forked from zietzm/Helmholtz_Test_Bench
180 lines
9.7 KiB
Python
180 lines
9.7 KiB
Python
# tThis file contains code for executing a sequence of magnetic fields from a csv file.
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# To do this without crashing the UI it has to run in a separate thread using the threading module.
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# import packages:
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import time
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import pandas
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import numpy as np
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from threading import *
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from tkinter import messagebox
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import matplotlib.pyplot as plt
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# import other project files:
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import User_Interface as ui
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import cage_func as func
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import globals as g
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import traceback # ToDo: remove!
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class ExecCSVThread(Thread):
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# main class for executing a CSV sequence
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# it inherits the threading.Thread class, enabling sequence execution in a separate thread
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def __init__(self, array, parent, controller):
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Thread.__init__(self)
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self.array = array # numpy array containing data from csv to be executed
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self.parent = parent # object from which this class is called, here the ExecuteCSVMode object of the UI
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self.controller = controller # object on which mainloop() is running, usually the main UI window
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self.__stop_event = Event() # event which can be set to stop the thread execution if needed
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def run(self): # called to start the execution of the thread
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ui.ui_print("\nStarting Sequence Execution...")
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self.execute_sequence(self.array, 0.1, self.parent, self.controller) # run sequence
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# when the sequence has ended, reset buttons on the UI:
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if not g.exitFlag: # main window is open
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self.parent.select_file_button["state"] = "normal"
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self.parent.execute_button["state"] = "normal"
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self.parent.stop_button["state"] = "disabled"
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self.parent.reinit_button["state"] = "normal"
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# setup ability to interrupt thread (https://stackoverflow.com/questions/323972/is-there-any-way-to-kill-a-thread)
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def stop(self): # stop thread execution, can be called from another thread to kill this one
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self.__stop_event.set()
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def stopped(self): # returns true if the thread has been stopped, used to check if a run should continue
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return self.__stop_event.is_set()
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def execute_sequence(self, array, delay, parent, controller):
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# main execution method of the class
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# runs through array with times and desired fields and commands test stand accordingly
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# array format: [time (s), xField (T), yField (T), zField (T)]
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func.power_down_all() # sets outputs on PSUs to 0 and Arduino pins to LOW before starting
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t_zero = time.time() # set reference time for start of run
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# Check if everything is properly connected:
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all_connected = func.devices_ok(parent.xy_override.get(), parent.z_override.get(),
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parent.arduino_override.get())
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# True or False depending on devices status, checks for some devices may be overridden by user
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i = 0 # index of the current array row
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while i < len(array) and all_connected and not self.stopped() and not g.exitFlag:
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# while array is not finished, devices are connected, user has not cancelled and application is running
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t = time.time() - t_zero # get time relative to start of run
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if t >= array[i, 0]: # time for this row has come
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g.threadLock.acquire() # execute all lines until threadLock.release() before going back to main thread
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# check if everything is still connected before sending commands:
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all_connected = func.devices_ok(parent.xy_override.get(), parent.z_override.get(),
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parent.arduino_override.get())
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if all_connected:
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field_vec = array[i, 1:4] # extract desired field vector
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ui.ui_print("%0.5f s: t = %0.2f s, target field vector ="
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% (time.time() - t_zero, array[i, 0]), field_vec * 1e6, "\u03BCT")
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func.set_field(field_vec) # send field vector to test stand
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controller.StatusDisplay.update_labels() # update status display after change
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# log change to the log file if user has selected event logging in the Configure Logging window
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logger = controller.pages[ui.ConfigureLogging] # get object of logging configurator
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if logger.event_logging: # data should be logged when test stand is commanded
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logger.log_datapoint() # log data
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i = i + 1 # next row
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g.threadLock.release() # allow going back to main thread now
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elif t <= array[i, 0] - delay - 0.02: # is there enough time to sleep before the next row?
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time.sleep(delay) # sleep to give other threads time to run
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if not self.stopped() and not g.exitFlag and all_connected: # sequence ended without interruption
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ui.ui_print("Sequence executed, powering down channels.")
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elif all_connected: # interrupted by user
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ui.ui_print("Sequence cancelled, powering down channels.")
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elif not all_connected: # interrupted by device error
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ui.ui_print("Error with at least one device, sequence aborted.")
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messagebox.showwarning("Device Error!", "Error with at least one device, sequence aborted.")
