diff --git a/Python_script/PostPlot.py b/Python_script/PostPlot.py
index 487d26ee13c6b28d4c53487664be3d20df5480f1..fe71d54c94653b02c92055ef3445930d8e6e9fe7 100644
--- a/Python_script/PostPlot.py
+++ b/Python_script/PostPlot.py
@@ -6,12 +6,11 @@ Created on Tue Mar 7 10:15:55 2023
"""
import pandas as pd
-import matplotlib.pyplot as plt
import sys
from pathlib import Path
import os
-import numpy as np
-from scipy.optimize import curve_fit
+import MeasurementPlot
+import time
# after measurement has finished from stored csv-data a post plot of all temperature steps is plotted and store in
@@ -24,6 +23,13 @@ class PostPlot:
if 'ipykernel' in sys.modules:
from IPython import get_ipython
get_ipython().run_line_magic('matplotlib', 'qt')
+
+
+ self.postplot_obj = MeasurementPlot.MeasurementPlot(legend_loc = 'upper left', \
+ legend_bbox_to_anchor = (1.09, 1))
+
+ # set parameter figure of class to object parameter figure
+ self.fig = self.postplot_obj.fig
# read csv-file and import data to data frame
def import_csv(self, csv_file):
@@ -33,258 +39,68 @@ class PostPlot:
return data_frame
# plot function for data frame data, Michael
- # labels for legend of external sensor is given in Parameterlist , Michael
- # optinal calculation of regression, a plot of the fitted function and the calculation of correlation
- # between DUT sensor Temperature and phase can be activated by parameterlist of function, michael
- def plot_frame_data(self, data_frame, title ='', legend_sensor0 = ['Temperature Sensor0', 'Humidity Sensor0'], \
- legend_sensor1 = ['Temperature Sensor1','Humidity Sensor1', 'Air Pressure Sensor1'], \
- time_unit ='min', regression_state = False, plot_regression = False, plot_corr_coeff = False):
-
- # set label of plots with legend entries in parameter list of plot frame data method
- label_temp_sensor0 = legend_sensor0[0]
- label_hum_sensor0 = legend_sensor0[1]
-
- label_temp_sensor1 = legend_sensor1[0]
- label_hum_sensor1 = legend_sensor1[1]
- label_air_press_sensor1 = legend_sensor1[2]
-
- data_frame.reset_index(inplace=True, drop=True)
-
- # fetch plot data from data frame given in parameter list of function
- timestamps = data_frame.TIMESTAMP
- phases = data_frame.S21_PHASE
- eq_indicator = data_frame.EQUILIBRIUM_INDICATOR
- magnitudes = data_frame.S21_MAGNITUDE
- temperatures = data_frame.READBACK_TEMPERATURE
- humidities = data_frame.READBACK_HUMIDITY
- temp_sensor0 = data_frame.TEMP_SENSOR0
- temp_sensor1 = data_frame.TEMP_SENSOR1
- hum_sensor0 = data_frame.HUM_SENSOR0
- hum_sensor1 = data_frame.HUM_SENSOR1
- air_press = data_frame.AIR_PRESSURE
- temp_heater = data_frame.TEMP_HEATER
- hum_heater = data_frame.HUM_HEATER
+ def plot_frame_data(self, data_frame, title ='', time_unit ='min'):
-
- # time stamp of list entry zero is the start point of time axis, Michael
- # substract all other timestamps with list entry of zero to scale time axis, Michael
- time_sec = timestamps - timestamps[0]
-
- # set scaling of time axis depending on the time unit given in parameter list, Michael
- # default unit are minutes, Michael
- time = self.scaling_time_axes(time_sec, time_unit)
-
- # calulate correlation betwenn trace of temp sensor 0 (DUT temeprature) and trace of the phase which is measured
- # by VNA, Michael
- corr_coeff_phase= np.corrcoef(phases, temp_sensor0)[0][1]
-
- # plot window with 5 subplots
- self.fig, self.ax1 = plt.subplots(5, figsize=(25, 20))
+ # set title of plot
