Add local var for chart.to_dict

Author: kdorr

mplaltair/parse_chart.py

@@ -8,7 +8,9 @@ class ChannelMetadata(object):
     Attributes
     ----------
     name : str
+        The name of the encoding channel
     data : np.array
+        The data linked to the channel (temporal data is converted)
     axis : dict
     bin : boolean, None
     field : str
@@ -20,16 +22,17 @@ class ChannelMetadata(object):
     type : str
     """
     def __init__(self, channel, alt_chart):
-        self.name = channel  # Not from Altair
-        self.data = self._locate_channel_data(alt_chart)  # Not from Altair
-        self.axis = alt_chart.to_dict()['encoding'][self.name].get('axis', {})
-        self.bin = alt_chart.to_dict()['encoding'][self.name].get('bin', None)
-        self.field = alt_chart.to_dict()['encoding'][self.name].get('field', None)
-        self.scale = alt_chart.to_dict()['encoding'][self.name].get('scale', {})
-        self.sort = alt_chart.to_dict()['encoding'][self.name].get('sort', None)
-        self.stack = alt_chart.to_dict()['encoding'][self.name].get('stack', None)
-        self.timeUnit = alt_chart.to_dict()['encoding'][self.name].get('aggregate', None)
-        self.title = alt_chart.to_dict()['encoding'][self.name].get('title', None)
+        chart_dict = alt_chart.to_dict()
+        self.name = channel
+        self.data = self._locate_channel_data(alt_chart)
+        self.axis = chart_dict['encoding'][self.name].get('axis', {})
+        self.bin = chart_dict['encoding'][self.name].get('bin', None)
+        self.field = chart_dict['encoding'][self.name].get('field', None)
+        self.scale = chart_dict['encoding'][self.name].get('scale', {})
+        self.sort = chart_dict['encoding'][self.name].get('sort', None)
+        self.stack = chart_dict['encoding'][self.name].get('stack', None)
+        self.timeUnit = chart_dict['encoding'][self.name].get('aggregate', None)
+        self.title = chart_dict['encoding'][self.name].get('title', None)
         self.type = self._locate_channel_dtype(alt_chart)
 
         if self.type == 'temporal':
@@ -67,6 +70,7 @@ def _locate_channel_data(self, alt_chart):
 
     def _locate_channel_dtype(self, alt_chart):
         """Locates dtype used for each channel
+
         Parameters
         ----------
         alt_chart : altair.Chart

mplaltair/tests/test_data.py

@@ -5,8 +5,6 @@
 import pytest
 from vega_datasets import data
 
-from mplaltair._data import _normalize_data
-from mplaltair._exceptions import ValidationError
 
 df = pd.DataFrame({
     "a": [1, 2, 3, 4, 5], "b": [1.1, 2.2, 3.3, 4.4, 5.5], "c": [1, 2.2, 3, 4.4, 5],
@@ -20,12 +18,12 @@
 
 def test_data_list():
     chart = alt.Chart(pd.DataFrame({'a': [1], 'b': [2], 'c': [3]})).mark_point()
-    _normalize_data(chart)
+    _data._normalize_data(chart)
     assert type(chart.data) == pd.DataFrame
 
 def test_data_url():
     chart = alt.Chart(data.cars.url).mark_point()
-    _normalize_data(chart)
+    _data._normalize_data(chart)
     assert type(chart.data) == pd.DataFrame
 
 # test date conversion:

mplaltair/tests/test_parse_chart.py

@@ -41,16 +41,6 @@ def test_data_shorthand_quantitative(column):
         else:
             assert list(data) == list(df[column].values)
 
-# TODO: figure out how to test
-# def test_data_value_quantitative():
-#     chart = alt.Chart(df).mark_point().encode(opacity=alt.value(0.5))
-#     try:
-#         chart = parse_chart.ChartMetadata(chart)
-#     except NotImplementedError:
-#         for channel in chart.encoding:
-#             data = chart.encoding[channel].data
-#             assert list(data) == 0.5
-
 
 @pytest.mark.parametrize("column", ['a', 'b', 'c'])
 def test_data_aggregate_quantitative_fail(column):