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Improve docs; Use custom Exceptions
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1 changed files with 104 additions and 37 deletions
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@ -7,7 +7,24 @@ import logging
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import warnings
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class Error(Exception):
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"""
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Main Error class derived from Exception.
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"""
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pass
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class FitError(Error):
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"""
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Exception raised if fitting fails.
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"""
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pass
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class Replicate():
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"""
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Represents a single replicate within a measurement
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"""
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@ -66,6 +83,7 @@ class Replicate():
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class Measurement():
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"""
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Represents a single measurement within an experiment.
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"""
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@ -112,6 +130,7 @@ class Measurement():
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class Experiment():
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"""
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Represents the actual experiment.
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@ -121,13 +140,17 @@ class Experiment():
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Attributes:
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logger: logging.Logger instance that is used for logging to console
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and log file.
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measurements: list of individual measurements of the experiment.
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measurements: array_like
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list of individual measurements of the experiment.
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Usually defined by different substrate concentrations.
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fit_to_replicates: whether to fit to individual replicates instead to
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the average of each measurement.
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raw_kinetic_data: dictionary storing x, y and std_err of each
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measurement for fitting kinetic curves.
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xlim: lower and upper bounds for calculating the v0 linear fit.
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fit_to_replicates: boolean
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whether to fit to individual replicates instead to the average of
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each measurement.
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raw_kinetic_data: dictionary
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storing x, y and std_err of each measurement for fitting kinetic
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curves.
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xlim: array_like
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lower and upper bounds for calculating the v0 linear fit.
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"""
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def __init__(self, data_files, xlim, do_hill=False,
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@ -217,12 +240,16 @@ class Experiment():
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Classical Michaelis-Menten enzyme kinetics function.
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Args:
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x: concentration at velocity v
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vmax: maximum velocity
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Km: Michaelis constant
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x: float
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concentration at velocity v
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vmax: float
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maximum velocity
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Km: float
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Michaelis constant
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Returns:
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v: velocity at given concentration x
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v: float
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velocity at given concentration x
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"""
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v = (vmax*x)/(Km+x)
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return v
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@ -234,23 +261,50 @@ class Experiment():
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Hill function for enzyme kinetics with cooperativity.
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Args:
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x: concentration at velocity v
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vmax: maximum velocity
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Kprime: kinetics constant related to Michaelis constant
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h: hill slope; if 1 function is identical to Michaelis-Menten
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function.
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x: float
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concentration at velocity v.
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vmax: float
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maximum velocity.
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Kprime: float
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kinetics constant related to Michaelis constant.
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h: float
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hill slope; if h=1, Hill function is identical to
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Michaelis-Menten function.
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Returns:
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v: velocity at given concentration x
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v: float
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velocity at given concentration x
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"""
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v = (vmax*(x**h))/(Kprime+(x**h))
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return v
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def do_mm_kinetics(self):
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"""
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Calculates Michaelis-Menten kinetics.
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Returns:
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On success, returns a dictionary containing the kinetic parameters
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and their errors:
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{'vmax': float,
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'Km': float,
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'vmax_err': float,
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'Km_err': float,
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'x': array_like}
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Raises:
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FitError if fitting fails.
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"""
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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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except ValueError:
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msg = ('Calculation of Michaelis-Menten kinetics failed! Your '
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'input data (either x or y) contain empty (NaN) values!')
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if self.logger:
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self.logger.error('{}'.format(msg))
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raise FitError(msg)
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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@ -261,23 +315,41 @@ class Experiment():
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self.logger.info(' v_max: {} ± {}'.format(vmax, perr[0]))
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self.logger.info(' Km: {} ± {}'.format(Km, perr[1]))
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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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return {'vmax': np.float(vmax),
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'Km': np.float(Km),
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'vmax_err': np.float(perr[0]),
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'Km_err': np.float(perr[1]),
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'x': x}
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except:
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msg = 'Calculation of Michaelis-Menten kinetics failed!'
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if self.logger:
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self.logger.error('{}'.format(msg))
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else:
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print(msg)
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return None
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def do_hill_kinetics(self):
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"""
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Calculates Hill kinetics.
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Returns:
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On success, returns a dictionary containing the kinetic parameters
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their errors:
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{'vmax': float,
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'Kprime': float,
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'vmax_err': float,
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'Km_prime': float,
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'h_err': float,
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'h': float,
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'x': array_like}
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Raises:
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FitError if fitting fails.
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"""
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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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except ValueError:
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msg = ('Calculation of Hill kinetics failed! Your input data '
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'(either x or y) contain empty (NaN) values!')
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if self.logger:
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self.logger.error('{}'.format(msg))
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raise FitError(msg)
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perr = np.sqrt(np.diag(pconv))
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vmax = popt[0]
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@ -291,15 +363,10 @@ class Experiment():
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self.logger.info(' K_prime: {} ± {}'.format(Kprime, perr[1]))
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self.logger.info(' h: {} ± {}'.format(h, perr[2]))
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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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return {'vmax': np.float(vmax),
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'Kprime': np.float(Kprime),
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'vmax_err': np.float(perr[0]),
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'Kprime_err': np.float(perr[1]),
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'h_err': np.float(perr[2]),
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'h': np.float(h),
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'x': x}
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except:
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msg = 'Calculation of Hill kinetics failed!'
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if self.logger:
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self.logger.error('{}'.format(msg))
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else:
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print(msg)
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return None
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