self.fig.suptitle("Measurement "+title, color="red")
- # scale subplots to fit into space of figure so that axes labels and legends easily can be read, Michael
- self.fig.subplots_adjust(bottom= 0.1, right=0.8, hspace = 0.4)
-
- minimum, maximum = self.get_extended_min_max(time)
- self.ax1[0].set_xlim(minimum, maximum)
- self.ax1[1].set_xlim(minimum, maximum)
- # set x-axes limits for addinal plot equal to the plot for magnitude and phase of DUT, Michael
- self.ax1[2].set_xlim(minimum, maximum)
- self.ax1[3].set_xlim(minimum, maximum)
- self.ax1[4].set_xlim(minimum, maximum)
- # First plot: Phase and magnitude of DUT
- self.path_collection_phase = self.ax1[0].scatter(time, phases, c='red', marker='<', label='DUT Phase')
- minimum, maximum = self.get_extended_min_max(phases)
- self.ax1[0].set_ylim(minimum, maximum)
+ # reset index of data frame
+ data_frame.reset_index(inplace=True, drop=True)
- self.magnitude_axis = self.ax1[0].twinx()
- self.path_collection_mag = self.magnitude_axis.scatter(time, magnitudes, c='#3120E0', marker='4', label='DUT Magnitude')
- minimum, maximum = self.get_extended_min_max(magnitudes)
- self.magnitude_axis.set_ylim(minimum, maximum)
+ # self.postplot_obj = MeasurementPlot.MeasurementPlot(legend_loc = 'upper left', \
+ # legend_bbox_to_anchor = (1.09, 1))
- self.equi_axis0 = self.ax1[0].twinx()
- # fix range to 0..31 with some extra margin for plotting
- self.equi_axis0.set_ylim(-1, 32)
- # increase outward position of axes for equilibrium indicator , Michael
- self.equi_axis0.spines['right'].set_position(('outward', 75))
- self.path_collection_equi0 = self.equi_axis0.scatter(time, eq_indicator, c='black', marker=".", label='Equilibrium_Indicator')
+ # set y-Achlabel in all subplots to Time an in square brackets the selected time unit
+ for element in self.postplot_obj.ax1:
+ element.set_xlabel("Time [%s]" %time_unit)
- if regression_state == True:
- self.phase_t0 = phases[0]
- self.K_phases = np.median(phases)
- func, popt = self.choose_fit( time, phases)
- annotate_string_fit = self.plot_fitted_func_param(func, *popt, time_unit = time_unit)
- self.ax1[0].annotate(annotate_string_fit,xy=(0,min(phases)), xycoords='data', xytext=(-0.16,0),textcoords='axes fraction',fontsize = 16, horizontalalignment='left',verticalalignment='bottom')
- if plot_regression == True:
- fit_phaeses = func(time, *popt)
- min_phases, max_phases = self.get_extended_min_max(phases)
- min_fit_phases, max_fit_phases = self.get_extended_min_max(fit_phaeses)
- minimum = min(min_phases, min_fit_phases)
- maximum = max(max_phases, max_fit_phases)
- self.ax1[0].set_ylim(minimum, maximum)
- self.path_collection_curvefit = self.ax1[0].scatter(time, func(time, *popt), c='green', s = 1, marker = "." , label = 'fitted with\n' + func.__name__)
- all_path_collections = [self.path_collection_phase, self.path_collection_mag, self.path_collection_equi0, self.path_collection_curvefit]
- else:
- all_path_collections = [self.path_collection_phase, self.path_collection_mag, self.path_collection_equi0]
- else:
- all_path_collections = [self.path_collection_phase, self.path_collection_mag, self.path_collection_equi0]
- delta_phase = max(phases) - min(phases)
- delta_magnitude = max(magnitudes) - min(magnitudes)
- # plot delta values for phase and magnitude at left position outside the plot, Michael
- annotate_string = "$\Delta\phi$($S_{21PkPk}$): %.3f °\n$\Delta$|$S_{21PkPk}$|: %.3f dB" % (delta_phase, delta_magnitude)
