def __init__(self):
# Create the data and the PlotData object
price1 = random_walk(100)
price2 = random_walk(100, start=50)
times = np.arange(100)
plotdata = ArrayPlotData(times=times, price1=price1, price2=price2)
# Create the scatter plot
plot1 = Plot(plotdata)
plot1.plot(("times", "price1"), type="line", color="blue")
plot1.plot(("times", "price1"), type="scatter", color="blue")
plot2 = Plot(plotdata)
plot2.plot(("times", "price2"), type="line", color="green")
plot2.plot(("times", "price2"), type="scatter", color="green")
scatterplot = Plot(plotdata)
scatterplot.plot(("price2", "price1"), type="scatter", color="green")
plot1.tools.append(PanTool(plot1))
plot1.tools.append(ZoomTool(plot1))
plot2.tools.append(PanTool(plot2))
plot2.tools.append(ZoomTool(plot2))
scatterplot.tools.append(PanTool(scatterplot))
scatterplot.tools.append(ZoomTool(scatterplot))
plot1.index_range = plot2.index_range
lineplots = VPlotContainer(plot1, plot2)
container = HPlotContainer(lineplots, scatterplot)
self.plot = container
self.plotdata = plotdata
def _container_default(self):
# Create the data and the PlotData object
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x = x, y = y)
# Create the scatter plot
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
# Create the line plot
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
# Add pan/zoom so we can see they are connected
scatter.tools.append(PanTool(scatter))
scatter.tools.append(ZoomTool(scatter))
line.tools.append(PanTool(line))
line.tools.append(ZoomTool(line))
# Set the two plots' ranges to be the same
scatter.index_range = line.index_range
# Create a horizontal container and put the two plots inside it
return HPlotContainer(scatter, line)
def _container_default(self):
# Create the data and the PlotData object
x = linspace(-14, 14, 100)
y = sin(x) * x ** 3
plotdata = ArrayPlotData(x=x, y=y)
# Create the scatter plot
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
# Create the line plot
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
# Add pan/zoom so we can see they are connected
scatter.tools.append(PanTool(scatter))
scatter.tools.append(ZoomTool(scatter))
line.tools.append(PanTool(line))
line.tools.append(ZoomTool(line))
# Set the two plots' ranges to be the same
scatter.index_range = line.index_range
# Create a horizontal container and put the two plots inside it
return HPlotContainer(scatter, line)
def _create_window(self):
# Create the model
#try:
# self.model = model = BrainModel()
# cmap = bone
#except SystemExit:
# sys.exit()
#except:
# print "Unable to load BrainModel, using generated data cube."
self.model = model = Model()
cmap = jet
self._update_model(cmap)
datacube = self.colorcube
# Create the plot
self.plotdata = ArrayPlotData()
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, padding=0)
imgplot = centerplot.img_plot("xy",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xy")
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, width=150, resizable="v", padding=0)
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(model.zs[0], model.zs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "yz")
self.right = imgplot
# Bottom Plot
bottomplot = Plot(self.plotdata, height=150, resizable="h", padding=0)
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.zs[0], model.zs[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xz")
self.bottom = imgplot
# Create Container and add all Plots
container = GridPlotContainer(padding=20, fill_padding=True,
bgcolor="white", use_backbuffer=True,
shape=(2,2), spacing=(12,12))
container.add(centerplot)
container.add(rightplot)
container.add(bottomplot)
self.container = container
return Window(self, -1, component=container)
def _create_window(self):
# Create the model
#try:
# self.model = model = BrainModel()
# cmap = bone
#except SystemExit:
# sys.exit()
#except:
# print "Unable to load BrainModel, using generated data cube."
self.model = model = Model()
cmap = jet
self._update_model(cmap)
datacube = self.colorcube
# Create the plot
self.plotdata = ArrayPlotData()
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, padding=0)
imgplot = centerplot.img_plot("xy",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xy")
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, width=150, resizable="v", padding=0)
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(model.zs[0], model.zs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "yz")
self.right = imgplot
# Bottom Plot
bottomplot = Plot(self.plotdata, height=150, resizable="h", padding=0)
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.zs[0], model.zs[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xz")
self.bottom = imgplot
# Create Container and add all Plots
container = GridPlotContainer(padding=20, fill_padding=True,
bgcolor="white", use_backbuffer=True,
shape=(2,2), spacing=(12,12))
container.add(centerplot)
container.add(rightplot)
container.add(bottomplot)
self.container = container
return Window(self, -1, component=container)
def _create_window(self):
self.model = model = Model()
self.cmap = jet
#self._update_model(self.cmap)
# Create the plot
self.plotdata = ArrayPlotData()
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, padding=0)
imgplot = centerplot.img_plot("xy",
xbounds=(model.min_x, model.max_x),
ybounds=(model.min_y, model.max_y),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "xy")
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, width=150, resizable="v", padding=0)
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(model.min_z, model.max_z),
ybounds=(model.min_y, model.max_y),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "yz")
self.right = imgplot
# Bottom Plot. Seismic plot axis1 (depth) down into earth
# i.e. z is depth, to altitude.
bottomplot = Plot(self.plotdata,
height=150,
resizable="h",
padding=0,
origin="top left")
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(model.min_x, model.max_x),
ybounds=(model.min_z, model.max_z),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "xz")
self.bottom = imgplot
# Create Container and add all Plots
container = GridPlotContainer(padding=20,
fill_padding=True,
bgcolor="white",
use_backbuffer=True,
shape=(2, 2),
spacing=(20, 20))
container.add(centerplot)
container.add(rightplot)
container.add(bottomplot)
self.container = container
return Window(self, -1, component=container)
def test_range_change(self):
arr = arange(10)
data = ArrayPlotData(x=arr, y=arr)
plot = Plot(data)
renderer = plot.plot(('x', 'y'))[0]
new_range = DataRange1D()
old_range = plot.index_range
self.assertIsNot(old_range, new_range)
self.assertIs(renderer.index_range, old_range)
plot.index_range = new_range
self.assertIs(plot.index_range, new_range)
self.assertIs(renderer.index_range, new_range)
def test_range_change(self):
arr = arange(10)
data = ArrayPlotData(x=arr, y=arr)
plot = Plot(data)
renderer = plot.plot(('x', 'y'))[0]
new_range = DataRange1D()
old_range = plot.index_range
self.assertIsNot(old_range, new_range)
self.assertIs(renderer.index_range, old_range)
plot.index_range = new_range
self.assertIs(plot.index_range, new_range)
self.assertIs(renderer.index_range, new_range)
def _create_plot_component():
# Create the index
numpoints = 100
low = -5
high = 15.0
x = arange(low, high, (high - low) / numpoints)
plotdata = ArrayPlotData(x=x, y1=jn(0, x), y2=jn(1, x))
# Create the left plot
left_plot = Plot(plotdata)
left_plot.x_axis.title = "X"
left_plot.y_axis.title = "j0(x)"
renderer = left_plot.plot(("x", "y1"),
type="line",
color="blue",
width=2.0)[0]
renderer.overlays.append(
LineInspector(renderer,
axis='value',
write_metadata=True,
is_listener=True))
renderer.overlays.append(
LineInspector(renderer,
axis="index",
write_metadata=True,
is_listener=True))
left_plot.overlays.append(ZoomTool(left_plot, tool_mode="range"))
left_plot.tools.append(PanTool(left_plot))
# Create the right plot
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = "v"
right_plot.x_axis.title = "j1(x)"
right_plot.y_axis.title = "X"
renderer2 = right_plot.plot(("x", "y2"),
type="line",
color="red",
width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(
LineInspector(renderer2, write_metadata=True, is_listener=True))
renderer2.overlays.append(
LineInspector(renderer2, axis="value", is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode="range"))
right_plot.tools.append(PanTool(right_plot))
container = HPlotContainer(background="lightgray")
container.add(left_plot)
container.add(right_plot)
return container
def _create_window(self):
self.model = model = Model()
self.cmap = jet
#self._update_model(self.cmap)
# Create the plot
self.plotdata = ArrayPlotData()
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, padding=0)
imgplot = centerplot.img_plot("xy",
xbounds=(model.min_x, model.max_x),
ybounds=(model.min_y, model.max_y),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "xy")
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, width=150, resizable="v", padding=0)
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(model.min_z, model.max_z),
ybounds=(model.min_y, model.max_y),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "yz")
