Merge pull request #24 from jGaboardi/dual_testing

addressing pysal/pysal#1145

.travis.yml

@@ -20,7 +20,7 @@ matrix:
         env: PYSAL_PYPI=false
 
 before_install:
-  - wget https://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
+  - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
   - chmod +x miniconda.sh
   - ./miniconda.sh -b -p ./miniconda
   - export PATH=`pwd`/miniconda/bin:$PATH
@@ -31,21 +31,24 @@ before_install:
 
 install:
   - conda install --yes pip
-  - conda install --yes --file requirements.txt;
-  - pip install https://github.com/pysal/splot/archive/master.zip
+  - conda install --yes --file requirements.txt
   - pip install -r requirements_tests.txt
   - if "$PYSAL_PYPI"; then
         echo 'testing pypi libpysal spreg spglm';
     else
         echo 'testing git libpysal spreg spglm';
-        pip install https://github.com/pysal/libpysal/archive/master.zip;
-        pip install https://github.com/pysal/spreg/archive/master.zip;
-        pip install https://github.com/pysal/spglm/archive/master.zip; 
+        git clone https://github.com/pysal/libpysal.git;
+        cd libpysal; pip install .; cd ../;
+        git clone https://github.com/pysal/spreg.git;
+        cd spreg; pip install .; cd ../;
+        git clone https://github.com/pysal/spglm.git;
+        cd spglm; pip install .; cd ../;
    fi;
 
 script:
   - python setup.py sdist >/dev/null
   - python setup.py install
+  - python -c 'import libpysal; libpysal.examples.load_example("nyc_bikes")'
   - nosetests --verbose --with-doctest --with-coverage --cover-package=spint;
 
 notifications:

spint/gravity.py

@@ -866,7 +866,8 @@ class Attraction(BaseGravity):
     >>> import numpy as np
     >>> import libpysal
     >>> from spint.gravity import Attraction
-    >>> db = libpysal.io.open(libpysal.examples.get_path('nyc_bikes_ct.csv'))
+    >>> nyc_bikes = libpysal.examples.load_example('nyc_bikes')
+    >>> db = libpysal.io.open(nyc_bikes.get_path('nyc_bikes_ct.csv'))
     >>> cost = np.array(db.by_col('tripduration')).reshape((-1,1))
     >>> flows = np.array(db.by_col('count')).reshape((-1,1))
     >>> d = np.array(db.by_col('d_tract')).reshape((-1,1))