Use ArrayOrNone

chaco/axis.py

@@ -11,7 +11,7 @@
 from enable.api import ColorTrait, LineStyle
 from kiva.trait_defs.kiva_font_trait import KivaFont
 from traits.api import Any, Float, Int, Str, Trait, Unicode, \
-     Bool, Event, List, Array, Instance, Enum, Callable
+     Bool, Event, List, Array, Instance, Enum, Callable, ArrayOrNone
 
 # Local relative imports
 from ticks import AbstractTickGenerator, DefaultTickGenerator, MinorTickGenerator
@@ -148,9 +148,9 @@ class PlotAxis(AbstractOverlay):
     # Cached position calculations
 
     _tick_list = List  # These are caches of their respective positions
-    _tick_positions = Any #List
-    _tick_label_list = Any
-    _tick_label_positions = Any
+    _tick_positions = ArrayOrNone()
+    _tick_label_list = ArrayOrNone()
+    _tick_label_positions = ArrayOrNone()
     _tick_label_bounding_boxes = List
     _major_axis_size = Float
     _minor_axis_size = Float

chaco/base.py

@@ -10,23 +10,23 @@
                    nonzero, pi, searchsorted, seterr, sin, int8)
 
 # Enthought library imports
-from traits.api import CArray, Enum, Trait
+from traits.api import Enum, ArrayOrNone
 
 delta = {'ascending': 1, 'descending': -1, 'flat': 0}
 
 # Dimensions
 
 # A single array of numbers.
-NumericalSequenceTrait = Trait(None, None, CArray(value=empty(0)))
+NumericalSequenceTrait = ArrayOrNone()
 
 # A sequence of pairs of numbers, i.e., an Nx2 array.
-PointTrait = Trait(None, None, CArray(value=empty(0)))
+PointTrait = ArrayOrNone(shape=(None, 2))
 
-# An NxM array of numbers.
-ImageTrait = Trait(None, None, CArray(value=empty(0)))
+# An NxM array of numbers or NxMxRGB(A) array of colors.
+ImageTrait = ArrayOrNone()
 
 # An 3D array of numbers of shape (Nx, Ny, Nz)
-CubeTrait = Trait(None, None, CArray(value=empty(0)))
+CubeTrait = ArrayOrNone(shape=(None, None, None))
 
 
 # This enumeration lists the fundamental mathematical coordinate types that

chaco/data_label.py

@@ -6,7 +6,7 @@
 from numpy.linalg import norm
 
 # Enthought library imports
-from traits.api import Any, Array, Bool, Enum, Float, Int, List, \
+from traits.api import Any, ArrayOrNone, Bool, Enum, Float, Int, List, \
      Str, Tuple, Trait, on_trait_change, Property
 from enable.api import ColorTrait, MarkerTrait
 
@@ -163,7 +163,7 @@ class DataLabel(ToolTip):
     custom_symbol = Any
 
     # The point in data space where this label should anchor itself.
-    data_point = Trait(None, None, Tuple, List, Array)
+    data_point = ArrayOrNone()
 
     # The location of the data label relative to the data point.
     label_position = LabelPositionTrait

chaco/label_axis.py

@@ -5,7 +5,7 @@
 from numpy import array, float64, inf, searchsorted, take, unique
 
 # Enthought library imports
-from traits.api import Any, Str, List, Float
+from traits.api import ArrayOrNone, Str, List, Float
 
 # Local, relative imports
 from axis import PlotAxis
@@ -23,7 +23,7 @@ class LabelAxis(PlotAxis):
     label_rotation = Float(0)
 
     # List of indices of ticks
-    positions = Any  # List(Float), Array
+    positions = ArrayOrNone()
 
     def _compute_tick_positions(self, gc, component=None):
         """ Calculates the positions for the tick marks.

chaco/legend.py

@@ -9,8 +9,8 @@
 from enable.api import black_color_trait, white_color_trait
 from enable.font_metrics_provider import font_metrics_provider
 from kiva.trait_defs.kiva_font_trait import KivaFont
-from traits.api import Any, Dict, Enum, Bool, HasTraits, Int, \
-                                 Instance, List, CList, Float, Str
+from traits.api import ArrayOrNone, Bool, CList, Dict, Enum, Float, \
+    HasTraits, Instance, Int, List, Str
 
