def make_custom_marker():
path = CompiledPath()
path.move_to(-5, -5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, 5)
path.line_to(-5, -5)
return path
def make_custom_marker():
path = CompiledPath()
path.move_to(-5,-5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, 5)
path.line_to(-5, -5)
return path
def test_scatter_1d_custom(self):
path = CompiledPath()
path.move_to(-5, -5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, 5)
path.line_to(-5, -5)
self.scatterplot.marker = 'custom'
self.scatterplot.custom_symbol = path
gc = PlotGraphicsContext(self.size)
gc.render_component(self.scatterplot)
actual = gc.bmp_array[:, :, :]
self.assertFalse(alltrue(actual == 255))
def test_scatter_1d_custom(self):
path = CompiledPath()
path.move_to(-5, -5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, 5)
path.line_to(-5, -5)
self.scatterplot.marker = 'custom'
self.scatterplot.custom_symbol = path
gc = PlotGraphicsContext(self.size)
gc.render_component(self.scatterplot)
actual = gc.bmp_array[:, :, :]
self.assertFalse(alltrue(actual == 255))
def _geojs_filename_changed(self, name):
data = file(name).read()
polys = process_raw(data.replace('\r\n', ''))
# Generate compiled path from the polygons
paths = []
for poly in polys:
path = CompiledPath()
for p in poly:
path.lines(p)
paths.append(path)
self._paths = paths
red = np.array([202, 0, 32])/255.
blue = np.array([5, 113, 176])/255.
colors = red * np.random.random_integers(0,1,len(paths)).reshape(-1,1)
colors[np.sum(colors,axis=-1)==0] = blue
self._colors = colors
# Store the polygons just in case we need to regenerate the path
self._polys = polys
self.request_redraw()
def _geojs_filename_changed(self, name):
data = file(name).read()
polys = process_raw(data.replace('\r\n', ''))
# Generate compiled path from the polygons
paths = []
for poly in polys:
path = CompiledPath()
for p in poly:
path.lines(p)
paths.append(path)
self._paths = paths
red = np.array([202, 0, 32]) / 255.
blue = np.array([5, 113, 176]) / 255.
colors = red * np.random.random_integers(0, 1, len(paths)).reshape(
-1, 1)
colors[np.sum(colors, axis=-1) == 0] = blue
self._colors = colors
# Store the polygons just in case we need to regenerate the path
self._polys = polys
self.request_redraw()
def test_scatter_custom(self):
""" Coverage test to check custom markers work """
# build path
path = CompiledPath()
path.move_to(-5, -5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, 5)
path.line_to(-5, -5)
size = (50, 50)
scatterplot = create_scatter_plot(
data=[range(10), range(10)],
marker='custom',
border_visible=False,
)
scatterplot.custom_symbol = path
scatterplot.outer_bounds = list(size)
gc = PlotGraphicsContext(size)
gc.render_component(scatterplot)
actual = gc.bmp_array[:, :, :]
self.assertFalse(alltrue(actual == 255))
def get_lion():
"""get_lion() -> path_and_color, size, center
path_and_color: [(path,color), ...]
size: [width, height]
center: [x, y]
Defines a function to return a vector image of a cartoon lion.
"""
mins = []
maxs = []
colors = []
paths = []
for line in LION_DATA:
fields = line.split()
if len(fields) == 0:
pass
elif len(fields) == 1:
hex_color = fields[0]
r = int(hex_color[:2], 16) / 255.0
g = int(hex_color[2:4], 16) / 255.0
b = int(hex_color[4:6], 16) / 255.0
colors.append(array((r, g, b, 1.0)))
paths.append(CompiledPath())
path = paths[-1]
else:
fields = array(fields, "O")
cmd = fields[::2]
pts = [array(eval(x), dtype=float) for x in fields[1::2]]
mins.append(amin(pts, axis=0))
maxs.append(amax(pts, axis=0))
path_def = list(zip(cmd, pts))
for cmd, pt in path_def:
pt[0] -= 119
pt[1] -= 190.5
if cmd == "M":
path.move_to(pt[0], pt[1])
if cmd == "L":
path.line_to(pt[0], pt[1])
min_pt = amin(array(mins), axis=0)
max_pt = amax(array(maxs), axis=0)
sz = max_pt - min_pt
center = min_pt + sz / 2.0
return list(zip(paths, colors)), sz, center
def build_paths(lion_string):
mins = []
maxs = []
colors = []
paths = []
lines = lion_string.split('\n')
for line in lines:
fields = line.split()
if len(fields) == 0:
pass
elif len(fields) == 1:
hex_color = fields[0]
r = int(hex_color[:2], 16) / 255.