self.right = imgplot
# Bottom Plot. Seismic plot axis1 (depth) down into earth
# i.e. z is depth, to altitude.
bottomplot = Plot(self.plotdata, height=150, resizable="h",
padding=0, origin="top left")
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(model.min_x, model.max_x),
ybounds=(model.min_z, model.max_z),
colormap=self.cmap)[0]
self._add_plot_tools(imgplot, "xz")
self.bottom = imgplot
# Create Container and add all Plots
container = GridPlotContainer(padding=20, fill_padding=True,
bgcolor="white", use_backbuffer=True,
shape=(2,2), spacing=(20,20))
container.add(centerplot)
container.add(rightplot)
container.add(bottomplot)
self.container = container
return Window(self, -1, component=container)
def _create_plot_component():
# Create the index
numpoints = 100
low = -5
high = 15.0
x = arange(low, high, (high - low) / numpoints)
plotdata = ArrayPlotData(x=x, y1=jn(0, x), y2=jn(1, x))
# Create the left plot
left_plot = Plot(plotdata)
left_plot.x_axis.title = "X"
left_plot.y_axis.title = "j0(x)"
renderer = left_plot.plot(("x", "y1"), type="line", color="blue",
width=2.0)[0]
renderer.overlays.append(LineInspector(renderer, axis='value',
write_metadata=True,
is_listener=True))
renderer.overlays.append(LineInspector(renderer, axis="index",
write_metadata=True,
is_listener=True))
left_plot.overlays.append(ZoomTool(left_plot, tool_mode="range"))
left_plot.tools.append(PanTool(left_plot))
# Create the right plot
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = "v"
right_plot.x_axis.title = "j1(x)"
right_plot.y_axis.title = "X"
renderer2 = right_plot.plot(("x", "y2"), type="line", color="red",
width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(LineInspector(renderer2, write_metadata=True,
is_listener=True))
renderer2.overlays.append(LineInspector(renderer2, axis="value",
is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode="range"))
right_plot.tools.append(PanTool(right_plot))
container = HPlotContainer(background="lightgray")
container.add(left_plot)
container.add(right_plot)
return container
def _mic_spectrum_plot_default(self):
plot = Plot(self.tf_data)
plot.plot(('frequency', 'spectrum'), type='line', color='black',
index_scale='log')
plot.index_range = DataRange1D(low_setting=500, high_setting=50e3)
plot.underlays = []
axis = PlotAxis(orientation='bottom', component=plot,
title='Frequency (Hz)')
plot.underlays.append(axis)
axis = PlotAxis(orientation='left', component=plot,
title='Exp. mic. (dB re 1mV)')
plot.underlays.append(axis)
grid = PlotGrid(mapper=plot.index_mapper, component=plot,
orientation='vertical', line_style='dot',
line_color='lightgray')
plot.underlays.append(grid)
grid = PlotGrid(mapper=plot.value_mapper, component=plot,
orientation='horizontal', line_style='dot',
line_color='lightgray')
plot.underlays.append(grid)
return plot
def __init__(self):
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x=x, y=y)
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
self.container = HPlotContainer(scatter, line)
scatter.tools.append(PanTool(scatter))
scatter.tools.append(ZoomTool(scatter))
line.tools.append(PanTool(line))
line.tools.append(ZoomTool(line))
#scatter.range2d = line.range2d
scatter.index_range = line.index_range
def __init__(self):
# Create the data and the PlotData object
price1 = random_walk(100)
price2 = random_walk(100, start=50)
times = np.arange(100)
plotdata = ArrayPlotData(times=times, price1=price1, price2=price2)
# Create the scatter plot
plot1 = Plot(plotdata)
line1 = plot1.plot(("times", "price1"), type="line", color="blue")[0]
scatter1 = plot1.plot(("times", "price1"), type="scatter", color="blue")[0]
plot2 = Plot(plotdata)
line2 = plot2.plot(("times", "price2"), type="line", color="green")[0]
scatter2 = plot2.plot(("times", "price2"), type="scatter", color="green")[0]
scatterplot = Plot(plotdata)
scatterplot.plot(("price2", "price1"), type="scatter", color="green")
#plot1.tools.append(PanTool(plot1))
plot1.tools.append(ZoomTool(plot1))
plot1.tools.append(RangeSelection(line1, auto_handle_event=False))
plot1.overlays.append(RangeSelectionOverlay(line1, metadata_name="selections"))
plot1.overlays.append(RangeSelectionOverlay(line1, metadata_name="selections"))
#plot2.tools.append(PanTool(plot2))
plot2.tools.append(ZoomTool(plot2))
plot2.tools.append(RangeSelection(line2, auto_handle_event=False))
plot2.overlays.append(RangeSelectionOverlay(line2, metadata_name="selections"))
#scatterplot.tools.append(PanTool(scatterplot))
scatterplot.tools.append(ZoomTool(scatterplot))
plot1.index_range = plot2.index_range
lineplots = VPlotContainer(plot1, plot2)
container = HPlotContainer(lineplots, scatterplot)
self.plot = container
self.plotdata = plotdata
def _add_new_plot(self, new_data):
code = self.data_provider.code
if code in self.dataset.list_data():
create_new_plot = False
else:
create_new_plot = True
self.dataset.set_data(code, new_data)
if create_new_plot:
new_plot = Plot(self.dataset)
new_plot.plot(('dates', code), type='line')
new_plot.tools.append(PanTool(new_plot))
tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem())
new_plot.x_axis.tick_generator = tick_generator
# connect the index of the first plot with the new plot
first_plot = self.container.components[0]
new_plot.index_range = first_plot.index_range
self.container.add(new_plot)
self.container.request_redraw()
def make_plots(self, n_dfe_taps):
""" Create the plots used by the PyBERT GUI."""
post_chnl_str = "Channel"
post_tx_str = "Channel + Tx Preemphasis"
post_ctle_str = "Channel + Tx Preemphasis + CTLE (+ AMI DFE)"
post_dfe_str = "Channel + Tx Preemphasis + CTLE (+ AMI DFE) + PyBERT DFE"
plotdata = self.plotdata
# - DFE tab
plot2 = Plot(plotdata, padding_left=75)
plot2.plot(("t_ns", "ui_ests"), type="line", color="blue")
plot2.title = "CDR Adaptation"
plot2.index_axis.title = "Time (ns)"
plot2.value_axis.title = "UI (ps)"
plot9 = Plot(
plotdata,
auto_colors=["red", "orange", "yellow", "green", "blue", "purple"],
padding_left=75,
)
for i in range(n_dfe_taps):
plot9.plot(
("tap_weight_index", "tap%d_weights" % (i + 1)),
type="line",
color="auto",
name="tap%d" % (i + 1),
)
plot9.title = "DFE Adaptation"
plot9.tools.append(
PanTool(plot9,
constrain=True,
constrain_key=None,
constrain_direction="x"))
zoom9 = ZoomTool(plot9, tool_mode="range", axis="index", always_on=False)
plot9.overlays.append(zoom9)
plot9.legend.visible = True
plot9.legend.align = "ul"
plot_clk_per_hist = Plot(plotdata, padding_left=75)
plot_clk_per_hist.plot(("clk_per_hist_bins", "clk_per_hist_vals"),
type="line",
color="blue")
plot_clk_per_hist.title = "CDR Clock Period Histogram"
plot_clk_per_hist.index_axis.title = "Clock Period (ps)"
plot_clk_per_hist.value_axis.title = "Bin Count"
plot_clk_per_spec = Plot(plotdata, padding_left=75)
plot_clk_per_spec.plot(("clk_freqs", "clk_spec"),
type="line",
color="blue")
plot_clk_per_spec.title = "CDR Clock Period Spectrum"
plot_clk_per_spec.index_axis.title = "Frequency (bit rate)"
plot_clk_per_spec.value_axis.title = "|H(f)| (dB mean)"
plot_clk_per_spec.value_range.low_setting = -10
zoom_clk_per_spec = ZoomTool(plot_clk_per_spec,
tool_mode="range",
axis="index",
always_on=False)
plot_clk_per_spec.overlays.append(zoom_clk_per_spec)
container_dfe = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_dfe.add(plot2)
container_dfe.add(plot9)
container_dfe.add(plot_clk_per_hist)
container_dfe.add(plot_clk_per_spec)
self.plots_dfe = container_dfe
self._dfe_plot = plot9
# - EQ Tune tab
# plot_h_tune = Plot(plotdata, padding_left=75)
plot_h_tune = Plot(plotdata, padding_bottom=75)
plot_h_tune.plot(("t_ns_chnl", "ctle_out_h_tune"),
type="line",
color="blue")
plot_h_tune.plot(("t_ns_chnl", "clocks_tune"), type="line", color="gray")
plot_h_tune.title = "Channel + Tx Preemphasis + CTLE (+ AMI DFE) + Ideal DFE"
plot_h_tune.index_axis.title = "Time (ns)"
plot_h_tune.y_axis.title = "Pulse Response (V)"
zoom_tune = ZoomTool(plot_h_tune,
tool_mode="range",
axis="index",
always_on=False)
plot_h_tune.overlays.append(zoom_tune)
self.plot_h_tune = plot_h_tune
# - Impulse Responses tab
plot_h_chnl = Plot(plotdata, padding_left=75)
plot_h_chnl.plot(("t_ns_chnl", "chnl_h"),
type="line",
color="blue",
name="Incremental")
plot_h_chnl.title = post_chnl_str
plot_h_chnl.index_axis.title = "Time (ns)"
plot_h_chnl.y_axis.title = "Impulse Response (V/ns)"
plot_h_chnl.legend.visible = True