 # Local relative imports
 from abstract_overlay import AbstractOverlay
@@ -161,7 +161,7 @@ class Legend(AbstractOverlay):
     _cached_labels = List
 
     # A cached array of label sizes.
-    _cached_label_sizes = Any
+    _cached_label_sizes = ArrayOrNone()
 
     # A cached list of label names.
     _cached_label_names = CList
@@ -173,7 +173,7 @@ class Legend(AbstractOverlay):
     _cached_visible_plots = CList
 
     # A cached array of label positions relative to the legend's origin
-    _cached_label_positions = Any
+    _cached_label_positions = ArrayOrNone()
 
     def is_in(self, x, y):
         """ overloads from parent class because legend alignment

chaco/log_mapper.py

@@ -3,6 +3,7 @@
 # Major library imports
 from numpy import array, isnan, log, log10, exp, zeros, sometrue,\
     floor, ceil, ndarray
+import numpy as np
 
 # Enthought library imports
 from traits.api import Bool, Float
@@ -54,7 +55,8 @@ def map_screen(self, data_array):
             intermediate = data_array*0.0
         else:
             try:
-                mask = (data_array <= LOG_MINIMUM) | isnan(data_array)
+                with np.errstate(invalid='ignore'):
+                    mask = (data_array <= LOG_MINIMUM) | isnan(data_array)
                 if sometrue(mask):
                     data_array = array(data_array, copy=True, ndmin=1)
                     data_array[mask] = self.fill_value

chaco/multi_array_data_source.py

@@ -1,5 +1,7 @@
 """ Defines the MultiArrayDataSource class.
 """
+import warnings
+
 # Major package imports
 from numpy import nanmax, nanmin, array, shape, ones, bool, newaxis, nan_to_num
 
@@ -179,8 +181,11 @@ def get_bounds(self, value = None, index = None):
                 mini = nanmin(self._data[::, index])
         else:
             # value is None and index is None:
-            maxi = nanmax(self._data)
-            mini = nanmin(self._data)
+            with warnings.catch_warnings():
+                warnings.filterwarnings(
+                    'ignore', "All-NaN (slice|axis) encountered", RuntimeWarning)
+                maxi = nanmax(self._data)
+                mini = nanmin(self._data)
 
         return (mini, maxi)
 

chaco/polygon_plot.py

@@ -9,7 +9,7 @@
 # Enthought library imports.
 from enable.api import LineStyle, black_color_trait, \
                                   transparent_color_trait
-from kiva.agg import points_in_polygon
+from kiva.api import points_in_polygon
 from traits.api import Enum, Float, Tuple, Property, cached_property, \
                         on_trait_change
 

chaco/scatterplot.py

@@ -11,10 +11,10 @@
 
 # Enthought library imports
 from enable.api import black_color_trait, ColorTrait, AbstractMarker, \
-        CustomMarker, MarkerNameDict, MarkerTrait
+    CustomMarker, MarkerNameDict, MarkerTrait
 from kiva.constants import STROKE
-from traits.api import Any, Array, Bool, Float, Trait, Callable, Property, \
-        Tuple, Either, cached_property
+from traits.api import Any, Array, ArrayOrNone, Bool, Float, Callable, \
+    Property, Tuple, Either, cached_property
 from traitsui.api import View, VGroup, Item
 
 # Local relative imports
@@ -232,7 +232,7 @@ class ScatterPlot(BaseXYPlot):
     # Private traits
     #------------------------------------------------------------------------
 
-    _cached_selected_pts = Trait(None, None, Array)
+    _cached_selected_pts = ArrayOrNone
     _cached_selected_screen_pts = Array
     _cached_point_mask = Array
     _cached_selection_point_mask = Array

