def _create_plot_component():
# Generate some data for the eye diagram.
num_samples = 5000
samples_per_symbol = 24
y = demo_data(num_samples, samples_per_symbol)
# Compute the eye diagram array.
ybounds = (-0.25, 1.25)
grid = grid_count(y,
2 * samples_per_symbol,
offset=16,
size=(480, 480),
bounds=ybounds).T
# Convert the array to floating point, and replace 0 with np.nan.
# These points will be transparent in the image plot.
grid = grid.astype(np.float32)
grid[grid == 0] = np.nan
#---------------------------------------------------------------------
# The rest of the function creates the chaco image plot.
pd = ArrayPlotData()
pd.set_data("eyediagram", grid)
plot = Plot(pd)
img_plot = plot.img_plot("eyediagram",
xbounds=(0, 2),
ybounds=ybounds,
bgcolor=(0, 0, 0),
colormap=cool)[0]
# Tweak some of the plot properties
plot.title = "Eye Diagram"
plot.padding = 50
# Axis grids
vgrid = PlotGrid(component=plot,
mapper=plot.index_mapper,
orientation='vertical',
line_color='gray',
line_style='dot')
hgrid = PlotGrid(component=plot,
mapper=plot.value_mapper,
orientation='horizontal',
line_color='gray',
line_style='dot')
plot.underlays.append(vgrid)
plot.underlays.append(hgrid)
# Add pan and zoom tools.
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=img_plot, tool_mode="box", always_on=False)
img_plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Generate some data for the eye diagram.
num_samples = 5000
samples_per_symbol = 24
y = demo_data(num_samples, samples_per_symbol)
# Compute the eye diagram array.
ybounds = (-0.25, 1.25)
grid = grid_count(y, 2 * samples_per_symbol, offset=16, size=(480, 480), bounds=ybounds).T
# Convert the array to floating point, and replace 0 with np.nan.
# These points will be transparent in the image plot.
grid = grid.astype(np.float32)
grid[grid == 0] = np.nan
# ---------------------------------------------------------------------
# The rest of the function creates the chaco image plot.
pd = ArrayPlotData()
pd.set_data("eyediagram", grid)
plot = Plot(pd)
img_plot = plot.img_plot("eyediagram", xbounds=(0, 2), ybounds=ybounds, bgcolor=(0, 0, 0), colormap=cool)[0]
# Tweak some of the plot properties
plot.title = "Eye Diagram"
plot.padding = 50
# Axis grids
vgrid = PlotGrid(
component=plot, mapper=plot.index_mapper, orientation="vertical", line_color="gray", line_style="dot"
)
hgrid = PlotGrid(
component=plot, mapper=plot.value_mapper, orientation="horizontal", line_color="gray", line_style="dot"
)
plot.underlays.append(vgrid)
plot.underlays.append(hgrid)
# Add pan and zoom tools.
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=img_plot, tool_mode="box", always_on=False)
img_plot.overlays.append(zoom)
return plot
m = counts.max()
colors = np.zeros((m+1, 4), dtype=np.uint8)
r = np.linspace(color1[0], color2[0], m)
g = np.linspace(color1[1], color2[1], m)
b = np.linspace(color1[2], color2[2], m)
colors[1:, 0] = r
colors[1:, 1] = g
colors[1:, 2] = b
colors[1:, 3] = 255
colors[0, 3] = 0
img = colors[counts]
return img
# Generate image data
y = demo_data(5000, 24)
ybounds = (-0.25, 1.25)
# Compute the eye diagram image data.
counts = grid_count(y, 48, offset=16, size=(480, 480), bounds=ybounds)
# Convert counts to an array of RGBA values.
yellow = (224, 192, 48)
img_data = colorize(counts, yellow)
#-------------------------------------------------------------------------
# The rest of this script uses pyqtgraph to create a plot
# of the eye diagram.
pg.mkQApp()
# Copyright (c) 2015, Warren Weckesser. All rights reserved. # This software is licensed according to the "BSD 2-clause" license. from eyediagram.demo_data import demo_data from eyediagram.mpl import eyediagram import matplotlib.pyplot as plt # Get some data for the demonstration. num_symbols = 5000 samples_per_symbol = 24 y = demo_data(num_symbols, samples_per_symbol) eyediagram(y, 2 * samples_per_symbol, offset=16, cmap=plt.cm.coolwarm) plt.show()
m = counts.max()
colors = np.zeros((m + 1, 4), dtype=np.uint8)
r = np.linspace(color1[0], color2[0], m)
g = np.linspace(color1[1], color2[1], m)
b = np.linspace(color1[2], color2[2], m)
colors[1:, 0] = r
colors[1:, 1] = g
colors[1:, 2] = b
colors[1:, 3] = 255
colors[0, 3] = 0
img = colors[counts]
return img
# Generate image data
y = demo_data(5000, 24)
ybounds = (-0.25, 1.25)
# Compute the eye diagram image data.
counts = grid_count(y, 48, offset=16, size=(480, 480), bounds=ybounds)
# Convert counts to an array of RGBA values.
yellow = (224, 192, 48)
img_data = colorize(counts, yellow)
#-------------------------------------------------------------------------
# The rest of this script uses pyqtgraph to create a plot
# of the eye diagram.
pg.mkQApp()
# Copyright (c) 2015, Warren Weckesser. All rights reserved. # This software is licensed according to the "BSD 2-clause" license. from eyediagram.demo_data import demo_data from eyediagram.mpl import eyediagram import matplotlib.pyplot as plt # Get some data for the demonstration. num_symbols = 5000 samples_per_symbol = 24 y = demo_data(num_symbols, samples_per_symbol) eyediagram(y, 2*samples_per_symbol, offset=16, cmap=plt.cm.coolwarm) plt.show()