plot_h_chnl.legend.align = "ur"
zoom_h = ZoomTool(plot_h_chnl,
tool_mode="range",
axis="index",
always_on=False)
plot_h_chnl.overlays.append(zoom_h)
plot_h_tx = Plot(plotdata, padding_left=75)
plot_h_tx.plot(("t_ns_chnl", "tx_out_h"),
type="line",
color="red",
name="Cumulative")
plot_h_tx.title = post_tx_str
plot_h_tx.index_axis.title = "Time (ns)"
plot_h_tx.y_axis.title = "Impulse Response (V/ns)"
plot_h_tx.legend.visible = True
plot_h_tx.legend.align = "ur"
plot_h_tx.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
plot_h_ctle = Plot(plotdata, padding_left=75)
plot_h_ctle.plot(("t_ns_chnl", "ctle_out_h"),
type="line",
color="red",
name="Cumulative")
plot_h_ctle.title = post_ctle_str
plot_h_ctle.index_axis.title = "Time (ns)"
plot_h_ctle.y_axis.title = "Impulse Response (V/ns)"
plot_h_ctle.legend.visible = True
plot_h_ctle.legend.align = "ur"
plot_h_ctle.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
plot_h_dfe = Plot(plotdata, padding_left=75)
plot_h_dfe.plot(("t_ns_chnl", "dfe_out_h"),
type="line",
color="red",
name="Cumulative")
plot_h_dfe.title = post_dfe_str
plot_h_dfe.index_axis.title = "Time (ns)"
plot_h_dfe.y_axis.title = "Impulse Response (V/ns)"
plot_h_dfe.legend.visible = True
plot_h_dfe.legend.align = "ur"
plot_h_dfe.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
container_h = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_h.add(plot_h_chnl)
container_h.add(plot_h_tx)
container_h.add(plot_h_ctle)
container_h.add(plot_h_dfe)
self.plots_h = container_h
# - Step Responses tab
plot_s_chnl = Plot(plotdata, padding_left=75)
plot_s_chnl.plot(("t_ns_chnl", "chnl_s"),
type="line",
color="blue",
name="Incremental")
plot_s_chnl.title = post_chnl_str
plot_s_chnl.index_axis.title = "Time (ns)"
plot_s_chnl.y_axis.title = "Step Response (V)"
plot_s_chnl.legend.visible = True
plot_s_chnl.legend.align = "lr"
zoom_s = ZoomTool(plot_s_chnl,
tool_mode="range",
axis="index",
always_on=False)
plot_s_chnl.overlays.append(zoom_s)
plot_s_tx = Plot(plotdata, padding_left=75)
plot_s_tx.plot(("t_ns_chnl", "tx_s"),
type="line",
color="blue",
name="Incremental")
plot_s_tx.plot(("t_ns_chnl", "tx_out_s"),
type="line",
color="red",
name="Cumulative")
plot_s_tx.title = post_tx_str
plot_s_tx.index_axis.title = "Time (ns)"
plot_s_tx.y_axis.title = "Step Response (V)"
plot_s_tx.legend.visible = True
plot_s_tx.legend.align = "lr"
plot_s_tx.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
plot_s_ctle = Plot(plotdata, padding_left=75)
plot_s_ctle.plot(("t_ns_chnl", "ctle_s"),
type="line",
color="blue",
name="Incremental")
plot_s_ctle.plot(("t_ns_chnl", "ctle_out_s"),
type="line",
color="red",
name="Cumulative")
plot_s_ctle.title = post_ctle_str
plot_s_ctle.index_axis.title = "Time (ns)"
plot_s_ctle.y_axis.title = "Step Response (V)"
plot_s_ctle.legend.visible = True
plot_s_ctle.legend.align = "lr"
plot_s_ctle.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
plot_s_dfe = Plot(plotdata, padding_left=75)
plot_s_dfe.plot(("t_ns_chnl", "dfe_s"),
type="line",
color="blue",
name="Incremental")
plot_s_dfe.plot(("t_ns_chnl", "dfe_out_s"),
type="line",
color="red",
name="Cumulative")
plot_s_dfe.title = post_dfe_str
plot_s_dfe.index_axis.title = "Time (ns)"
plot_s_dfe.y_axis.title = "Step Response (V)"
plot_s_dfe.legend.visible = True
plot_s_dfe.legend.align = "lr"
plot_s_dfe.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
container_s = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_s.add(plot_s_chnl)
container_s.add(plot_s_tx)
container_s.add(plot_s_ctle)
container_s.add(plot_s_dfe)
self.plots_s = container_s
# - Pulse Responses tab
plot_p_chnl = Plot(plotdata, padding_left=75)
plot_p_chnl.plot(("t_ns_chnl", "chnl_p"),
type="line",
color="blue",
name="Incremental")
plot_p_chnl.title = post_chnl_str
plot_p_chnl.index_axis.title = "Time (ns)"
plot_p_chnl.y_axis.title = "Pulse Response (V)"
plot_p_chnl.legend.visible = True
plot_p_chnl.legend.align = "ur"
zoom_p = ZoomTool(plot_p_chnl,
tool_mode="range",
axis="index",
always_on=False)
plot_p_chnl.overlays.append(zoom_p)
plot_p_tx = Plot(plotdata, padding_left=75)
plot_p_tx.plot(("t_ns_chnl", "tx_out_p"),
type="line",
color="red",
name="Cumulative")
plot_p_tx.title = post_tx_str
plot_p_tx.index_axis.title = "Time (ns)"
plot_p_tx.y_axis.title = "Pulse Response (V)"
plot_p_tx.legend.visible = True
plot_p_tx.legend.align = "ur"
plot_p_tx.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
plot_p_ctle = Plot(plotdata, padding_left=75)
plot_p_ctle.plot(("t_ns_chnl", "ctle_out_p"),
type="line",
color="red",
name="Cumulative")
plot_p_ctle.title = post_ctle_str
plot_p_ctle.index_axis.title = "Time (ns)"
plot_p_ctle.y_axis.title = "Pulse Response (V)"
plot_p_ctle.legend.visible = True
plot_p_ctle.legend.align = "ur"
plot_p_ctle.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
plot_p_dfe = Plot(plotdata, padding_left=75)
plot_p_dfe.plot(("t_ns_chnl", "dfe_out_p"),
type="line",
color="red",
name="Cumulative")
plot_p_dfe.title = post_dfe_str
plot_p_dfe.index_axis.title = "Time (ns)"
plot_p_dfe.y_axis.title = "Pulse Response (V)"
plot_p_dfe.legend.visible = True
plot_p_dfe.legend.align = "ur"
plot_p_dfe.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
container_p = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_p.add(plot_p_chnl)
container_p.add(plot_p_tx)
container_p.add(plot_p_ctle)
container_p.add(plot_p_dfe)
self.plots_p = container_p
# - Frequency Responses tab
plot_H_chnl = Plot(plotdata, padding_left=75)
plot_H_chnl.plot(("f_GHz", "chnl_H"),
type="line",
color="blue",
name="Original Impulse",
index_scale="log")
plot_H_chnl.plot(("f_GHz", "chnl_trimmed_H"),
type="line",
color="red",
name="Trimmed Impulse",
index_scale="log")
plot_H_chnl.title = post_chnl_str
plot_H_chnl.index_axis.title = "Frequency (GHz)"
plot_H_chnl.y_axis.title = "Frequency Response (dB)"
plot_H_chnl.index_range.low_setting = 0.01
plot_H_chnl.index_range.high_setting = 40.0
plot_H_chnl.legend.visible = True
plot_H_chnl.legend.align = "ll"
plot_H_tx = Plot(plotdata, padding_left=75)
plot_H_tx.plot(("f_GHz", "tx_H"),
type="line",
color="blue",
name="Incremental",
index_scale="log")
plot_H_tx.plot(("f_GHz", "tx_out_H"),
type="line",
color="red",
name="Cumulative",
index_scale="log")
plot_H_tx.title = post_tx_str
plot_H_tx.index_axis.title = "Frequency (GHz)"
plot_H_tx.y_axis.title = "Frequency Response (dB)"
plot_H_tx.index_range.low_setting = 0.01
plot_H_tx.index_range.high_setting = 40.0
plot_H_tx.legend.visible = True
plot_H_tx.legend.align = "ll"
plot_H_ctle = Plot(plotdata, padding_left=75)
plot_H_ctle.plot(("f_GHz", "ctle_H"),
type="line",
color="blue",
name="Incremental",
index_scale="log")
plot_H_ctle.plot(("f_GHz", "ctle_out_H"),
type="line",
color="red",
name="Cumulative",
index_scale="log")
plot_H_ctle.title = post_ctle_str
plot_H_ctle.index_axis.title = "Frequency (GHz)"
plot_H_ctle.y_axis.title = "Frequency Response (dB)"
plot_H_ctle.index_range.low_setting = 0.01
plot_H_ctle.index_range.high_setting = 40.0
plot_H_ctle.value_range.low_setting = -40.0
plot_H_ctle.legend.visible = True
plot_H_ctle.legend.align = "ll"
plot_H_chnl.value_range = plot_H_ctle.value_range
plot_H_tx.value_range = plot_H_ctle.value_range
plot_H_dfe = Plot(plotdata, padding_left=75)
plot_H_dfe.plot(("f_GHz", "dfe_H"),
type="line",
color="blue",
name="Incremental",
index_scale="log")
plot_H_dfe.plot(("f_GHz", "dfe_out_H"),
type="line",
color="red",
name="Cumulative",
index_scale="log")
plot_H_dfe.title = post_dfe_str
plot_H_dfe.index_axis.title = "Frequency (GHz)"
plot_H_dfe.y_axis.title = "Frequency Response (dB)"
plot_H_dfe.index_range.low_setting = 0.01
plot_H_dfe.index_range.high_setting = 40.0
plot_H_dfe.value_range = plot_H_ctle.value_range
plot_H_dfe.legend.visible = True
plot_H_dfe.legend.align = "ll"
container_H = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_H.add(plot_H_chnl)
container_H.add(plot_H_tx)
container_H.add(plot_H_ctle)
container_H.add(plot_H_dfe)
self.plots_H = container_H
# - Outputs tab
plot_out_chnl = Plot(plotdata, padding_left=75)
# plot_out_chnl.plot(("t_ns", "ideal_signal"), type="line", color="lightgrey")
plot_out_chnl.plot(("t_ns", "chnl_out"), type="line", color="blue")
plot_out_chnl.title = post_chnl_str
plot_out_chnl.index_axis.title = "Time (ns)"
plot_out_chnl.y_axis.title = "Output (V)"
plot_out_chnl.tools.append(
PanTool(plot_out_chnl,
