for root_dir in root_dirs:
filtered_frame = input_frame[input_frame.root_dir == root_dir]
samples_s = sorted([a for a in filtered_frame.sample_dir.unique()])
for sample in samples_s:
for pressure in pressures:
for voltage in voltages:
p_diff_color_map.reset()
plt.ioff()
plt.figure()
plt.ioff()
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))
line, = axes.plot(numpy_2d_array[0],
numpy_2d_array[1],
color=cur_data.line_plot_settings_color,
linewidth=cur_data.line_plot_settings_line_width,
ls=cur_data.line_plot_settings_line_style,
marker=cur_data.line_plot_settings_marker,
ms=cur_data.line_plot_settings_marker_size)
else:
pass
# =============================================================================
# LINE-LABEL PLOT FOR EACH LINE
# =============================================================================
if cur_data.line_label_plot_settings_plot == "each" and cur_data.line_plot_settings_plot == "each":
fplot.add_label(cur_data.labels_line[number], line.get_color(),
cur_data.line_label_plot_settings_line_width,
cur_data.line_label_plot_settings_line_style,
cur_data.line_label_plot_settings_marker,
cur_data.line_label_plot_settings_marker_size)
else:
pass
# =============================================================================
# DERIVATION LINE PLOT FOR EACH LINE
# =============================================================================
if cur_data.derivation_plot_settings_plot == "each" and cur_data.derivation_plot_settings_color == "random" and cur_data.derivation_calculation_settings_calculate:
line2, = axes.plot(
numpy_2d_array[0][low:high],
derivation,
color=c_map.get_der_color(),
linewidth=cur_data.derivation_plot_settings_line_width,
ls=cur_data.derivation_plot_settings_line_style,
marker=cur_data.derivation_plot_settings_marker,
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.figure(len(unique_root_dirs) + 1) # combined 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)
plt.plot(time, weight, 'b')
fplot.add_label('A', 'b')
filesb = fio.get_files(path, contains=['B0'], extension=['csv'])
filesbb = fio.get_files(path, contains=['B1'], extension=['csv'])
filesb = filesb + filesbb
for file in filesb:
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, 'r')
fplot.add_label('B', 'r')
plt.figure()
plt.ioff()
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,
samples = sorted([ a for a in result_frame['sample'].unique() ])
for sample in samples:
next_frame = result_frame[result_frame['sample'] == sample]
pressures = sorted([ a for a in next_frame['pressure'].unique() ])
for pressure in pressures:
next_frame2 = next_frame[next_frame['pressure'] == pressure]
voltages = sorted([ a for a in next_frame2['voltage'].unique()])
for voltage in voltages:
last_frame = next_frame2[next_frame2['voltage'] == voltage]
p_diff_color_map.reset()
plt.figure()
last_frame = last_frame.sort_values(by='temperature')
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))
samples = sorted([a for a in hydra_frame['Ident No.'].unique()])
print('sample', ' ', 'volumetric', ' ', 'p_diff')
for sample in samples:
p_diff = hydra_frame.loc[
(hydra_frame['Ident No.'] == sample),
['066_Diff_BMP_VIS_P_Mess_6_0bar_MP4_Sp1']].values[0]
volumetric = hydra_frame.loc[
(hydra_frame['Ident No.'] == sample),
['006_BerechnetesHubvolumen_6_0bar_3_Sp1']].values[0]
plt.plot(volumetric / volumetric_constant - 1,
p_diff,
color=c_map.get_color(False),
marker='o',
markeredgecolor='k')
fplot.add_label(sample, c_map.get_color(True), 0, '-', 'o')
print(sample, ' ', volumetric / volumetric_constant - 1, ' ', p_diff)
x = np.linspace(-0.08, 0.08, 20000)
over_200_ppm = 6372549.02 * x**6 - 800150.8296 * x**5 + 19541.8552 * x**4 + 562.4057315 * x**3 - 18.20980735 * x**2 - 9.135497395 * x**1 + 1.300099753 * x**0
over_10_ppm = 4017242.862 * x**6 - 438603.9335 * x**5 - 8783.299926 * x**4 + 1736.291492 * x**3 + 8.192154187 * x**2 - 10.47552085 * x**1 + 0.990573908 * x**0
under_200_ppm = -59264.74327 * x**6 - 4554.65587 * x**5 + 335.2822676 * x**4 + 57.22096531 * x**3 + 2.013566176 * x**2 - 8.579590974 * x**1 - 0.383176295 * x**0
under_10_ppm = -169755.1637 * x**6 - 13455.58466 * x**5 + 3216.230457 * x**4 + 89.40620783 * x**3 - 19.32913576 * x**2 - 8.298948559 * x**1 - 0.070463402 * x**0
aa = np.where(under_200_ppm < -0.5)[0][0]
start = np.where((x >= -0.04))[0][0]
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'
)