next_frame = filtered_frame[ (filtered_frame.sample_dir == sample) & (filtered_frame.pressure == pressure) & (filtered_frame.voltage == voltage)]
next_frame = next_frame.sort_values(by='temperature')
if plot_p_diff:
plt.plot(next_frame.temperature.tolist(),next_frame.result.tolist(), color= p_diff_color_map.get_color(False), lw = 1, marker = 'o')
fplot.add_label('p_diff', p_diff_color_map.get_color(True), marker = 'o' )
if plot_p_BMP:
plt.plot(next_frame.temperature.tolist(),next_frame.p_BMP.tolist(), color = p_diff_color_map.get_color(False), lw = 1, marker = 'o')
fplot.add_label('p_BMP', p_diff_color_map.get_color(True), marker = 'o' )
if plot_p_MSP:
plt.plot(next_frame.temperature.tolist(),next_frame.p_MSP.tolist(), color = p_diff_color_map.get_color(False), lw = 1, marker = 'o')
fplot.add_label('p_MSP', p_diff_color_map.get_color(True), marker = 'o' )
plt.plot([-8,-5,0,10,22,40], [-700,-700,-700,-700,-500,-700], 'k', ls = '--')
plt.plot([-8,-5,0,10,22,40], [ 700, 700, 700, 700, 500, 700], 'k', ls = '--')
fplot.set_plot_config('Temperature [°C]', 'Pressure [mbar]', '{}; {}; {} bar; {} V'.format(root_dir.replace('_',' '), sample, pressure/1000 ,voltage), ylim = [-2000,None])
plt.savefig( '{}/{}/{}/{}/{}_{}_bar_{}_V.png'.format( cwd, results_dir, p_diff_graphs, p_diff_base, sample, pressure/1000, voltage))
plt.close()
print('Generating p_diff graphs ....... ({:02d}/{:02d})'.format(g_num, g_total), end="\r", flush=True)
g_num += 1
print('Generating p_diff graphs ....... ({:02d}/{:02d})'.format(g_num-1, g_total))
# =============================================================================
# generating p_diff graphs for each file
# =============================================================================
os.makedirs('{}/{}/{}/{}'.format(cwd, results_dir, p_diff_graphs, p_diff_file), exist_ok=True)
g_num, g_total = 1, 0
for root_dir in root_dirs:
filtered_frame = input_frame[input_frame.root_dir == root_dir]
min_index, min_value = fdproc.minimum_index_calculation_using_derivation(
time, force, low_threshold, high_threshold)
max_index, max_value = fdproc.maximum_index_calculation_by_index(
time, force, 0, min_index)
results_frame = pd.DataFrame(
[[root_dir, sample_dir, filename, max_value]],
columns=['root_dir', 'sample_dir', 'filename', 'max_force'])
results_frames_list.append(results_frame)
plt.figure() # single figure
plt.plot(time, force, c=c_map_single_graph.get_color(False), label='')
plt.plot(time[min_index], force[min_index], 'r', marker=min_marker)
plt.plot(time[max_index], force[max_index], 'k', marker=max_marker)
fplot.set_plot_config(xa_label='Time [s]',
ya_label='Force [N]',
title='{}; {}'.format(root_dir, sample_dir))
fplot.add_label(sample_dir, c_map_single_graph.get_color(False))
fplot.add_label('maximum_force', 'k', 0, '-', max_marker, 6)
fplot.add_label('minimum_force', 'r', 0, '-', min_marker, 6)
plt.savefig('{}/{}/{}/{}_{}.png'.format(cwd, results_dir,
single_file_graphs, root_dir,
sample_dir))
plt.close()
plt.figure(number) # dirr figure
plt.plot(data_frame['sec'],
data_frame['N'],
c=c_map_root_graph.get_color(False),
label='')
plt.plot(time[max_index], force[max_index], 'ko')
plt.plot(last_frame.temperature,last_frame.pDiff, color= p_diff_color_map.get_color(False), lw = 1, marker = 'o', label = '')
fplot.add_label('p_diff', p_diff_color_map.get_color(True), marker = 'o' )
for msp, msp_cor, msp_cor_new, temp, pDiff in zip(last_frame.valid_MSP_rate, last_frame.valid_msp_rate_cor,last_frame.valid_msp_rate_cor2, last_frame.temperature, last_frame.pDiff ):