- if plot_corr_coeff == True:
- annotate_string +="\n"
- annotate_string += "$R_{\phi(S_{21}),Temp_{DUT}}$ = %.3f" % corr_coeff_phase
- self.ax1[0].annotate(annotate_string ,xy=(0,min(phases)), xycoords='data', xytext=(-0.16,1),textcoords='axes fraction',fontsize = 16, horizontalalignment='left',verticalalignment='bottom')
+ # make a copy of data_frame in parameterlist without changing original during modification
+ postplot_data_frame = data_frame.copy()
- # units added to the y-axes labels, Michael
- self.ax1[0].set_xlabel("TIME [%s]" %time_unit)
- self.ax1[0].set_ylabel("PHASE [°]", color='red')
- self.magnitude_axis.set_ylabel("MAGNITUDE [dB]", color='#3120E0')
- # label of y-axis for equilibrium indicator is changed to Indiccator Value because it's shorter, Michael
- self.equi_axis0.set_ylabel("INDICATOR VALUE", color='black')
-
- self.ax1[0].grid(True, linestyle=":")
- labels = [pc.get_label() for pc in all_path_collections]
+ # time stamp of index = 0 is the start point of time axis, Michael
+ # substract all other timestamps with time stamp of index zero to get time scale in
+ # seconds, Michael
+ time_sec = postplot_data_frame.TIMESTAMP - postplot_data_frame.TIMESTAMP[0]
- # set legend at rigth upper position outside subplot for phase and magnitude, Michael
- self.ax1[0].legend(all_path_collections, labels, loc='upper left', bbox_to_anchor=(1.09, 1))
-
- # Second plot: Humidity and temperature of climate chamber requested from internal sensors of climate chamber
- self.path_collection_temp = self.ax1[1].scatter(time, temperatures, c='blue', marker='p', label="Chamber Temperature")
- minimum, maximum = self.get_extended_min_max(temperatures)
- self.ax1[1].set_ylim(minimum, maximum)
+ # set scaling of time axis depending on the time unit given in parameter list, Michael
+ # default unit is minutes, Michael
+ time = self.scaling_time_axes(time_sec, time_unit)
- self.humidity_axis = self.ax1[1].twinx()
- self.path_collection_hum = self.humidity_axis.scatter(time, humidities , c='green', marker="*", label="Chamber Humidity")
- minimum, maximum = self.get_extended_min_max(humidities)
- self.humidity_axis.set_ylim(minimum, maximum)
+ # update Timestamps with calculated time values
+ postplot_data_frame.update(time)
- self.equi_axis1 = self.ax1[1].twinx()
+ # refresh subflots with data in data frame
+ self.postplot_obj.draw(postplot_data_frame, pdf_name = '')
- # increase outward position of axes for equilibrium indicator , Michael
- self.equi_axis1.spines['right'].set_position(('outward', 75))
- self.path_collection_equi1 = self.equi_axis1.scatter(time, eq_indicator, c='black', marker=".", label="Equilibrium_Indicator")
- self.equi_axis1.set_ylim(-1, 32)
-
- # units added to the y-axes labels, Michael
- self.ax1[1].set_xlabel("TIME [%s]" %time_unit)
- self.ax1[1].set_ylabel("TEMPERATURE [°C] ", color='blue')
- self.humidity_axis.set_ylabel("HUMIDITY [%RH]", color='green')
- # label of y-axis for equilibrium indicator ist changed to Indiccator Value because it's shorter, Michael
- self.equi_axis1.set_ylabel("INDICATOR VALUE", color='black')
+ # cal PK2PK values of magnitude and phase
+ PK2PK = self.calc_mag_phase_pkpk_values(data_frame)
-
- self.ax1[1].grid(True, linestyle=":")
- all_path_collections = [self.path_collection_temp, self.path_collection_hum, self.path_collection_equi1]
- labels = [pc.get_label() for pc in all_path_collections]
