Style and grammar.

cosgen/cli.py

@@ -32,7 +32,7 @@ def cli_algorithm(population_size=20, library_size=20, storage_path='~/.cosgen',
 	"""
 	Run default optimization.
 
-	This function attempts to optimize find a good sequence with only few input parameters.
+	This function attempts to optimize towards a viable sequence, while only requiring few input parameters.
 	It uses a generic design matrix construction and a first order autoregressive model.
 
 	Parameters

cosgen/cross_over.py

@@ -12,7 +12,7 @@ def cross_over(sequence1, sequence2):
 	"""
 	Create offspring of sequence1 and sequence2.
 
-	This function creats an offspring of sequence1 and sequence2 by
+	This function creates an offspring of sequence1 and sequence2 by
 	cutting them at a random point and merging the two ends.
 
 	Parameters

cosgen/function_crate.py

@@ -8,17 +8,17 @@ class MissingAttrError(Exception):
 	pass
 
 class WrongOrderError(Exception):
-	"""This error is raised if the functions are added to a
+	"""This error is raised if functions are added to a
 	FunctionCrate object in the wrong order."""
 	pass
 
 class RmAttrError(Exception):
-	"""This error is raised if an attribut of a FunctionCrate object
+	"""This error is raised if an attribute of a FunctionCrate object
 	can not be removed because it does not exist."""
 	pass
 
 class OverwriteAttrError(Exception):
-	"""This error is raised if an attribut of a FunctionCrate object
+	"""This error is raised if an attribute of a FunctionCrate object
 	already exist."""
 	pass
 
@@ -36,7 +36,7 @@ def partition(population, left, right, pivotIndex):
 	return storeIndex
 
 def quickselect(population, left, right, k):
-	"""Returns the k-th smallest, (k >= 0), element of population within population[left:right+1] inclusive.
+	"""Returns the k-th smallest, (k >= 0), element of `population` within `population[left:right+1]` inclusive.
 	Implementation of the quickselect algorithm from https://rosettacode.org/wiki/Quickselect_algorithm#Python."""
 	while True:
 		pivotIndex = random.randint(left, right)     # select pivotIndex between left and right
@@ -85,7 +85,7 @@ def find_best(population, n):
 		"""
 		Find n best sequences in population.
 
-		This method finds the n sequences with the highest fitness in population.
+		This method finds the n sequences with the highest fitness in the population.
 
 		Parameters
 		----------
@@ -107,7 +107,7 @@ def add_fitness_measure(self, name, function):
 		Add fitness measure function to object.
 
 		This method adds a fitness measure function to the
-		object, that is used in the evaluate fitness method. The
+		object, that is used in the `evaluate_fitness` method. The
 		function must take a sequences as parameter and retrun a
 		float.
 
@@ -144,7 +144,7 @@ def set_mutate(self, function):
 		"""
 		Set a mutate function.
 
-		This methode sets a mutate function used by the genetic
+		This method sets a mutate function used by the genetic
 		algorithm. The function should normally take a
 		cosgen.sequence.Sequence object as input and return a
 		cosgen.sequence.Sequence object.
@@ -173,7 +173,7 @@ def set_cross_over(self, function):
 		"""
 		Set a cross over function.
 
-		This methode sets a cross over function used by the
+		This method sets a cross over function used by the
 		genetic algorithm. The function should normally take two
 		cosgen.sequence.Sequence objects as input and return a
 		cosgen.sequence.Sequence object.
@@ -202,7 +202,7 @@ def set_generate_immigrants(self,function):
 		"""
 		Set a generate immigrants function.
 
-		This methode sets a generate immigrants function used by
+		This method sets a generate immigrants function used by
 		the genetic algorithm. The function should normally return
 		a list of cosgen.sequence.Sequence objects. If the
 		function as an argument 'cross_over_fct' a cross over

cosgen/models.py

@@ -76,7 +76,7 @@ def cov_beta(self, X):
 
 class EstimationModel(Model):
 	"""
-	This class implements a model for estimating the hrf.
+	This class implements a model for estimating the Haemodynamic Response Function (HRF).
 
 	The model employes pre-whitening to account for
 	autocorrelation for the errors. Either 'whitening_mat or
@@ -191,7 +191,7 @@ def cov_beta(self, X):
 class DetectionModel(Model):
 	"""
 	This class implements a model for detecting specific
-	constrasts for a given/known hrf.
+	constrasts for a given/known Haemodynamic Response Function (HRF).
 
 	Unless otherwise specified the parameters and returns are the same
 	as for EstimationModel.
@@ -228,8 +228,8 @@ def design_matrix(self, sequence):
 
 		This method calculates the desing matrix for a given
 		sequence. Colums of the desing matrix are a constant
-		(ones) a linear time course and the convolution of the
-		hrf with the sequence.
+		(ones) a linear time course and the convolution of `hrf`
+		with the sequence.
 
 		Parameters
 		----------
@@ -321,9 +321,9 @@ def get_FIR_basis_set(length):
 
 def get_gamma_hrf(TR, length, a1=6, a2=16, a3=1, a4=1, a5=1, a6=0):
 	"""
-	Return hrf that is difference of two gamma function.
+	Return Haemodynamic Response Function (HRF) that is difference of two gamma function.
 
-	This function returns an hrf array constructed using the following
+	This function returns an HRF array constructed using the following
 	formula\:
 
 	..  math::  h(t) = \\frac{(t-a_6)^{a_1/a_3-1}\\exp(-(t-a_6)/a_3)}{\\Gamma (a_1/a_3)a_3^{a_1/a_3}} - a_5\\frac{(t-a_6)^{a_2/a_4-1}\\exp(-(t-a_6)/a_4)}{\\Gamma (a_2/a_4)a_4^{a_2/a_4}}