Athemis/pyKinetics
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Split in library and cli

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This commit is contained in:
Alexander Minges 2015-08-18 23:58:57 +02:00
parent 7bbb368499
commit 7a943cb945
2 changed files with 141 additions and 76 deletions
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65
analyze-cli.py Executable file
View file

@ -0,0 +1,65 @@
#!/usr/bin/python
import argparse
import logging
import csv
from pathlib import Path
import libkinetics
def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument('-v',
'--verbose',
action='store_true',
help='increase output verbosity')
parser.add_argument('-wh',
'--with_hill',
action='store_true',
help='compute additional kinetics using Hill equation')
parser.add_argument('input',
type=str,
help='directory containing input files in csv format')
parser.add_argument('output',
type=str,
help='results will be written to this directory')
args = parser.parse_args()
return args
def main():
# parse command line arguments
args = parse_arguments()
if args.with_hill:
do_hill = args.with_hill
else:
do_hill = False
try:
input_path = Path(args.input).resolve()
except FileNotFoundError:
print('Path containing input data not found: {}'.format(args.input))
raise
try:
output_path = Path(args.output).resolve()
except FileNotFoundError:
print('Path for writing results not found: {}'.format(args.output))
raise
if output_path.is_dir():
if input_path.is_dir():
data_files = sorted(input_path.glob('**/*.csv'))
exp = libkinetics.Experiment(data_files, (10, 25), do_hill)
exp.plot_data(str(output_path))
exp.plot_kinetics(str(output_path))
exp.write_data(str(output_path))
else:
raise ValueError('{} is not a directory!'.format(input_path))
else:
raise ValueError('{} is not a directory!'.format(output_path))
if __name__ == "__main__":
main()

76
analyze.py → libkinetics/__init__.py Executable file → Normal file
View file

@ -3,11 +3,11 @@
from scipy import stats, optimize
import numpy as np
import matplotlib.pyplot as plt
import glob
import csv
class Replicate():
def __init__(self, x, y, owner):
self.x = x
self.y = y
@ -59,7 +59,7 @@ class Measurement():
self.avg_slope = np.average(self.slopes)
self.avg_slope_err = np.std(self.slopes)
def plot(self):
def plot(self, outpath):
fig, ax = plt.subplots()
ax.set_xlabel('Time [s]')
ax.set_ylabel('Absorption (340 nm) [Au]')
@ -73,7 +73,8 @@ class Measurement():
'k-')
ax.axvspan(self.xlim[0], self.xlim[1], facecolor='0.8', alpha=0.5)
plt.savefig('out/fit_{}_{}.png'.format(self.concentration,
plt.savefig('{}/fit_{}_{}.png'.format(outpath,
self.concentration,
self.concentration_unit),
bbox_inches='tight')
plt.close(fig)
@ -88,7 +89,7 @@ class Measurement():
class Experiment():
def __init__(self, data_files, xlim):
def __init__(self, data_files, xlim, do_hill=False):
# collction of indepentend measurements
self.measurements = []
@ -98,14 +99,10 @@ class Experiment():
'yerr': []}
self.xlim = xlim
# variables to store calculated Michaelis-Menten and Hill kinetics
self.mm = None
self.hill = None
# parse data files and generate measurements
for csvfile in data_files:
tmp = np.genfromtxt(csvfile, comments='#')
with open(csvfile) as datafile:
tmp = np.genfromtxt(str(csvfile), comments='#')
with open(str(csvfile)) as datafile:
head = [next(datafile) for x in range(2)]
# extract concentration and unit from header
# TODO: move unit to parameter
@ -129,9 +126,18 @@ class Experiment():
self.raw_kinetic_data['y'].append(np.absolute(m.avg_slope))
self.raw_kinetic_data['yerr'].append(m.avg_slope_err)
def plot_data(self):
# calculate kinetics
self.mm = self.do_mm_kinetics()
if do_hill:
self.hill = self.do_hill_kinetics()
else:
self.hill = None
def plot_data(self, outpath):
# iterate over all measurements
for m in self.measurements:
m.plot()
# plot each measurement
m.plot(outpath)
def mm_kinetics_function(self, x, vmax, Km):
v = (vmax*x)/(Km+x)
@ -142,6 +148,7 @@ class Experiment():
return v
def do_mm_kinetics(self):
try:
popt, pconv = optimize.curve_fit(self.mm_kinetics_function,
self.raw_kinetic_data['x'],
self.raw_kinetic_data['y'])
@ -155,8 +162,12 @@ class Experiment():
'Km': float(Km),
'perr': perr,
'x': x}
except:
print('Calculation of Hill kinetics failed!')
return None
def do_hill_kinetics(self):
try:
popt, pconv = optimize.curve_fit(self.hill_kinetics_function,
self.raw_kinetic_data['x'],
self.raw_kinetic_data['y'])
@ -173,8 +184,11 @@ class Experiment():
'perr': perr,
'h': h,
'x': x}
except:
print('Calculation of Hill kinetics failed!')
return None
def plot_kinetics(self):
def plot_kinetics(self, outpath):
fig, ax = plt.subplots()
ax.set_xlabel('c [mM]')
ax.set_ylabel('dA/dt [Au/s]')
@ -184,28 +198,24 @@ class Experiment():
self.raw_kinetic_data['y'],
yerr=self.raw_kinetic_data['yerr'],
fmt='ok', ms=3, fillstyle='none', label="Data with error")
# linestyle='None', marker='o', ms=3, fillstyle='none'
self.mm = self.do_mm_kinetics()
self.hill = self.do_hill_kinetics()
print(self.mm)
print(self.hill)
if self.mm:
ax.plot(self.mm['x'],
(self.mm['vmax']*self.mm['x'])/(self.mm['Km']+self.mm['x']),
'b-', label="Michaelis-Menten")
(self.mm['vmax']*self.mm['x'])/(self.mm['Km']+self.mm['x']), 'b-', label="Michaelis-Menten")
if self.hill:
ax.plot(self.hill['x'],
((self.hill['vmax']*(self.hill['x']**self.hill['h'])) /
(self.hill['Kprime'] + (self.hill['x']**self.hill['h']))),
'g-', label="Hill")
(self.hill['Kprime'] + (self.hill['x']**self.hill['h']))), 'g-', label="Hill")
ax.legend(loc='best', fancybox=True)
plt.savefig('out/kinetics.png', bbox_inches='tight')
plt.savefig('{}/kinetics.png'.format(outpath), bbox_inches='tight')
plt.close(fig)
def write_data(self):
def write_data(self, outpath):
with open('out/results.csv', 'w', newline='\n') as csvfile:
with open('{}/results.csv'.format(outpath),
'w',
newline='\n') as csvfile:
writer = csv.writer(csvfile, dialect='excel-tab')
writer.writerow(['# LINEAR FITS'])
@ -223,22 +233,12 @@ class Experiment():
writer.writerow(row)
writer.writerow([])
if self.mm:
writer.writerow(['# MICHAELIS-MENTEN KINETICS'])
writer.writerow(['# vmax', 'Km'])
writer.writerow([self.mm['vmax'], self.mm['Km']])
if self.hill:
writer.writerow(['# HILL KINETICS'])
writer.writerow(['# vmax', 'Kprime', 'h'])
writer.writerow([self.hill['vmax'], self.hill['Kprime'],
self.hill['h']])
def main():
data_files = glob.glob('csv/*.csv')
exp = Experiment(data_files, (10, 25))
exp.plot_data()
exp.plot_kinetics()
exp.write_data()
if __name__ == "__main__":
main()