asc_to_tidy_384well_ODfirst.py

#!/usr/bin/env python
# Jared Bard 2019-01-14
# Modified on 2020-11-13 to account for multiple kinetic loops,
# n_channels doesn't include the initial A600 read
# needs some more generalization
# Script to process tecan data into tidy_data
# Written for python 3.7
# Export to ascii file settings: Decimal = point, Delimiter = Tabulator, Encoding = Unicode
# export options: Direction=horizontal, result=matrix(separated)
# insert data names=yes, add kinetic time stamps=yes, add temperatures=yes
# date/time of measurement=yes,filter wavelength=yes, measurement params=yes
# usage: python asc_to_tidy_384well.py n_channels filepath
# usage example: 'python asc_to_tidy_384well.py 1 190129-1.asc'

# For a different plates size, change the n_rows and n_cols appropriately


import sys
import os
import numpy as np
import csv
import pathlib

n_rows = 16
n_cols = 24


def main():
	# This basic command line argument parsing code is provided.
	# Add code to call your functions below.

	# Make a list of command line arguments, omitting the [0] element
	# which is the script itself.
	args = sys.argv[1:]
	if not args:
		print('ERROR! Usage: n_channels filepath')
		sys.exit(1)
	elif len(args) > 2:
		print('ERROR! Usage: n_channels filepath')
		sys.exit(1)

	try:
		n_channels = int(args[0])
	except:
		print('ERROR! Usage: n_channels filepath')
		sys.exit(1)

	filename = pathlib.Path(args[1])
	if filename.suffix != '.asc':
		print('ERROR! Please provide a .asc file')
		sys.exit(1)
	#Debug
	#filename = pathlib.Path("C:/Users/jabar/Dropbox (Drummond Lab)/Data_JB/Plate/Luminescence/201112/src/201112-2-0min.asc")
	#n_channels = 1
	# initalize storage variables
	block_size = n_rows + 2
	channels = []  # names of channels
	time = []  # all of the time stamps
	data = []  # list of each matrix of data
	temperature = []  # list of all temperatures
	date = ''
	start_time = ''

	with open(filename,'rt',encoding='utf-16') as f:
		for line_num,line in enumerate(f):
			line = line.strip('\n')
			# watch out for the trailing tab (last column has a tab after)
			columns = line.split('\t')

			c1 = columns[0]
			if c1:  # look for the measurement parameters
				first_word = c1.split()[0]
				if first_word == 'Date':
					date = c1.split()[3][0:10]
					start_time = c1.split()[6]
					break

			block_i = (line_num - n_channels - 1)%block_size #modified
			if line_num == n_channels + 1: #modified
				if columns[0] != '0s':
					print('ERROR! Possibly the number of channels is incorrect.')
					sys.exit(1)
			if line_num < n_channels+1:  # the first few lines are the names of the channels
				channels.append(columns[0])
			elif block_i == 0:
				time.append(columns[0][0:-1])  # removes the trailing s
				data_temp = np.zeros((n_rows,n_cols),dtype=np.float_)  # initialze the data array for this block
			elif block_i == 1:
				temperature.append(columns[0].split(' ')[0])  # extract just the number
			elif block_i > 1:
				row_i = block_i - 2  # which row of the data are we in
				for column_i,c in enumerate(columns[0:-1]): #strip the last tab
					if c:
						data_temp[row_i,column_i] = float(c)
					else:
						data_temp[row_i,column_i] = float('NaN')
				if block_i == (block_size - 1):  # for the last row, add the matrix to the list of all data
					data.append(data_temp)
	# Determine how many measurements were made
	channels = channels[1:] #modified
	A600_data = data[0] #modified
	data = data[1:] #modified
	A600_time = time[0]
	time = time[1:] #modified
	A600_temp = temperature[0]
	temperature = temperature[1:] #modified
	
	n_measurements = divmod(len(data),n_channels)[0]
	measured_wells_i = np.transpose(np.nonzero(~np.isnan(data[0][:,:])))  # extract the locations of all non-zero measurements
	alphabet = ('A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P')
	measured_wells = []

	for well_i in measured_wells_i:
		alpha_i = well_i[0]
		num_i = well_i[1]
		measured_wells.append(alphabet[alpha_i] + str(num_i + 1))  # creates a list of which wells were measured

	# Goal is to make a table in tidy format. Go through each channel
	# Extract the correct time, temp and value, and assign to a list
	col_headers = ('Well','Time_s','Temp_C','Channel','Value','Date','Start_Time')
	tidy_data = [col_headers]
	#add A600 data first
	for which_well,well_i in enumerate(measured_wells_i):
		channel = "A600"
		read_index = 0
		value_temp = A600_data[well_i[0],well_i[1]]
		well_temp = measured_wells[which_well]
		tidy_data.append([well_temp,A600_time,A600_temp,
						  channel,value_temp,date,start_time])
								  
	for which_channel,channel in enumerate(channels):
		for which_well,well_i in enumerate(measured_wells_i):
			for which_read in range(n_measurements):
				read_index = which_channel*n_measurements + which_read
				value_temp = data[read_index][well_i[0],well_i[1]]
				time_temp = time[read_index]
				temperature_temp = temperature[read_index]
				well_temp = measured_wells[which_well]
				tidy_data.append([well_temp,time_temp,temperature_temp,
				                  channel,value_temp,date,start_time])
	
	file_to_write = filename.parent/(filename.name[0:-4] + '.csv')
	with open(file_to_write,'w',newline='') as f:
		writer = csv.writer(f)
		writer.writerows(tidy_data)
	print('Output file = ',end='')
	print(file_to_write)


# This is the standard boilerplate that calls the main() function.
if __name__ == '__main__':
	main()