Preparing release 0.4

CHANGES.rst

@@ -1,4 +1,4 @@
-0.4 (unreleased)
+0.4 (2016-08-11)
 ----------------
 
 - All models now support an optional ``seed`` keyword argument, allowing for deterministic Monte Carlo realizations of models. As a result of this feature, it is now mandatory that all user-defined models obey a new constraint. Any function appearing in the ``mock_generation_calling_sequence`` must now use the kwargs Python syntax to catch any additional inputs passed to these functions by the MockFactory.

README.md

@@ -1,38 +1,38 @@
 # Halotools
 
-Halotools is a specialized python package for building and testing models of the galaxy-halo connection, and analyzing catalogs of dark matter halos. 
+Halotools is a specialized python package for building and testing models of the galaxy-halo connection, and analyzing catalogs of dark matter halos.
 The core feature of Halotools is a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. Functionality of the package includes:
 
 * Fast generation of synthetic galaxy populations using HODs, abundance matching, and related methods
-* Efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics 
+* Efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics
 * A modular, object-oriented framework for designing your own galaxy evolution model
 * End-to-end support for downloading publicly-available halo catalogs and reducing them to fast-loading hdf5 files
 
-The code is publicly available at https://github.com/astropy/halotools. 
+The code is publicly available at https://github.com/astropy/halotools.
 
 ---
 
 ## Documentation
 
-The latest build of the documentation can be found at http://halotools.readthedocs.io. The documentation includes installation instructions, quickstart guides and step-by-step tutorials. The *Basic features* section below gives an overview of the primary functionality of the package. 
+The latest build of the documentation can be found at http://halotools.readthedocs.io. The documentation includes installation instructions, quickstart guides and step-by-step tutorials. The *Basic features* section below gives an overview of the primary functionality of the package.
 
 ---
 
-## Installation 
+## Installation
 
-You can find detailed installation instructions 
-in the *Package Installation* section of http://halotools.readthedocs.io. After installing the package, you should navigate to the *Quickstart Guides and Tutorials* section and follow the *Getting started with Halotools* 10-minute tutorial. This will get you set up with the default halo catalog so that you can quickly get started with creating mock galaxy populations. 
+You can find detailed installation instructions
+in the *Package Installation* section of http://halotools.readthedocs.io. After installing the package, you should navigate to the *Quickstart Guides and Tutorials* section and follow the *Getting started with Halotools* 10-minute tutorial. This will get you set up with the default halo catalog so that you can quickly get started with creating mock galaxy populations.
 
 ---
 
 
 ## Basic features
 
-Once you have installed the code and downloaded the default halo catalog (see the Getting Started guide in the documentation), you can use Halotools models to populate mock galaxy populations. 
+Once you have installed the code and downloaded the default halo catalog (see the Getting Started guide in the documentation), you can use Halotools models to populate mock galaxy populations.
 
-``` 
-# Select a model 
-from halotools.empirical_models import PrebuiltHodModelFactory 
+```
+# Select a model
+from halotools.empirical_models import PrebuiltHodModelFactory
 model = PrebuiltHodModelFactory('zheng07')
 
 # Select a halo catlaog
@@ -42,11 +42,11 @@ halocat = CachedHaloCatalog(simname='bolshoi', redshift=0, halo_finder='rockstar
 # populate the catalog with the model
 model.populate_mock(halocat)
 ```
-After calling *populate_mock*, your model will have a *mock* attribute storing your synthetic galaxy population. All Halotools models have a populate_mock method that works in this way, regardless of the features of the model. There are no restrictions on the simulation or halo-finder with which you can use the populate_mock method. 
+After calling *populate_mock*, your model will have a *mock* attribute storing your synthetic galaxy population. All Halotools models have a populate_mock method that works in this way, regardless of the features of the model. There are no restrictions on the simulation or halo-finder with which you can use the populate_mock method.
 
 ### Creating alternate mocks
 
-All Halotools models have a *param_dict* that controls the behavior of the model. By changing the parameters in this dictionary, you can create alternative versions of your mock universe by re-populating the halo catalog as follows. 
+All Halotools models have a *param_dict* that controls the behavior of the model. By changing the parameters in this dictionary, you can create alternative versions of your mock universe by re-populating the halo catalog as follows.
 
 ```
 model.param_dict['logMmin'] = 12.1
@@ -57,19 +57,19 @@ Note how much faster the call to *mock.populate* is relative to *model.populate_
 
 ### Modeling the galaxy-halo connection
 
-The pre-built model factories give you a wide range of models to choose from, each based on an existing publication. Alternatively, you can use the Halotools factories to design a customized model of your own creation, such as models for stellar mass, color, size, morphology, or any property of your choosing. The modular design of the *empirical_models* sub-package allows you to mix-and-match an arbitrary number or kind of features to create your own composite model of the full galaxy population. You can choose from component models provided by Halotools, components exclusively written by you, or anywhere in between. Whatever science features you choose, any Halotools model can populate any Halotools-formatted halo catalog with the same syntax shown above. 
+The pre-built model factories give you a wide range of models to choose from, each based on an existing publication. Alternatively, you can use the Halotools factories to design a customized model of your own creation, such as models for stellar mass, color, size, morphology, or any property of your choosing. The modular design of the *empirical_models* sub-package allows you to mix-and-match an arbitrary number or kind of features to create your own composite model of the full galaxy population. You can choose from component models provided by Halotools, components exclusively written by you, or anywhere in between. Whatever science features you choose, any Halotools model can populate any Halotools-formatted halo catalog with the same syntax shown above.
 
