test plotting and catch quilt error (#79)

* add plotting tests

* catch error when quilt data have been updated on the server

* typo in requirements_tests

* include geosnap image

geosnap/data/data.py

@@ -9,11 +9,11 @@
 import quilt
 
 import sys
-sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+sys.path.insert(0,
+                os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
 from util import adjust_inflation, convert_gdf
 
-
 try:
     from quilt.data.spatialucr import census
 except ImportError:
@@ -46,13 +46,20 @@ def __dir__(self):
 
 _package_directory = os.path.dirname(os.path.abspath(__file__))
 _cbsa = pd.read_parquet(os.path.join(_package_directory, 'cbsas.parquet'))
-
 dictionary = pd.read_csv(os.path.join(_package_directory, "variables.csv"))
 
-states = census.states()
-counties = census.counties()
-tracts = census.tracts_2010
-metros = convert_gdf(census.msas())
+try:  # if any of these aren't found, the user needs to refresh the quilt data package
+    states = census.states()
+    counties = census.counties()
+    tracts = census.tracts_2010
+    metros = convert_gdf(census.msas())
+except AttributeError:
+    warn(
+        'Quilt data is outdated... rebuilding\n'
+        ' You will need to restart your Python kernel once downloading has completed'
+    )
+    quilt.install("spatialucr/census", force=True)
+    quilt.install("spatialucr/census_cartographic", force=True)
 
 
 def _db_checker(database):
@@ -69,12 +76,11 @@ def _db_checker(database):
 
 
 #: A dict containing tabular data available to geosnap
-db = Bunch(census_90=census.variables_1990(),
-           census_00=census.variables_2000(),
-           ltdb=_db_checker('ltdb'),
-           ncdb=_db_checker('ncdb')
-           )
-
+db = Bunch(
+    census_90=census.variables_1990(),
+    census_00=census.variables_2000(),
+    ltdb=_db_checker('ltdb'),
+    ncdb=_db_checker('ncdb'))
 
 # LTDB importer
 
@@ -135,14 +141,16 @@ def _ltdb_reader(path, file, year, dropcols=None):
 
         df["year"] = year
 
-        inflate_cols = ["mhmval", "mrent", "incpc",
-                        "hinc", "hincw", "hincb", "hinch", "hinca"]
+        inflate_cols = [
+            "mhmval", "mrent", "incpc", "hinc", "hincw", "hincb", "hinch",
+            "hinca"
+        ]
 
-        inflate_available = list(set(df.columns).intersection(set(
-            inflate_cols)))
+        inflate_available = list(
+            set(df.columns).intersection(set(inflate_cols)))
 
         if len(inflate_available):
-        # try:
+            # try:
             df = adjust_inflation(df, inflate_available, year)
         # except KeyError:  # half the dfs don't have these variables
         #     pass
@@ -206,8 +214,8 @@ def _ltdb_reader(path, file, year, dropcols=None):
         fullcount00.iloc[:, 7:], how="left")
     ltdb_2010 = sample10
 
-    df = pd.concat(
-        [ltdb_1970, ltdb_1980, ltdb_1990, ltdb_2000, ltdb_2010], sort=True)
+    df = pd.concat([ltdb_1970, ltdb_1980, ltdb_1990, ltdb_2000, ltdb_2010],
+                   sort=True)
 
     renamer = dict(
         zip(dictionary['ltdb'].tolist(), dictionary['variable'].tolist()))
@@ -218,7 +226,8 @@ def _ltdb_reader(path, file, year, dropcols=None):
     for row in dictionary['formula'].dropna().tolist():
         df.eval(row, inplace=True)
 
-    keeps = df.columns[df.columns.isin(dictionary['variable'].tolist() + ['year'])]
+    keeps = df.columns[df.columns.isin(dictionary['variable'].tolist() +
+                                       ['year'])]
     df = df[keeps]
 
     data_store._set(['ltdb'], df)
@@ -325,7 +334,8 @@ def read_ncdb(filepath):
 
     df = df.round(0)
 
