improvements in analysis

- use list of measurements instead of start/end
- use naming scheme
- code formatting

Python_script/analysis.py

@@ -2,6 +2,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import math
 
+
 def extract_stable_data(datafile):
     datapoint = {}
     #df is a pandas data frame
@@ -15,59 +16,61 @@ def extract_stable_data(datafile):
     datapoint['phase_var']=phases.var()
 
     magnitudes = df.loc[df['EQUILIBRIUM_INDICATOR'] == 31, 'S21_MAGNITUDE']
-    datapoint['magnitude_mean']=magnitudes.mean()
-    datapoint['magnitude_var']=magnitudes.var()
+    datapoint['magnitude_mean'] = magnitudes.mean()
+    datapoint['magnitude_var'] = magnitudes.var()
 
     temperatures = df.loc[df['EQUILIBRIUM_INDICATOR'] == 31, 'READBACK_TEMPERATURE']
-    datapoint['temperature_mean']=temperatures.mean()
-    datapoint['temperature_var']=temperatures.var()
+    datapoint['temperature_mean'] = temperatures.mean()
+    datapoint['temperature_var'] = temperatures.var()
 
     humidities = df.loc[df['EQUILIBRIUM_INDICATOR'] == 31, 'READBACK_HUMIDITY']
-    datapoint['humidity_mean']=humidities.mean()
-    datapoint['humidity_var']=humidities.var()
+    datapoint['humidity_mean'] = humidities.mean()
+    datapoint['humidity_var'] = humidities.var()
 
     return datapoint
 
-#FIXME: Come up with a naming scheme
-def plot_temperature_sweep(start_temp, stop_temp, humidity, basename):
-    temps = []
+
+# FIXME: Come up with a naming scheme
+def plot_temperature_sweep(temperatures, humidity, basename):
+    temps_from_data = []
     phases = []
     phase_vars = []
     magnitudes = []
     magnitude_vars = []
-    for temp in range(start_temp, stop_temp+1):
-        datafile = str(temp)+'deg_'+str(humidity)+'rh_'+basename+'.csv'
+    for temp in temperatures:
+        datafile = basename+'_'+str(temp)+'deg_'+str(humidity)+'rh.csv'
         print(datafile)
         datapoint = extract_stable_data(datafile)
         if datapoint is None:
             continue
         
-        temps.append(datapoint['temperature_mean'])
+        temps_from_data.append(datapoint['temperature_mean'])
         phases.append(datapoint['phase_mean'])
         phase_vars.append(datapoint['phase_var'])
         magnitudes.append(datapoint['magnitude_mean'])
         magnitude_vars.append(datapoint['magnitude_var'])
 
-    magnitudes_db = [ 20* math.log10(x) for x in magnitudes ]
-    #approximate formula for small errors (linear approximation)
-    magnitude_vars_db = [ 20 / math.log(10) * dx/x for x, dx in zip( magnitudes,  magnitude_vars )]
+    magnitudes_db = [20 * math.log10(x) for x in magnitudes ]
+    # approximate formula for small errors (linear approximation)
+    magnitude_vars_db = [20 / math.log(10) * dx/x for x, dx in zip(magnitudes,  magnitude_vars)]
 
     fig, ax1 = plt.subplots()
 
-    plt.title('Temperature sweep at ' +str(humidity) + ' % r.h.')
+    plt.title(basename + ': Temperature sweep at ' + str(humidity) + ' % r.h.')
 
-    ax1.errorbar(temps,phases,phase_vars,marker='+',linewidth=0)
+    ax1.errorbar(temps_from_data, phases, phase_vars, marker='+', linewidth=0)
     ax1.set_xlabel('temperature [deg C]')
     ax1.set_ylabel('S21 phase [deg]', color='blue')
 
     ax2 = ax1.twinx()
-    ax2.errorbar(temps,magnitudes_db,magnitude_vars_db,marker='x',color='red',linewidth=0)
+    ax2.errorbar(temps_from_data, magnitudes_db, magnitude_vars_db, marker='x', color='red', linewidth=0)
     ax2.set_ylabel('S21 magnitude [dB]', color='red')
     
     fig.tight_layout()  # otherwise the right y-label is slightly clipped
     plt.show()
 
+
 if __name__ == '__main__':
-    plot_temperature_sweep(20, 30, 40, 'tempsweep1')
+    plot_temperature_sweep(range(20, 30+1), 40, 'tempsweep1')