 ### Making mock observations
 
-The *mock_observables* sub-package contains a wide variety of optimized functions that you can use to study your mock galaxy population. For example, you can calculate projected clustering via the *wp* function, identify friends-of-friends groups with *FoFGroups*, or compute galaxy-galaxy lensing with *delta_sigma*. 
+The *mock_observables* sub-package contains a wide variety of optimized functions that you can use to study your mock galaxy population. For example, you can calculate projected clustering via the *wp* function, identify friends-of-friends groups with *FoFGroups*, or compute galaxy-galaxy lensing with *delta_sigma*.
 
 ```
 from halotools.mock_observables import wp
 from halotools.mock_observables import FoFGroups
 from halotools.mock_observables import delta_sigma
 ```
 
-There are many other functions provided by the *mock_observables* package, such as RSD multipoles, pairwise velocities, generalized marked correlation functions, customizable isolation criteria, void statistics, and more. 
+There are many other functions provided by the *mock_observables* package, such as RSD multipoles, pairwise velocities, generalized marked correlation functions, customizable isolation criteria, void statistics, and more.
 
 ### Managing simulation data
 
@@ -79,15 +79,15 @@ Halotools provides end-to-end support for downloading simulation data, reducing
 from halotools import sim_manager
 ```
 
-The *sim_manager* package comes with a memory-efficient *TabularAsciiReader* designed to handle the very large file sizes that are typical of contemporary cosmological simulations. There are 20 halo catalogs available for download from the Halotools website using the *halotools/scripts/download_additional_halocat.py* script, including simulations run with different volumes, resolutions and cosmologies, and also catalogs identified using different halo-finders and at different redshift. Any simulation you store in cache can be loaded into memory in the same way, and all such catalogs have a *halo_table* attribute storing the actual data. 
+The *sim_manager* package comes with a memory-efficient *TabularAsciiReader* designed to handle the very large file sizes that are typical of contemporary cosmological simulations. There are 20 halo catalogs available for download from the Halotools website using the *halotools/scripts/download_additional_halocat.py* script, including simulations run with different volumes, resolutions and cosmologies, and also catalogs identified using different halo-finders and at different redshift. Any simulation you store in cache can be loaded into memory in the same way, and all such catalogs have a *halo_table* attribute storing the actual data.
 
 ```
 from halotools.sim_manager import CachedHaloCatalog
 halocat = CachedHaloCatalog(simname = any_simname, redshift = any_redshift, halo_finder = any_halo_finder)
 print(halocat.halo_table[0:10])
 ```
 
-You are not limited to use the halo catalogs pre-processed by Halotools. The *UserSuppliedHaloCatalog* allows you to use your own simulation data and transform it into a Halotools-formatted catalog in a simple way. 
+You are not limited to use the halo catalogs pre-processed by Halotools. The *UserSuppliedHaloCatalog* allows you to use your own simulation data and transform it into a Halotools-formatted catalog in a simple way.
 
 ```
 from halotools.sim_manager import UserSuppliedHaloCatalog
@@ -102,28 +102,28 @@ Although the *sim_manager* provides an object-oriented framework for creating a
 
 [![Coverage Status](https://coveralls.io/repos/astropy/halotools/badge.svg?branch=master&service=github)](https://coveralls.io/github/astropy/halotools?branch=master)
 
-Halotools is a fully open-source package with contributing scientists spread across many universities. The latest stable release of the package, v0.3, is now available on pip. You can also install the development version of the package by cloning the master branch on GitHub and locally building the source code, as described in the installation instructions. 
+Halotools is a fully open-source package with contributing scientists spread across many universities. The latest stable release of the package, v0.4, is now available on pip. You can also install the development version of the package by cloning the master branch on GitHub and locally building the source code, as described in the installation instructions.
 
 ---
 
 ## Asking questions and staying up-to-date
 
-If you would like to receive notifications of new code releases, sign up for the google group 
+If you would like to receive notifications of new code releases, sign up for the google group
 
 https://groups.google.com/forum/#!forum/halotools
 
-The google group also serves as a public forum for asking questions about the code. You are also welcome to contact Andrew Hearin directly by email or by tagging @aphearin on GitHub. 
+The google group also serves as a public forum for asking questions about the code. You are also welcome to contact Andrew Hearin directly by email or by tagging @aphearin on GitHub.
 
 ---
 
 ## Citing Halotools
 
-If you use Halotools modules to support your science publication, we ask that you cite the code-release paper, http://arxiv.org/abs/1606.04106 paper. Depending on what modules you use, other citations may also be appropriate; see the *License and Citation Information* section of http://halotools.readthedocs.io for further information about how to properly cite Halotools and its supporting science and software. 
+If you use Halotools modules to support your science publication, we ask that you cite the code-release paper, http://arxiv.org/abs/1606.04106 paper. Depending on what modules you use, other citations may also be appropriate; see the *License and Citation Information* section of http://halotools.readthedocs.io for further information about how to properly cite Halotools and its supporting science and software.
 
 
 ---
 
-## License 
+## License
 
 Halotools is licensed under a 3-clause BSD style license - see the licenses/LICENSE.rst file.
 

setup.py

@@ -55,7 +55,7 @@
 builtins._ASTROPY_PACKAGE_NAME_ = PACKAGENAME
 
 # VERSION should be PEP386 compatible (http://www.python.org/dev/peps/pep-0386)
-VERSION = '0.4.dev'
+VERSION = '0.4'
 
 # Indicates if this version is a release version
 RELEASE = 'dev' not in VERSION