Introduced red status indicator line, minor warning fixes

src/csv_threading.py

@@ -9,6 +9,7 @@ import numpy as np
 from threading import *
 from tkinter import messagebox
 import matplotlib.pyplot as plt
+from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
 
 from src.exceptions import DeviceBusy, DeviceAccessError
 from src.utility import ui_print
@@ -79,6 +80,9 @@ class ExecCSVThread(Thread):
             messagebox.showwarning("Device Error!", "Required devices are not present, sequence aborted.")
             return
 
+        # Initialize plot
+        figure, avx_lines = display_plot(parent)
+
         i = 0  # index of the current array row
         while i < len(array):
             if self.stopped or g.exit_flag:
@@ -88,9 +92,17 @@ class ExecCSVThread(Thread):
                 return
 
             # while array is not finished, devices are connected, user has not cancelled and application is running
-
             t = time.time() - t_zero  # get time relative to start of run
             target_t = array[i, 0]  # Target execution time of data point
+
+            # Update figure
+            try:
+                for j in range(4):
+                    avx_lines[j].set_data([t, t], [0, 1])
+                parent.plot_canvas.draw()  # equivalent to matplotlib.show()
+            except DeviceAccessError as e:
+                ui_print("Failed to update figure: ", e)
+
             if t >= target_t:  # time for this row has come
                 field_vec = array[i, 1:4]  # extract desired field vector
                 ui_print("[{:5.3f}s] B=[{:.1f}, {:.1f}, {:.1f}]\u03BCT for t={:.2f}s".format(t,
@@ -106,7 +118,6 @@ class ExecCSVThread(Thread):
                 logger = controller.pages[ui.ConfigureLogging]  # get object of logging configurator
                 if logger.event_logging:  # data should be logged when test bench is commanded
                     logger.log_datapoint()  # log data
-
                 i = i + 1  # next row
 
             elif t <= target_t - delay - 0.02:  # is there enough time to sleep before the next row?
@@ -117,7 +128,7 @@ 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 separator!
+    # decimal or period commas. Do not use these characters as a thousand separator!
     with open(filepath, 'r') as csv_file:
         # Normalize separators
         csv_string = csv_file.read()
@@ -153,6 +164,38 @@ def check_array_ok(array):
         messagebox.showwarning("Value Limits Warning!", warning_msg)
 
 
+def display_plot(parent):  # create plot of fixed size (pixels) from array
+    # calculate available height for plot (in pixels):
+    height_others = 0  # initialize variable to calculate height of other widgets
+    for element in parent.row_elements:  # go through all rows in the widget except the plot frame
+        height_others += element.winfo_height()  # add up heights
+
+    # calculate available plot height:
+    height = parent.parent.winfo_height() - height_others - 50  # height of parent frame - other widgets - margin
+    width = min(parent.parent.winfo_width() - 100, 1100)  # set width to available space but max. 1100
+
+    # Create plot
+    figure = plot_field_sequence(parent.sequence_array, width, height)  # create figure to be displayed
+    # Clear previous plots first
+    try:
+        if parent.plot_canvas is not None:
+            parent.plot_canvas.get_tk_widget().destroy()
+    except Exception as e:
+        ui_print("Something went wrong while plotting csv data!", e)
+        messagebox.showerror("Error!", "Something went wrong while plotting csv data: \n%s" % e)
+        pass
+
+    axes = figure.axes
+    avx_lines = [axes[0].axvline(x=0, color="r"), axes[1].axvline(x=0, color="r"),
+                 axes[2].axvline(x=0, color="r"), axes[3].axvline(x=0, color="r")]
+    # Show new plot
+    parent.plot_canvas = FigureCanvasTkAgg(figure, parent.plot_frame)  # create canvas to draw figure on
+    parent.plot_canvas.draw()  # equivalent to matplotlib.show()
+    parent.plot_canvas.get_tk_widget().grid(row=0, column=0, sticky="nesw")  # place canvas in the UI
+
+    return figure, avx_lines
+
+
 def plot_field_sequence(array, width, height):  # create plot of fixed size (pixels) from array
     # ToDo (optional): polar plots, plots of angle...
     fig_dpi = 100  # set figure resolution (dots per inch)
@@ -160,12 +203,12 @@ def plot_field_sequence(array, width, height):  # create plot of fixed size (pix
     figure = plt.Figure(figsize=(width*px, height*px), dpi=fig_dpi)  # create figure with correct size
 
     # noinspection PyTypeChecker,SpellCheckingInspection
-    axes = figure.subplots(4, sharex=True, sharey=False, gridspec_kw={'hspace': 0.4})  # create subplots with shared axes
+    axes = figure.subplots(4, sharex=True, sharey=False, gridspec_kw={'hspace': 0.4})  # make subplots with shared axes
 
     figure.suptitle("Magnetic Field Sequence")  # set figure title
 
     # modify data to show instantaneous jumps in field to reflect test bench operation
-    new_array = np.array([[0, 0, 0, 0, 0]], dtype=float)  # initialize modified array, zeros to show start from no fields
+    new_array = np.array([[0, 0, 0, 0, 0]], dtype=float)  # initialize modified array, zeros to show start from no field
 
     last_values = [0, 0, 0, 0]  # [x,y,z, rr] field values / rot rate from last data point (zero here)
     for row in array[:, 0:5]:  # go through each row in the original array
@@ -200,8 +243,8 @@ def plot_field_sequence(array, width, height):  # create plot of fixed size (pix
     ylim_mag = ([min(axes[0].get_ylim()), max(axes[0].get_ylim()),
                  min(axes[1].get_ylim()), max(axes[1].get_ylim()),
                  min(axes[2].get_ylim()), max(axes[2].get_ylim())])
-    for i in range(3): axes[0].set_ylim(min(ylim_mag),max(ylim_mag))
-
+    for i in range(3):
+        axes[0].set_ylim(min(ylim_mag), max(ylim_mag))
 
     # set shared axis labels:
     axes[2].set_xlabel("Time [s])")