Visual improvements for csv graphs

csv_threading.py

@@ -11,7 +11,6 @@ import globals as g
 
 
 class ExecCSVThread(Thread):
-    # ToDo: handling for disconnected devices
     def __init__(self, threadID, array, parent, controller):
         Thread.__init__(self)
 
@@ -79,46 +78,57 @@ def execute_sequence(array, delay, parent, controller):  # runs through array co
 def read_csv_to_array(filepath):
     # csv format: time (s); xField (T); yField (T); zField (T) (german excel)
     # decimal commas
-    ui.ui_print("Reading File:", filepath)
     file = pandas.read_csv(filepath, sep=';', decimal=',', header=0)  # read csv file
     array = file.to_numpy()  # convert csv to array
     return array
 
 
-def check_array(array):
-    # ToDo: message formatting, pop up warning
-    # ToDo: comments
-    concerns = []
-    for row in array:
-        i = 1
-        for axis in g.AXES:
-            value = row[i]
-            if value > axis.max_comp_field[1]:
-                concerns.append(row)
-            elif value < axis.max_comp_field[0]:
-                concerns.append(row)
-            i += 1
-    ui.ui_print("Checked csv, found %i concerns." % len(concerns))
-    if len(concerns) > 0:
-        ui.ui_print(concerns)
+def check_array_ok(array):  # check if any magnetic fields in an array exceed the limits
+    values_ok = True
+    for i in [0, 1, 2]:  # go through axes
+        max_val = g.AXES[i].max_comp_field[1]  # get limits
+        min_val = g.AXES[i].max_comp_field[0]
+        data = array[:, i + 1]  # extract data for this axis from array
+        # noinspection PyTypeChecker
+        if any(data > max_val) or any(data < min_val):  # if any datapoint is out of bounds
+            values_ok = False
+    if not values_ok:  # show warning pop-up if values are exceeding limits
+        messagebox.showwarning("Value Limits Warning!", "Found field values exceeding limits of test stand."
+                                                        "\nSee plot and check values in csv.")
 
 
-def plot_field_sequence(array, width, height):  # ToDo: comments
-    # ToDo: make pretty
-    fig_dpi = 100
-    px = 1/fig_dpi
-    figure = plt.Figure(figsize=(width*px, height*px), dpi=fig_dpi)
+def plot_field_sequence(array, width, height):  # create plot of fixed size from array
+    # ToDo (optional): polar plots, plots of angle...
+    # ToDo (optional): show graphs as steps (as performed by test stand)
+    fig_dpi = 100  # set figure resolution
+    px = 1/fig_dpi  # get pixel to inch size conversion
+    figure = plt.Figure(figsize=(width*px, height*px), dpi=fig_dpi)  # create figure with correct size
 
     # noinspection PyTypeChecker,SpellCheckingInspection
-    axes = figure.subplots(3, sharex=True, sharey=True, gridspec_kw={'hspace': 0.4})
+    axes = figure.subplots(3, sharex=True, sharey=True, gridspec_kw={'hspace': 0.4})  # create subplots with shared axes
 
     figure.suptitle("Magnetic Field Sequence")
-    t = array[:, 0]
 
-    for i in [0, 1, 2]:
-        data = array[:, i + 1] * 1e6
-        plot = axes[i]
-        plot.plot(t, data)
-        plot.set_title(g.AXIS_NAMES[i])
+    t = array[:, 0]  # extract time column
+    for i in [0, 1, 2]:  # go through all three axes
+        data = array[:, i + 1] * 1e6  # extract field column of this axis
+        max_val = g.AXES[i].max_comp_field[1] * 1e6  # get limits of achievable field
+        min_val = g.AXES[i].max_comp_field[0] * 1e6
+        plot = axes[i]  # get appropriate subplot
 
-    return figure
+        plot.plot(t, data, linestyle='solid', marker='.')  # plot data
+
+        if any(data > max_val):  # if any value is higher than the maximum
+            plot.axhline(y=max_val, linestyle='dashed', color='r')  # plot horizontal line to show maximum
+            # add label to line:
+            plot.text(t[-1], max_val, "max", horizontalalignment='center', verticalalignment='top', color='r')
+        if any(data < min_val):  # same as above
+            plot.axhline(y=min_val, linestyle='dashed', color='r')
+            plot.text(t[-1], min_val, "min", horizontalalignment='center', color='r')
+        plot.set_title(g.AXIS_NAMES[i], size=10)  # set subplot title (e.g. "X-Axis")
+
+    # set shared axis labels:
+    axes[2].set_xlabel("Time (s)")
+    axes[1].set_ylabel("Magnetic Field (\u03BCT)")
+
+    return figure  # return the created figure to be inserted somewhere else