def main(argv):
config = read_parser(argv, Inputs, InputsOpt_Defaults)
from Main_Analysis import main as invoke_signal
if config['mode'] == 'spectrum':
t, x, f, magX = invoke_signal([
'--channel', 'AE_3', '--fs', '1.e6', '--power2', 'OFF', '--plot',
'OFF'
])
plt.show()
df = f[2] - f[1]
f_fund = 40.2093
n_harm = 5
F_harm = [(i + 1) * f_fund for i in range(n_harm)]
NL_harm = [f_harm / df for f_harm in F_harm]
AMP_harm = [magX[int(nl_harm)] for nl_harm in NL_harm]
plt.plot(f, magX, 'r', F_harm, AMP_harm, 'o')
plt.show()
else:
print('unknown mode')
return
def main(argv):
config_input = read_parser(argv, Inputs, Inputs_opt, Defaults)
# path = config_input['path']
file = config_input['file']
channel = config_input['channel']
power2 = config_input['power2']
save = config_input['save']
file_h1 = config_input['file_h1']
min_iter = int(config_input['min_iter'])
max_iter = int(config_input['max_iter'])
s_number = int(config_input['s_number'])
tolerance = float(config_input['tolerance'])
file_h2 = config_input['file_h2']
file_h3 = config_input['file_h3']
file_h4 = config_input['file_h4']
file_h5 = config_input['file_h5']
file_h6 = config_input['file_h6']
file_h7 = config_input['file_h7']
# filepath_x = join(path, file)
# filename = filepath_x
# # x = f_open_mat(filepath_x, channel)
# # x = np.ndarray.flatten(x)
# point_index = filepath_x.find('.')
# extension = filepath_x[point_index+1] +filepath_x[point_index+2] + filepath_x[point_index+3]
# # x = load_signal(filename, channel)
# if extension == 'mat':
# # x, channel = f_open_mat_2(filename)
# # x = f_open_mat(filename, channel)
# # x = np.ndarray.flatten(x)
# print(filename)
# print(channel)
# x = f_open_mat_2(filename, channel)
# x = np.ndarray.flatten(x)
# elif extension == 'tdm': #tdms
# x = f_open_tdms(filename, channel)
# # x = f_open_tdms_2(filename)
# elif extension == 'txt': #tdms
# x = np.loadtxt(filename)
# # filename = os.path.basename(filename) #changes from path to file
# print(filepath_x)
from Main_Analysis import invoke_signal
dict_int = invoke_signal(config_input)
x = dict_int['signal']
filename = dict_int['filename']
if power2 == 'auto':
n_points = 2**(max_2power(len(x)))
elif power2 == 'OFF':
n_points = len(x)
else:
n_points = 2**power2
x = x[0:n_points]
# n_points = 2**int(power2)
# x = x[0:n_points]
if file_h1 != None and file_h2 == None:
print('To calculate: h2')
name_out = 'h2_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
x = x - h1
elif file_h1 != None and file_h2 != None and file_h3 == None:
print('To calculate: h3')
name_out = 'h3_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
filepath_h2 = file_h2
h2 = read_pickle(filepath_h2)
x = x - h1 - h2
elif file_h1 != None and file_h2 != None and file_h3 != None and file_h4 == None:
print('To calculate: h4')
name_out = 'h4_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
filepath_h2 = file_h2
h2 = read_pickle(filepath_h2)
filepath_h3 = file_h3
h3 = read_pickle(filepath_h3)
x = x - h1 - h2 - h3
elif file_h1 != None and file_h2 != None and file_h3 != None and file_h4 != None and file_h5 == None:
print('To calculate: h5')
name_out = 'h5_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
filepath_h2 = file_h2
h2 = read_pickle(filepath_h2)
filepath_h3 = file_h3
h3 = read_pickle(filepath_h3)
filepath_h4 = file_h4
h4 = read_pickle(filepath_h4)
x = x - h1 - h2 - h3 - h4
elif file_h1 != None and file_h2 != None and file_h3 != None and file_h4 != None and file_h5 != None and file_h6 == None:
print('To calculate: h6')
name_out = 'h6_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
filepath_h2 = file_h2
h2 = read_pickle(filepath_h2)
filepath_h3 = file_h3
h3 = read_pickle(filepath_h3)
filepath_h4 = file_h4
h4 = read_pickle(filepath_h4)
filepath_h5 = file_h5
h5 = read_pickle(filepath_h5)
x = x - h1 - h2 - h3 - h4 - h5
elif file_h1 != None and file_h2 != None and file_h3 != None and file_h4 != None and file_h5 != None and file_h6 != None and file_h7 == None:
print('To calculate: h7')
name_out = 'h7_'
filepath_h1 = file_h1
h1 = read_pickle(filepath_h1)
filepath_h2 = file_h2
h2 = read_pickle(filepath_h2)
filepath_h3 = file_h3
h3 = read_pickle(filepath_h3)
filepath_h4 = file_h4
h4 = read_pickle(filepath_h4)
filepath_h5 = file_h5
h5 = read_pickle(filepath_h5)
filepath_h6 = file_h6
h6 = read_pickle(filepath_h6)
x = x - h1 - h2 - h3 - h4 - h5 - h6
else:
print('To calculate: h1')
name_out = 'h1_'
print('Fs = 1 MHz for AE')
fs = 1000000.