constrain=True,
constrain_key=None,
constrain_direction="x"))
zoom_out_chnl = ZoomTool(plot_out_chnl,
tool_mode="range",
axis="index",
always_on=False)
plot_out_chnl.overlays.append(zoom_out_chnl)
plot_out_tx = Plot(plotdata, padding_left=75)
plot_out_tx.plot(("t_ns", "tx_out"), type="line", color="blue")
plot_out_tx.title = post_tx_str
plot_out_tx.index_axis.title = "Time (ns)"
plot_out_tx.y_axis.title = "Output (V)"
plot_out_tx.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
plot_out_ctle = Plot(plotdata, padding_left=75)
plot_out_ctle.plot(("t_ns", "ctle_out"), type="line", color="blue")
plot_out_ctle.title = post_ctle_str
plot_out_ctle.index_axis.title = "Time (ns)"
plot_out_ctle.y_axis.title = "Output (V)"
plot_out_ctle.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
plot_out_dfe = Plot(plotdata, padding_left=75)
plot_out_dfe.plot(("t_ns", "dfe_out"), type="line", color="blue")
plot_out_dfe.title = post_dfe_str
plot_out_dfe.index_axis.title = "Time (ns)"
plot_out_dfe.y_axis.title = "Output (V)"
plot_out_dfe.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
container_out = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_out.add(plot_out_chnl)
container_out.add(plot_out_tx)
container_out.add(plot_out_ctle)
container_out.add(plot_out_dfe)
self.plots_out = container_out
# - Eye Diagrams tab
seg_map = dict(
red=[
(0.00, 0.00, 0.00), # black
(0.00001, 0.00, 0.00), # blue
(0.15, 0.00, 0.00), # cyan
(0.30, 0.00, 0.00), # green
(0.45, 1.00, 1.00), # yellow
(0.60, 1.00, 1.00), # orange
(0.75, 1.00, 1.00), # red
(0.90, 1.00, 1.00), # pink
(1.00, 1.00, 1.00), # white
],
green=[
(0.00, 0.00, 0.00), # black
(0.00001, 0.00, 0.00), # blue
(0.15, 0.50, 0.50), # cyan
(0.30, 0.50, 0.50), # green
(0.45, 1.00, 1.00), # yellow
(0.60, 0.50, 0.50), # orange
(0.75, 0.00, 0.00), # red
(0.90, 0.50, 0.50), # pink
(1.00, 1.00, 1.00), # white
],
blue=[
(0.00, 0.00, 0.00), # black
(1e-18, 0.50, 0.50), # blue
(0.15, 0.50, 0.50), # cyan
(0.30, 0.00, 0.00), # green
(0.45, 0.00, 0.00), # yellow
(0.60, 0.00, 0.00), # orange
(0.75, 0.00, 0.00), # red
(0.90, 0.50, 0.50), # pink
(1.00, 1.00, 1.00), # white
],
)
clr_map = ColorMapper.from_segment_map(seg_map)
self.clr_map = clr_map
plot_eye_chnl = Plot(plotdata, padding_left=75)
plot_eye_chnl.img_plot("eye_chnl", colormap=clr_map)
plot_eye_chnl.y_direction = "normal"
plot_eye_chnl.components[0].y_direction = "normal"
plot_eye_chnl.title = post_chnl_str
plot_eye_chnl.x_axis.title = "Time (ps)"
plot_eye_chnl.x_axis.orientation = "bottom"
plot_eye_chnl.y_axis.title = "Signal Level (V)"
plot_eye_chnl.x_grid.visible = True
plot_eye_chnl.y_grid.visible = True
plot_eye_chnl.x_grid.line_color = "gray"
plot_eye_chnl.y_grid.line_color = "gray"
plot_eye_tx = Plot(plotdata, padding_left=75)
plot_eye_tx.img_plot("eye_tx", colormap=clr_map)
plot_eye_tx.y_direction = "normal"
plot_eye_tx.components[0].y_direction = "normal"
plot_eye_tx.title = post_tx_str
plot_eye_tx.x_axis.title = "Time (ps)"
plot_eye_tx.x_axis.orientation = "bottom"
plot_eye_tx.y_axis.title = "Signal Level (V)"
plot_eye_tx.x_grid.visible = True
plot_eye_tx.y_grid.visible = True
plot_eye_tx.x_grid.line_color = "gray"
plot_eye_tx.y_grid.line_color = "gray"
plot_eye_ctle = Plot(plotdata, padding_left=75)
plot_eye_ctle.img_plot("eye_ctle", colormap=clr_map)
plot_eye_ctle.y_direction = "normal"
plot_eye_ctle.components[0].y_direction = "normal"
plot_eye_ctle.title = post_ctle_str
plot_eye_ctle.x_axis.title = "Time (ps)"
plot_eye_ctle.x_axis.orientation = "bottom"
plot_eye_ctle.y_axis.title = "Signal Level (V)"
plot_eye_ctle.x_grid.visible = True
plot_eye_ctle.y_grid.visible = True
plot_eye_ctle.x_grid.line_color = "gray"
plot_eye_ctle.y_grid.line_color = "gray"
plot_eye_dfe = Plot(plotdata, padding_left=75)
plot_eye_dfe.img_plot("eye_dfe", colormap=clr_map)
plot_eye_dfe.y_direction = "normal"
plot_eye_dfe.components[0].y_direction = "normal"
plot_eye_dfe.title = post_dfe_str
plot_eye_dfe.x_axis.title = "Time (ps)"
plot_eye_dfe.x_axis.orientation = "bottom"
plot_eye_dfe.y_axis.title = "Signal Level (V)"
plot_eye_dfe.x_grid.visible = True
plot_eye_dfe.y_grid.visible = True
plot_eye_dfe.x_grid.line_color = "gray"
plot_eye_dfe.y_grid.line_color = "gray"
container_eye = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_eye.add(plot_eye_chnl)
container_eye.add(plot_eye_tx)
container_eye.add(plot_eye_ctle)
container_eye.add(plot_eye_dfe)
self.plots_eye = container_eye
# - Jitter Distributions tab
plot_jitter_dist_chnl = Plot(plotdata, padding_left=75)
plot_jitter_dist_chnl.plot(("jitter_bins", "jitter_chnl"),
type="line",
color="blue",
name="Measured")
plot_jitter_dist_chnl.plot(("jitter_bins", "jitter_ext_chnl"),
type="line",
color="red",
name="Extrapolated")
plot_jitter_dist_chnl.title = post_chnl_str
plot_jitter_dist_chnl.index_axis.title = "Time (ps)"
plot_jitter_dist_chnl.value_axis.title = "Count"
plot_jitter_dist_chnl.legend.visible = True
plot_jitter_dist_chnl.legend.align = "ur"
plot_jitter_dist_tx = Plot(plotdata, padding_left=75)
plot_jitter_dist_tx.plot(("jitter_bins", "jitter_tx"),
type="line",
color="blue",
name="Measured")
plot_jitter_dist_tx.plot(("jitter_bins", "jitter_ext_tx"),
type="line",
color="red",
name="Extrapolated")
plot_jitter_dist_tx.title = post_tx_str
plot_jitter_dist_tx.index_axis.title = "Time (ps)"
plot_jitter_dist_tx.value_axis.title = "Count"
plot_jitter_dist_tx.legend.visible = True
plot_jitter_dist_tx.legend.align = "ur"
plot_jitter_dist_ctle = Plot(plotdata, padding_left=75)
plot_jitter_dist_ctle.plot(("jitter_bins", "jitter_ctle"),
type="line",
color="blue",
name="Measured")
plot_jitter_dist_ctle.plot(("jitter_bins", "jitter_ext_ctle"),
type="line",
color="red",
name="Extrapolated")
plot_jitter_dist_ctle.title = post_ctle_str
plot_jitter_dist_ctle.index_axis.title = "Time (ps)"
plot_jitter_dist_ctle.value_axis.title = "Count"
plot_jitter_dist_ctle.legend.visible = True
plot_jitter_dist_ctle.legend.align = "ur"
plot_jitter_dist_dfe = Plot(plotdata, padding_left=75)
plot_jitter_dist_dfe.plot(("jitter_bins", "jitter_dfe"),
type="line",
color="blue",
name="Measured")
plot_jitter_dist_dfe.plot(("jitter_bins", "jitter_ext_dfe"),
type="line",
color="red",
name="Extrapolated")
plot_jitter_dist_dfe.title = post_dfe_str
plot_jitter_dist_dfe.index_axis.title = "Time (ps)"
plot_jitter_dist_dfe.value_axis.title = "Count"
plot_jitter_dist_dfe.legend.visible = True
plot_jitter_dist_dfe.legend.align = "ur"
container_jitter_dist = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING,
PLOT_SPACING))
container_jitter_dist.add(plot_jitter_dist_chnl)
container_jitter_dist.add(plot_jitter_dist_tx)
container_jitter_dist.add(plot_jitter_dist_ctle)
container_jitter_dist.add(plot_jitter_dist_dfe)
self.plots_jitter_dist = container_jitter_dist
# - Jitter Spectrums tab
plot_jitter_spec_chnl = Plot(plotdata)
plot_jitter_spec_chnl.plot(("f_MHz", "jitter_spectrum_chnl"),
type="line",
color="blue",
name="Total")
plot_jitter_spec_chnl.plot(("f_MHz", "jitter_ind_spectrum_chnl"),
type="line",
color="red",
name="Data Independent")
plot_jitter_spec_chnl.plot(("f_MHz", "thresh_chnl"),
type="line",
color="magenta",
name="Pj Threshold")
plot_jitter_spec_chnl.title = post_chnl_str
plot_jitter_spec_chnl.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_chnl.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_chnl.tools.append(
PanTool(plot_jitter_spec_chnl,
constrain=True,
constrain_key=None,
constrain_direction="x"))
zoom_jitter_spec_chnl = ZoomTool(plot_jitter_spec_chnl,
tool_mode="range",
axis="index",
always_on=False)
plot_jitter_spec_chnl.overlays.append(zoom_jitter_spec_chnl)
plot_jitter_spec_chnl.legend.visible = True
plot_jitter_spec_chnl.legend.align = "lr"
plot_jitter_spec_tx = Plot(plotdata)
plot_jitter_spec_tx.plot(("f_MHz", "jitter_spectrum_tx"),
type="line",
color="blue",
name="Total")
plot_jitter_spec_tx.plot(("f_MHz", "jitter_ind_spectrum_tx"),
type="line",
color="red",
name="Data Independent")
plot_jitter_spec_tx.plot(("f_MHz", "thresh_tx"),
type="line",
color="magenta",
name="Pj Threshold")
plot_jitter_spec_tx.title = post_tx_str
plot_jitter_spec_tx.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_tx.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_tx.value_range.low_setting = -40.0
plot_jitter_spec_tx.index_range = plot_jitter_spec_chnl.index_range # Zoom x-axes in tandem.
