def get_contour_line_plot():
NPOINTS_X, NPOINTS_Y = 600, 300
# Create a scalar field to contour
xs = np.linspace(-2 * np.pi, +2 * np.pi, NPOINTS_X)
ys = np.linspace(-1.5 * np.pi, +1.5 * np.pi, NPOINTS_Y)
x, y = np.meshgrid(xs, ys)
z = scipy.special.jn(2, x) * y * x
index = GridDataSource(xdata=xs, ydata=ys)
index_mapper = GridMapper(range=DataRange2D(index))
value = ImageData(data=z, value_depth=1)
color_mapper = dc.Blues(DataRange1D(value))
contour_plot = ContourLinePlot(index=index,
index_mapper=index_mapper,
value=value,
colors=color_mapper,
widths=list(range(1, 11)),
**PLOT_DEFAULTS)
add_axes(contour_plot, x_label='x', y_label='y')
return contour_plot
def get_contour_poly_plot():
NPOINTS_X, NPOINTS_Y = 600, 300
# Create a scalar field to contour
xs = np.linspace(-2 * np.pi, +2 * np.pi, NPOINTS_X)
ys = np.linspace(-1.5 * np.pi, +1.5 * np.pi, NPOINTS_Y)
x, y = np.meshgrid(xs, ys)
z = scipy.special.jn(2, x) * y * x
# FIXME: we have set the xbounds and ybounds manually to work around
# a bug in CountourLinePlot, see comment in contour_line_plot.py at
# line 112 (the workaround is the +1 at the end)
xs_bounds = np.linspace(xs[0], xs[-1], z.shape[1] + 1)
ys_bounds = np.linspace(ys[0], ys[-1], z.shape[0] + 1)
index = GridDataSource(xdata=xs_bounds, ydata=ys_bounds)
index_mapper = GridMapper(range=DataRange2D(index))
value = ImageData(data=z, value_depth=1)
color_mapper = dc.Blues(DataRange1D(value))
contour_plot = ContourPolyPlot(index=index,
index_mapper=index_mapper,
value=value,
colors=color_mapper,
**PLOT_DEFAULTS)
add_axes(contour_plot, x_label='x', y_label='y')
return contour_plot
def get_cmap_image_plot():
# Create a scalar field to colormap
NPOINTS = 200
xs = np.linspace(-2 * np.pi, +2 * np.pi, NPOINTS)
ys = np.linspace(-1.5*np.pi, +1.5*np.pi, NPOINTS)
x, y = np.meshgrid(xs, ys)
z = scipy.special.jn(2, x)*y*x
index = GridDataSource(xdata=xs, ydata=ys)
index_mapper = GridMapper(range=DataRange2D(index))
color_source = ImageData(data=z, value_depth=1)
color_mapper = dc.Spectral(DataRange1D(color_source))
cmap_plot = CMapImagePlot(
index=index,
index_mapper=index_mapper,
value=color_source,
value_mapper=color_mapper,
**PLOT_DEFAULTS
)
add_axes(cmap_plot, x_label='x', y_label='y')
return cmap_plot
def get_image_from_file():
import os.path
filename = os.path.join('..', '..', 'demo', 'basic', 'capitol.jpg')
image_source = ImageData.fromfile(filename)
w, h = image_source.get_width(), image_source.get_height()
index = GridDataSource(np.arange(w), np.arange(h))
index_mapper = GridMapper(
range=DataRange2D(low=(0, 0), high=(w - 1, h - 1)))
image_plot = ImagePlot(index=index,
value=image_source,
index_mapper=index_mapper,
origin='top left',
**PLOT_DEFAULTS)
add_axes(image_plot, x_label='x', y_label='y')
return image_plot
def get_image_plot():
# Create some RGBA image data
image = np.zeros((200, 400, 4), dtype=np.uint8)
image[:, 0:40, 0] += 255 # Vertical red stripe
image[0:25, :, 1] += 255 # Horizontal green stripe; also yellow square
image[-80:, -160:, 2] += 255 # Blue square
image[:, :, 3] = 255
index = GridDataSource(np.linspace(0, 4., 400), np.linspace(-1, 1., 200))
index_mapper = GridMapper(range=DataRange2D(low=(0, -1), high=(4., 1.)))
image_source = ImageData(data=image, value_depth=4)
image_plot = ImagePlot(index=index,
value=image_source,
index_mapper=index_mapper,
**PLOT_DEFAULTS)
add_axes(image_plot, x_label='x', y_label='y')
return image_plot