dt = 1 / fs
n = len(x)
t = np.array([i * dt for i in range(n)])
#++++++++++++++++++++++++++++ENVELOPES AND MEAN
# x = butter_highpass(x=x, fs=1.e6, freq=80.e3, order=3, warm_points=None)
# x = butter_demodulation(x=x, fs=10.e6, filter=['lowpass', 5000., 3], prefilter=['highpass', 80.e3, 3], type_rect='only_positives', dc_value='without_dc')
# plt.plot(x)
# plt.show()
# h1 = sifting_iteration(t, x, min_iter, max_iter, s_number, tolerance)
h1 = sifting_iteration_sd(t, x, min_iter, max_iter, tolerance)
# h1 = sifting_iteration_sd_opt(t, x, min_iter, max_iter, tolerance)
file = basename(file)
if save == 'ON':
print('Saving...')
save_pickle(name_out + file[:-4] + '.pkl', h1)
# np.savetxt(name_out + file[:-4] + '.txt', h1)
print("--- %s seconds ---" % (time.time() - start_time))
sys.exit()
def main(argv):
config_input = read_parser(argv, Inputs, Inputs_opt, Defaults)
file = config_input['file']
if file == None:
root = Tk()
root.withdraw()
root.update()
file = filedialog.askopenfilename()
config_input['file'] = file
root.destroy()
channel = config_input['channel']
power2 = config_input['power2']
save = config_input['save']
min_iter = int(config_input['min_iter'])
max_iter = int(config_input['max_iter'])
s_number = int(config_input['s_number'])
tolerance = float(config_input['tolerance'])
dict_int = invoke_signal(config_input)
x = dict_int['signal']
filename = dict_int['filename']
if power2 == 'auto':
n_points = 2**(max_2power(len(x)))
elif power2 == 'OFF':
n_points = len(x)
else:
n_points = 2**power2
x = x[0:n_points]
dt = 1. / config_input['fs']
n = len(x)
t = np.array([i * dt for i in range(n)])
for count in range(config_input['n_imf']):
count += 1
print('To calculate: h' + str(count))
name_out = 'h' + str(count) + '_'
print("--- %s seconds Inicia Sifting ---" % (time.time() - start_time))
# h = sifting_iteration_sd(t, x, min_iter, max_iter, tolerance)
# h = sifting_iteration_ez_opt(t, x, min_iter, max_iter, s_number, tolerance)
h = sifting_iteration_s_corr(t, x, min_iter, max_iter, s_number,
tolerance)
file = basename(file)
print('Saving...')