chaco/tests/test_array_or_none.py

@@ -0,0 +1,62 @@
+import unittest
+import warnings
+
+import numpy as np
+
+from chaco.array_data_source import ArrayDataSource
+from chaco.axis import PlotAxis
+from chaco.data_label import DataLabel
+from chaco.data_range_1d import DataRange1D
+from chaco.label_axis import LabelAxis
+from chaco.legend import Legend
+from chaco.linear_mapper import LinearMapper
+from chaco.scatterplot import ScatterPlot
+
+
+class TestArrayOrNone(unittest.TestCase):
+    """ Test that the FutureWarning from numpy concerning comparison of arrays
+    against None are not issued.
+
+    These warnings began with numpy 1.9.
+    """
+
+    def test_array_data_source(self):
+        with warnings.catch_warnings(record=True) as w:
+            src = ArrayDataSource(np.arange(5))
+        self.assertEqual(w, [])
+
+    def test_scatter_plot(self):
+        x = np.linspace(0.0, 1.0, 5)
+        sp = ScatterPlot()
+        with warnings.catch_warnings(record=True) as w:
+            sp._cached_selected_pts = None
+            sp._cached_selected_pts = np.column_stack([x, x])
+        self.assertEqual(w, [])
+
+    def test_plot_axis(self):
+        axis = PlotAxis()
+        with warnings.catch_warnings(record=True) as w:
+            axis._tick_positions = np.arange(10)
+            axis._tick_label_list = np.arange(10)
+            axis._tick_label_positions = np.arange(10)
+        self.assertEqual(w, [])
+
+    def test_legend(self):
+        legend = Legend()
+        with warnings.catch_warnings(record=True) as w:
+            legend._cached_label_sizes = np.arange(10)
+            legend._cached_label_positions = np.arange(10)
+        self.assertEqual(w, [])
+
+    def test_data_label(self):
+        label = DataLabel()
+        with warnings.catch_warnings(record=True) as w:
+            label.data_point = np.array([10.0, 20.0])
+        self.assertEqual(w, [])
+
+    def test_label_axis(self):
+        axis = LabelAxis()
+        with warnings.catch_warnings(record=True) as w:
+            axis.positions = np.arange(10)
+        self.assertEqual(w, [])
+

chaco/text_plot_1d.py

@@ -11,12 +11,13 @@
 from numpy import array, empty
 
 # Enthought library imports
-from chaco.api import ArrayDataSource, Label
 from enable.api import black_color_trait
 from kiva.trait_defs.kiva_font_trait import KivaFont
 from traits.api import Bool, Enum, Float, Int, Instance, List, on_trait_change
 
 # local imports
+from .array_data_source import ArrayDataSource
+from .label import Label
 from .base_1d_plot import Base1DPlot
 
 

chaco/tools/lasso_selection.py

@@ -7,7 +7,7 @@
 # Enthought library imports
 from traits.api import Any, Array, Enum, Event, Bool, Instance, \
                                  Property, Str, Trait, List
-from kiva.agg import points_in_polygon
+from kiva.api import points_in_polygon
 
 # Chaco imports
 from chaco.api import AbstractController, AbstractDataSource, \

chaco/tools/range_selection.py

@@ -4,8 +4,8 @@
 from numpy import array
 
 # Enthought library imports
-from traits.api import Any, Array, Bool, Enum, Event, Float, Int, Instance, \
-                         List, Property, Str, Trait, Tuple
+from traits.api import Any, Array, ArrayOrNone, Bool, Enum, Event, Float, \
+    Instance, Int, List, Property, Str, Trait
 from enable.api import KeySpec
 
 # Chaco imports
@@ -132,8 +132,8 @@ class RangeSelection(AbstractController):
     _axis_index = Trait(None, None, Int)
 
     # The data space start and end coordinates of the selected region,
-    # expressed as a list.
-    _selection = Trait(None, None, Tuple, List, Array)
+    # expressed as an array.
+    _selection = ArrayOrNone()
 
     # The selection in mask form.
     _selection_mask = Array

chaco/tools/tests/range_selection_test_case.py

@@ -1,4 +1,5 @@
 import unittest
+import warnings
 
 import numpy as np
 
@@ -51,6 +52,23 @@ def test_selecting_mouse_leave_clipping(self):
                         self.assertTrue(selection[0] <= selection[1])
                         self.mouse_up(tool, x=x, y=y)
 
+    def test_selection_no_warning(self):
+        plot_data = ArrayPlotData()
+        arr = np.arange(4)
+        plot_data.set_data("x", arr)
+        plot_data.set_data("y", arr)
+        plot = Plot(plot_data)
+        renderer = plot.plot(('x', 'y'))[0]
+        tool = RangeSelection(renderer)
+        with warnings.catch_warnings(record=True) as w:
+            tool.selection = np.array([2.0, 3.0])
+        self.assertEqual(w, [])
+
+        # Accept tuples and lists and None
+        tool.selection = (1.5, 3.5)
+        tool.selection = [1.0, 2.0]
+        tool.selection = None
+
 
 if __name__ == '__main__':
     import nose