-    keeps = df.columns[df.columns.isin(dictionary['variable'].tolist() + ['year'])]
+    keeps = df.columns[df.columns.isin(dictionary['variable'].tolist() +
+                                       ['year'])]
 
     df = df[keeps]
 
@@ -416,12 +426,13 @@ def __init__(self,
             self.boundary = boundary
             if boundary.crs != self.tracts.crs:
                 if not boundary.crs:
-                    raise('Boundary must have a CRS to ensure valid spatial \
+                    raise ('Boundary must have a CRS to ensure valid spatial \
                     selection')
                 self.tracts = self.tracts.to_crs(boundary.crs)
 
-            self.tracts = self.tracts[self.tracts.representative_point()
-                                      .within(self.boundary.unary_union)]
+            self.tracts = self.tracts[
+                self.tracts.representative_point().within(
+                    self.boundary.unary_union)]
             self.counties = convert_gdf(self.counties[counties.geoid.isin(
                 self.tracts.geoid.str[0:5])])
             self.states = convert_gdf(self.states[states.geoid.isin(
@@ -471,7 +482,9 @@ def __init__(self,
         if source in ['ltdb', 'ncdb']:
             _df = _db_checker(source)
             if len(_df) == 0:
-                raise ValueError("Unable to locate {source} data. Please import the database with the `read_{source}` function".format(source=source))
+                raise ValueError(
+                    "Unable to locate {source} data. Please import the database with the `read_{source}` function"
+                    .format(source=source))
         elif source == "external":
             _df = data
         else:
@@ -481,8 +494,8 @@ def __init__(self,
         if cbsafips:
             if not add_indices:
                 add_indices = []
-            add_indices += _cbsa[_cbsa['CBSA Code'] == cbsafips][
-                'stcofips'].tolist()
+            add_indices += _cbsa[_cbsa['CBSA Code'] ==
+                                 cbsafips]['stcofips'].tolist()
         if add_indices:
             for index in add_indices:
 
@@ -492,8 +505,8 @@ def __init__(self,
                     convert_gdf(counties[counties.geoid.str.startswith(
                         index[0:5])]))
         self.tracts = self.tracts[~self.tracts.geoid.duplicated(keep='first')]
-        self.counties = self.counties[
-            ~self.counties.geoid.duplicated(keep='first')]
+        self.counties = self.counties[~self.counties.geoid.duplicated(
+            keep='first')]
         self.census = _df[_df.index.isin(self.tracts.geoid)]
 
     def plot(self,
@@ -545,8 +558,8 @@ def plot(self,
             else:
                 if self.name:
                     plt.title(
-                        self.name + " " + str(year) + '\n' +
-                        colname, fontsize=20)
+                        self.name + " " + str(year) + '\n' + colname,
+                        fontsize=20)
                 else:
                     plt.title(colname + " " + str(year), fontsize=20)
             plt.axis("off")
@@ -561,10 +574,7 @@ def plot(self,
 
         if plot_counties is True:
             self.counties.plot(
-                edgecolor="#5c5353",
-                linewidth=0.8,
-                facecolor="none",
-                ax=ax)
+                edgecolor="#5c5353", linewidth=0.8, facecolor="none", ax=ax)
 
         return ax
 

geosnap/tests/test_plots.py

@@ -0,0 +1,15 @@
+from context import analyze, data
+import matplotlib
+import pytest
+#matplotlib.use('agg')
+
+from matplotlib.testing.decorators import image_comparison
+import matplotlib.pyplot as plt
+
+@pytest.mark.mpl_image_compare
+def test_plot():
+    fig, ax = plt.subplots()
+    sd = data.Community(name='sd', source='ltdb', cbsafips='41740')
+    sd_clusters = analyze.cluster(sd, columns=['median_household_income', 'p_poverty_rate', 'p_edu_college_greater', 'p_unemployment_rate'], method='kmeans')
+    sd_clusters.plot(column='kmeans', ax=ax)
+    return fig

requirements_tests.txt

@@ -4,3 +4,4 @@ nose-exclude
 coverage
 coveralls
 matplotlib
+pytest-mpl