-
- # set legend at rigth upper position outside subplot for temperature and humidity from internal sensors of
- # climate chamber, Michael
- self.ax1[1].legend(all_path_collections, labels, loc='upper left', bbox_to_anchor=(1.09, 1))
+ self.edit_annotation_in_plot(annotate_string = PK2PK)
- # Third plot: temperatur external sensor0, humidity external sensors0, Michael
- # sensor 0 is the sensor at port 0 of ahlborn and used for the DUT temperature, DUT humidity, Michael
- # label for temeprature and humidity of sensor 0 can be configure by ext_sens_data.json, Michael
+
+ def edit_annotation_in_plot(self, annotate_string ='', anno_fontsize = 16):
- self.path_collection_temp_sensor0 = self.ax1[2].scatter(time,temp_sensor0, c='red', marker='p', label=label_temp_sensor0)
- minimum, maximum = self.get_extended_min_max(temp_sensor0)
- self.ax1[2].set_ylim(minimum, maximum)
+ # update text of annotation in first subplot
+ self.postplot_obj.annotation.set_text(annotate_string)
- # second y-axis on the right for humidity of external sensor0
- self.ext_sens_hum_axis = self.ax1[2].twinx()
- minimum, maximum = self.get_extended_min_max(hum_sensor0)
- self.ext_sens_hum_axis.set_ylim(minimum, maximum)
- self.path_collection_hum_sensor0 = self.ext_sens_hum_axis.scatter(time, hum_sensor0, c='purple', marker='*', label=label_hum_sensor0)
+ # edit annotation fontsize in first subplot
+ self.postplot_obj.annotation.set_fontsize(anno_fontsize)
+
+ def calc_mag_phase_pkpk_values(self, data_frame):
- # units added to the y-axes labels, Michael
- self.ax1[2].set_xlabel("TIME [%s]" %time_unit)
- self.ax1[2].set_ylabel("TEMPERATURE [°C]", color='red')
- self.ext_sens_hum_axis.set_ylabel("HUMIDITY [%RH]", color = 'purple')
-
- self.ax1[2].grid(True, linestyle=":")
- all_path_collections = [self.path_collection_temp_sensor0, self.path_collection_hum_sensor0]
- labels = [pc.get_label() for pc in all_path_collections]
+ # calc PK2PK values of magnitude and phase
+ delta_phase = max(data_frame.S21_PHASE) - min(data_frame.S21_PHASE)
+ delta_magnitude = max(data_frame.S21_MAGNITUDE) - min(data_frame.S21_MAGNITUDE)
- # set legend at rigth upper position outside subplot for temperature and humidity from external sensor 0, Michael
- self.ax1[2].legend(all_path_collections, labels, loc='upper left', bbox_to_anchor=(1.09, 1))
-
+ # generate text for annoation in first subplot
+ delta_vals_string = "$\Delta\phi$($S_{21PkPk}$): %.3f °\n$\Delta$|$S_{21PkPk}$|: %.3f dB" \
+ % (delta_phase, delta_magnitude)
- # Forth plot: temperatur external sensor1, humidity external sensors1, air pressure external sensor1, Michael
- # sensor 1 is the sensor at port 1 of ahlborn and used for the room temperature, the room humidity
- # and the air pressure in the room, Michael
- # label for temeprature and humidity of sensor0 can be configure by ext_sens_data.json, Michael
-
- self.path_collection_temp_sensor1 = self.ax1[3].scatter(time,temp_sensor1, c='green', marker='*', label=label_temp_sensor1)
- minimum, maximum = self.get_extended_min_max(temp_sensor1)
- self.ax1[3].set_ylim(minimum, maximum)
-
- # second y-axis on the right for humidity
- self.sec_ext_hum_sens_axis = self.ax1[3].twinx()
- minimum, maximum = self.get_extended_min_max(hum_sensor1)
- self.sec_ext_hum_sens_axis.set_ylim(minimum, maximum)
- self.path_collection_hum_sensor1 = self.sec_ext_hum_sens_axis.scatter(time,hum_sensor1, c='orange', marker='>', label=label_hum_sensor1)