myname = name_out + file[:-4] + '.pkl'
save_pickle(myname, h)
print("--- %s seconds ---" % (time.time() - start_time))
x = x - h
sys.exit()
def main(argv):
config = read_parser(argv, Inputs, InputsOpt_Defaults)
from Main_Analysis import invoke_signal
if config['mode'] == 'avg_spectrum':
n_avg = config['n_avg']
magX_list = []
for i in range(n_avg):
dict_int = invoke_signal(config)
x = dict_int['signal']
t = dict_int['time']
f = dict_int['freq']
magX = dict_int['mag_fft']
filename = dict_int['filename']
if i == 0:
magX_avg = np.zeros(len(magX))
magX_avg = magX_avg + magX
magX_avg = magX_avg / float(n_avg)
fig, ax = plt.subplots()
ax.plot(f, magX_avg)
ax.set_xlabel('Frequency [Hz]')
plt.show()
if config['save'] == 'ON':
mydict = {}
mydict['freq_array'] = f
mydict['avg_spectrum'] = magX_avg
if config['name'] == 'auto':
import datetime
stamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
else:
stamp = config['name']
save_pickle('avg_spectrum_' + config['channel'] + stamp + '.pkl', mydict)
else:
print('no save')
# plt.plot(f/1000., magX_avg)
# plt.xlabel('Frequenz [kHz]')
# params = {'mathtext.default': 'regular' }
# plt.rcParams.update(params)
# plt.ylabel('Amplitude [mV]')
# plt.show()
elif config['mode'] == 'plot_spectrum':
magX_avg_list = []
f_list = []
root = Tk()
root.withdraw()
root.update()
Filenames = filedialog.askopenfilenames()
root.destroy()
for filename in Filenames:
print(os.path.basename(filename))
mydict = read_pickle(filename)
f_list.append(mydict['freq_array'])
magX_avg_list.append(mydict['avg_spectrum'])
channel = 'AE_1'
element = 'Mag-FFT'
fig, ax = plt.subplots(nrows=3, ncols=1, sharex=True, sharey=True)
# ax[].set_title(channel + ' ' + element + '\n' + os.path.basename(filename), fontsize=10)
ax[0].set_title('BMB am Punkt D', fontsize=10, fontweight='bold')
ax[1].set_title('Drahtbuerste am Punkt F', fontsize=10, fontweight='bold')
ax[2].set_title('Kugelfall Maximale Hoehe', fontsize=10, fontweight='bold')
ax[0].title.set_position([0.5, 1.0])
ax[1].title.set_position([0.5, 0.8])
ax[2].title.set_position([0.5, 0.8])
ax[0].plot(f_list[0]/1000., magX_avg_list[0], 'r')
ax[1].plot(f_list[1]/1000., magX_avg_list[1], 'r')
ax[2].plot(f_list[2]/1000., magX_avg_list[2], 'r')
ax[2].set_xlabel('Frequenz kHz')
ax[0].ticklabel_format(axis='y', style='sci', scilimits=(-1, 1))
ax[1].ticklabel_format(axis='y', style='sci', scilimits=(-1, 1))
ax[2].ticklabel_format(axis='y', style='sci', scilimits=(-1, 1))
params = {'mathtext.default': 'regular' }
plt.rcParams.update(params)
ax[0].set_ylabel('Amplitude (m$V_{in}$)')
ax[1].set_ylabel('Amplitude (m$V_{in}$)')
ax[2].set_ylabel('Amplitude (m$V_{in}$)')
plt.show()
elif config['mode'] == 'plot_avg_spectrum':
magX_avg_list = []
f_list = []
root = Tk()
root.withdraw()
root.update()
Filenames = filedialog.askopenfilenames()
root.destroy()
for filename in Filenames:
print(os.path.basename(filename))
mydict = read_pickle(filename)
f_list.append(mydict['freq_array'])
magX_avg_list.append(mydict['avg_spectrum'])
channel = config['channel']
element = 'Mag-FFT'
fig, ax = plt.subplots(nrows=2, ncols=1, sharex=True, sharey=True)
# ax[].set_title(channel + ' ' + element + '\n' + os.path.basename(filename), fontsize=10)
# ax.set_title(config['channel'] + ' FFT-Average WB-Source at F', fontsize=10, fontweight='bold')
# title = config['channel'] + ' FFT-Mittelwert Hsu-Nielsen-Bursts'
title = config['channel'] + ' FFT-Mittelwert'
title = title.replace('_', '-')
ax[0].set_title('Mit Lack', fontsize=12)
ax[1].set_title('Ohne Lack', fontsize=12)
# ax.ticklabel_format(axis='y', style='sci', scilimits=(-1, 1))
ax[0].plot(np.array(f_list[0])/1000., magX_avg_list[0]*1000., 'r')
ax[1].plot(np.array(f_list[1])/1000., magX_avg_list[1]*1000., 'darkred')
# ax.set_xlabel('Frequency (kHz)')
ax[1].set_xlabel('Frequenz [kHz]', fontsize=12)
params = {'mathtext.default': 'regular' }
plt.rcParams.update(params)
ax[1].set_ylabel('Amplitude [mV]', fontsize=12)
ax[0].set_ylabel('Amplitude [mV]', fontsize=12)
ax[0].tick_params(axis='both', labelsize=11)
ax[1].tick_params(axis='both', labelsize=11)
plt.tight_layout()
plt.show()
else:
print('unknown mode')
return
def main(argv):
config = read_parser(argv, Inputs, InputsOpt_Defaults)
if config['mode'] == 'boxplot_features':
print('Select normal signal..')