g = int(hex_color[2:4], 16) / 255.
b = int(hex_color[4:6], 16) / 255.
colors.append(array((r, g, b, 1.0)))
paths.append(CompiledPath())
path = paths[-1]
else:
fields = array(fields, 'O')
cmd = fields[::2]
pts = [array(eval(x), dtype=float) for x in fields[1::2]]
mins.append(amin(pts, axis=0))
maxs.append(amax(pts, axis=0))
path_def = list(zip(cmd, pts))
for cmd, pt in path_def:
pt[0] -= 119
pt[1] -= 190.5
if cmd == 'M':
path.move_to(pt[0], pt[1])
if cmd == 'L':
path.line_to(pt[0], pt[1])
min_pt = amin(array(mins), axis=0)
max_pt = amax(array(maxs), axis=0)
sz = max_pt - min_pt
center = min_pt + sz / 2.0
return list(zip(paths, colors)), sz, center
def test_scatter_custom(self):
""" Coverage test to check custom markers work...
XXX ...which apparently they currently don't. See #232.
"""
# build path
path = CompiledPath()
path.begin_path()
path.move_to(-5, -5)
path.line_to(-5, 5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, -5)
self.scatterplot.marker = 'custom'
self.scatterplot.custom_symbol = path
self.gc.render_component(self.scatterplot)
actual = self.gc.bmp_array[:, :, :]
self.assertFalse(alltrue(actual == 255))
return self.dataframe.columns[-1]
def _data_columns_default(self):
return list(self.dataframe.columns[1:][::-1])
if __name__ == "__main__":
populations = pandas.read_csv('state_populations.csv')
from mapping.enable.geojson_overlay import process_raw
polys = process_raw(file("states.geojs").read().replace('\r\n', ''))
# generate compiled paths from polys
paths = []
coords = numpy.zeros((len(polys), 2))
for poly, coord in zip(polys, coords):
path = CompiledPath()
total = numpy.sum((numpy.sum(p, axis=0) for p in poly), axis=0)
coord[:] = total / sum(map(len, poly))
for p in poly:
path.lines(p - coord) # recenter on origin
paths.append(path)
with enaml.imports():
from choropleth_view import MapView
view = MapView(model=Demo(title="State population from 1900 to 2010",
index_ds=ArrayDataSource(coords[:, 0]),
value_ds=ArrayDataSource(coords[:, 1]),
paths=paths,
dataframe=populations), )
def test_get_compiled_path(self):
path = CompiledPath()
path.begin_path()
path.move_to(-5, -5)
path.line_to(-5, 5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, -5)
marker = CustomMarker(path=path)
# should not fail
marker.get_compiled_path(np.int64(0))
def test_add_to_path(self):
path = CompiledPath()
path.begin_path()
path.move_to(-5, -5)
path.line_to(-5, 5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, -5)
marker = CustomMarker(path=path)
gc = GraphicsContext((50, 50))
# should not fail
marker.add_to_path(gc.get_empty_path(), np.int64(0))
return self.dataframe.columns[-1]
def _data_columns_default(self):
return list(self.dataframe.columns[1:][::-1])
if __name__ == "__main__":
populations = pandas.read_csv('example/state_populations.csv')
from mapping.enable.geojson_overlay import process_raw
polys = process_raw(file("example/states.geojs").read().replace('\r\n',''))
# generate compiled paths from polys
paths = []
coords = numpy.zeros((len(polys), 2))
for poly, coord in zip(polys, coords):
path = CompiledPath()
total = numpy.sum((numpy.sum(p, axis=0) for p in poly), axis=0)
coord[:] = total/sum(map(len,poly))
for p in poly:
path.lines(p - coord) # recenter on origin
paths.append(path)
with enaml.imports():
from choropleth_view import MapView
view = MapView(
model = Demo(title = "State population from 1900 to 2010",
index_ds = ArrayDataSource(coords[:,0]),
value_ds = ArrayDataSource(coords[:,1]),
paths = paths,
dataframe = populations),
def test_scatter_custom(self):
""" Coverage test to check custom markers work...
XXX ...which apparently they currently don't. See #232.
"""
# build path
path = CompiledPath()
path.begin_path()
path.move_to(-5, -5)
path.line_to(-5, 5)
path.line_to(5, 5)
path.line_to(5, -5)
path.line_to(-5, -5)
self.scatterplot.marker = 'custom'
self.scatterplot.custom_symbol = path
self.gc.render_component(self.scatterplot)
actual = self.gc.bmp_array[:, :, :]
self.assertFalse(alltrue(actual == 255))