Merge pull request #9 from jmenglund/develop

Develop

Author: jmenglund

.gitignore

@@ -16,6 +16,7 @@ lib64/
 parts/
 sdist/
 var/
+tmp/
 *.egg-info/
 .installed.cfg
 *.egg

.travis.yml

@@ -2,19 +2,18 @@ language: python
 
 python:
     - '2.7'
-    - '3.3'
-    - '3.4'
     - '3.5'
+    - '3.6'
 
 # whitelist
 branches:
     only:
         - master
 
 script:
-    - py.test --pep8
+    - py.test pandascharm.py --pep8
     - coverage run -m py.test
-    - coverage report --include test_*.py
+    - coverage report --omit test_*.py
 
 after_success:
   - codecov

CHANGELOG.rst

@@ -1,6 +1,25 @@
 Changelog
 =========
 
+0.1.3
+-----
+
+* Fixed bug in function ``frame_as_categorical`` that caused an error when
+  trying to change the dtype to "category".
+* Fixed problems with reporting test coverage.
+* Removed Travis-CI testing for Python 3.3 and 3.4.
+* Added Travis-CI testing for Python 3.6.
+* List of included categories are now ignored in matrix conversions involving
+  categorical data.
+* ``pytest-cov`` removed from *requirements.txt*.
+* Updates to *setup.py*.
+* Updates to *README.rst*.
+* Updates to *release-checklist.rst*.
+
+Release date: 2017-08-25
+
+`View commits <https://github.com/jmenglund/pandas-charm/compare/v0.1.2...v0.1.3>`_
+
 0.1.2
 -----
 

README.rst

@@ -15,14 +15,14 @@ following objects:
 * BioPython MultipleSeqAlignment <-> pandas DataFrame
 * DendroPy CharacterMatrix <-> pandas DataFrame
 
-The code has been tested with Python 2.7, 3.3, 3.4 and 3.5.
+The code has been tested with Python 2.7, 3.5 and 3.6.
 
 Source repository: `<https://github.com/jmenglund/pandas-charm>`_
 
 ------------------------------------------
 
 .. contents:: Table of contents
-   :backlinks: top
+   :backlinks: none
    :local:
 
 
@@ -56,13 +56,15 @@ Python path. See for example the environment management system
 Running tests
 -------------
 
-Testing is carried out with `pytest <http://pytest.org>`_. Here is an 
-example on how to run the test suite and generating a coverage report:
+Testing is carried out with `pytest <http://pytest.org>`_. The following
+example shows how you can run the test suite and generate a coverage report:
 
 .. code-block::
 
-    $ pip install pytest pytest-cov pytest-pep8 dendropy biopython 
-    $ py.test -v --cov-report term-missing --cov pandascharm.py --pep8
+    $ pip install pytest pytest-pep8 dendropy biopython 
+    $ py.test -v --pep8
+    $ coverage run -m py.test
+    $ coverage report --include pandascharm.py
 
 
 Usage
@@ -225,8 +227,8 @@ cite the Zenodo DOI of this project:
 
 |DOI-URI|
 
-You can select a citation style from the dropdown menu in the 
-"Cite as" section on the Zenodo page.
+Choose your preferred citation style in the "Cite as" section on the Zenodo
+page.
 
 
 Author

pandascharm.py

@@ -4,9 +4,9 @@
 import pandas
 
 
-__authors__ = 'Markus Englund'
+__author__ = 'Markus Englund'
 __license__ = 'MIT'
-__version__ = '0.1.2'
+__version__ = '0.1.3'
 
 
 def frame_as_categorical(frame, include_categories=None):

release-checklist.rst

@@ -9,11 +9,13 @@ Things to remember when making a new release of pandas-charm.
 
 #.  Make desirable changes to the code.
 