dict_signal_normal = invoke_signal(config)
x_normal = dict_signal_normal['signal']
t_normal = dict_signal_normal['time']
filename_signal_normal = dict_signal_normal['filename']
dict_features_normal = calculate_features_2(t_normal, x_normal, config)
print('Select ANORMAL signal!!.')
dict_signal_anormal = invoke_signal(config)
x_anormal = dict_signal_anormal['signal']
t_anormal = dict_signal_anormal['time']
filename_signal_anormal = dict_signal_anormal['filename']
dict_features_anormal = calculate_features_2(t_anormal, x_anormal,
config)
fig1, ax1 = plt.subplots()
ax1.boxplot(
[dict_features_normal['crest'], dict_features_anormal['crest']])
ax1.set_xticklabels(['Gearbox-Source', 'WB-Source'], fontsize=11)
ax1.set_ylabel('Crest Factor (-)', fontsize=11)
plt.tight_layout()
plt.savefig(config['channel'] +
'_crest_hp_80_box_thr_3_wt_1000_n_1.png')
fig1d, ax1d = plt.subplots()
ax1d.boxplot(
[dict_features_normal['crest'], dict_features_anormal['crest']])
ax1d.set_xticklabels(['Getriebe-Quelle', 'DB-Quelle'], fontsize=11)
ax1d.set_ylabel('Crest-Faktor (-)', fontsize=11)
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_crest_hp_80_box_thr_3_wt_1000_n_1.png')
fig2, ax2 = plt.subplots()
ax2.boxplot(
[dict_features_normal['rms'], dict_features_anormal['rms']])
ax2.set_xticklabels(['Gearbox-Source', 'WB-Source'], fontsize=11)
ax2.set_ylabel('RMS Value (m$V_{in}$)', fontsize=11)
plt.tight_layout()
plt.savefig(config['channel'] + '_rms_hp_80_box_thr_3_wt_1000_n_1.png')
fig2d, ax2d = plt.subplots()
ax2d.boxplot(
[dict_features_normal['rms'], dict_features_anormal['rms']])
ax2d.set_xticklabels(['Getriebe-Quelle', 'DB-Quelle'], fontsize=11)
ax2d.set_ylabel('RMS-Wert (m$V_{in}$)', fontsize=11)
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_rms_hp_80_box_thr_3_wt_1000_n_1.png')
fig3, ax3 = plt.subplots()
ax3.boxplot(
[dict_features_normal['count'], dict_features_anormal['count']])
ax3.set_xticklabels(['Gearbox-Source', 'WB-Source'], fontsize=11)
ax3.set_ylabel('Cycles Count (-)', fontsize=11)
plt.tight_layout()
plt.savefig(config['channel'] +
'_count_hp_80_box_thr_3_wt_1000_n_1.png')
fig3, ax3d = plt.subplots()
ax3d.boxplot(
[dict_features_normal['count'], dict_features_anormal['count']])
ax3d.set_xticklabels(['Getriebe-Quelle', 'DB-Quelle'], fontsize=11)
ax3d.set_ylabel('Zyklusanzahl (-)', fontsize=11)
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_count_hp_80_box_thr_3_wt_1000_n_1.png')
elif config['mode'] == 'plot_three_burst':
Xs = []
Ts = []
Filenames = []
for i in range(3):
dict_int = invoke_signal(config)
x = dict_int['signal']
t = dict_int['time']
f = dict_int['freq']
magX = dict_int['mag_fft']
filename_x = dict_int['filename']
Xs.append(x)
Ts.append(t)
Filenames.append(filename_x)
fig, ax = plt.subplots(nrows=1, ncols=3)
for i in range(3):
ax[i].plot(Ts[i], Xs[i])
ax[i].set_ylabel('Amplitude [m$V_{in}$]', fontsize=12)
title = config['channel'] + ' WFM Burst an F (Wdh. ' + str(i +
1) + ')'
title = title.replace('_', '-')
ax[i].set_title(title, fontsize=12)
ax[i].set_xlabel('Dauer [s]', fontsize=12)
ax[i].tick_params(axis='both', labelsize=11)
ax[i].ticklabel_format(axis='x', style='sci', scilimits=(-1, 1))
fig.set_size_inches(16, 4)
