def _startX_changed(self):
if self.imageInspectorReference is None:
return # not yet initialized yet
self.imageInspectorReference.ROIPolyPlot.index = chaco.ArrayDataSource(
[self.startX, self.endX, self.endX, self.startX])
self.imageInspectorReference.ROIPolyPlot.value = chaco.ArrayDataSource(
[self.startY, self.startY, self.endY, self.endY])
def drawRescaleRegion(self, framePlot):
if self.optionsDict["rescale?"]:
logger.warning("drawRescaleRegion")
if True:
# create line polygon plot to display fit region
points = np.asarray([
[ self.optionsDict["rescaleInitialX"], self.optionsDict["rescaleInitialX"]+self.optionsDict["rescaleWidth"],
self.optionsDict["rescaleInitialX"]+self.optionsDict["rescaleWidth"], self.optionsDict["rescaleInitialX"] ],
[ self.optionsDict["rescaleInitialY"], self.optionsDict["rescaleInitialY"],
self.optionsDict["rescaleInitialY"]+self.optionsDict["rescaleHeight"],
self.optionsDict["rescaleInitialY"]+self.optionsDict["rescaleHeight"] ]
])
phi = self.optionsDict["rotationAngle"] * np.pi / 180.
rotMatrix = np.asarray([
[np.cos(phi), np.sin(phi)],
[-np.sin(phi), np.cos(phi)]
])
print points
# get old and new dimensions for scale and center of image
widthOld = self.atomsArray.shape[0]
heightOld = self.atomsArray.shape[1]
width = self.opticalDensityArray.shape[0]
height = self.opticalDensityArray.shape[1]
# rotate around center
points[0] = points[0] - widthOld/2.
points[1] = points[1] - heightOld/2.
points = rotMatrix.dot(points)
points[0] = points[0] + width/2.
points[1] = points[1] + height/2.
rescaleRegionFrameXs = chaco.ArrayDataSource( points[0] )
rescaleRegionFrameYs = chaco.ArrayDataSource( points[1] )
framePlot.index = rescaleRegionFrameXs
framePlot.value = rescaleRegionFrameYs
framePlot.visible = self.optionsDict["drawRescaleRegion?"]
self.framePlot = framePlot
def _create_render(self):
# Create our data sources
idx = _chaco.ArrayDataSource(_np.arange(self.ds.n_vars))
vals = _chaco.ArrayDataSource(self.ds.mat.ix[self.row_id].values)
# Create the index range
index_range = _chaco.DataRange1D(idx,
tight_bounds=False,
low_setting='auto',
margin=0.15)
index_mapper = _chaco.LinearMapper(range=index_range)
# Create the value range
value_range = _chaco.DataRange1D(vals,
low_setting=0,
high_setting=self.ceiling)
value_mapper = _chaco.LinearMapper(range=value_range)
# Create the plot
bars = _chaco.BarPlot(index=idx,
value=vals,
value_mapper=value_mapper,
index_mapper=index_mapper,
line_color='black',
fill_color='springgreen',
bar_width=0.8,
antialias=False)
return bars
def _render_data(self, pec):
idx = _chaco.ArrayDataSource(_np.arange(self.ds.n_objs))
mvals = self.stair_ds
# Create the index range
index_range = _chaco.DataRange1D(idx,
tight_bounds=False,
low_setting='auto',
margin=0.15)
index_mapper = _chaco.LinearMapper(range=index_range)
# Create the value range
value_range = _chaco.DataRange1D(mvals, tight_bounds=True)
value_mapper = _chaco.LinearMapper(range=value_range)
colors = hue_span(mvals.get_value_size())
bar_names = {}
for i in range(mvals.get_value_size() - 1, -1, -1):
vals = _chaco.ArrayDataSource(mvals.get_data(axes=i))
bars = _chaco.BarPlot(index=idx,
value=vals,
value_mapper=value_mapper,
index_mapper=index_mapper,
line_color='black',
fill_color=colors[i],
bar_width=0.8,
antialias=False)
name = str(self.ds.var_n[i])
bar_names[name] = bars
num = self.ds.mat.values[:, i]
pecl = pec[:, i]
self._add_data_labels(bars, num, pecl)
self.add(bars)
rvn = bar_names.keys()
rvn.sort(reverse=True)
legend = _chaco.Legend(component=self,
padding=2,
align="ur",
labels=rvn)
legend.plots = bar_names
self.overlays.append(legend)
return bars
def _create_renderer(self):
# Create our data sources
bmin = _chaco.ArrayDataSource(self.ds.mat['perc25'].values)
bmax = _chaco.ArrayDataSource(self.ds.mat['perc75'].values)
med = _chaco.ArrayDataSource(self.ds.mat['median'].values)
minv = _chaco.ArrayDataSource(self.ds.mat['min'].values)
maxv = _chaco.ArrayDataSource(self.ds.mat['max'].values)
idx = _chaco.ArrayDataSource(_np.arange(self.ds.n_objs))
# Create the index range
index_range = _chaco.DataRange1D(idx, tight_bounds=False)
index_mapper = _chaco.LinearMapper(range=index_range)
# Create the value range
value_range = _chaco.DataRange1D(minv, maxv, tight_bounds=False)
value_mapper = _chaco.LinearMapper(range=value_range)
# Color defined in enable.colors.color_table
boxes = _chaco.CandlePlot(index=idx,
center_values=med,
bar_min=bmin,
bar_max=bmax,
min_values=minv,
max_values=maxv,
index_mapper=index_mapper,
value_mapper=value_mapper,
bar_color='springgreen',
bar_line_color='black',
center_color='forestgreen',
stem_color='black',
line_width=1.0,
center_width=5,
stem_width=1,
end_cap=False)
return boxes