Use seconds now

canny_shock_finder.py

@@ -126,8 +126,8 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
     import numpy as np
     import copy
 
-    print ('-'*60)
-    print ("Running Canny shock finder version {0}".format(VERSION_STRING))
+    print('-'*60)
+    print("Running Canny shock finder version {0}".format(VERSION_STRING))
     
     # do some basic input checking
     if not isinstance(sigma, (float, int)):
@@ -148,7 +148,7 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
         start_time = time_list[0]
 
     if post_shock_pressure:
-        print ("Using post-shock pressure scaling so the post_suppression_threshold will be calculated using a post-shock pressure estimate.")
+        print("Using post-shock pressure scaling so the post_suppression_threshold will be calculated using a post-shock pressure estimate.")
 
         #  we need to calculate our post_suppression_threshold here based on the expected post-shock pressure and the
         # scaling caused by the first order gaussian data based on the maximum of the Gaussian
@@ -178,10 +178,10 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
             post_suppression_threshold = post_shock_pressure * gaussian_first_derivative_max
 
         #post_suppression_threshold = 0.5 * post_shock_pressure * gaussian_max/2.0
-        print ("Calculated post_suppression_threshold is {0}".format(post_suppression_threshold))
+        print("Calculated post_suppression_threshold is {0}".format(post_suppression_threshold))
 
         if calculate_automatic_derivative_threshold:
-            print ("Calculating automatic derivative threshold as the user has asked for this.")
+            print("Calculating automatic derivative threshold as the user has asked for this.")
 
             # this commented out code here was my original model, based on the actual second derivative of the Gaussian,
             # but it didn't seem to work too well (it got too small at very high sigma values, i.e. above 6 or so)
@@ -199,7 +199,7 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
             else:
                 derivative_threshold = post_shock_pressure / 2.5 * np.exp(-6) / 10.0
 
-            print ("Calculated derivative_threshold is {0}.".format(derivative_threshold))
+            print("Calculated derivative_threshold is {0}.".format(derivative_threshold))
 
     # make the input data arrays incase they didn't come in that way...
     time_list = np.array(time_list)
@@ -224,14 +224,14 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
     first_value_uncertainty = None
 
     if auto_derivative:
-        print ("Doing auto-derivative!")
+        print("Doing auto-derivative!")
         # remove points which have the same gradient on either side
         for i in range(0,len(first_order_data)-1):
             if np.sign(second_order_data[i-1]) == np.sign(second_order_data[i+1]):
                 suppressed_data[i] = 0
 
     else:
-        print ("Not doing auto-derivative!")
+        print("Not doing auto-derivative!")
         for i in range(0,len(first_order_data)-1):
 
             # check the gradients on either side using the second order data
@@ -345,7 +345,7 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
         
         try: # this is mainly so the code doesn't bail out if one closes a window before it has loaded properly
             import matplotlib.pyplot as mplt
-            
+
             figure, (data_ax, convolution_ax) = mplt.subplots(2,1, sharex=True, figsize = (14,8))
 
             data_ax.plot(time_list*plot_time_scale, pressure_list, '-o', label = 'original data')
@@ -476,7 +476,7 @@ def canny_shock_finder(time_list, pressure_list, sigma = 4, derivative_threshold
             
             mplt.show()
         except Exception as e:
-            print ("{0}: {1}".format(type(e).__name__, e.message))
+            print (e)
             print ("There was an issue plotting the result.")
             mplt.close('all')
 

main.py

@@ -160,10 +160,12 @@ def genGraph(gData):
 gData = data[loaded_data[0]]
 x2_time, scope_time, x2_timestamps = process_data(gData)
 
-x2_out = canny_shock_finder(x2_timestamps, (gData["x2"][4][:] - gData["x2"][4][0]) * 0.0148)
+time = (gData["x2"][0][:] - gData["x2"][0][0]).astype('int')
+
+x2_out = canny_shock_finder(time, (gData["x2"][4][:] - gData["x2"][4][0]) * 0.0148)
 
 print(x2_out)
-input("foo")
+print("Done")
 
 #print("Graphing Data")
 #genGraph(data[loaded_data[0]])