plot_jitter_spec_tx.legend.visible = True
plot_jitter_spec_tx.legend.align = "lr"
plot_jitter_spec_chnl.value_range = plot_jitter_spec_tx.value_range
plot_jitter_spec_ctle = Plot(plotdata)
plot_jitter_spec_ctle.plot(("f_MHz", "jitter_spectrum_ctle"),
type="line",
color="blue",
name="Total")
plot_jitter_spec_ctle.plot(("f_MHz", "jitter_ind_spectrum_ctle"),
type="line",
color="red",
name="Data Independent")
plot_jitter_spec_ctle.plot(("f_MHz", "thresh_ctle"),
type="line",
color="magenta",
name="Pj Threshold")
plot_jitter_spec_ctle.title = post_ctle_str
plot_jitter_spec_ctle.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_ctle.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_ctle.index_range = plot_jitter_spec_chnl.index_range # Zoom x-axes in tandem.
plot_jitter_spec_ctle.legend.visible = True
plot_jitter_spec_ctle.legend.align = "lr"
plot_jitter_spec_ctle.value_range = plot_jitter_spec_tx.value_range
plot_jitter_spec_dfe = Plot(plotdata)
plot_jitter_spec_dfe.plot(("f_MHz_dfe", "jitter_spectrum_dfe"),
type="line",
color="blue",
name="Total")
plot_jitter_spec_dfe.plot(("f_MHz_dfe", "jitter_ind_spectrum_dfe"),
type="line",
color="red",
name="Data Independent")
plot_jitter_spec_dfe.plot(("f_MHz_dfe", "thresh_dfe"),
type="line",
color="magenta",
name="Pj Threshold")
plot_jitter_spec_dfe.title = post_dfe_str
plot_jitter_spec_dfe.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_dfe.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_dfe.index_range = plot_jitter_spec_chnl.index_range # Zoom x-axes in tandem.
plot_jitter_spec_dfe.legend.visible = True
plot_jitter_spec_dfe.legend.align = "lr"
plot_jitter_spec_dfe.value_range = plot_jitter_spec_tx.value_range
container_jitter_spec = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING,
PLOT_SPACING))
container_jitter_spec.add(plot_jitter_spec_chnl)
container_jitter_spec.add(plot_jitter_spec_tx)
container_jitter_spec.add(plot_jitter_spec_ctle)
container_jitter_spec.add(plot_jitter_spec_dfe)
self.plots_jitter_spec = container_jitter_spec
# - Bathtub Curves tab
plot_bathtub_chnl = Plot(plotdata)
plot_bathtub_chnl.plot(("jitter_bins", "bathtub_chnl"),
type="line",
color="blue")
plot_bathtub_chnl.value_range.high_setting = 0
plot_bathtub_chnl.value_range.low_setting = -18
plot_bathtub_chnl.value_axis.tick_interval = 3
plot_bathtub_chnl.title = post_chnl_str
plot_bathtub_chnl.index_axis.title = "Time (ps)"
plot_bathtub_chnl.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_tx = Plot(plotdata)
plot_bathtub_tx.plot(("jitter_bins", "bathtub_tx"),
type="line",
color="blue")
plot_bathtub_tx.value_range.high_setting = 0
plot_bathtub_tx.value_range.low_setting = -18
plot_bathtub_tx.value_axis.tick_interval = 3
plot_bathtub_tx.title = post_tx_str
plot_bathtub_tx.index_axis.title = "Time (ps)"
plot_bathtub_tx.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_ctle = Plot(plotdata)
plot_bathtub_ctle.plot(("jitter_bins", "bathtub_ctle"),
type="line",
color="blue")
plot_bathtub_ctle.value_range.high_setting = 0
plot_bathtub_ctle.value_range.low_setting = -18
plot_bathtub_ctle.value_axis.tick_interval = 3
plot_bathtub_ctle.title = post_ctle_str
plot_bathtub_ctle.index_axis.title = "Time (ps)"
plot_bathtub_ctle.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_dfe = Plot(plotdata)
plot_bathtub_dfe.plot(("jitter_bins", "bathtub_dfe"),
type="line",
color="blue")
plot_bathtub_dfe.value_range.high_setting = 0
plot_bathtub_dfe.value_range.low_setting = -18
plot_bathtub_dfe.value_axis.tick_interval = 3
plot_bathtub_dfe.title = post_dfe_str
plot_bathtub_dfe.index_axis.title = "Time (ps)"
plot_bathtub_dfe.value_axis.title = "Log10(P(Transition occurs inside.))"
container_bathtub = GridPlotContainer(shape=(2, 2),
spacing=(PLOT_SPACING, PLOT_SPACING))
container_bathtub.add(plot_bathtub_chnl)
container_bathtub.add(plot_bathtub_tx)
container_bathtub.add(plot_bathtub_ctle)
container_bathtub.add(plot_bathtub_dfe)
self.plots_bathtub = container_bathtub
update_eyes(self)
def create_hplot(self, key=None, mini=False):
if mini:
hpc = HPlotContainer(bgcolor='darkgrey',
height=MINI_HEIGHT,
resizable='h',
padding=HPLOT_PADDING
)
else:
hpc = HPlotContainer(bgcolor='lightgrey',
padding=HPLOT_PADDING,
resizable='hv'
)
# make slice plot for showing intesity profile of main plot
#************************************************************
slice_plot = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM,
bgcolor='beige',
origin='top left'
)
mini_slice = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM,
bgcolor='beige',
origin='top left'
)
slice_plot.x_axis.visible = True
slice_key = key + '_slice'
ydata_key = key + '_y'
slice_plot.plot((ydata_key, slice_key), name=slice_key)
# make plot to show line at depth of cursor. y values constant
slice_depth_key = key + '_depth'
slice_plot.plot(('slice_depth_depth', 'slice_depth_y'),
name=slice_depth_key, color='red')
self.update_slice_depth_line_plot(slice_plot, depth=0)
# make main plot for editing depth lines
#************************************************************
main = Plot(self.data,
border_visible=True,
bgcolor='beige',
origin='top left',
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM
)
if mini:
#main.padding = MINI_PADDING
main.padding_bottom = MINI_PADDING_BOTTOM
# add intensity img to plot and get reference for line inspector
#************************************************************
img_plot = main.img_plot(key, name=key,
xbounds=self.model.xbounds[key],
ybounds=self.model.ybounds[key],
colormap=self._cmap
)[0]
# add line plots: use method since these may change
#************************************************************
self.update_line_plots(key, main, update=True)
self.plot_mask_array(key, main)
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add vertical core lines to main plots and slices
#************************************************************
# save pos and distance in session dict for view info and control
for core in self.model.core_samples:
# add boundarys to slice plot
self.plot_core_depths(slice_plot, core, ref_depth_line=None)
# add positions to main plots
self.plot_core(main, core, ref_depth_line=None)
# now add tools depending if it is a mini plot or not
#************************************************************
if mini:
# add range selection tool only
# first add a reference line to attach it to
reference = self.make_reference_plot()
main.add(reference)
main.plots['reference'] = [reference]
# attache range selector to this plot
range_tool = RangeSelection(reference)
reference.tools.append(range_tool)
range_overlay = RangeSelectionOverlay(reference,
metadata_name="selections")
reference.overlays.append(range_overlay)
range_tool.on_trait_change(self._range_selection_handler,
"selection")
# add zoombox to mini plot
main.plot(('zoombox_x', 'zoombox_y'), type='polygon',
face_color=ZOOMBOX_COLOR, alpha=ZOOMBOX_ALPHA)
# add to hplot and dict
hpc.add(main, mini_slice)
self.hplot_dict['mini'] = hpc
else:
# add zoom tools
zoom = ZoomTool(main, tool_mode='box', axis='both', alpha=0.5,
drag_button="left")
main.tools.append(zoom)
main.overlays.append(zoom)
self.zoom_tools[key] = zoom
main.value_mapper.on_trait_change(self.zoom_all_value, 'updated')
main.index_mapper.on_trait_change(self.zoom_all_index, 'updated')
# add line inspector and attach to freeze tool
#*********************************************
line_inspector = LineInspector(component=img_plot,
axis='index_x',
inspect_mode="indexed",
is_interactive=True,
write_metadata=True,
metadata_name='x_slice',
is_listener=True,
color="white")
img_plot.overlays.append(line_inspector)
self.inspector_freeze_tool.tool_set.add(line_inspector)
# add listener for changes to metadata made by line inspector
#************************************************************
img_plot.on_trait_change(self.metadata_changed, 'index.metadata')
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add clickable legend ; must update legend when depth_dict updated
#******************************************************************
legend = Legend(component=main, padding=0,
align="ur", font='modern 8')
legend_highlighter = LegendHighlighter(legend,
drag_button="right")
legend.tools.append(legend_highlighter)
self.legend_dict[key] = [legend, legend_highlighter]
self.update_legend_plots(legend, main)
legend.visible = False
main.overlays.append(legend)
legend_highlighter.on_trait_change(self.legend_moved, '_drag_state')
# add pan tool
pan_tool = PanTool(main, drag_button="right")
main.tools.append(pan_tool)
self.pan_tool_dict[key] = pan_tool
# add main and slice plot to hplot container and dict
#****************************************************
main.title = 'frequency = {} kHz'.format(key)
main.title_font = TITLE_FONT
hpc.add(main, slice_plot)
self.hplot_dict[key] = hpc
return hpc
def make_plots(self, n_dfe_taps):
""" Create the plots used by the PyBERT GUI."""
