def recalculate(self):
if self.func is not None and self.data_range is not None:
newarray = self.func(self.data_range.x_range.low, self.data_range.x_range.high,
self.data_range.y_range.low, self.data_range.y_range.high)
ImageData.set_data(self, newarray)
else:
self._data = array([], dtype=float)
def do_imread(*data, **kwargs):
""" Returns image file as array. """
# Check to see if the data given is either a file path or a file object
if isinstance(data[0], basestring) or isinstance(data[0], file):
return ImageData.fromfile(data[0])
else:
raise ValueError("do_imread takes a string filename")
def _load(self):
try:
# Load the image with the user supplied filename
image = ImageData.fromfile(self._load_file)
# Update the plot data. NB we must extract _date from the image
# for the time being, until ImageData is made more friendly
self.pd.set_data("imagedata", image._data)
# Set the title and redraw
self.plot.title = os.path.basename(self._load_file)
self.plot.request_redraw()
except:
# If loading fails, simply do nothing
pass
def __init__(self, **kw):
super(WorldMapPlot, self).__init__(**kw)
self._download_map_image()
image = ImageData.fromfile(self.image_path)
# For now, the locations are hardcoded, though this can be changed
# eassily to take command line args, read from a file, or by other
# means
austin_loc = (30.16, -97.44)
locations_x = numpy.array([austin_loc[1]])
locations_y = numpy.array([austin_loc[0]])
# transform each of the locations to the image data space, including
# moving the origin from bottom left to top left
locations_x = (locations_x + 180) * image.data.shape[1]/360
locations_y = (locations_y*-1 + 90) * image.data.shape[0]/180
# Create the plott data, adding the image and the locations
plot_data = ArrayPlotData()
plot_data.set_data("imagedata", image._data)
plot_data.set_data("locations_x", locations_x)
plot_data.set_data("locations_y", locations_y)
# Create the plot with the origin as top left, which matches
# how the image data is aligned
self.plot = Plot(plot_data, default_origin="top left")
self.plot.img_plot('imagedata')
# Plot the locations as a scatter plot to be overlayed on top
# of the map
loc_plot = self.plot.plot(('locations_x', 'locations_y'),
type='scatter', size=3, color='yellow',
marker='dot')[0]
loc_plot.x_mapper.range.high = image.data.shape[1]
loc_plot.x_mapper.range.low = 0
loc_plot.y_mapper.range.high = image.data.shape[0]
loc_plot.y_mapper.range.low = -0
# set up any tools, in this case just the zoom tool
zoom = ZoomTool(component=self.plot, tool_mode="box", always_on=False)
self.plot.overlays.append(zoom)
def _filename_changed(self, new):
image = ImageData.fromfile(new)
self.plot_image(image._data)
def recalculate(self):
if self.func is not None and self.data_range is not None:
newarray = self.func(self.data_range.low, self.data_range.high)
ImageData.set_data(self, newarray)
else:
self._data = zeros((512,512),dtype=float)
def __init__(self, **kw):
# Explicitly call the AbstractDataSource constructor because
# the ArrayDataSource ctor wants a data array
ImageData.__init__(self, **kw)
self.recalculate()
def _file_changed(self, new):
image = ImageData.fromfile(new)
self.update_image(image.data)
def recalculate(self):
if self.func is not None and self.data_range is not None:
newarray = self.func(self.data_range.low, self.data_range.high)
ImageData.set_data(self, newarray)
else:
self._data = zeros((512, 512), dtype=float)
def __init__(self, **kw):
# Explicitly call the AbstractDataSource constructor because
# the ArrayDataSource ctor wants a data array
ImageData.__init__(self, **kw)
self.recalculate()