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else: # if this happens there is a mistake in the logic above, it really should not
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# tell the user something weird happened:
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ui.ui_print("Encountered unexpected sequence end state:"
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"\nThread Stopped:", self.stopped(), ", Application Closed:", g.exitFlag,
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", Devices connected:", all_connected)
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messagebox.showwarning("Unexpected state",
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"Encountered unexpected sequence end state, see console output for details.")
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func.power_down_all() # set currents and voltages to 0, set arduino pins to low
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def read_csv_to_array(filepath): # convert a given csv file to a numpy array
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# csv format: time (s); xField (T); yField (T); zField (T) (german excel)
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# decimal commas
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file = pandas.read_csv(filepath, sep=';', decimal=',', header=0) # read csv file without column headers
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array = file.to_numpy() # convert csv to array
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return array
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def check_array_ok(array):
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# check if any magnetic fields in an array exceed the test stand limits and if so display a warning message
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values_ok = True
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for i in [0, 1, 2]: # go through axes/columns
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max_val = g.AXES[i].max_comp_field[1] # get limits the test stand can do
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min_val = g.AXES[i].max_comp_field[0]
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data = array[:, i + 1] # extract data for this axis from array
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# noinspection PyTypeChecker
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if any(data > max_val) or any(data < min_val): # if any datapoint is out of bounds
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values_ok = False
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if not values_ok: # show warning pop-up if values are exceeding limits
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messagebox.showwarning("Value Limits Warning!", "Found field values exceeding limits of test stand."
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"\nSee plot and check values in csv.")
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def plot_field_sequence(array, width, height): # create plot of fixed size (pixels) from array
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# ToDo (optional): polar plots, plots of angle...
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fig_dpi = 100 # set figure resolution (dots per inch)
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px = 1/fig_dpi # get pixel to inch size conversion
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figure = plt.Figure(figsize=(width*px, height*px), dpi=fig_dpi) # create figure with correct size
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# noinspection PyTypeChecker,SpellCheckingInspection
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axes = figure.subplots(3, sharex=True, sharey=True, gridspec_kw={'hspace': 0.4}) # create subplots with shared axes
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figure.suptitle("Magnetic Field Sequence") # set figure title
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# modify data to show instantaneous jumps in field to reflect test stand operation
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new_array = np.array([[0, 0, 0, 0]], dtype=float) # initialize modified array, zeros to show start from no fields
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last_vals = [0, 0, 0] # [x,y,z] field values from last data point (zero here), used to create step in data
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for row in array[:, 0:4]: # go through each row in the original array
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# create extra datapoint at current timestamp, with field values from last, this creates "step" in plot:
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new_array = np.append(new_array, [[row[0], *last_vals]], axis=0)
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new_array = np.append(new_array, [row], axis=0) # add actual datapoint for current timestamp
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last_vals = row[1:4] # save values from current timestamp for next
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new_array = np.append(new_array, [[new_array[-1, 0], 0, 0, 0]], axis=0) # append last datapoint with 0 fields
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# extract data and plot:
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t = new_array[:, 0] # extract time column
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for i in [0, 1, 2]: # go through all three axes
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data = new_array[:, i + 1] * 1e6 # extract field column of this axis and convert to microtesla
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max_val = g.AXES[i].max_comp_field[1] * 1e6 # get limits of achievable field
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min_val = g.AXES[i].max_comp_field[0] * 1e6
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plot = axes[i] # get appropriate subplot
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plot.plot(t, data, linestyle='solid', marker='.') # plot data
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if any(data > max_val): # if any value is higher than the maximum
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plot.axhline(y=max_val, linestyle='dashed', color='r') # plot horizontal line to show maximum
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# add label to line:
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plot.text(t[-1], max_val, "max", horizontalalignment='center', verticalalignment='top', color='r')
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if any(data < min_val): # same as above
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plot.axhline(y=min_val, linestyle='dashed', color='r')
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plot.text(t[-1], min_val, "min", horizontalalignment='center', color='r')
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plot.set_title(g.AXIS_NAMES[i], size=10) # set subplot title (e.g. "X-Axis")
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# set shared axis labels:
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axes[2].set_xlabel("Time (s)")
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axes[1].set_ylabel("Magnetic Field (\u03BCT)")
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return figure # return the created figure to be inserted somewhere
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