plt.show()
elif config['mode'] == 'wfm_features':
params = {'mathtext.default': 'regular'}
plt.rcParams.update(params)
dict_signal = invoke_signal(config)
x = dict_signal['signal']
t = dict_signal['time']
filename = dict_signal['filename']
dict_features = calculate_features_2(t, x, config)
fig1, ax1 = plt.subplots()
ax1.plot(t, x)
ax1b = ax1.twinx()
ax1.set_ylabel('Amplitude (m$V_{in}$)')
ax1.set_xlabel('Time (s)')
ax1.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax1b.plot(dict_features['ini_time'], dict_features['crest'], 'ro')
ax1b.set_ylabel('Crest Factor (-)', color='r')
ax1b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig(config['channel'] +
'_crest_hp_80_source_brush_thr_3_wt_1000_n_1.png')
fig2, ax2 = plt.subplots()
ax2.plot(t, x)
ax2b = ax2.twinx()
ax2.set_ylabel('Amplitude (m$V_{in}$)')
ax2.set_xlabel('Zeit (s)')
ax2.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax2b.plot(dict_features['ini_time'], dict_features['crest'], 'ro')
ax2b.set_ylabel('Crest-Faktor (-)', color='r')
ax2b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_crest_hp_80_source_brush_thr_3_wt_1000_n_1.png')
fig3, ax3 = plt.subplots()
ax3.plot(t, x)
ax3b = ax3.twinx()
ax3.set_ylabel('Amplitude (m$V_{in}$)')
ax3.set_xlabel('Time (s)')
ax3.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax3b.plot(dict_features['ini_time'], dict_features['rms'], 'ro')
ax3b.set_ylabel('RMS Value (m$V_{in}$)', color='r')
ax3b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig(config['channel'] +
'_rms_hp_80_source_brush_thr_3_wt_1000_n_1.png')
fig4, ax4 = plt.subplots()
ax4.plot(t, x)
ax4b = ax4.twinx()
ax4.set_ylabel('Amplitude (m$V_{in}$)')
ax4.set_xlabel('Zeit (s)')
ax4.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax4b.plot(dict_features['ini_time'], dict_features['rms'], 'ro')
ax4b.set_ylabel('RMS Wert (m$V_{in}$)', color='r')
ax4b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_rms_hp_80_source_brush_thr_3_wt_1000_n_1.png')
fig5, ax5 = plt.subplots()
ax5.plot(t, x)
ax5b = ax5.twinx()
ax5.set_ylabel('Amplitude (m$V_{in}$)')
ax5.set_xlabel('Time (s)')
ax5.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax5b.plot(dict_features['ini_time'], dict_features['count'], 'ro')
ax5b.set_ylabel('Cycles Count (-)', color='r')
ax5b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig(config['channel'] +
'_count_hp_80_source_brush_thr_3_wt_1000_n_1.png')
fig6, ax6 = plt.subplots()
ax6.plot(t, x)
ax6b = ax6.twinx()
ax6.set_ylabel('Amplitude (m$V_{in}$)')
ax6.set_xlabel('Zeit (s)')
ax6.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax6b.plot(dict_features['ini_time'], dict_features['count'], 'ro')
ax6b.set_ylabel('Zyklusanzahl (-)', color='r')
ax6b.tick_params('y', colors='r')
plt.tight_layout()
plt.savefig('DE_' + config['channel'] +
'_count_hp_80_source_brush_thr_3_wt_1000_n_1.png')
elif config['mode'] == 'obtain_features':
rise = []
dura = []
crest = []
count = []
maxcorr = []
rms = []
freq = []
max = []
print('Select reference burst')
root = Tk()
root.withdraw()
root.update()
filename_burst = filedialog.askopenfilename()
root.destroy()
reference = read_pickle(filename_burst)
for i in range(config['n_signals']):
print('Select signal..')