plotdata = self.plotdata
# - DFE tab
plot1 = Plot(plotdata)
plot1.plot(("t_ns", "dfe_out"), type="line", color="blue")
plot1.plot(("t_ns", "clocks"), type="line", color="green")
plot1.plot(("t_ns", "lockeds"), type="line", color="red")
plot1.title = "DFE Output, Recovered Clocks, & Locked"
plot1.index_axis.title = "Time (ns)"
plot1.tools.append(PanTool(plot1, constrain=True, constrain_key=None, constrain_direction='x'))
zoom1 = ZoomTool(plot1, tool_mode="range", axis='index', always_on=False)
plot1.overlays.append(zoom1)
plot2 = Plot(plotdata)
plot2.plot(("t_ns", "ui_ests"), type="line", color="blue")
plot2.title = "CDR Adaptation"
plot2.index_axis.title = "Time (ns)"
plot2.value_axis.title = "UI (ps)"
plot2.index_range = plot1.index_range # Zoom x-axes in tandem.
plot3 = Plot(plotdata)
plot3.plot(('f_MHz_dfe', 'jitter_rejection_ratio'), type="line", color="blue")
plot3.title = "CDR/DFE Jitter Rejection Ratio"
plot3.index_axis.title = "Frequency (MHz)"
plot3.value_axis.title = "Ratio (dB)"
zoom3 = ZoomTool(plot3, tool_mode="range", axis='index', always_on=False)
plot3.overlays.append(zoom3)
plot4 = Plot(plotdata)
plot4.plot(('auto_corr'), type="line", color="blue")
plot4.title = "Received to Transmitted Bits Correlation"
plot4.index_axis.title = "Offset (bits)"
plot4.value_axis.title = "Correlation"
plot4.value_range.high_setting = 1
plot4.value_range.low_setting = 0
zoom4 = ZoomTool(plot4, tool_mode="range", axis='index', always_on=False)
plot4.overlays.append(zoom4)
plot9 = Plot(plotdata, auto_colors=['red', 'orange', 'yellow', 'green', 'blue', 'purple'])
for i in range(n_dfe_taps):
plot9.plot(("tap_weight_index", "tap%d_weights" % (i + 1)), type="line", color="auto", name="tap%d"%(i+1))
plot9.title = "DFE Adaptation"
plot9.tools.append(PanTool(plot9, constrain=True, constrain_key=None, constrain_direction='x'))
zoom9 = ZoomTool(plot9, tool_mode="range", axis='index', always_on=False)
plot9.overlays.append(zoom9)
plot9.legend.visible = True
plot9.legend.align = 'ul'
plot_clk_per_hist = Plot(plotdata)
plot_clk_per_hist.plot(('clk_per_hist_bins', 'clk_per_hist_vals'), type="line", color="blue")
plot_clk_per_hist.title = "CDR Clock Period Histogram"
plot_clk_per_hist.index_axis.title = "Clock Period (ps)"
plot_clk_per_hist.value_axis.title = "Bin Count"
plot_clk_per_spec = Plot(plotdata)
plot_clk_per_spec.plot(('clk_freqs', 'clk_spec'), type="line", color="blue")
plot_clk_per_spec.title = "CDR Clock Period Spectrum"
plot_clk_per_spec.index_axis.title = "Frequency (bit rate)"
plot_clk_per_spec.value_axis.title = "|H(f)| (dB mean)"
plot_clk_per_spec.value_range.low_setting = -10
zoom_clk_per_spec = ZoomTool(plot_clk_per_spec, tool_mode="range", axis='index', always_on=False)
plot_clk_per_spec.overlays.append(zoom_clk_per_spec)
container_dfe = GridPlotContainer(shape=(2,2))
container_dfe.add(plot2)
container_dfe.add(plot9)
container_dfe.add(plot_clk_per_hist)
container_dfe.add(plot_clk_per_spec)
self.plots_dfe = container_dfe
# - EQ Tune tab
plot_h_tune = Plot(plotdata)
plot_h_tune.plot(("t_ns_chnl", "ctle_out_h_tune"), type="line", color="red", name="Cumulative")
plot_h_tune.plot(("t_ns_chnl", "ctle_out_g_tune"), type="line", color="gray")
plot_h_tune.title = "Channel + Tx Preemphasis + CTLE"
plot_h_tune.index_axis.title = "Time (ns)"
plot_h_tune.y_axis.title = "Response"
zoom_tune = ZoomTool(plot_h_tune, tool_mode="range", axis='index', always_on=False)
plot_h_tune.overlays.append(zoom_tune)
self.plot_h_tune = plot_h_tune
# - Impulse Responses tab
plot_h_chnl = Plot(plotdata)
plot_h_chnl.plot(("t_ns_chnl", "chnl_h"), type="line", color="blue")
plot_h_chnl.title = "Channel"
plot_h_chnl.index_axis.title = "Time (ns)"
plot_h_chnl.y_axis.title = "Impulse Response (V/ns)"
zoom_h = ZoomTool(plot_h_chnl, tool_mode="range", axis='index', always_on=False)
plot_h_chnl.overlays.append(zoom_h)
plot_h_tx = Plot(plotdata)
plot_h_tx.plot(("t_ns_chnl", "tx_out_h"), type="line", color="red", name="Cumulative")
plot_h_tx.title = "Channel + Tx Preemphasis"
plot_h_tx.index_axis.title = "Time (ns)"
plot_h_tx.y_axis.title = "Impulse Response (V/ns)"
plot_h_tx.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
plot_h_ctle = Plot(plotdata)
plot_h_ctle.plot(("t_ns_chnl", "ctle_out_h"), type="line", color="red", name="Cumulative")
plot_h_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_h_ctle.index_axis.title = "Time (ns)"
plot_h_ctle.y_axis.title = "Impulse Response (V/ns)"
plot_h_ctle.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
plot_h_dfe = Plot(plotdata)
plot_h_dfe.plot(("t_ns_chnl", "dfe_out_h"), type="line", color="red", name="Cumulative")
plot_h_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_h_dfe.index_axis.title = "Time (ns)"
plot_h_dfe.y_axis.title = "Impulse Response (V/ns)"
plot_h_dfe.index_range = plot_h_chnl.index_range # Zoom x-axes in tandem.
container_h = GridPlotContainer(shape=(2,2))
container_h.add(plot_h_chnl)
container_h.add(plot_h_tx)
container_h.add(plot_h_ctle)
container_h.add(plot_h_dfe)
self.plots_h = container_h
# - Step Responses tab
plot_s_chnl = Plot(plotdata)
plot_s_chnl.plot(("t_ns_chnl", "chnl_s"), type="line", color="blue")
plot_s_chnl.title = "Channel"
plot_s_chnl.index_axis.title = "Time (ns)"
plot_s_chnl.y_axis.title = "Step Response (V)"
zoom_s = ZoomTool(plot_s_chnl, tool_mode="range", axis='index', always_on=False)
plot_s_chnl.overlays.append(zoom_s)
plot_s_tx = Plot(plotdata)
plot_s_tx.plot(("t_ns_chnl", "tx_s"), type="line", color="blue", name="Incremental")
plot_s_tx.plot(("t_ns_chnl", "tx_out_s"), type="line", color="red", name="Cumulative")
plot_s_tx.title = "Channel + Tx Preemphasis"
plot_s_tx.index_axis.title = "Time (ns)"
plot_s_tx.y_axis.title = "Step Response (V)"
plot_s_tx.legend.visible = True
plot_s_tx.legend.align = 'lr'
plot_s_tx.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
plot_s_ctle = Plot(plotdata)
plot_s_ctle.plot(("t_ns_chnl", "ctle_s"), type="line", color="blue", name="Incremental")
plot_s_ctle.plot(("t_ns_chnl", "ctle_out_s"), type="line", color="red", name="Cumulative")
plot_s_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_s_ctle.index_axis.title = "Time (ns)"
plot_s_ctle.y_axis.title = "Step Response (V)"
plot_s_ctle.legend.visible = True
plot_s_ctle.legend.align = 'lr'
plot_s_ctle.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
plot_s_dfe = Plot(plotdata)
plot_s_dfe.plot(("t_ns_chnl", "dfe_s"), type="line", color="blue", name="Incremental")
plot_s_dfe.plot(("t_ns_chnl", "dfe_out_s"), type="line", color="red", name="Cumulative")
plot_s_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_s_dfe.index_axis.title = "Time (ns)"
plot_s_dfe.y_axis.title = "Step Response (V)"
plot_s_dfe.legend.visible = True
plot_s_dfe.legend.align = 'lr'
plot_s_dfe.index_range = plot_s_chnl.index_range # Zoom x-axes in tandem.
