines = len(lines) + mol_temp_data = [] + mol_nc_temp_data = np.array(np.zeros(len_lines-2)) + for j, line in enumerate(lines[2:len_lines]): + line_list = line.split() + + mol_nc_temp_data[j] = float(zi_data[line_list[0]]) + line_data = np.array(np.asarray(line_list[1:4], dtype=float)) + mol_temp_data.append(line_data) + + mol_data.append(mol_temp_data) + mol_nc_data.append(mol_nc_temp_data) + + # Convert everything to a numpy array. + molecules = np.array([np.array(mol) for mol in mol_data]) + nuclear_charge = np.array([nc_d for nc_d in mol_nc_data]) + energy_pbe0 = np.array([energy_temp_shuffled[k][0] + for k in energy_temp_shuffled.keys()]) + energy_delta = np.array([energy_temp_shuffled[k][1] + for k in energy_temp_shuffled.keys()]) + + return molecules, nuclear_charge, energy_pbe0, energy_delta + + +def read_qm7_data(): + """ + Reads all the qm7 data. + """ + tic = time.perf_counter() + printc('Data reading started.', 'CYAN') + + init_path = os.getcwd() + os.chdir('data') + data_path = os.getcwd() + + zi_data = read_nc_data(data_path) + molecules, nuclear_charge, energy_pbe0, energy_delta = \ + reas_db_data(zi_data, data_path) + + os.chdir(init_path) + toc = time.perf_counter() + printc('\tData reading took {:.4f} seconds.'.format(toc-tic), 'GREEN') + + return zi_data, molecules, nuclear_charge, energy_pbe0, energy_delta -- cgit v1.2.3-70-g09d2 From 124c3c5eb77c807b8a8a78413f3800720914c8e1 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Wed, 18 Dec 2019 08:15:18 -0700 Subject: Fix bugs --- lj_matrix/__init__.py | 23 ++++++++++ lj_matrix/__main__.py | 13 +++--- lj_matrix/c_matrix.py | 2 +- lj_matrix/do_ml.py | 4 +- lj_matrix/gauss_kernel.py | 2 +- lj_matrix/lj_matrix.py | 2 +- lj_matrix/read_qm7_data.py | 2 +- lj_matrix/version.py | 23 ++++++++++ setup.py | 102 +++++++++++++++++++++++++++++++++++++++++++++ 9 files changed, 161 insertions(+), 12 deletions(-) create mode 100644 lj_matrix/version.py create mode 100644 setup.py (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index 48cd14913..47d7e5013 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -20,3 +20,26 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ +from misc import printc +from read_qm7_data import read_qm7_data, read_nc_data, reas_db_data +from c_matrix import c_matrix, c_matrix_multiple +from cholesky_solve import cholesky_solve +from do_ml import do_ml +from frob_norm import frob_norm +from gauss_kernel import gauss_kernel +from lj_matrix import lj_matrix, lj_matrix_multiple + +# If somebody does "from package import *", this is what they will +# be able to access: +__all__ = ['printc', + 'read_qm7_data', + 'read_nc_data', + 'reas_db_data', + 'c_matrix', + 'c_matrix_multiple', + 'cholesky_solve', + 'do_ml', + 'frob_norm', + 'gauss_kernel', + 'lj_matrix', + 'lj_matrix_multiple'] diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 4e13f4995..5a0e95b94 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -24,11 +24,11 @@ import time from multiprocessing import Process, Pipe # import matplotlib.pyplot as plt import pandas as pd -from lj_matrix.misc import printc -from lj_matrix.read_qm7_data import read_qm7_data -from lj_matrix.c_matrix import c_matrix_multiple -from lj_matrix.lj_matrix import lj_matrix_multiple -from lj_matrix.do_ml import do_ml +from misc import printc +from read_qm7_data import read_qm7_data +from c_matrix import c_matrix_multiple +from lj_matrix import lj_matrix_multiple +from do_ml import do_ml # Test @@ -235,4 +235,5 @@ def pl(): if __name__ == '__main__': # ml() - pl() + # pl() + print('OK!') diff --git a/lj_matrix/c_matrix.py b/lj_matrix/c_matrix.py index f40a18c68..4de711a1b 100644 --- a/lj_matrix/c_matrix.py +++ b/lj_matrix/c_matrix.py @@ -21,7 +21,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import time -from lj_matrix.misc import printc +from misc import printc import math import numpy as np from numpy.linalg import eig diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index acf5455f4..c88533e68 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -23,8 +23,8 @@ SOFTWARE. import time from misc import printc import numpy as np -from lj_matrix.gauss_kernel import gauss_kernel -from lj_matrix.cholesky_solve import cholesky_solve +from gauss_kernel import gauss_kernel +from cholesky_solve import cholesky_solve def do_ml(desc_data, diff --git a/lj_matrix/gauss_kernel.py b/lj_matrix/gauss_kernel.py index 5dd8e6406..0dfc65d59 100644 --- a/lj_matrix/gauss_kernel.py +++ b/lj_matrix/gauss_kernel.py @@ -22,7 +22,7 @@ SOFTWARE. """ import math import numpy as np -from lj_matrix.frob_norm import frob_norm +from frob_norm import frob_norm def gauss_kernel(X_1, X_2, sigma): diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py index 4f63e95ca..2a8e0d956 100644 --- a/lj_matrix/lj_matrix.py +++ b/lj_matrix/lj_matrix.py @@ -21,7 +21,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import time -from lj_matrix.misc import printc +from misc import printc import math import numpy as np from numpy.linalg import eig diff --git a/lj_matrix/read_qm7_data.py b/lj_matrix/read_qm7_data.py index b54691fb0..068ea1a42 100644 --- a/lj_matrix/read_qm7_data.py +++ b/lj_matrix/read_qm7_data.py @@ -24,7 +24,7 @@ import os import time import numpy as np import random -from lj_matrix.misc import printc +from misc import printc # 'periodic_table_of_elements.txt' retrieved from diff --git a/lj_matrix/version.py b/lj_matrix/version.py new file mode 100644 index 000000000..fab58433d --- /dev/null +++ b/lj_matrix/version.py @@ -0,0 +1,23 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +__version__ = '0.0.1' diff --git a/setup.py b/setup.py new file mode 100644 index 000000000..719ef3ce0 --- /dev/null +++ b/setup.py @@ -0,0 +1,102 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +# This setup.py template was obtained from +# https://github.com/navdeep-G/setup.py/blob/master/setup.py +# ---------------------------------------------------------------------- +# Note: To use the 'upload' functionality of this file, you must: +# $ pipenv install twine --dev + +import io +import os + +from setuptools import find_packages, setup + +from lj_matrix.version import __version__ + +# Package meta-data. +NAME = 'lj_matrix' +DESCRIPTION = 'A Lennard Jones matrix exploration.' +URL = 'https://github.com/luevano/lj_matrix' +EMAIL = 'a301436@uach.mx' +AUTHOR = 'David Luevano Alvarado' +REQUIRES_PYTHON = '>=3.7' +VERSION = __version__ +# VERSION = '0.0.1' + +# What packages are required for this module to be executed? +REQUIRED = [ + # 'requests', 'maya', 'records', +] + +# What packages are optional? +EXTRAS = { + # 'fancy feature': ['django'], +} + +# The rest you shouldn't have to touch too much :) +# ------------------------------------------------ +# Except, perhaps the License and Trove Classifiers! +# If you do change the License, remember to change +# the Trove Classifier for that! + +here = os.path.abspath(os.path.dirname(__file__)) + +# Import the README and use it as the long-description. +# Note: this will only work if 'README.md' +# is present in your MANIFEST.in file! +try: + with io.open(os.path.join(here, 'README.md'), encoding='utf-8') as f: + long_description = '\n' + f.read() +except FileNotFoundError: + long_description = DESCRIPTION + +# Where the magic happens: +setup( + name=NAME, + version=VERSION, + description=DESCRIPTION, + long_description=long_description, + long_description_content_type='text/markdown', + author=AUTHOR, + author_email=EMAIL, + python_requires=REQUIRES_PYTHON, + url=URL, + packages=find_packages(exclude=["tests", + "*.tests", + "*.tests.*", + "tests.*"]), + # If your package is a single module, use this instead of 'packages': + # py_modules=['mypackage'], + install_requires=REQUIRED, + extras_require=EXTRAS, + include_package_data=True, + license='MIT', + classifiers=[ + # Trove classifiers + # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers + 'License :: OSI Approved :: MIT License', + 'Programming Language :: Python', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.7' + ] +) -- cgit v1.2.3-70-g09d2 From a50d424d0ab7dd4cc6a2d6fc94371fa65a0d89b2 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Wed, 18 Dec 2019 09:53:44 -0700 Subject: Fix test issues --- lj_matrix/__init__.py | 27 ++++++++++++++------------- lj_matrix/__main__.py | 10 +++++----- lj_matrix/c_matrix.py | 2 +- lj_matrix/do_ml.py | 6 +++--- lj_matrix/gauss_kernel.py | 2 +- lj_matrix/lj_matrix.py | 2 +- lj_matrix/read_qm7_data.py | 2 +- test/__init__.py | 22 ++++++++++++++++++++++ test/test_c_matrix.py | 33 +++++++++++++++++++++++++++++++++ 9 files changed, 81 insertions(+), 25 deletions(-) create mode 100644 test/__init__.py create mode 100644 test/test_c_matrix.py (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index 47d7e5013..5019bd51d 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -20,26 +20,27 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ -from misc import printc -from read_qm7_data import read_qm7_data, read_nc_data, reas_db_data -from c_matrix import c_matrix, c_matrix_multiple -from cholesky_solve import cholesky_solve -from do_ml import do_ml -from frob_norm import frob_norm -from gauss_kernel import gauss_kernel -from lj_matrix import lj_matrix, lj_matrix_multiple +from lj_matrix.misc import printc +from lj_matrix.read_qm7_data import read_nc_data, reas_db_data, read_qm7_data +from lj_matrix.c_matrix import c_matrix, c_matrix_multiple +from lj_matrix.lj_matrix import lj_matrix, lj_matrix_multiple +from lj_matrix.frob_norm import frob_norm +from lj_matrix.gauss_kernel import gauss_kernel +from lj_matrix.cholesky_solve import cholesky_solve +from lj_matrix.do_ml import do_ml + # If somebody does "from package import *", this is what they will # be able to access: __all__ = ['printc', - 'read_qm7_data', 'read_nc_data', 'reas_db_data', + 'read_qm7_data', 'c_matrix', 'c_matrix_multiple', - 'cholesky_solve', - 'do_ml', + 'lj_matrix', + 'lj_matrix_multiple', 'frob_norm', 'gauss_kernel', - 'lj_matrix', - 'lj_matrix_multiple'] + 'cholesky_solve', + 'do_ml'] diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 5a0e95b94..0b2a7c6f8 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -24,11 +24,11 @@ import time from multiprocessing import Process, Pipe # import matplotlib.pyplot as plt import pandas as pd -from misc import printc -from read_qm7_data import read_qm7_data -from c_matrix import c_matrix_multiple -from lj_matrix import lj_matrix_multiple -from do_ml import do_ml +from lj_matrix.misc import printc +from lj_matrix.read_qm7_data import read_qm7_data +from lj_matrix.c_matrix import c_matrix_multiple +from lj_matrix.lj_matrix import lj_matrix_multiple +from lj_matrix.do_ml import do_ml # Test diff --git a/lj_matrix/c_matrix.py b/lj_matrix/c_matrix.py index 4de711a1b..f21ccfd8c 100644 --- a/lj_matrix/c_matrix.py +++ b/lj_matrix/c_matrix.py @@ -21,10 +21,10 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import time -from misc import printc import math import numpy as np from numpy.linalg import eig +from lj_matrix.misc import printc def c_matrix(mol_data, diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index c88533e68..ba88a6fd8 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -21,10 +21,10 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import time -from misc import printc import numpy as np -from gauss_kernel import gauss_kernel -from cholesky_solve import cholesky_solve +from lj_matrix.misc import printc +from lj_matrix.gauss_kernel import gauss_kernel +from lj_matrix.cholesky_solve import cholesky_solve def do_ml(desc_data, diff --git a/lj_matrix/gauss_kernel.py b/lj_matrix/gauss_kernel.py index 0dfc65d59..5dd8e6406 100644 --- a/lj_matrix/gauss_kernel.py +++ b/lj_matrix/gauss_kernel.py @@ -22,7 +22,7 @@ SOFTWARE. """ import math import numpy as np -from frob_norm import frob_norm +from lj_matrix.frob_norm import frob_norm def gauss_kernel(X_1, X_2, sigma): diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py index 2a8e0d956..2a56a3cdf 100644 --- a/lj_matrix/lj_matrix.py +++ b/lj_matrix/lj_matrix.py @@ -21,10 +21,10 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import time -from misc import printc import math import numpy as np from numpy.linalg import eig +from lj_matrix.misc import printc def lj_matrix(mol_data, diff --git a/lj_matrix/read_qm7_data.py b/lj_matrix/read_qm7_data.py index 068ea1a42..b54691fb0 