dict_signal = invoke_signal(config)
x = dict_signal['signal']
t = dict_signal['time']
filename_signal = dict_signal['filename']
dict_features = calculate_features(t, x, reference, config)
rise.append(dict_features['rise'])
dura.append(dict_features['dura'])
crest.append(dict_features['crest'])
count.append(dict_features['count'])
maxcorr.append(dict_features['maxcorr'])
rms.append(dict_features['rms'])
freq.append(dict_features['freq'])
max.append(dict_features['max'])
rise = [element for list_in in rise for element in list_in]
dura = [element for list_in in dura for element in list_in]
crest = [element for list_in in crest for element in list_in]
count = [element for list_in in count for element in list_in]
maxcorr = [element for list_in in maxcorr for element in list_in]
rms = [element for list_in in rms for element in list_in]
freq = [element for list_in in freq for element in list_in]
max = [element for list_in in max for element in list_in]
caca = 'AA'
names = [
'Rise time (us)', 'Duration (us)', 'Crest Factor (-)', 'Count (-)',
'Max. Cross-Corr. (-)', 'RMS Value (mV)', 'Main Freq. (kHz)',
'Max. Value (mV)', 'Initial Time (s)'
]
features = [rise, dura, crest, count, maxcorr, rms, freq, max]
box_8_plot(caca, names, features)
dict_out = {'features': features, 'names': names}
save_pickle(
config['channel'] + '_features_thr_05_wt_500_HSN_point_E.pkl',
dict_out)
elif config['mode'] == 'plot_8_box_vs':
print('Select features normal pickle')
root = Tk()
root.withdraw()
root.update()
filename = filedialog.askopenfilename()
root.destroy()
dict_normal = read_pickle(filename)
print('Select features Anormal pickle...')
root = Tk()
root.withdraw()
root.update()
filename = filedialog.askopenfilename()
root.destroy()
dict_anormal = read_pickle(filename)
features_normal = dict_normal['features']
features_anormal = dict_anormal['features']
names = dict_normal['names']
labels = ['Gearbox', 'HSN']
box_8_plot_vs(labels, names, features_normal, features_anormal)
names = [
'Steigungszeit [us]', 'Dauer [us]', 'Crest-Faktor [-]',
'Überschwingungen [-]', 'Max. Kreuzkorrelation [-]',
'RMS-Wert [mV]', 'Frequenz [kHz]', 'Max. Wert [mV]',
'Initial Time (s)'
]
labels = ['Getriebe', 'HSN']
box_8_plot_vs(labels, names, features_normal, features_anormal)
else:
print('unknown mode')
return
def main(argv):
config = read_parser(argv, Inputs, InputsOpt_Defaults)
from Main_Analysis import invoke_signal
if config['mode'] == 'plot_envelope':
# t, x, f, magX, filename = invoke_signal(config)
dict_int = invoke_signal(config)
xraw = dict_int['signal_raw']
x = dict_int['signal']
t = dict_int['time']
filename = dict_int['filename']
v_max = np.max(xraw)
xraw = xraw / v_max
x = x / np.max(x)
x = x - np.min(x)
xraw = xraw * v_max
x = x * v_max
fig1, ax1 = plt.subplots()
ax1.plot(t, xraw, label='Signal')
ax1.plot(t, x, label='Envelope')
ax1.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax1.set_xlabel('Time (s)')
params = {'mathtext.default': 'regular'}
plt.rcParams.update(params)
ax1.set_ylabel('Amplitude (m$V_{in}$)')
plt.legend()
plt.tight_layout()
plt.savefig('AE_3_demod_bp_100_450_lp_36_source_gearbox_n_1.png')
ax1.set_xlim(left=2.74, right=4.76)
plt.savefig('AE_3_demod_bp_100_450_lp_36_source_gearbox_n_2.png')
fig2, ax2 = plt.subplots()
ax2.plot(t, xraw, label='Signal')
ax2.plot(t, x, label='Huellkurve')
ax2.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
ax2.set_xlabel('Zeit (s)')
params = {'mathtext.default': 'regular'}
plt.rcParams.update(params)
ax2.set_ylabel('Amplitude (m$V_{in}$)')
plt.legend()
plt.tight_layout()
plt.savefig('DE_AE_3_demod_bp_100_450_lp_36_source_gearbox_n_1.png')
ax2.set_xlim(left=2.74, right=4.76)
plt.savefig('DE_AE_3_demod_bp_100_450_lp_36_source_gearbox_n_2.png')
# fig_22, ax_22 = plt.subplots(nrows=2, ncols=1, sharex=True)
# ax_22[1].plot(t, xnewraw)
# ax_22[0].plot(t, xraw)
# ax_22[1].set_title(config['channel'] + ' WFM Erkennung der Bursts', fontsize=11)
# ax_22[1].set_xlabel('Zeit (s)', fontsize=12)
# ax_22[1].set_ylabel('Amplitude (m$V_{in}$)', fontsize=12)
# # params = {'mathtext.default': 'regular' }
# # plt.rcParams.update(params)
# ax_22[0].set_ylabel('Amplitude (m$V_{in}$)', fontsize=12)
# ax_22[0].tick_params(axis='both', labelsize=11)
# ax_22[1].tick_params(axis='both', labelsize=11)
# ax_22[0].set_title(config['channel'] + ' WFM mit Filter', fontsize=11)
plt.show()
elif config['mode'] == 'compare_envelope':
print('invoke NO drahtburst')
dict_int = invoke_signal(config)
xraw = dict_int['signal_raw']
x = dict_int['signal']
t = dict_int['time']
filename = dict_int['filename']
v_max = np.max(xraw)
xraw = xraw / v_max
x = x / np.max(x)
x = x - np.min(x)
xraw = xraw * v_max
x = x * v_max
print('invoke WITH drahtburst')
dict_int = invoke_signal(config)
yraw = dict_int['signal_raw']
y = dict_int['signal']
ty = dict_int['time']
filename_y = dict_int['filename']
m_max = np.max(yraw)
yraw = yraw / m_max
y = y / np.max(y)
y = y - np.min(y)
yraw = yraw * m_max
y = y * m_max
# fig1, ax1 = plt.subplots()
# ax1.plot(t, xraw, label='Signal')
# ax1.plot(t, x, label='Envelope')
# ax1.set_title(config['channel'] + ' WFM ' + filename, fontsize=10)
# ax1.set_xlabel('Time (s)')
# params = {'mathtext.default': 'regular' }
# plt.rcParams.update(params)
# ax1.set_ylabel('Amplitude (m$V_{in}$)')
# plt.legend()
# plt.tight_layout()
# plt.savefig('AE_3_demod_bp_100_450_lp_36_source_gearbox_n_1.png')
# ax1.set_xlim(left=2.74, right=4.76)
# plt.savefig('AE_3_demod_bp_100_450_lp_36_source_gearbox_n_2.png')
label = config['channel']
label = label.replace('_', '-')
fig2, ax2 = plt.subplots(nrows=2, ncols=1, sharex=True, sharey=True)
ax2[0].plot(t, xraw, label='Signal')
ax2[0].plot(t, x, label='Huellkurve')
ax2[0].set_title(label + ' ohne Drahtbuerste', fontsize=11)
# ax2[0].set_xlabel('Zeit (s)', fontsize=12)
params = {'mathtext.default': 'regular'}
plt.rcParams.update(params)
ax2[0].set_ylabel('Amplitude [m$V_{in}$]', fontsize=12)
# plt.legend(fontsize=10)
# ax2[0].set_xlim(left=2.74, right=4.76)
ax2[0].tick_params(axis='both', labelsize=11)
ax2[1].plot(t, yraw, label='Signal')
ax2[1].plot(ty, y, label='Huellkurve')
ax2[1].set_title(label + ' mit Drahtbuerste', fontsize=11)
ax2[1].set_xlabel('Dauer [s]', fontsize=12)
params = {'mathtext.default': 'regular'}
plt.rcParams.update(params)
ax2[1].set_ylabel('Amplitude [m$V_{in}$]', fontsize=12)
# ax2[1].set_xlim(left=2.74, right=4.76)
ax2[1].tick_params(axis='both', labelsize=11)
plt.legend(fontsize=10)
plt.tight_layout()
# fig_22, ax_22 = plt.subplots(nrows=2, ncols=1, sharex=True)
# ax_22[1].plot(t, xnewraw)
# ax_22[0].plot(t, xraw)
# ax_22[1].set_title(config['channel'] + ' WFM Erkennung der Bursts', fontsize=11)
# ax_22[1].set_xlabel('Zeit (s)', fontsize=12)
# ax_22[1].set_ylabel('Amplitude (m$V_{in}$)', fontsize=12)
# # params = {'mathtext.default': 'regular' }
# # plt.rcParams.update(params)
# ax_22[0].set_ylabel('Amplitude (m$V_{in}$)', fontsize=12)
# ax_22[0].tick_params(axis='both', labelsize=11)
# ax_22[1].tick_params(axis='both', labelsize=11)
# ax_22[0].set_title(config['channel'] + ' WFM mit Filter', fontsize=11)
plt.show()
else:
print('unknown mode')
return