res_reg_lmnt_awikner.helpers

 1import numpy as np
 2from numba import jit, objmode
 3from scipy.signal import find_peaks
 4import os
 5
 6
 7def get_windows_path(path_base):
 8    path = path_base.replace('/', '\\')
 9    path = u"\\\\?\\" + path
10    return path
11
12
13@jit(nopython=True, fastmath=True)
14def poincare_max(traj, idxs=np.empty(1, dtype=np.intc)):
15    if idxs.size == 0:
16        idxs = np.arange(traj.shape[0])
17    poincare_map = []
18    for j in idxs:
19        with objmode(peaks='int64[:]'):
20            peaks, tmp = find_peaks(traj[j])
21        pmap = np.zeros(peaks.size)
22        for i, peak in enumerate(peaks):
23            with objmode(polyvals='double[:]'):
24                polyvals = np.polyfit(np.arange(3), traj[j, peak - 1:peak + 2], 2)
25            if polyvals[0] == 0:
26                if polyvals[1] <= 0:
27                    pmap[i] = polyvals[2]
28                else:
29                    pmap[i] = polyvals[2] + polyvals[1] * 2
30            else:
31                pmap[i] = polyvals[2] - polyvals[1] ** 2.0 / (4 * polyvals[0])
32        poincare_map.append(pmap)
33    return poincare_map
34
35
36@jit(nopython=True, fastmath=True)
37def poincare_max_peaks(traj, idxs=np.empty(1, dtype=np.intc)):
38    if idxs.size == 0:
39        idxs = np.arange(traj.shape[0])
40    poincare_map = []
41    peaks_all = []
42    for j in idxs:
43        with objmode(peaks='int64[:]'):
44            peaks, tmp = find_peaks(traj[j])
45        pmap = np.zeros(peaks.size)
46        for i, peak in enumerate(peaks):
47            with objmode(polyvals='double[:]'):
48                polyvals = np.polyfit(np.arange(3), traj[j, peak - 1:peak + 2], 2)
49            if polyvals[0] == 0:
50                if polyvals[1] <= 0:
51                    pmap[i] = polyvals[2]
52                else:
53                    pmap[i] = polyvals[2] + polyvals[1] * 2
54            else:
55                pmap[i] = polyvals[2] - polyvals[1] ** 2.0 / (4 * polyvals[0])
56        poincare_map.append(pmap)
57        peaks_all.append(peaks)
58    return poincare_map, peaks_all
59
60
61def set_numba(root_folder, disable_jit):
62    config_file = open(os.path.join(root_folder, '.numba_config.yaml'), 'w')
63    config_file.write('---\n')
64    config_file.write('disable_jit: %d' % int(disable_jit))
65    config_file.close()
66
67def get_filename(run_folder_name, var_str, res_itr, train_seed, noise_val, reg_train_time, **kwargs):
68    if 'test_idx' in kwargs:
69        if 'reg' in kwargs:
70            filename = os.path.join(run_folder_name, '%s_res%d_train%d_test%d_noise%e_reg%e_regtrain%d.csv' % (
71                var_str, res_itr, train_seed, kwargs['test_idx'], noise_val, kwargs['reg'], reg_train_time))
72        else:
73            filename = os.path.join(run_folder_name, '%s_res%d_train%d_test%d_noise%e_regtrain%d.csv' % (
74                var_str, res_itr, train_seed, kwargs['test_idx'], noise_val, reg_train_time))
75    else:
76        filename = os.path.join(run_folder_name, '%s_res%d_train%d_noise%e_regtrain%d.csv' % (
77            var_str, res_itr, train_seed, noise_val, reg_train_time))
78    if 'just_file' in kwargs:
79        if isinstance(kwargs['just_file'], bool):
80            if kwargs['just_file']:
81                return os.path.basename(filename)
82            else:
83                return filename
84        else:
85            raise TypeError()
86    else:
87        return filename