100644 --- a/lj_matrix/read_qm7_data.py +++ b/lj_matrix/read_qm7_data.py @@ -24,7 +24,7 @@ import os import time import numpy as np import random -from misc import printc +from lj_matrix.misc import printc # 'periodic_table_of_elements.txt' retrieved from diff --git a/test/__init__.py b/test/__init__.py new file mode 100644 index 000000000..8b866e928 --- /dev/null +++ b/test/__init__.py @@ -0,0 +1,22 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" \ No newline at end of file diff --git a/test/test_c_matrix.py b/test/test_c_matrix.py new file mode 100644 index 000000000..a8bb5ae34 --- /dev/null +++ b/test/test_c_matrix.py @@ -0,0 +1,33 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import unittest +from lj_matrix.c_matrix import c_matrix + + +class TestCMatrix(unittest.TestCase): + def test_c_matrix(self): + self.assertAlmostEqual(1, 1) + + +if __name__ == '__main__': + unittest.main() -- cgit v1.2.3-70-g09d2 From 72be4105825c639cf9dfad6229c7a1d62a16c44d Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Mon, 23 Dec 2019 11:48:32 -0700 Subject: Change name convention --- lj_matrix/do_ml.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index ba88a6fd8..bb954a0ae 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -79,17 +79,17 @@ def do_ml(desc_data, printc('\tTest size: {}'.format(test_size), 'CYAN') printc('\tSigma: {}'.format(sigma), 'CYAN') - Xcm_training = desc_data[:training_size] - Ycm_training = energy_data[:training_size] - Kcm_training = gauss_kernel(Xcm_training, Xcm_training, sigma) - alpha_cm = cholesky_solve(Kcm_training, Ycm_training) + X_training = desc_data[:training_size] + Y_training = energy_data[:training_size] + K_training = gauss_kernel(X_training, X_training, sigma) + alpha_ = cholesky_solve(K_training, Y_training) - Xcm_test = desc_data[-test_size:] - Ycm_test = energy_data[-test_size:] - Kcm_test = gauss_kernel(Xcm_test, Xcm_training, sigma) - Ycm_predicted = np.dot(Kcm_test, alpha_cm) + X_test = desc_data[-test_size:] + Y_test = energy_data[-test_size:] + K_test = gauss_kernel(X_test, X_training, sigma) + Y_predicted = np.dot(K_test, alpha_) - mae = np.mean(np.abs(Ycm_predicted - Ycm_test)) + mae = np.mean(np.abs(Y_predicted - Y_test)) if show_msgs: printc('\tMAE for {}: {:.4f}'.format(desc_type, mae), 'GREEN') -- cgit v1.2.3-70-g09d2 From db64425a5580a49312e313a6e75e7a296eb93b35 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Mon, 23 Dec 2019 12:23:46 -0700 Subject: Restructure code and bug fix --- lj_matrix/__init__.py | 4 +- lj_matrix/__main__.py | 31 ++-------------- lj_matrix/lj_matrix.py | 6 ++- lj_matrix/parallel_create_matrices.py | 70 +++++++++++++++++++++++++++++++++++ lj_matrix/read_qm7_data.py | 6 +-- 5 files changed, 83 insertions(+), 34 deletions(-) create mode 100644 lj_matrix/parallel_create_matrices.py (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index 5019bd51d..d7794d3be 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -21,7 +21,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from lj_matrix.misc import printc -from lj_matrix.read_qm7_data import read_nc_data, reas_db_data, read_qm7_data +from lj_matrix.read_qm7_data import read_nc_data, read_db_data, read_qm7_data from lj_matrix.c_matrix import c_matrix, c_matrix_multiple from lj_matrix.lj_matrix import lj_matrix, lj_matrix_multiple from lj_matrix.frob_norm import frob_norm @@ -34,7 +34,7 @@ from lj_matrix.do_ml import do_ml # be able to access: __all__ = ['printc', 'read_nc_data', - 'reas_db_data', + 'read_db_data', 'read_qm7_data', 'c_matrix', 'c_matrix_multiple', diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 0b2a7c6f8..8e52031f1 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -26,8 +26,7 @@ from multiprocessing import Process, Pipe import pandas as pd from lj_matrix.misc import printc from lj_matrix.read_qm7_data import read_qm7_data -from lj_matrix.c_matrix import c_matrix_multiple -from lj_matrix.lj_matrix import lj_matrix_multiple +from lj_matrix.parallel_create_matrices import parallel_create_matrices from lj_matrix.do_ml import do_ml @@ -40,32 +39,10 @@ def ml(): init_time = time.perf_counter() # Data reading. - zi_data, molecules, nuclear_charge, energy_pbe0, energy_delta =\ - read_qm7_data() + molecules, nuclear_charge, energy_pbe0, energy_delta = read_qm7_data() # Matrices calculation. - procs = [] - pipes = [] - - # cm_recv, cm_send = Pipe(False) - # p1 = Process(target=c_matrix_multiple, - # args=(molecules, nuclear_charge, cm_send)) - # procs.append(p1) - # pipes.append(cm_recv) - # p1.start() - - ljm_recv, ljm_send = Pipe(False) - p2 = Process(target=lj_matrix_multiple, - args=(molecules, nuclear_charge, ljm_send, 1, 0.25)) - procs.append(p2) - pipes.append(ljm_recv) - p2.start() - - # cm_data = pipes[0].recv() - ljm_data = pipes[0].recv() - - for proc in procs: - proc.join() + cm_data, ljm_data = parallel_create_matrices(molecules, nuclear_charge) # ML calculation. procs = [] @@ -234,6 +211,6 @@ def pl(): if __name__ == '__main__': - # ml() + ml() # pl() print('OK!') diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py index 2a56a3cdf..0c16b5686 100644 --- a/lj_matrix/lj_matrix.py +++ b/lj_matrix/lj_matrix.py @@ -38,6 +38,8 @@ def lj_matrix(mol_data, Creates the Lennard-Jones Matrix from the molecule data given. mol_data: molecule data, matrix of atom coordinates. nc_data: nuclear charge data, array of atom data. + sigma: sigma value. + epsilon: epsilon value. max_len: maximum amount of atoms in molecule. as_eig: if data should be returned as matrix or array of eigenvalues. bohr_radius_units: if units should be in bohr's radius units. @@ -171,8 +173,8 @@ def lj_matrix(mol_data, def lj_matrix_multiple(mol_data, nc_data, pipe=None, - sigma=1, - epsilon=1, + sigma=1.0, + epsilon=1.0, max_len=25, as_eig=True, bohr_radius_units=False): diff --git a/lj_matrix/parallel_create_matrices.py b/lj_matrix/parallel_create_matrices.py new file mode 100644 index 000000000..0ab691525 --- /dev/null +++ b/lj_matrix/parallel_create_matrices.py @@ -0,0 +1,70 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +from multiprocessing import Process, Pipe +from lj_matrix.c_matrix import c_matrix_multiple +from lj_matrix.lj_matrix import lj_matrix_multiple + + +def parallel_create_matrices(mol_data, + nc_data, + sigma=1.0, + epsilon=1.0, + max_len=25, + as_eig=True, + bohr_radius_units=False): + """ + Creates the Coulomb and L-J matrices in parallel. + mol_data: molecule data, matrix of atom coordinates. + nc_data: nuclear charge data, array of atom data. + sigma: sigma value for L-J matrix. + epsilon: epsilon value for L-J matrix. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + """ + + # Matrices calculation. + procs = [] + pipes = [] + + cm_recv, cm_send = Pipe(False) + p1 = Process(target=c_matrix_multiple, + args=(mol_data, nc_data, cm_send)) + procs.append(p1) + pipes.append(cm_recv) + p1.start() + + ljm_recv, ljm_send = Pipe(False) + p2 = Process(target=lj_matrix_multiple, + args=(mol_data, nc_data, ljm_send, sigma, epsilon)) + procs.append(p2) + pipes.append(ljm_recv) + p2.start() + + cm_data = pipes[0].recv() + ljm_data = pipes[1].recv() + + for proc in procs: + proc.join() + + return cm_data, ljm_data diff --git a/lj_matrix/read_qm7_data.py b/lj_matrix/read_qm7_data.py index b54691fb0..9bb7629ca 100644 --- a/lj_matrix/read_qm7_data.py +++ b/lj_matrix/read_qm7_data.py @@ -51,7 +51,7 @@ def read_nc_data(data_path): # 'hof_qm7.txt.txt' retrieved from # https://github.com/qmlcode/tutorial -def reas_db_data(zi_data, +def read_db_data(zi_data, data_path, r_seed=111): """ @@ -135,10 +135,10 @@ def read_qm7_data(): zi_data = read_nc_data(data_path) molecules, nuclear_charge, energy_pbe0, energy_delta = \ - reas_db_data(zi_data, data_path) + read_db_data(zi_data, data_path) os.chdir(init_path) toc = time.perf_counter() printc('\tData reading took {:.4f} seconds.'.format(toc-tic), 'GREEN') - return zi_data, molecules, nuclear_charge, energy_pbe0, energy_delta + return molecules, nuclear_charge, energy_pbe0, energy_delta -- cgit v1.2.3-70-g09d2 From f8bd690096e432b313ee17baa93c7422b45ee9b8 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Mon, 23 Dec 2019 12:29:35 -0700 Subject: Fix init --- lj_matrix/__init__.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index d7794d3be..0c2407a57 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -28,6 +28,7 @@ from lj_matrix.frob_norm import frob_norm from lj_matrix.gauss_kernel import gauss_kernel from lj_matrix.cholesky_solve import cholesky_solve from lj_matrix.do_ml import do_ml +from lj_matrix.parallel_create_matrices import parallel_create_matrices # If somebody does "from package import *", this is what they will @@ -43,4 +44,5 @@ __all__ = ['printc', 'frob_norm', 'gauss_kernel', 'cholesky_solve', - 'do_ml'] + 'do_ml', + 'parallel_create_matrices'] -- cgit v1.2.3-70-g09d2 From f5d72558ed6ec63c7de4940c29d4f6c92605a30d Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Mon, 23 Dec 2019 12:39:28 -0700 Subject: Fix init --- lj_matrix/__init__.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index 0c2407a57..d59e3481c 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -20,7 +20,6 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ -from lj_matrix.misc import printc from lj_matrix.read_qm7_data import read_nc_data, read_db_data, read_qm7_data from lj_matrix.c_matrix import c_matrix, c_matrix_multiple from lj_matrix.lj_matrix import lj_matrix, lj_matrix_multiple @@ -33,8 +32,7 @@ from lj_matrix.parallel_create_matrices import parallel_create_matrices # If somebody does "from package import *", this is what they will # be able to access: -__all__ = ['printc', - 'read_nc_data', +__all__ = ['read_nc_data', 'read_db_data', 'read_qm7_data', 'c_matrix', -- cgit v1.2.3-70-g09d2 From b14c581ca5fdab47d7e1c0b688331368cb7f29d0 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Mon, 23 Dec 2019 13:11:12 -0700 Subject: Refactor ml code --- lj_matrix/do_ml.py | 104 +++++++++++++++++++++++++++++++++++++++++++++++------ 1 file changed, 93 insertions(+), 11 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index bb954a0ae..ac044cfb3 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -22,19 +22,22 @@ SOFTWARE. """ import time import numpy as np +from multiprocessing import Process, Pipe from lj_matrix.misc import printc from lj_matrix.gauss_kernel import gauss_kernel from lj_matrix.cholesky_solve import cholesky_solve - - -def do_ml(desc_data, - energy_data, - training_size, - desc_type=None, - pipe=None, - test_size=None, - sigma=1000.0, - show_msgs=True): +from lj_matrix.read_qm7_data import read_qm7_data +from lj_matrix.parallel_create_matrices import parallel_create_matrices + + +def ml(desc_data, + energy_data, + training_size, + desc_type=None, + pipe=None, + test_size=None, + sigma=1000.0, + show_msgs=True): """ Does the ML methodology. desc_data: descriptor (or representation) data. @@ -51,6 +54,7 @@ def do_ml(desc_data, Also, training is done with the first part of the data and testing with the ending part of the data. """ + tic = time.perf_counter() # Initial calculations for later use. d_len = len(desc_data) e_len = len(energy_data) @@ -72,7 +76,6 @@ def do_ml(desc_data, if test_size > 1500: test_size = 1500 - tic = time.perf_counter() if show_msgs: printc('{} ML started.'.format(desc_type), 'GREEN') printc('\tTraining size: {}'.format(training_size), 'CYAN') @@ -106,3 +109,82 @@ def do_ml(desc_data, pipe.send([desc_type, training_size, test_size, sigma, mae, tictoc]) return mae, tictoc + + +# Test +def do_ml(min_training_size, + max_training_size=None, + training_increment_size=None, + ljm_sigma=1.0, + ljm_epsilon=1.0, + save_benchmarks=False): + """ + Main function that does the whole ML process. + min_training_size: minimum training size. + max_training_size: maximum training size. + training_increment_size: training increment size. + ljm_sigma: sigma value for lj matrix. + ljm_epsilon: epsilon value for lj matrix. + save_benchmarks: if benchmarks should be saved. + """ + # Initialization time. + init_time = time.perf_counter() + + # Data reading. + molecules, nuclear_charge, energy_pbe0, energy_delta = read_qm7_data() + + # Matrices calculation. + cm_data, ljm_data = parallel_create_matrices(molecules, + nuclear_charge, + ljm_sigma, + ljm_epsilon) + + # ML calculation. + procs = [] + cm_pipes = [] + ljm_pipes = [] + for i in range(min_training_size, + max_training_size + 1, + training_increment_size): + cm_recv, cm_send = Pipe(False) + p1 = Process(target=ml, + args=(cm_data, energy_pbe0, i, 'CM', cm_send)) + procs.append(p1) + cm_pipes.append(cm_recv) + p1.start() + + ljm_recv, ljm_send = Pipe(False) + p2 = Process(target=ml, + args=(ljm_data, energy_pbe0, i, 'L-JM', ljm_send)) + procs.append(p2) + ljm_pipes.append(ljm_recv) + p2.start() + + cm_bench_results = [] + ljm_bench_results = [] + for cd_pipe, ljd_pipe in zip(cm_pipes, ljm_pipes): + cm_bench_results.append(cd_pipe.recv()) + ljm_bench_results.append(ljd_pipe.recv()) + + for proc in procs: + proc.join() + + if save_benchmarks: + with open('data\\benchmarks.csv', 'a') as save_file: + # save_file.write(''.join(['ml_type,tr_size,te_size,kernel_s,', + # 'mae,time,lj_s,lj_e,date_ran\n'])) + ltime = time.localtime()[:3][::-1] + ljm_se = ',' + str(ljm_sigma) + ',' + str(ljm_epsilon) + ',' + date = '/'.join([str(field) for field in ltime]) + for cm, ljm, in zip(cm_bench_results, ljm_bench_results): + cm_text = ','.join([str(field) for field in cm])\ + + ',' + date + '\n' + ljm_text = ','.join([str(field) for field in ljm])\ + + ljm_se + date + '\n' + save_file.write(cm_text) + save_file.write(ljm_text) + + # End of program + end_time = time.perf_counter() + printc('Program took {:.4f} seconds.'.format(end_time - init_time), + 'CYAN') -- cgit v1.2.3-70-g09d2 From b4c2dc01ab17248814988c8e141bf16072c45abd Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 10:37:49 -0700 Subject: Add options to do_ml function --- lj_matrix/do_ml.py | 36 +++++++++++++++++++++++++++++++----- 1 file changed, 31 insertions(+), 5 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index ac044cfb3..12323780a 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -111,13 +111,17 @@ def ml(desc_data, return mae, tictoc -# Test def do_ml(min_training_size, max_training_size=None, training_increment_size=None, ljm_sigma=1.0, ljm_epsilon=1.0, - save_benchmarks=False): + save_benchmarks=False, + max_len=25, + as_eig=True, + bohr_radius_units=False, + sigma=1000.0, + show_msgs=True): """ Main function that does the whole ML process. min_training_size: minimum training size. @@ -126,6 +130,11 @@ def do_ml(min_training_size, ljm_sigma: sigma value for lj matrix. ljm_epsilon: epsilon value for lj matrix. save_benchmarks: if benchmarks should be saved. + max_len: maximum amount of atoms in molecule. + as_eig: if data should be returned as matrix or array of eigenvalues. + bohr_radius_units: if units should be in bohr's radius units. + sigma: depth of the kernel. + show_msgs: Show debug messages or not. """ # Initialization time. init_time = time.perf_counter() @@ -137,7 +146,10 @@ def do_ml(min_training_size, cm_data, ljm_data = parallel_create_matrices(molecules, nuclear_charge, ljm_sigma, - ljm_epsilon) + ljm_epsilon, + max_len, + as_eig, + bohr_radius_units) # ML calculation. procs = [] @@ -148,14 +160,28 @@ def do_ml(min_training_size, training_increment_size): cm_recv, cm_send = Pipe(False) p1 = Process(target=ml, - args=(cm_data, energy_pbe0, i, 'CM', cm_send)) + args=(cm_data, + energy_pbe0, + i, + 'CM', + cm_send, + max_training_size, + sigma, + show_msgs)) procs.append(p1) cm_pipes.append(cm_recv) p1.start() ljm_recv, ljm_send = Pipe(False) p2 = Process(target=ml, - args=(ljm_data, energy_pbe0, i, 'L-JM', ljm_send)) + args=(ljm_data, + energy_pbe0, + i, + 'L-JM', + ljm_send, + max_training_size, + sigma, + show_msgs)) procs.append(p2) ljm_pipes.append(ljm_recv) p2.start() -- cgit v1.2.3-70-g09d2 From cdbb1ac890cb0d062cdb2f216c347f681fbfa7b8 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 10:47:20 -0700 Subject: Fix bug --- lj_matrix/__main__.py | 68 +-------------------------------------------------- lj_matrix/do_ml.py | 4 ++- 2 files changed, 4 insertions(+), 68 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 8e52031f1..f7e4065da 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -20,76 +20,10 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ -import time -from multiprocessing import Process, Pipe -# import matplotlib.pyplot as plt import pandas as pd -from lj_matrix.misc import printc -from lj_matrix.read_qm7_data import read_qm7_data -from lj_matrix.parallel_create_matrices import parallel_create_matrices from lj_matrix.do_ml import do_ml -# Test -def ml(): - """ - Main function that does the whole ML process. - """ - # Initialization time. - init_time = time.perf_counter() - - # Data reading. - molecules, nuclear_charge, energy_pbe0, energy_delta = read_qm7_data() - - # Matrices calculation. - cm_data, ljm_data = parallel_create_matrices(molecules, nuclear_charge) - - # ML calculation. - procs = [] - # cm_pipes = [] - ljm_pipes = [] - for i in range(1500, 6500 + 1, 500): - # cm_recv, cm_send = Pipe(False) - # p1 = Process(target=do_ml, - # args=(cm_data, energy_pbe0, i, 'CM', cm_send)) - # procs.append(p1) - # cm_pipes.append(cm_recv) - # p1.start() - - ljm_recv, ljm_send = Pipe(False) - p2 = Process(target=do_ml, - args=(ljm_data, energy_pbe0, i, 'L-JM', ljm_send)) - procs.append(p2) - ljm_pipes.append(ljm_recv) - p2.start() - - # cm_bench_results = [] - ljm_bench_results = [] - for ljd_pipe in ljm_pipes: # cd_pipe, ljd_pipe in zip(cm_pipes, ljm_pipes): - # cm_bench_results.append(cd_pipe.recv()) - ljm_bench_results.append(ljd_pipe.recv()) - - for proc in procs: - proc.join() - - with open('data\\benchmarks.csv', 'a') as save_file: - # save_file.write(''.join(['ml_type,tr_size,te_size,kernel_s,', - # 'mae,time,lj_s,lj_e,date_ran\n'])) - date = '/'.join([str(field) for field in time.localtime()[:3][::-1]]) - for ljm in ljm_bench_results: # cm, ljm, in zip(cm_bench_results, ljm_bench_results): - # cm_text = ','.join([str(field) for field in cm])\ - # + ',' + date + '\n' - ljm_text = ','.join([str(field) for field in ljm])\ - + ',1,0.25,' + date + '\n' - # save_file.write(cm_text) - save_file.write(ljm_text) - - # End of program - end_time = time.perf_counter() - printc('Program took {:.4f} seconds.'.format(end_time - init_time), - 'CYAN') - - def pl(): """ Function for plotting the benchmarks. @@ -211,6 +145,6 @@ def pl(): if __name__ == '__main__': - ml() + do_ml(min_training_size=1500, max_training_size=3000) # pl() print('OK!') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index 12323780a..8724e6831 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -113,7 +113,7 @@ def ml(desc_data, def do_ml(min_training_size, max_training_size=None, - training_increment_size=None, + training_increment_size=500, ljm_sigma=1.0, ljm_epsilon=1.0, save_benchmarks=False, @@ -138,6 +138,8 @@ def do_ml(min_training_size, """ # Initialization time. init_time = time.perf_counter() + if not max_training_size: + max_training_size = min_training_size + training_increment_size # Data reading. molecules, nuclear_charge, energy_pbe0, energy_delta = read_qm7_data() -- cgit v1.2.3-70-g09d2 From f9cd430d8e66cdac5d78a643f87445e3dd6bdf8e Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 10:54:36 -0700 Subject: Refactor code --- lj_matrix/__init__.py | 4 +- lj_matrix/__main__.py | 125 +------------------------------------------------- lj_matrix/misc.py | 121 ++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 126 insertions(+), 124 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__init__.py b/lj_matrix/__init__.py index d59e3481c..a430aac68 100644 --- a/lj_matrix/__init__.py +++ b/lj_matrix/__init__.py @@ -28,6 +28,7 @@ from lj_matrix.gauss_kernel import gauss_kernel from lj_matrix.cholesky_solve import cholesky_solve from lj_matrix.do_ml import do_ml from lj_matrix.parallel_create_matrices import parallel_create_matrices +from lj_matrix.misc import plot_benchmarks # If somebody does "from package import *", this is what they will @@ -43,4 +44,5 @@ __all__ = ['read_nc_data', 'gauss_kernel', 'cholesky_solve', 'do_ml', - 'parallel_create_matrices'] + 'parallel_create_matrices', + 'plot_benchmarks'] diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index f7e4065da..98f341e1e 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -20,131 +20,10 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ -import pandas as pd from lj_matrix.do_ml import do_ml - - -def pl(): - """ - Function for plotting the benchmarks. - """ - # Original columns. - or_cols = ['ml_type', - 'tr_size', - 'te_size', - 'kernel_s', - 'mae', - 'time', - 'lj_s', - 'lj_e', - 'date_ran'] - # Drop some original columns. - dor_cols = ['te_size', - 'kernel_s', - 'time', - 'date_ran'] - - # Read benchmarks data and drop some columns. - data_temp = pd.read_csv('data\\benchmarks.csv',) - data = pd.DataFrame(data_temp, columns=or_cols) - data = data.drop(columns=dor_cols) - - # Get the data of the first benchmarks and drop unnecesary columns. - first_data = pd.DataFrame(data, index=range(0, 22)) - first_data = first_data.drop(columns=['lj_s', 'lj_e']) - - # Columns to keep temporarily. - fd_columns = ['ml_type', - 'tr_size', - 'mae'] - - # Create new dataframes for each matrix descriptor and fill them. - first_data_cm = pd.DataFrame(columns=fd_columns) - first_data_ljm = pd.DataFrame(columns=fd_columns) - for i in range(first_data.shape[0]): - temp_df = first_data.iloc[[i]] - if first_data.at[i, 'ml_type'] == 'CM': - first_data_cm = first_data_cm.append(temp_df) - else: - first_data_ljm = first_data_ljm.append(temp_df) - - # Drop unnecesary column and rename 'mae' for later use. - first_data_cm = first_data_cm.drop(columns=['ml_type'])\ - .rename(columns={'mae': 'cm_mae'}) - first_data_ljm = first_data_ljm.drop(columns=['ml_type'])\ - .rename(columns={'mae': 'ljm_mae'}) - # print(first_data_cm) - # print(first_data_ljm) - - # Get the cm data axis so it can be joined with the ljm data axis. - cm_axis = first_data_cm.plot(x='tr_size', - y='cm_mae', - kind='line') - # Get the ljm data axis and join it with the cm one. - plot_axis = first_data_ljm.plot(ax=cm_axis, - x='tr_size', - y='ljm_mae', - kind='line') - plot_axis.set_xlabel('tr_size') - plot_axis.set_ylabel('mae') - plot_axis.set_title('mae for different tr_sizes') - # Get the figure and save it. - # plot_axis.get_figure().savefig('.figs\\mae_diff_tr_sizes.pdf') - - # Get the rest of the benchmark data and drop unnecesary column. - new_data = data.drop(index=range(0, 22)) - new_data = new_data.drop(columns=['ml_type']) - - # Get the first set and rename it. - nd_first = first_data_ljm.rename(columns={'ljm_mae': '1, 1'}) - ndf_axis = nd_first.plot(x='tr_size', - y='1, 1', - kind='line') - last_axis = ndf_axis - for i in range(22, 99, 11): - lj_s = new_data['lj_s'][i] - lj_e = new_data['lj_e'][i] - new_mae = '{}, {}'.format(lj_s, lj_e) - nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ - .drop(columns=['lj_s', 'lj_e'])\ - .rename(columns={'mae': new_mae}) - last_axis = nd_temp.plot(ax=last_axis, - x='tr_size', - y=new_mae, - kind='line') - print(nd_temp) - - last_axis.set_xlabel('tr_size') - last_axis.set_ylabel('mae') - last_axis.set_title('mae for different parameters of lj(s)') - - last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_s.pdf') - - ndf_axis = nd_first.plot(x='tr_size', - y='1, 1', - kind='line') - last_axis = ndf_axis - for i in range(99, data.shape[0], 11): - lj_s = new_data['lj_s'][i] - lj_e = new_data['lj_e'][i] - new_mae = '{}, {}'.format(lj_s, lj_e) - nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ - .drop(columns=['lj_s', 'lj_e'])\ - .rename(columns={'mae': new_mae}) - last_axis = nd_temp.plot(ax=last_axis, - x='tr_size', - y=new_mae, - kind='line') - print(nd_temp) - - last_axis.set_xlabel('tr_size') - last_axis.set_ylabel('mae') - last_axis.set_title('mae for different parameters of lj(e)') - - last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_e.pdf') - +# from lj_matrix.misc import plot_benchmarks if __name__ == '__main__': do_ml(min_training_size=1500, max_training_size=3000) - # pl() + # plot_benchmarks() print('OK!') diff --git a/lj_matrix/misc.py b/lj_matrix/misc.py index c50653a5c..e9142b05f 100644 --- a/lj_matrix/misc.py +++ b/lj_matrix/misc.py @@ -21,6 +21,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from colorama import init, Fore, Style +import pandas as pd init() @@ -51,3 +52,123 @@ def printc(text, color): actual_color = color_dic[color] print(actual_color + text + Style.RESET_ALL) + + +def plot_benchmarks(): + """ + For plotting the benchmarks. + """ + # Original columns. + or_cols = ['ml_type', + 'tr_size', + 