container_s = GridPlotContainer(shape=(2,2))
container_s.add(plot_s_chnl)
container_s.add(plot_s_tx)
container_s.add(plot_s_ctle)
container_s.add(plot_s_dfe)
self.plots_s = container_s
# - Pulse Responses tab
plot_p_chnl = Plot(plotdata)
plot_p_chnl.plot(("t_ns_chnl", "chnl_p"), type="line", color="blue")
plot_p_chnl.title = "Channel"
plot_p_chnl.index_axis.title = "Time (ns)"
plot_p_chnl.y_axis.title = "Pulse Response (V)"
zoom_p = ZoomTool(plot_p_chnl, tool_mode="range", axis='index', always_on=False)
plot_p_chnl.overlays.append(zoom_p)
plot_p_tx = Plot(plotdata)
plot_p_tx.plot(("t_ns_chnl", "tx_out_p"), type="line", color="red", name="Cumulative")
plot_p_tx.title = "Channel + Tx Preemphasis"
plot_p_tx.index_axis.title = "Time (ns)"
plot_p_tx.y_axis.title = "Pulse Response (V)"
plot_p_tx.legend.align = 'lr'
plot_p_tx.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
plot_p_ctle = Plot(plotdata)
plot_p_ctle.plot(("t_ns_chnl", "ctle_out_p"), type="line", color="red", name="Cumulative")
plot_p_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_p_ctle.index_axis.title = "Time (ns)"
plot_p_ctle.y_axis.title = "Pulse Response (V)"
plot_p_ctle.legend.align = 'lr'
plot_p_ctle.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
plot_p_dfe = Plot(plotdata)
plot_p_dfe.plot(("t_ns_chnl", "dfe_out_p"), type="line", color="red", name="Cumulative")
plot_p_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_p_dfe.index_axis.title = "Time (ns)"
plot_p_dfe.y_axis.title = "Pulse Response (V)"
plot_p_dfe.legend.align = 'lr'
plot_p_dfe.index_range = plot_p_chnl.index_range # Zoom x-axes in tandem.
container_p = GridPlotContainer(shape=(2,2))
container_p.add(plot_p_chnl)
container_p.add(plot_p_tx)
container_p.add(plot_p_ctle)
container_p.add(plot_p_dfe)
self.plots_p = container_p
# - Frequency Responses tab
plot_H_chnl = Plot(plotdata)
plot_H_chnl.plot(("f_GHz", "chnl_H"), type="line", color="blue", index_scale='log')
plot_H_chnl.title = "Channel"
plot_H_chnl.index_axis.title = "Frequency (GHz)"
plot_H_chnl.y_axis.title = "Frequency Response (dB)"
plot_H_chnl.index_range.low_setting = 0.01
plot_H_chnl.index_range.high_setting = 40.
plot_H_tx = Plot(plotdata)
plot_H_tx.plot(("f_GHz", "tx_H"), type="line", color="blue", name="Incremental", index_scale='log')
plot_H_tx.plot(("f_GHz", "tx_out_H"), type="line", color="red", name="Cumulative", index_scale='log')
plot_H_tx.title = "Channel + Tx Preemphasis"
plot_H_tx.index_axis.title = "Frequency (GHz)"
plot_H_tx.y_axis.title = "Frequency Response (dB)"
plot_H_tx.index_range.low_setting = 0.01
plot_H_tx.index_range.high_setting = 40.
plot_H_tx.legend.visible = True
plot_H_tx.legend.align = 'll'
plot_H_ctle = Plot(plotdata)
plot_H_ctle.plot(("f_GHz", "ctle_H"), type="line", color="blue", name="Incremental", index_scale='log')
plot_H_ctle.plot(("f_GHz", "ctle_out_H"), type="line", color="red", name="Cumulative", index_scale='log')
plot_H_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_H_ctle.index_axis.title = "Frequency (GHz)"
plot_H_ctle.y_axis.title = "Frequency Response (dB)"
plot_H_ctle.index_range.low_setting = 0.01
plot_H_ctle.index_range.high_setting = 40.
plot_H_ctle.value_range.low_setting = -40.
plot_H_ctle.legend.visible = True
plot_H_ctle.legend.align = 'll'
plot_H_chnl.value_range = plot_H_ctle.value_range
plot_H_tx.value_range = plot_H_ctle.value_range
plot_H_dfe = Plot(plotdata)
plot_H_dfe.plot(("f_GHz", "dfe_H"), type="line", color="blue", name="Incremental", index_scale='log')
plot_H_dfe.plot(("f_GHz", "dfe_out_H"), type="line", color="red", name="Cumulative", index_scale='log')
plot_H_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_H_dfe.index_axis.title = "Frequency (GHz)"
plot_H_dfe.y_axis.title = "Frequency Response (dB)"
plot_H_dfe.index_range.low_setting = 0.01
plot_H_dfe.index_range.high_setting = 40.
plot_H_dfe.value_range = plot_H_ctle.value_range
plot_H_dfe.legend.visible = True
plot_H_dfe.legend.align = 'll'
container_H = GridPlotContainer(shape=(2,2))
container_H.add(plot_H_chnl)
container_H.add(plot_H_tx)
container_H.add(plot_H_ctle)
container_H.add(plot_H_dfe)
self.plots_H = container_H
# - Outputs tab
plot_out_chnl = Plot(plotdata)
plot_out_chnl.plot(("t_ns", "ideal_signal"), type="line", color="lightgrey")
plot_out_chnl.plot(("t_ns", "chnl_out"), type="line", color="blue")
plot_out_chnl.title = "Channel"
plot_out_chnl.index_axis.title = "Time (ns)"
plot_out_chnl.y_axis.title = "Output (V)"
zoom_out_chnl = ZoomTool(plot_out_chnl, tool_mode="range", axis='index', always_on=False)
plot_out_chnl.overlays.append(zoom_out_chnl)
plot_out_tx = Plot(plotdata)
plot_out_tx.plot(("t_ns", "tx_out"), type="line", color="blue")
plot_out_tx.title = "Channel + Tx Preemphasis (Noise added here.)"
plot_out_tx.index_axis.title = "Time (ns)"
plot_out_tx.y_axis.title = "Output (V)"
plot_out_tx.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
plot_out_ctle = Plot(plotdata)
plot_out_ctle.plot(("t_ns", "ctle_out"), type="line", color="blue")
plot_out_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_out_ctle.index_axis.title = "Time (ns)"
plot_out_ctle.y_axis.title = "Output (V)"
plot_out_ctle.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
plot_out_dfe = Plot(plotdata)
plot_out_dfe.plot(("t_ns", "dfe_out"), type="line", color="blue")
plot_out_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_out_dfe.index_axis.title = "Time (ns)"
plot_out_dfe.y_axis.title = "Output (V)"
plot_out_dfe.index_range = plot_out_chnl.index_range # Zoom x-axes in tandem.
container_out = GridPlotContainer(shape=(2,2))
container_out.add(plot_out_chnl)
container_out.add(plot_out_tx)
container_out.add(plot_out_ctle)
container_out.add(plot_out_dfe)
self.plots_out = container_out
# - Eye Diagrams tab
seg_map = dict(
red = [
(0.00, 0.00, 0.00), # black
(0.00001, 0.00, 0.00), # blue
(0.15, 0.00, 0.00), # cyan
(0.30, 0.00, 0.00), # green
(0.45, 1.00, 1.00), # yellow
(0.60, 1.00, 1.00), # orange
(0.75, 1.00, 1.00), # red
(0.90, 1.00, 1.00), # pink
(1.00, 1.00, 1.00) # white
],
green = [
(0.00, 0.00, 0.00), # black
(0.00001, 0.00, 0.00), # blue
(0.15, 0.50, 0.50), # cyan
(0.30, 0.50, 0.50), # green
(0.45, 1.00, 1.00), # yellow
(0.60, 0.50, 0.50), # orange
(0.75, 0.00, 0.00), # red
(0.90, 0.50, 0.50), # pink
(1.00, 1.00, 1.00) # white
],
blue = [
(0.00, 0.00, 0.00), # black
(1e-18, 0.50, 0.50), # blue
(0.15, 0.50, 0.50), # cyan
(0.30, 0.00, 0.00), # green
(0.45, 0.00, 0.00), # yellow
(0.60, 0.00, 0.00), # orange
(0.75, 0.00, 0.00), # red
(0.90, 0.50, 0.50), # pink
(1.00, 1.00, 1.00) # white
]
)
clr_map = ColorMapper.from_segment_map(seg_map)
self.clr_map = clr_map
plot_eye_chnl = Plot(plotdata)
plot_eye_chnl.img_plot("eye_chnl", colormap=clr_map,)
plot_eye_chnl.y_direction = 'normal'
plot_eye_chnl.components[0].y_direction = 'normal'
plot_eye_chnl.title = "Channel"
plot_eye_chnl.x_axis.title = "Time (ps)"
plot_eye_chnl.x_axis.orientation = "bottom"
plot_eye_chnl.y_axis.title = "Signal Level (V)"
plot_eye_chnl.x_grid.visible = True
plot_eye_chnl.y_grid.visible = True
plot_eye_chnl.x_grid.line_color = 'gray'
plot_eye_chnl.y_grid.line_color = 'gray'
plot_eye_tx = Plot(plotdata)
plot_eye_tx.img_plot("eye_tx", colormap=clr_map,)
plot_eye_tx.y_direction = 'normal'
plot_eye_tx.components[0].y_direction = 'normal'
plot_eye_tx.title = "Channel + Tx Preemphasis (Noise added here.)"
