forked from zietzm/Helmholtz_Test_Bench
Martin Zietz
100 lines
4.4 KiB
Python
100 lines
4.4 KiB
Python
# This file contains functions related to logging data from the program to a CSV file
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# They are mainly but not only called by the ConfigureLogging class in User_Interface.py
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import pandas as pd
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import globals as g
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from datetime import datetime
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import os
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from tkinter import filedialog
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from tkinter import messagebox
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import User_Interface as ui
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log_data = pd.DataFrame() # pandas data frame containing logged data
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logging = False # Bool to indicate if data should be logged at the moment
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unsaved_data = False # Bool to indicate if there is unsaved data, set to True each time a datapoint is logged
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zero_time = datetime.now()
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# create dictionary with all value handles that could be logged
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# Key: String that is displayed in UI and column headers. Also serves as handle to access dictionary elements.
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# Keys are the same as the rows in the status display ToDo (optional): use this for the status display
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# Content: name of the corresponding attribute in the Axis class (in cage_func.py).
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# Important: attribute handle must match definition in Axis class exactly, used with axis.getattr() to get values.
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axis_data_dict = {
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'PSU Status': 'connected',
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'Voltage Setpoint': 'voltage_setpoint',
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'Actual Voltage': 'voltage',
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'Current Setpoint': 'current_setpoint',
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'Actual Current': 'current',
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'Target Field': 'target_field_comp',
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'Trgt. Field Raw': 'target_field_comp',
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'Target Current': 'target_current',
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'Inverted': 'polarity_switched'
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}
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def triple_list(key_list): # creates list with each entry of key_list tripled with axis names before it
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new_list = [] # initialize list
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for key in key_list: # go through the given list
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for axis_name in ['X', 'Y', 'Z']: # per given list entry create three, one for each axis
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new_list.append(' '.join((axis_name, key))) # put axis_name before the given entry and append to new list
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return new_list
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def init_log_dataframe(key_list): # probably not needed, ToDo: remove
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global log_data
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columns = triple_list(key_list)
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log_data = pd.DataFrame(columns=columns)
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def log_datapoint(key_list): # ToDo: comments
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global log_data
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global unsaved_data
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date = datetime.now().date()
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time = datetime.now().strftime("%H:%M:%S,%f")
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t = (datetime.now() - zero_time).total_seconds()
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data = [[date, time, t]]
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for key in key_list:
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for axis in g.AXES:
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data[0].append(getattr(axis, axis_data_dict[key])) # get value
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column_names = ["Date", "Time", "t (s)", *triple_list(key_list)]
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new_row = pd.DataFrame(data, columns=column_names)
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log_data = log_data.append(new_row, ignore_index=True)
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unsaved_data = True
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def select_file(): # select a file to write logs to
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directory = os.path.abspath(os.getcwd()) # get project directory
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# open file selection dialogue and save path of selected file
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filepath = filedialog.asksaveasfilename(initialdir=directory, title="Set log file",
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filetypes=([("Comma Separated Values", "*.csv*")]),
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defaultextension=[("Comma Separated Values", "*.csv*")])
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if filepath == '': # this happens when file selection window is closed without selecting a file
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ui.ui_print("No file selected, can not save logged data.")
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return None
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else: # a valid file name was entered
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return filepath
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def write_to_file(dataframe, filepath):
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# get global variables for use in this function:
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global unsaved_data
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if filepath is not None: # user has selected a file and no errors occurred
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ui.ui_print("Writing logged data to file", filepath)
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try:
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# write data collected in log_data DataFrame to csv file in german excel format:
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dataframe.to_csv(filepath, index=False, sep=';', decimal=',')
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except PermissionError:
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message = "No permission to write to: \n%s. \nFile may be open in another program." % filepath
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messagebox.showerror("Permission Error", message)
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except BaseException as e:
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message = "Error while trying to write to file \n%s.\n%s" % (filepath, e)
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messagebox.showerror("Error!", message)
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else: # no exceptions occurred
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unsaved_data = False # data has been saved, so no unsaved data remains
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def clear_logged_data(): # clears all logged data from data frame
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global log_data # get global variable
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log_data = pd.DataFrame() # reset to an empty data frame, i.e. clear all logged data
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