Minor bug fixes

src/csv_threading.py

@@ -113,9 +113,9 @@ class ExecCSVThread(Thread):
 
 def read_csv_to_array(filepath):  # convert a given csv file to a numpy array
     # csv format: time [s], xField [T], yField [T], zField [T] (german excel)
-    # decimal or period commas. Do not use these characters as a thousands seperator!
+    # decimal or period commas. Do not use these characters as a thousands separator!
     with open(filepath, 'r') as csv_file:
-        # Normalize seperators
+        # Normalize separators
         csv_string = csv_file.read()
         # read csv file without column headers
         file = pandas.read_csv(StringIO(csv_string), sep=',', decimal='.', header=0)
@@ -163,12 +163,12 @@ def plot_field_sequence(array, width, height):  # create plot of fixed size (pix
     # modify data to show instantaneous jumps in field to reflect test bench operation
     new_array = np.array([[0, 0, 0, 0]], dtype=float)  # initialize modified array, zeros to show start from no fields
 
-    last_vals = [0, 0, 0]  # [x,y,z] field values from last data point (zero here), used to create step in data
+    last_values = [0, 0, 0]  # [x,y,z] field values from last data point (zero here), used to create step in data
     for row in array[:, 0:4]:  # go through each row in the original array
         # create extra datapoint at current timestamp, with field values from last to create a "step" in the plot:
-        new_array = np.append(new_array, [[row[0], *last_vals]], axis=0)
+        new_array = np.append(new_array, [[row[0], *last_values]], axis=0)
         new_array = np.append(new_array, [row], axis=0)  # add actual datapoint for current timestamp
-        last_vals = row[1:4]  # save values from current timestamp for next
+        last_values = row[1:4]  # save values from current timestamp for next
     new_array = np.append(new_array, [[new_array[-1, 0], 0, 0, 0]], axis=0)  # append last datapoint with 0 fields
 
     # extract data and plot: