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https://github.com/Athemis/pyKinetics.git
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Split in library and cli
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parent
7bbb368499
commit
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2 changed files with 141 additions and 76 deletions
65
analyze-cli.py
Executable file
65
analyze-cli.py
Executable file
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@ -0,0 +1,65 @@
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#!/usr/bin/python
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import argparse
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import logging
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import csv
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from pathlib import Path
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import libkinetics
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def parse_arguments():
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parser = argparse.ArgumentParser()
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parser.add_argument('-v',
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'--verbose',
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action='store_true',
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help='increase output verbosity')
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parser.add_argument('-wh',
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'--with_hill',
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action='store_true',
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help='compute additional kinetics using Hill equation')
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parser.add_argument('input',
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type=str,
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help='directory containing input files in csv format')
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parser.add_argument('output',
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type=str,
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help='results will be written to this directory')
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args = parser.parse_args()
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return args
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def main():
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# parse command line arguments
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args = parse_arguments()
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if args.with_hill:
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do_hill = args.with_hill
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else:
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do_hill = False
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try:
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input_path = Path(args.input).resolve()
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except FileNotFoundError:
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print('Path containing input data not found: {}'.format(args.input))
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raise
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try:
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output_path = Path(args.output).resolve()
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except FileNotFoundError:
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print('Path for writing results not found: {}'.format(args.output))
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raise
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if output_path.is_dir():
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if input_path.is_dir():
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data_files = sorted(input_path.glob('**/*.csv'))
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exp = libkinetics.Experiment(data_files, (10, 25), do_hill)
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exp.plot_data(str(output_path))
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exp.plot_kinetics(str(output_path))
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exp.write_data(str(output_path))
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else:
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raise ValueError('{} is not a directory!'.format(input_path))
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else:
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raise ValueError('{} is not a directory!'.format(output_path))
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if __name__ == "__main__":
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main()
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152
analyze.py → libkinetics/__init__.py
Executable file → Normal file
152
analyze.py → libkinetics/__init__.py
Executable file → Normal file
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@ -3,11 +3,11 @@
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from scipy import stats, optimize
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import numpy as np
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import matplotlib.pyplot as plt
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import glob
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import csv
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class Replicate():
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def __init__(self, x, y, owner):
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self.x = x
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self.y = y
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@ -59,7 +59,7 @@ class Measurement():
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self.avg_slope = np.average(self.slopes)
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self.avg_slope_err = np.std(self.slopes)
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def plot(self):
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def plot(self, outpath):
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fig, ax = plt.subplots()
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ax.set_xlabel('Time [s]')
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ax.set_ylabel('Absorption (340 nm) [Au]')
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@ -73,8 +73,9 @@ class Measurement():
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'k-')
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ax.axvspan(self.xlim[0], self.xlim[1], facecolor='0.8', alpha=0.5)
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plt.savefig('out/fit_{}_{}.png'.format(self.concentration,
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self.concentration_unit),
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plt.savefig('{}/fit_{}_{}.png'.format(outpath,
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self.concentration,
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self.concentration_unit),
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bbox_inches='tight')
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plt.close(fig)
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@ -88,7 +89,7 @@ class Measurement():
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class Experiment():
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def __init__(self, data_files, xlim):
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def __init__(self, data_files, xlim, do_hill=False):
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# collction of indepentend measurements
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self.measurements = []
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@ -97,15 +98,11 @@ class Experiment():
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'y': [],
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'yerr': []}
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self.xlim = xlim
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# variables to store calculated Michaelis-Menten and Hill kinetics
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self.mm = None
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self.hill = None
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# parse data files and generate measurements
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for csvfile in data_files:
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tmp = np.genfromtxt(csvfile, comments='#')
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with open(csvfile) as datafile:
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tmp = np.genfromtxt(str(csvfile), comments='#')
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with open(str(csvfile)) as datafile:
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head = [next(datafile) for x in range(2)]
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# extract concentration and unit from header
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# TODO: move unit to parameter
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@ -113,25 +110,34 @@ class Experiment():
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conc = head[0].strip('#').strip()
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unit = head[1].strip('#').strip()
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# split x and y data apart
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# first column is x data (time); following columns contain
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# first column is x data (time); following columns contain
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# replicates of y data (absorption, etc.)
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x = tmp[:, 0]
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y = tmp[:, 1:]
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# create new measurement and append to list
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measurement = Measurement(x, y, conc, unit, self)
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self.measurements.append(measurement)
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# iterate over all measurements
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for m in self.measurements:
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# extract relevant data for kinetics calculation (concentration,
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# extract relevant data for kinetics calculation (concentration,
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# average slope and error)
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self.raw_kinetic_data['x'].append(m.concentration)
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self.raw_kinetic_data['y'].append(np.absolute(m.avg_slope))
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self.raw_kinetic_data['yerr'].append(m.avg_slope_err)
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def plot_data(self):
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# calculate kinetics
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self.mm = self.do_mm_kinetics()
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if do_hill:
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self.hill = self.do_hill_kinetics()
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else:
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self.hill = None
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def plot_data(self, outpath):
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# iterate over all measurements
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for m in self.measurements:
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m.plot()
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# plot each measurement
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m.plot(outpath)
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def mm_kinetics_function(self, x, vmax, Km):
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v = (vmax*x)/(Km+x)
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@ -142,39 +148,47 @@ class Experiment():
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return v
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def do_mm_kinetics(self):
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popt, pconv = optimize.curve_fit(self.mm_kinetics_function,
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self.raw_kinetic_data['x'],
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self.raw_kinetic_data['y'])
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try:
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popt, pconv = optimize.curve_fit(self.mm_kinetics_function,
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self.raw_kinetic_data['x'],
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self.raw_kinetic_data['y'])
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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Km = popt[1]
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x = np.arange(0, max(self.raw_kinetic_data['x']), 0.0001)
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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Km = popt[1]
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x = np.arange(0, max(self.raw_kinetic_data['x']), 0.0001)
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return {'vmax': float(vmax),
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'Km': float(Km),
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'perr': perr,
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'x': x}
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return {'vmax': float(vmax),
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'Km': float(Km),
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'perr': perr,
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'x': x}
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except:
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print('Calculation of Hill kinetics failed!')
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return None
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def do_hill_kinetics(self):
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popt, pconv = optimize.curve_fit(self.hill_kinetics_function,
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self.raw_kinetic_data['x'],
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self.raw_kinetic_data['y'])
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try:
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popt, pconv = optimize.curve_fit(self.hill_kinetics_function,
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self.raw_kinetic_data['x'],
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self.raw_kinetic_data['y'])
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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Kprime = popt[1]
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h = popt[2]
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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Kprime = popt[1]
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h = popt[2]
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x = np.arange(0, max(self.raw_kinetic_data['x']), 0.0001)
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x = np.arange(0, max(self.raw_kinetic_data['x']), 0.0001)
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return {'vmax': float(vmax),
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'Kprime': float(Kprime),
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'perr': perr,
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'h': h,
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'x': x}
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return {'vmax': float(vmax),
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'Kprime': float(Kprime),
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'perr': perr,
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'h': h,
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'x': x}
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except:
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print('Calculation of Hill kinetics failed!')
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return None
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def plot_kinetics(self):
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def plot_kinetics(self, outpath):
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fig, ax = plt.subplots()
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ax.set_xlabel('c [mM]')
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ax.set_ylabel('dA/dt [Au/s]')
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@ -184,28 +198,24 @@ class Experiment():
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self.raw_kinetic_data['y'],
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yerr=self.raw_kinetic_data['yerr'],
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fmt='ok', ms=3, fillstyle='none', label="Data with error")
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# linestyle='None', marker='o', ms=3, fillstyle='none'
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self.mm = self.do_mm_kinetics()
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self.hill = self.do_hill_kinetics()
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print(self.mm)
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print(self.hill)
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ax.plot(self.mm['x'],
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(self.mm['vmax']*self.mm['x'])/(self.mm['Km']+self.mm['x']),
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'b-', label="Michaelis-Menten")
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ax.plot(self.hill['x'],
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((self.hill['vmax']*(self.hill['x']**self.hill['h'])) /
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(self.hill['Kprime'] + (self.hill['x']**self.hill['h']))),
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'g-', label="Hill")
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if self.mm:
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ax.plot(self.mm['x'],
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(self.mm['vmax']*self.mm['x'])/(self.mm['Km']+self.mm['x']), 'b-', label="Michaelis-Menten")
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if self.hill:
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ax.plot(self.hill['x'],
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((self.hill['vmax']*(self.hill['x']**self.hill['h'])) /
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(self.hill['Kprime'] + (self.hill['x']**self.hill['h']))), 'g-', label="Hill")
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ax.legend(loc='best', fancybox=True)
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plt.savefig('out/kinetics.png', bbox_inches='tight')
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plt.savefig('{}/kinetics.png'.format(outpath), bbox_inches='tight')
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plt.close(fig)
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def write_data(self):
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def write_data(self, outpath):
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with open('out/results.csv', 'w', newline='\n') as csvfile:
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with open('{}/results.csv'.format(outpath),
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'w',
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newline='\n') as csvfile:
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writer = csv.writer(csvfile, dialect='excel-tab')
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writer.writerow(['# LINEAR FITS'])
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@ -223,22 +233,12 @@ class Experiment():
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writer.writerow(row)
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writer.writerow([])
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writer.writerow(['# MICHAELIS-MENTEN KINETICS'])
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writer.writerow(['# vmax', 'Km'])
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writer.writerow([self.mm['vmax'], self.mm['Km']])
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writer.writerow(['# HILL KINETICS'])
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writer.writerow(['# vmax', 'Kprime', 'h'])
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writer.writerow([self.hill['vmax'], self.hill['Kprime'],
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self.hill['h']])
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def main():
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data_files = glob.glob('csv/*.csv')
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exp = Experiment(data_files, (10, 25))
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exp.plot_data()
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exp.plot_kinetics()
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exp.write_data()
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if __name__ == "__main__":
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main()
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if self.mm:
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writer.writerow(['# MICHAELIS-MENTEN KINETICS'])
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writer.writerow(['# vmax', 'Km'])
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writer.writerow([self.mm['vmax'], self.mm['Km']])
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if self.hill:
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writer.writerow(['# HILL KINETICS'])
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writer.writerow(['# vmax', 'Kprime', 'h'])
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writer.writerow([self.hill['vmax'], self.hill['Kprime'],
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self.hill['h']])
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