Merge pull request #254 from YeoLab/fix_docs

Fix docs

.travis.yml

@@ -31,6 +31,7 @@ install:
 before_script:
   - git config --global user.email "olga.botvinnik@gmail.com"
   - git config --global user.name "olgabot"
+  - git config --global push.default simple
   - export REPO_URL_GITHUB="https://$GH_TOKEN@github.com/$GH_REPO.git"
   - . ./.travis/setup.sh # make any change needed for setup.sh
   - echo $DEPLOY_HTML_DIR
@@ -47,7 +48,6 @@ after_script:
   - sudo apt-get install pandoc
   - pip install sphinx numpydoc sphinx_bootstrap_theme runipy
   - sudo pip install -r doc/requirements.txt --use-mirrors
-  - RELEASE=release
   - MASTER=master
   - if [[ $TRAVIS_BRANCH == "v*.*.*" ]] ; then export DEPLOY_HTML_DIR=docs ; fi
   - if [[ $TRAVIS_BRANCH == "$MASTER" ]] ; then export DEPLOY_HTML_DIR=docs-dev ; fi

examples/plot_classifier.py

@@ -8,5 +8,5 @@
 
 """
 import flotilla
-study = flotilla.embark(flotilla._shalek2013)
-study.plot_classifier('phenotype: Immature BDMC')
+study = flotilla.embark(flotilla._brainspan)
+study.plot_classifier('structure_name: cerebellar cortex')

flotilla/__init__.py

@@ -22,6 +22,8 @@
 # 250 cells, ensembl and miso ids on index, need renaming, lots of celltypes
 _test_data = 'https://raw.githubusercontent.com/YeoLab/flotilla_test_data/' \
              'master/datapackage.json'
+_brainspan = 'https://s3-us-west-2.amazonaws.com/flotilla/' \
+             'brainspan_batch_corrected_for_amazon_s3/datapackage.json'
 
 
 def embark(study_name, load_species_data=True):

flotilla/data_model/study.py

@@ -940,7 +940,7 @@ def plot_classifier(self, trait, sample_subset=None,
         try:
             trait_data = self.metadata.data[trait]
         except KeyError:
-            trait_ids = self.sample_subset_to_sample_ids(sample_subset)
+            trait_ids = self.sample_subset_to_sample_ids(trait)
             trait_data = self.metadata.data.index.isin(trait_ids)
 
         all_true = np.all(trait_data)

flotilla/visualize/network.py

@@ -106,7 +106,7 @@ def draw_graph(self,
         try:
             feature_id = self.DataModel.maybe_renamed_to_feature_id(
                 feature_of_interest)[0]
-        except (ValueError, KeyError):
+        except (ValueError, KeyError, IndexError):
             feature_id = ''
 
         if featurewise:

flotilla/visualize/predict.py

@@ -53,9 +53,7 @@ def do_pca(self, **plotting_kwargs):
         assert self.has_been_fit
         assert self.has_been_scored
 
-        ax = plt.gca() if 'ax' not in plotting_kwargs \
-            else plotting_kwargs['ax']
-        # del plotting_kwargs['ax']
+        ax = plotting_kwargs.pop('ax', plt.gca())
         local_plotting_kwargs = self._reducer_plotting_args
         local_plotting_kwargs.update(plotting_kwargs)
         pca = self.pca()