'te_size', + 'kernel_s', + 'mae', + 'time', + 'lj_s', + 'lj_e', + 'date_ran'] + # Drop some original columns. + dor_cols = ['te_size', + 'kernel_s', + 'time', + 'date_ran'] + + # Read benchmarks data and drop some columns. + data_temp = pd.read_csv('data\\benchmarks.csv',) + data = pd.DataFrame(data_temp, columns=or_cols) + data = data.drop(columns=dor_cols) + + # Get the data of the first benchmarks and drop unnecesary columns. + first_data = pd.DataFrame(data, index=range(0, 22)) + first_data = first_data.drop(columns=['lj_s', 'lj_e']) + + # Columns to keep temporarily. + fd_columns = ['ml_type', + 'tr_size', + 'mae'] + + # Create new dataframes for each matrix descriptor and fill them. + first_data_cm = pd.DataFrame(columns=fd_columns) + first_data_ljm = pd.DataFrame(columns=fd_columns) + for i in range(first_data.shape[0]): + temp_df = first_data.iloc[[i]] + if first_data.at[i, 'ml_type'] == 'CM': + first_data_cm = first_data_cm.append(temp_df) + else: + first_data_ljm = first_data_ljm.append(temp_df) + + # Drop unnecesary column and rename 'mae' for later use. + first_data_cm = first_data_cm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'cm_mae'}) + first_data_ljm = first_data_ljm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'ljm_mae'}) + # print(first_data_cm) + # print(first_data_ljm) + + # Get the cm data axis so it can be joined with the ljm data axis. + cm_axis = first_data_cm.plot(x='tr_size', + y='cm_mae', + kind='line') + # Get the ljm data axis and join it with the cm one. + plot_axis = first_data_ljm.plot(ax=cm_axis, + x='tr_size', + y='ljm_mae', + kind='line') + plot_axis.set_xlabel('tr_size') + plot_axis.set_ylabel('mae') + plot_axis.set_title('mae for different tr_sizes') + # Get the figure and save it. + # plot_axis.get_figure().savefig('.figs\\mae_diff_tr_sizes.pdf') + + # Get the rest of the benchmark data and drop unnecesary column. + new_data = data.drop(index=range(0, 22)) + new_data = new_data.drop(columns=['ml_type']) + + # Get the first set and rename it. + nd_first = first_data_ljm.rename(columns={'ljm_mae': '1, 1'}) + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(22, 99, 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(s)') + + last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_s.pdf') + + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(99, data.shape[0], 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(e)') + + last_axis.get_figure().savefig('.figs\\mae_diff_param_lj_e.pdf') -- cgit v1.2.3-70-g09d2 From c1e7b327655ebaa5c44e4bef5b9b675b23782952 Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 11:05:39 -0700 Subject: Refactor code and fix bug --- lj_matrix/do_ml.py | 3 +++ lj_matrix/lj_matrix.py | 17 +++++++++++++++-- lj_matrix/parallel_create_matrices.py | 27 +++++++++++++++++++++------ 3 files changed, 39 insertions(+), 8 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index 8724e6831..45dc7a5f0 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -114,6 +114,7 @@ def ml(desc_data, def do_ml(min_training_size, max_training_size=None, training_increment_size=500, + ljm_diag_value=None, ljm_sigma=1.0, ljm_epsilon=1.0, save_benchmarks=False, @@ -127,6 +128,7 @@ def do_ml(min_training_size, min_training_size: minimum training size. max_training_size: maximum training size. training_increment_size: training increment size. + ljm_diag_value: if a special diagonal value should be used in lj matrix. ljm_sigma: sigma value for lj matrix. ljm_epsilon: epsilon value for lj matrix. save_benchmarks: if benchmarks should be saved. @@ -147,6 +149,7 @@ def do_ml(min_training_size, # Matrices calculation. cm_data, ljm_data = parallel_create_matrices(molecules, nuclear_charge, + ljm_diag_value, ljm_sigma, ljm_epsilon, max_len, diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py index 0c16b5686..c3b61becb 100644 --- a/lj_matrix/lj_matrix.py +++ b/lj_matrix/lj_matrix.py @@ -29,6 +29,7 @@ from lj_matrix.misc import printc def lj_matrix(mol_data, nc_data, + diag_value=None, sigma=1.0, epsilon=1.0, max_len=25, @@ -38,6 +39,7 @@ def lj_matrix(mol_data, Creates the Lennard-Jones Matrix from the molecule data given. mol_data: molecule data, matrix of atom coordinates. nc_data: nuclear charge data, array of atom data. + diag_value: if special diagonal value is to be used. sigma: sigma value. epsilon: epsilon value. max_len: maximum amount of atoms in molecule. @@ -86,7 +88,10 @@ def lj_matrix(mol_data, z = (z_i-z_j)**2 if i == j: - lj[i, j] = (0.5*Z_i**2.4) + if not diag_value: + lj[i, j] = (0.5*Z_i**2.4) + else: + lj[i, j] = diag_value else: # Calculations are done after i==j is checked # so no division by zero is done. @@ -144,7 +149,10 @@ def lj_matrix(mol_data, z = (z_i-z_j)**2 if i == j: - lj_row.append(0.5*Z_i**2.4) + if not diag_value: + lj_row.append(0.5*Z_i**2.4) + else: + lj_row.append(diag_value) else: # Calculations are done after i==j is checked # so no division by zero is done. @@ -173,6 +181,7 @@ def lj_matrix(mol_data, def lj_matrix_multiple(mol_data, nc_data, pipe=None, + diag_value=None, sigma=1.0, epsilon=1.0, max_len=25, @@ -184,6 +193,9 @@ def lj_matrix_multiple(mol_data, nc_data: nuclear charge data, array of atom data. pipe: for multiprocessing purposes. Sends the data calculated through a pipe. + diag_value: if special diagonal value is to be used. + sigma: sigma value. + epsilon: epsilon value. max_len: maximum amount of atoms in molecule. as_eig: if data should be returned as matrix or array of eigenvalues. bohr_radius_units: if units should be in bohr's radius units. @@ -193,6 +205,7 @@ def lj_matrix_multiple(mol_data, ljm_data = np.array([lj_matrix(mol, nc, + diag_value, sigma, epsilon, max_len, diff --git a/lj_matrix/parallel_create_matrices.py b/lj_matrix/parallel_create_matrices.py index 0ab691525..cd5ef5c8e 100644 --- a/lj_matrix/parallel_create_matrices.py +++ b/lj_matrix/parallel_create_matrices.py @@ -27,8 +27,9 @@ from lj_matrix.lj_matrix import lj_matrix_multiple def parallel_create_matrices(mol_data, nc_data, - sigma=1.0, - epsilon=1.0, + ljm_diag_value=None, + ljm_sigma=1.0, + ljm_epsilon=1.0, max_len=25, as_eig=True, bohr_radius_units=False): @@ -36,8 +37,9 @@ def parallel_create_matrices(mol_data, Creates