updates readme, setup, and headers before PyPI upload

README.md

@@ -1,12 +1,17 @@
 [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
+[![PyPI Version](https://badge.fury.io/py/hydroeval.svg)](https://pypi.python.org/pypi/hydroeval)
 
 # HydroEval - An open-source evaluator for stream flow time series in Python
 
-HydroEval is an open-source evaluator of stream flow time series in Python. It is licensed under GNU GPL-3.0 (see [licence file](https://github.com/ThibHlln/hydroeval/blob/master/LICENCE.md) provided). The purpose of this evaluator is to compare observed and simulated hydrographs using one or more objective functions. HydroEval is designed to calculate all objective functions in a vectorised way which makes all computations very efficient using [numpy](https://github.com/numpy/numpy) (and hence C code under the hood).
+HydroEval is an open-source evaluator for stream flow time series in Python. It is licensed under GNU GPL-3.0 (see [licence file](https://github.com/ThibHlln/hydroeval/blob/master/LICENCE.md) provided). The purpose of this evaluator is to compare observed and simulated hydrographs using one or more objective functions. HydroEval is designed to calculate all objective functions in a vectorised way (using [numpy](https://github.com/numpy/numpy), and therefore C code in the background) which makes for very efficient computation of the objective functions.
 
 ## How to Install
 
-The simplest way to install HydroEval is to use pip and a link to the GitHub repository:
+HydroEval is available on PyPI, so you can simply use pip and the name of the package:
+
+    python -m pip install hydroeval
+
+You can also use pip and a link to the GitHub repository directly:
 
 	python -m pip install git+https://github.com/ThibHlln/hydroeval.git
 
@@ -20,7 +25,7 @@ A tutorial in the form of a [Jupyter notebook](https://github.com/ThibHlln/hydro
 
 ## Objective Functions Available
 
-The objective functions currently available in HydroEval that evaluate the fit between observed and simulated stream flow timeseries are as follows:
+The objective functions currently available in HydroEval to evaluate the fit between observed and simulated stream flow time series are as follows:
 * [Nash-Sutcliffe Efficiency](https://doi.org/10.1016/0022-1694(70)90255-6) (`nse`)
 * [Original Kling-Gupta Efficiency](https://doi.org/10.1016/j.jhydrol.2009.08.003) (`kge`) and its three components (r, α, β)
 * [Modified Kling-Gupta Efficiency](https://doi.org/10.1016/j.jhydrol.2012.01.011) (`kgeprime`) and its three components (r, γ, β)
@@ -34,7 +39,7 @@ Moreover, KGE and NSE can be calculated in a bounded version following [Mathevet
 * Bounded Original Kling-Gupta Efficiency (`kge_c2m`)
 * Bounded Modified Kling-Gupta Efficiency (`kgeprime_c2m`)
 
-Finally, any of the objective functions can take an optimal argument `transform`. This argument allows to apply a transformation on the observed and simulated stream flow timeseries prior the calculation of the objective function. The possible transformations are as follows:
+Finally, any of the objective functions can take an optimal argument `transform`. This argument allows to apply a transformation on both the observed and the simulated stream flow time series prior the calculation of the objective function. The possible transformations are as follows:
 * Inverted flows (using `transform='inv'`)
 * Square Root-transformed flows (using `transform='sqrt'`)
 * Natural Logarithm-transformed flows (using `transform='log'`)
@@ -45,7 +50,7 @@ HydroEval requires the popular Python package `numpy` to be installed on the Pyt
 
 ## Version History
 
-* 0.0.1 [14 Oct 2018]: First version of HydroEval
+* 0.0.1 [26 Oct 2018]: First version of HydroEval
 
 ## Acknowledgment
 

hydroeval/hydroeval.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-# This file is part of HydroEval: An Evaluator for Hydrological Time Series
+# This file is part of HydroEval: An Evaluator for Stream Flow Time Series
 # Copyright (C) 2018  Thibault Hallouin (1)
 #
 # (1) Dooge Centre for Water Resources Research, University College Dublin, Ireland

hydroeval/objective_functions.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-# This file is part of HydroEval: An Evaluator for Hydrological Time Series
+# This file is part of HydroEval: An Evaluator for Stream Flow Time Series
 # Copyright (C) 2018  Thibault Hallouin (1)
 #
 # (1) Dooge Centre for Water Resources Research, University College Dublin, Ireland
@@ -54,7 +54,7 @@ def kge(simulation_s, evaluation):
     return np.vstack((kge_, r, alpha[:, 0], beta[:, 0])).T
 
 
-# Modified kling-Gupta Efficiency (kling et al. 2012 - https://doi.org/10.1016/j.jhydrol.2012.01.011)
+# Modified Kling-Gupta Efficiency (Kling et al. 2012 - https://doi.org/10.1016/j.jhydrol.2012.01.011)
 def kgeprime(simulation_s, evaluation):
     # calculate correlation coefficient
     sim_mean = np.reshape(np.mean(simulation_s, axis=1), (simulation_s.shape[0], 1))

setup.py

@@ -8,7 +8,7 @@
 
     version='0.0.1',
 
-    description='HydroEval: An Evaluator for Hydrological Time Series',
+    description='HydroEval: An Evaluator for Stream Flow Time Series',
 
     url='https://github.com/ThibHlln/hydroeval',