-
- # third y-axis on the right for air pressure
- self.press_axis = self.ax1[3].twinx()
- self.press_axis.spines['right'].set_position(('outward', 60))
- minimum, maximum = self.get_extended_min_max(air_press)
- self.press_axis.set_ylim(minimum, maximum)
- self.path_collection_press = self.press_axis.scatter(time,air_press, c='grey', marker='4', label=label_air_press_sensor1)
-
- # units added to the y-axes labels, Michael
- self.ax1[3].set_xlabel("TIME [%s]" %time_unit)
- self.ax1[3].set_ylabel("TEMPERATURE [°C]", color='green')
- self.sec_ext_hum_sens_axis.set_ylabel("HUMIDITY [%RH]", color = 'orange')
- self.press_axis.set_ylabel("AIR PRESSURE [mb]", color ='grey')
-
- self.ax1[3].grid(True, linestyle=":")
- all_path_collections = [self.path_collection_temp_sensor1, self.path_collection_hum_sensor1, \
- self.path_collection_press]
- labels = [pc.get_label() for pc in all_path_collections]
- # set legend at rigth upper position outside subplot for temperature and humidity from external sensor 1, Michael
- self.ax1[3].legend(all_path_collections, labels, loc='upper left', bbox_to_anchor=(1.09, 1))
-
- # Fifth plot: heater activity of temeprature heater and humidity heater
- # values for activity are requested from climate chamber, Michael
-
- self.path_collection_temp_heater = self.ax1[4].scatter(time,temp_heater, c='black', marker='<', label='Temp Heater')
- self.path_collection_hum_heater = self.ax1[4].scatter(time, hum_heater, c='brown', marker='o', label='Hum Heater')
-
- # get min max values for temperature heater and humdity heater, Michael
- # select the lowest minimum and the highest maximum for limit of the y-axis, Michael
- min_temp_heater, max_temp_heater = self.get_extended_min_max(temp_heater)
- min_hum_heater, max_hum_heater = self.get_extended_min_max(hum_heater)
- minimum = min(min_temp_heater, min_hum_heater)
- maximum = max(max_temp_heater, max_hum_heater)
- distance = maximum - minimum
-
- self.ax1[4].set_ylim(minimum-0.05*distance, maximum+0.05*(distance))
-
- # units added to the y-axes labels, Michael
- self.ax1[4].set_xlabel("TIME [%s]" %time_unit)
- self.ax1[4].set_ylabel("HEATER PERCENTAGE [%]", color='black')
-
- self.ax1[4].grid(True, linestyle=":")
- all_path_collections = [self.path_collection_temp_heater, \
- self.path_collection_hum_heater]
- labels = [pc.get_label() for pc in all_path_collections]
- # set legend at rigth upper position outside subplot for temperature heater and humidity heater, Michael
- self.ax1[4].legend(all_path_collections, labels, loc='upper left', bbox_to_anchor=(1.08, 1))
-
- # sclae fontsize of all plot window elements to size 14, Michael
- plt.rcParams.update({'font.size':16})
-
- # add 5 % of the distance between min and max to the range
- @staticmethod
- def get_extended_min_max(array):
- distance = array.max() - array.min()
- if distance == 0.:
- distance = 1
- return array.min()-0.05*distance, array.max()+0.05*distance
-
+ return delta_vals_string
+
+
# save figure under the given storepath in parameterlist with the given filename in parameter list, Michael
# file extension is part of filename, Michael
def save_fig(self, storepath, filename):
@@ -309,102 +125,16 @@ class PostPlot:
return time
- # step response of PT1 with initial behavior , Michael
- def PT1(self, x, K, T1):
- return K * (1 - np.exp(-x/T1)) + self.phase_t0 * np.exp(-x/T1)
-
- # step response of PT2 (D > 1) with initial behavior