-#.  Run tests with coverage report and PEP8 check:
+#.  Run tests with PEP8 check and report coverage:
 
     .. code-block::
 
-        $ py.test -v --cov-report term-missing --cov pandascharm.py --pep8
+        $ py.test -v --pep8 pandascharm.py
+        $ coverage run -m py.test
+        $ coverage report --include pandascharm.py -m
 
 #.  Update the documentation in *README.rst*.
 

requirements.txt

@@ -2,6 +2,5 @@ pandas>=0.16
 pytest>=2.8
 codecov
 pytest-pep8
-pytest-cov
 DendroPy>=4.0
 BioPython

setup.py

@@ -8,7 +8,7 @@
 
 setup(
     name='pandas-charm',
-    version='0.1.2',
+    version='0.1.3',
     description=(
         'A small Python library for getting character matrices '
         '(alignments) into and out of pandas'),
@@ -18,7 +18,7 @@
     py_modules=['pandascharm'],
     install_requires=['pandas>=0.16', 'numpy'],
     extras_require={'testing': [
-        'coverage', 'pytest', 'pytest-cov', 'biopython', 'dendropy']},
+        'coverage', 'pytest', 'biopython', 'dendropy']},
     author='Markus Englund',
     author_email='[email protected]',
     url='https://github.com/jmenglund/pandas-charm',
@@ -32,9 +32,8 @@
         'Programming Language :: Python :: 2',
         'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.3',
-        'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
     ],
     keywords=['alignment', 'BioPython', 'DendroPy', 'pandas'],
 )

test_pandascharm.py

@@ -75,32 +75,32 @@ def test_conversion(self):
 class TestCharmatrixConversion():
 
     dna_charmatrix_string = '3 5\nt1  TCCAA\nt2  TGCAA\nt3  TG-AA\n'
-    dna_charmatrix = dendropy.DnaCharacterMatrix.get_from_string(
-        dna_charmatrix_string, schema='phylip')
+    dna_charmatrix = dendropy.DnaCharacterMatrix.get(
+        data=dna_charmatrix_string, schema='phylip')
     dna_frame = pandas.DataFrame({
         't1': ['T', 'C', 'C', 'A', 'A'],
         't2': ['T', 'G', 'C', 'A', 'A'],
         't3': ['T', 'G', '-', 'A', 'A']}, dtype='category')
 
     rna_charmatrix_string = '3 5\nt1  UCCAA\nt2  UGCAA\nt3  UG-AA\n'
-    rna_charmatrix = dendropy.RnaCharacterMatrix.get_from_string(
-        rna_charmatrix_string, schema='phylip')
+    rna_charmatrix = dendropy.RnaCharacterMatrix.get(
+        data=rna_charmatrix_string, schema='phylip')
     rna_frame = pandas.DataFrame({
         't1': ['U', 'C', 'C', 'A', 'A'],
         't2': ['U', 'G', 'C', 'A', 'A'],
         't3': ['U', 'G', '-', 'A', 'A']}, dtype='category')
 
     protein_charmatrix_string = '3 5\nt1  VKYPN\nt2  VLYPN\nt3  VL-PN\n'
-    protein_charmatrix = dendropy.ProteinCharacterMatrix.get_from_string(
-        protein_charmatrix_string, schema='phylip')
+    protein_charmatrix = dendropy.ProteinCharacterMatrix.get(
+        data=protein_charmatrix_string, schema='phylip')
     protein_frame = pandas.DataFrame({
         't1': ['V', 'K', 'Y', 'P', 'N'],
         't2': ['V', 'L', 'Y', 'P', 'N'],
         't3': ['V', 'L', '-', 'P', 'N']}, dtype='category')
 
     standard_charmatrix_string = '3 5\nt1  01010\nt2  02010\nt3  02-10\n'
-    standard_charmatrix = dendropy.StandardCharacterMatrix.get_from_string(
-        standard_charmatrix_string, schema='phylip')
+    standard_charmatrix = dendropy.StandardCharacterMatrix.get(
+        data=standard_charmatrix_string, schema='phylip')
     standard_frame = pandas.DataFrame({
         't1': ['0', '1', '0', '1', '0'],
         't2': ['0', '2', '0', '1', '0'],