the Coulomb and L-J matrices in parallel. mol_data: molecule data, matrix of atom coordinates. nc_data: nuclear charge data, array of atom data. - sigma: sigma value for L-J matrix. - epsilon: epsilon value for L-J matrix. + ljm_diag_value: if special diagonal value is to be used for lj matrix. + ljm_sigma: sigma value for lj matrix. + ljm_epsilon: psilon value for lj matrix. max_len: maximum amount of atoms in molecule. as_eig: if data should be returned as matrix or array of eigenvalues. bohr_radius_units: if units should be in bohr's radius units. @@ -49,14 +51,27 @@ def parallel_create_matrices(mol_data, cm_recv, cm_send = Pipe(False) p1 = Process(target=c_matrix_multiple, - args=(mol_data, nc_data, cm_send)) + args=(mol_data, + nc_data, + cm_send, + max_len, + as_eig, + bohr_radius_units)) procs.append(p1) pipes.append(cm_recv) p1.start() ljm_recv, ljm_send = Pipe(False) p2 = Process(target=lj_matrix_multiple, - args=(mol_data, nc_data, ljm_send, sigma, epsilon)) + args=(mol_data, + nc_data, + ljm_send, + ljm_diag_value, + ljm_sigma, + ljm_epsilon, + max_len, + as_eig, + bohr_radius_units)) procs.append(p2) pipes.append(ljm_recv) p2.start() -- cgit v1.2.3-70-g09d2 From e4f9e15588ec796f73c000a683cc9152454a913c Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 11:12:36 -0700 Subject: Fix bugs --- lj_matrix/__main__.py | 10 +++++++++- lj_matrix/do_ml.py | 7 +++++-- 2 files changed, 14 insertions(+), 3 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 98f341e1e..811024ff0 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -24,6 +24,14 @@ from lj_matrix.do_ml import do_ml # from lj_matrix.misc import plot_benchmarks if __name__ == '__main__': - do_ml(min_training_size=1500, max_training_size=3000) + do_ml(min_training_size=1500, + max_training_size=2000, + training_increment_size=500, + test_size=None, + ljm_diag_value=None, + ljm_sigma=1.0, + ljm_epsilon=1.0, + save_benchmarks=False, + show_msgs=True) # plot_benchmarks() print('OK!') diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index 45dc7a5f0..da9386bf7 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -114,6 +114,7 @@ def ml(desc_data, def do_ml(min_training_size, max_training_size=None, training_increment_size=500, + test_size=None, ljm_diag_value=None, ljm_sigma=1.0, ljm_epsilon=1.0, @@ -128,6 +129,8 @@ def do_ml(min_training_size, min_training_size: minimum training size. max_training_size: maximum training size. training_increment_size: training increment size. + test_size: size of the test set to use. If no size is given, + the last remaining molecules are used. ljm_diag_value: if a special diagonal value should be used in lj matrix. ljm_sigma: sigma value for lj matrix. ljm_epsilon: epsilon value for lj matrix. @@ -170,7 +173,7 @@ def do_ml(min_training_size, i, 'CM', cm_send, - max_training_size, + test_size, sigma, show_msgs)) procs.append(p1) @@ -184,7 +187,7 @@ def do_ml(min_training_size, i, 'L-JM', ljm_send, - max_training_size, + test_size, sigma, show_msgs)) procs.append(p2) -- cgit v1.2.3-70-g09d2 From 4704314c9b4d1066383da5c3d6ca87bba9067c8d Mon Sep 17 00:00:00 2001 From: David Luevano <55825613+luevano@users.noreply.github.com> Date: Sat, 28 Dec 2019 11:37:22 -0700 Subject: Refactor code --- lj_matrix/__main__.py | 1 + lj_matrix/do_ml.py | 5 ++++- lj_matrix/lj_matrix.py | 2 +- lj_matrix/read_qm7_data.py | 7 ++++--- 4 files changed, 10 insertions(+), 5 deletions(-) (limited to 'lj_matrix') diff --git a/lj_matrix/__main__.py b/lj_matrix/__main__.py index 811024ff0..688e5adcc 100644 --- a/lj_matrix/__main__.py +++ b/lj_matrix/__main__.py @@ -31,6 +31,7 @@ if __name__ == '__main__': ljm_diag_value=None, ljm_sigma=1.0, ljm_epsilon=1.0, + r_seed=111, save_benchmarks=False, show_msgs=True) # plot_benchmarks() diff --git a/lj_matrix/do_ml.py b/lj_matrix/do_ml.py index da9386bf7..25a55e823 100644 --- a/lj_matrix/do_ml.py +++ b/lj_matrix/do_ml.py @@ -118,6 +118,7 @@ def do_ml(min_training_size, ljm_diag_value=None, ljm_sigma=1.0, ljm_epsilon=1.0, + r_seed=111, save_benchmarks=False, max_len=25, as_eig=True, @@ -134,6 +135,7 @@ def do_ml(min_training_size, ljm_diag_value: if a special diagonal value should be used in lj matrix. ljm_sigma: sigma value for lj matrix. ljm_epsilon: epsilon value for lj matrix. + r_seed: random seed to use for the shuffling. save_benchmarks: if benchmarks should be saved. max_len: maximum amount of atoms in molecule. as_eig: if data should be returned as matrix or array of eigenvalues. @@ -147,7 +149,8 @@ def do_ml(min_training_size, max_training_size = min_training_size + training_increment_size # Data reading. - molecules, nuclear_charge, energy_pbe0, energy_delta = read_qm7_data() + molecules, nuclear_charge, energy_pbe0, energy_delta =\ + read_qm7_data(r_seed) # Matrices calculation. cm_data, ljm_data = parallel_create_matrices(molecules, diff --git a/lj_matrix/lj_matrix.py b/lj_matrix/lj_matrix.py index c3b61becb..6739ae283 100644 --- a/lj_matrix/lj_matrix.py +++ b/lj_matrix/lj_matrix.py @@ -88,7 +88,7 @@ def lj_matrix(mol_data, z = (z_i-z_j)**2 if i == j: - if not diag_value: + if diag_value is None: lj[i, j] = (0.5*Z_i**2.4) else: lj[i, j] = diag_value diff --git a/lj_matrix/read_qm7_data.py b/lj_matrix/read_qm7_data.py index 9bb7629ca..4401ca1c0 100644 --- a/lj_matrix/read_qm7_data.py +++ b/lj_matrix/read_qm7_data.py @@ -59,7 +59,7 @@ def read_db_data(zi_data, its contents as usable variables. zi_data: dictionary containing nuclear charge data. data_path: path to the data directory. - r_seed: random seed. + r_seed: random seed to use for the shuffling. """ os.chdir(data_path) @@ -122,9 +122,10 @@ def read_db_data(zi_data, return molecules, nuclear_charge, energy_pbe0, energy_delta -def read_qm7_data(): +def read_qm7_data(r_seed=111): """ Reads all the qm7 data. + r_seed: random seed to use for the shuffling. """ tic = time.perf_counter() printc('Data reading started.', 'CYAN') @@ -135,7 +136,7 @@ def read_qm7_data(): zi_data = read_nc_data(data_path) molecules, nuclear_charge, energy_pbe0, energy_delta = \ - read_db_data(zi_data, data_path) + read_db_data(zi_data, data_path, r_seed) os.chdir(init_path) toc = time.perf_counter() -- cgit v1.2.3-70-g09d2