- def aperiodicPT2(self, x, K, T1, T2,):
- return K + self.phase_t0* np.exp(-x/T1)/(T2-T1) - K *T1* np.exp(-x/T1)/(T2-T1) \
- - self.phase_t0 * np.exp(-x/T2)/(T2-T1) + K* T2* np.exp(-x/T2)/(T2-T1)
-
- # step response of PT2 (D = 1) with initial behavior, Michael
- def aperiodic_borderPT2(self, x, K, T):
- return K + self.phase_t0*np.exp(-x/T) - K * np.exp(-x/T) + self.phase_t0*np.exp(-x/T)*x/T + \
- - K * np.exp(-x/T) * x/T
-
- # step response of PT2 (0 < D < 1) with initial behavior, Michael
- def periodicPT2(self, x, D, T):
- return self.K_phases + (self.phase_t0 -self.K_phases)*np.exp(-D*x/T)*np.cos(np.sqrt(1-np.square(D))*x/T) + \
- (self.phase_t0 - self.K_phases) * D * np.exp(-D*x/T)*np.sin(np.sqrt(1-np.square(D))*x/T)/np.sqrt(1-np.square(D))
-
- # step response series of PT2 ( D = 1) and PT1 with initial behavior, Michael
- def aperiodic_borderPT2_PT1(self, x, a, b, c, d, T1, T2):
- return a + b*np.exp(-x/T1)+c*x*np.exp(-x/T1) + d*np.exp(-x/T2)
-
- # method for cuvefit, Michael
- # two different algorithms for curvefit are use depending on used step response for fit, Michael
- def curvefit(self, func, time, phases):
- if func.__name__ == 'periodicPT2':
- popt, pcov = curve_fit(func, time, phases, method = 'trf', bounds = ([0.001, 0.001], [0.99, np.inf]))
- else:
- popt, pcov = curve_fit(func, time, phases, method = 'lm')
- return popt, pcov
-
- # method adds the parameter of the fit with the lowest error to annotation string, Michael
- # contens of annotation string is plotted on the left side of subplot 1 if regression state is activated, Michael
- def plot_fitted_func_param(self, func, *popt, time_unit):
+
- if func.__name__ == 'PT1':
- K = popt[0]
- T1 = popt[1]
- annotate_string = "K: %.2f\n$T_1$: %.3f %s" %(K, T1, time_unit)
- elif func.__name__ == 'aperiodicPT2':
- K = popt[0]
- T1 = popt[1]
- T2 = popt[2]
- annotate_string = "K: %.2f\n$T_1$: %.3f %s\n$T_2$: %.3f %s" % (K, T1, time_unit, T2, time_unit)
- elif func.__name__ == 'aperiodic_borderPT2':
- K = popt[0]
- T = popt[1]
- annotate_string = "K: %.2f\nT: %.3f %s" %(K, T, time_unit)
- elif func.__name__ == 'periodicPT2':
- K = self.K_phases
- D = popt[0]
- T = popt[1]
- T_2perc = 4*T/D
- annotate_string = "K: %.2f\nD: %.3f\nT: %.3f %s\n$T_E$(2%%): %.2f %s" %(K, D, T, time_unit, T_2perc, time_unit)
- elif func.__name__ == 'aperiodic_borderPT2_PT1':
- T1 = popt[4]
- T2 = popt[5]
- annotate_string = "T_1$: %.3f %s\n$T_2$: %.3f %s" % (T1, time_unit, T2, time_unit)
- else:
- # default value
- annotate_string =''
- return annotate_string
- # calculates the fit for all step responses and calulates the lowest error, Michael
- # parameter of the plot with the lowest error is returned by this function, Michael
- # if curve fit fails for one stept response it takes the next one and plots in comman window the functions
- # which failes, Michael
- def choose_fit(self, time, phases):
- popt = []
- perr = []
- used_functions = []
- functions = [self.PT1, self.aperiodic_borderPT2, self.aperiodicPT2, self.periodicPT2, \
- self.aperiodic_borderPT2_PT1]
- for func in functions:
- try:
- # call curvefit method and put the fitted parameter for step response function to a list, Michael
- popt.append(self.curvefit(func, time, phases)[0])
- # calculation of fitting error
- perr.append(np.sqrt(np.square(np.subtract(phases, func(time, *popt[-1]))).mean()))
- used_functions.append(func)
- except RuntimeError:
- print('curvefit of %s fails' %func.__name__)
- # get position of parameters in list which has the lowest calculated error, Michael
- pos = perr.index(min(perr))
- # return function name and parameter with the lowest calculated error during curvefit, Michael
- return used_functions[pos], popt[pos]
-
# for manually redo post plot after measurement has finished, Michael
if __name__ == '__main__':
+
# set result path for post plot
- Results_Path = r'C:\Users\pawelzik\Desktop\Results\THRU_27032023'
+ Results_Path = r'C:\Users\pawelzik\Desktop\Results\THRU_27032023Copy'
- # activate/deactivate calculation of regression with PT1 - PT3 elements, Michael
- regression_state = False
# set time unit for post post plot
# default is minutes if entry in parameterlist left empty
@@ -417,13 +147,13 @@ if __name__ == '__main__':
# search all csv files in results folder
csv_file_list = list(Path(Results_Path).glob("**/*.csv"))
- # set entires for the external sensors of ahlborn in legend of plot windows
- legend_sensor0=['TEMP-Sensor DUT', 'HUM-Sensor DUT']
- legend_sensor1 = ['Room Temperature','Room Humidity', 'Air Pressure Room']
# create postplot object, Michael
plot_obj = PostPlot()
+ # empty data frame for concat the data frames from csv import to plot full transistion
+ concat_data_frame = pd.DataFrame()
+
# plot results for each csv-file
for index, csv_file in enumerate(csv_file_list):
@@ -433,38 +163,27 @@ if __name__ == '__main__':
# determine title of plot from csv-filename, Michael
title = csv_file.name
- if index < 1:
-
- # set concate data frame to first dataframe in list, Michael
- concate_data_frame = data_frame
-
- # call post plot method, Michael
+ # concate datesframe for plotting full transistion data
+ concat_data_frame = pd.concat([concat_data_frame,data_frame],ignore_index=True, sort = False)
- plot_obj.plot_frame_data(data_frame, title,legend_sensor0, legend_sensor1, time_unit, \
- regression_state = False, plot_regression = True, plot_corr_coeff = False)
-
- else:
-
- concate_data_frame = concate_data_frame.append(data_frame)
- plot_obj.plot_frame_data(data_frame, title,legend_sensor0, legend_sensor1, time_unit, \
- regression_state, plot_regression = True)
-
+ plot_obj.plot_frame_data(data_frame, title, time_unit)
# set filename of post plot, Michael
- filename = str(csv_file.stem) + '.svg'
+ filename = str(csv_file.stem) + '.pdf'
- # store post plot under the path taht is set in storepath with the earlier defined filename, Michael
+ # store post plot under the path taht is set in storepath with the earlier defined filename
plot_obj.save_fig(storepath, filename)
-
+
+
# plot of all steps of a sweep is plotted in one diagram, Michael
# title of this plot will be always full transistion, Michel
- # legend for external sensors is steh to the pre defined values of lgend_snesor0 and legend_sensor1, Michael
- plot_obj.plot_frame_data(concate_data_frame, 'Full Transistion', legend_sensor0, legend_sensor1, time_unit)
+ plot_obj.plot_frame_data(concat_data_frame, 'Full Transistion', time_unit)
+
# filename of plot that contains all steps of sweep is set to FullTransistion, Michael
- filename = 'Full_Transistion' + '.svg'
+ filename = 'Full_Transistion' + '.pdf'
# plot with the results of all steps is store under the predefined storpath with the earlier defined filename, Michael
plot_obj.save_fig(storepath, filename)
-
\ No newline at end of file
+
\ No newline at end of file