plt.annotate("{} \n {} \n {}".format(msp, msp_cor, msp_cor_new), [temp, pDiff], fontsize = 16, fontweight='bold', color='red')
plt.plot(last_frame.temperature,last_frame.pDiff_BMP, color = p_diff_color_map.get_color(False), lw = 1, marker = 'o', label = '')
fplot.add_label('p_BMP', p_diff_color_map.get_color(True), marker = 'o' )
plt.plot(last_frame.temperature,last_frame.pDiff_MSP, color = p_diff_color_map.get_color(False), lw = 1, marker = 'o', label = '')
fplot.add_label('p_MSP', p_diff_color_map.get_color(True), marker = 'o' )
plt.plot([-8,-5,0,10,22,40], [-700,-700,-700,-700,-500,-700], 'k', ls = '--')
plt.plot([-8,-5,0,10,22,40], [ 700, 700, 700, 700, 500, 700], 'k', ls = '--')
plt.legend(loc = 'lower right')
fplot.set_plot_config('Temperature [°C]', 'Pressure [mbar]',' {}; {} bar; {} V'.format( sample, pressure/1000 ,voltage/1000), ylim = [-2000,None])
plt.savefig( '{}/{}/{}/{}_{}_bar_{}_V.png'.format( cwd, results_dir, p_diff_graphs, sample, pressure/1000, voltage/1000))
plt.close()
# =============================================================================
# Generating comparison graphs for each combination file/voltage/pressure
# =============================================================================
print('Generating comparison graphs')
os.makedirs('{}/{}/{}'.format(cwd, results_dir, comparison_graphs), exist_ok=True)
minimum, maximum = -800, 800
pressures = sorted([ a for a in result_frame.pressure.unique()])
for pressure in pressures:
filesc = fio.get_files(path, contains=['C0'], extension=['csv'])
filescc = fio.get_files(path, contains=['C1'], extension=['csv'])
filesc = filesc + filescc
for file in filesc:
print(file)
dataframe = pd.read_csv(file, sep=';', decimal=',')
weight = dataframe[r'Weight [g]'].tolist()
time = dataframe.Time
time = time.tolist()
time = time_stamp_to_time_diff(time)
plt.plot(time, weight, 'g')
fplot.add_label('C', 'g')
plt.grid()
fplot.set_plot_config('Time [s]', 'Weight [g]')
# =============================================================================
#
# =============================================================================
plt.figure()
filesa = fio.get_files(path, contains=['A0'], extension=['csv'])
filesaa = fio.get_files(path, contains=['A1'], extension=['csv'])
filesa = filesa + filesaa
for file in filesa:
print(file)
dataframe = pd.read_csv(file, sep=';', decimal=',')
weight = dataframe[r'Weight [g]'].tolist()
time = dataframe.Time
time = time.tolist()
time = time_stamp_to_time_diff(time)
fplot.set_rc_params(font_size_offset=4)
path = r'X:/Dnox/Tesla/2017/E1700224-08/data/recording/ecr_samples.xlsx'
frame = pd.read_excel(path, usecols=[0, 1]).dropna()
ecr_maxima = frame["Maximum force"].tolist()
fplot.plot_swarm([ecr_maxima], [1], color='b')
fplot.plot_violin([ecr_maxima], [1])
path = r'X:/Dnox/Tesla/2017/E1700224-08/data/recording/serial_samples.xlsx'
frame = pd.read_excel(path, usecols=[0, 1]).dropna()
series_maxima = frame["Maximum force"].tolist()
fplot.plot_violin([series_maxima], [2], body_color='g')
fplot.plot_swarm([series_maxima], [2], color='g')
fplot.set_plot_config(xa_label='sample groups sequence',
ya_label='Force [N]',
title='',
xlim=[0, 3],
ylim=[None, None])
fplot.modify_ticks(['ecr samples', 'series samples'], [1, 2])
fplot.add_label('ecr samples', 'b', line_width=0, marker='o', marker_size=6)
fplot.add_label('serial samples', 'g', line_width=0, marker='o', marker_size=6)
fplot.set_rc_params()
plt.grid()
plt.savefig(
r'X:/Dnox/Tesla/2017/E1700224-08/data/recording/results/swarm_comparison.png'
)