plot_eye_tx.x_axis.title = "Time (ps)"
plot_eye_tx.x_axis.orientation = "bottom"
plot_eye_tx.y_axis.title = "Signal Level (V)"
plot_eye_tx.x_grid.visible = True
plot_eye_tx.y_grid.visible = True
plot_eye_tx.x_grid.line_color = 'gray'
plot_eye_tx.y_grid.line_color = 'gray'
plot_eye_ctle = Plot(plotdata)
plot_eye_ctle.img_plot("eye_ctle", colormap=clr_map,)
plot_eye_ctle.y_direction = 'normal'
plot_eye_ctle.components[0].y_direction = 'normal'
plot_eye_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_eye_ctle.x_axis.title = "Time (ps)"
plot_eye_ctle.x_axis.orientation = "bottom"
plot_eye_ctle.y_axis.title = "Signal Level (V)"
plot_eye_ctle.x_grid.visible = True
plot_eye_ctle.y_grid.visible = True
plot_eye_ctle.x_grid.line_color = 'gray'
plot_eye_ctle.y_grid.line_color = 'gray'
plot_eye_dfe = Plot(plotdata)
plot_eye_dfe.img_plot("eye_dfe", colormap=clr_map,)
plot_eye_dfe.y_direction = 'normal'
plot_eye_dfe.components[0].y_direction = 'normal'
plot_eye_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_eye_dfe.x_axis.title = "Time (ps)"
plot_eye_dfe.x_axis.orientation = "bottom"
plot_eye_dfe.y_axis.title = "Signal Level (V)"
plot_eye_dfe.x_grid.visible = True
plot_eye_dfe.y_grid.visible = True
plot_eye_dfe.x_grid.line_color = 'gray'
plot_eye_dfe.y_grid.line_color = 'gray'
container_eye = GridPlotContainer(shape=(2,2))
container_eye.add(plot_eye_chnl)
container_eye.add(plot_eye_tx)
container_eye.add(plot_eye_ctle)
container_eye.add(plot_eye_dfe)
self.plots_eye = container_eye
# - Jitter Distributions tab
plot_jitter_dist_chnl = Plot(plotdata)
plot_jitter_dist_chnl.plot(('jitter_bins', 'jitter_chnl'), type="line", color="blue", name="Measured")
plot_jitter_dist_chnl.plot(('jitter_bins', 'jitter_ext_chnl'), type="line", color="red", name="Extrapolated")
plot_jitter_dist_chnl.title = "Channel"
plot_jitter_dist_chnl.index_axis.title = "Time (ps)"
plot_jitter_dist_chnl.value_axis.title = "Count"
plot_jitter_dist_chnl.legend.visible = True
plot_jitter_dist_chnl.legend.align = 'ur'
plot_jitter_dist_tx = Plot(plotdata)
plot_jitter_dist_tx.plot(('jitter_bins', 'jitter_tx'), type="line", color="blue", name="Measured")
plot_jitter_dist_tx.plot(('jitter_bins', 'jitter_ext_tx'), type="line", color="red", name="Extrapolated")
plot_jitter_dist_tx.title = "Channel + Tx Preemphasis (Noise added here.)"
plot_jitter_dist_tx.index_axis.title = "Time (ps)"
plot_jitter_dist_tx.value_axis.title = "Count"
plot_jitter_dist_tx.legend.visible = True
plot_jitter_dist_tx.legend.align = 'ur'
plot_jitter_dist_ctle = Plot(plotdata)
plot_jitter_dist_ctle.plot(('jitter_bins', 'jitter_ctle'), type="line", color="blue", name="Measured")
plot_jitter_dist_ctle.plot(('jitter_bins', 'jitter_ext_ctle'), type="line", color="red", name="Extrapolated")
plot_jitter_dist_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_jitter_dist_ctle.index_axis.title = "Time (ps)"
plot_jitter_dist_ctle.value_axis.title = "Count"
plot_jitter_dist_ctle.legend.visible = True
plot_jitter_dist_ctle.legend.align = 'ur'
plot_jitter_dist_dfe = Plot(plotdata)
plot_jitter_dist_dfe.plot(('jitter_bins', 'jitter_dfe'), type="line", color="blue", name="Measured")
plot_jitter_dist_dfe.plot(('jitter_bins', 'jitter_ext_dfe'), type="line", color="red", name="Extrapolated")
plot_jitter_dist_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_jitter_dist_dfe.index_axis.title = "Time (ps)"
plot_jitter_dist_dfe.value_axis.title = "Count"
plot_jitter_dist_dfe.legend.visible = True
plot_jitter_dist_dfe.legend.align = 'ur'
container_jitter_dist = GridPlotContainer(shape=(2,2))
container_jitter_dist.add(plot_jitter_dist_chnl)
container_jitter_dist.add(plot_jitter_dist_tx)
container_jitter_dist.add(plot_jitter_dist_ctle)
container_jitter_dist.add(plot_jitter_dist_dfe)
self.plots_jitter_dist = container_jitter_dist
# - Jitter Spectrums tab
plot_jitter_spec_chnl = Plot(plotdata)
plot_jitter_spec_chnl.plot(('f_MHz', 'jitter_spectrum_chnl'), type="line", color="blue", name="Total")
plot_jitter_spec_chnl.plot(('f_MHz', 'jitter_ind_spectrum_chnl'), type="line", color="red", name="Data Independent")
plot_jitter_spec_chnl.plot(('f_MHz', 'thresh_chnl'), type="line", color="magenta", name="Pj Threshold")
plot_jitter_spec_chnl.title = "Channel"
plot_jitter_spec_chnl.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_chnl.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_chnl.tools.append(PanTool(plot_jitter_spec_chnl, constrain=True, constrain_key=None, constrain_direction='x'))
zoom_jitter_spec_chnl = ZoomTool(plot_jitter_spec_chnl, tool_mode="range", axis='index', always_on=False)
plot_jitter_spec_chnl.overlays.append(zoom_jitter_spec_chnl)
plot_jitter_spec_chnl.legend.visible = True
plot_jitter_spec_chnl.legend.align = 'lr'
plot_jitter_spec_tx = Plot(plotdata)
plot_jitter_spec_tx.plot(('f_MHz', 'jitter_spectrum_tx'), type="line", color="blue", name="Total")
plot_jitter_spec_tx.plot(('f_MHz', 'jitter_ind_spectrum_tx'), type="line", color="red", name="Data Independent")
plot_jitter_spec_tx.plot(('f_MHz', 'thresh_tx'), type="line", color="magenta", name="Pj Threshold")
plot_jitter_spec_tx.title = "Channel + Tx Preemphasis (Noise added here.)"
plot_jitter_spec_tx.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_tx.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_tx.value_range.low_setting = -40.
plot_jitter_spec_tx.tools.append(PanTool(plot_jitter_spec_tx, constrain=True, constrain_key=None, constrain_direction='x'))
zoom_jitter_spec_tx = ZoomTool(plot_jitter_spec_tx, tool_mode="range", axis='index', always_on=False)
plot_jitter_spec_tx.overlays.append(zoom_jitter_spec_tx)
plot_jitter_spec_tx.legend.visible = True
plot_jitter_spec_tx.legend.align = 'lr'
plot_jitter_spec_chnl.value_range = plot_jitter_spec_tx.value_range
plot_jitter_spec_ctle = Plot(plotdata)
plot_jitter_spec_ctle.plot(('f_MHz', 'jitter_spectrum_ctle'), type="line", color="blue", name="Total")
plot_jitter_spec_ctle.plot(('f_MHz', 'jitter_ind_spectrum_ctle'), type="line", color="red", name="Data Independent")
plot_jitter_spec_ctle.plot(('f_MHz', 'thresh_ctle'), type="line", color="magenta", name="Pj Threshold")
plot_jitter_spec_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_jitter_spec_ctle.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_ctle.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_ctle.tools.append(PanTool(plot_jitter_spec_ctle, constrain=True, constrain_key=None, constrain_direction='x'))
zoom_jitter_spec_ctle = ZoomTool(plot_jitter_spec_ctle, tool_mode="range", axis='index', always_on=False)
plot_jitter_spec_ctle.overlays.append(zoom_jitter_spec_ctle)
plot_jitter_spec_ctle.legend.visible = True
plot_jitter_spec_ctle.legend.align = 'lr'
plot_jitter_spec_ctle.value_range = plot_jitter_spec_tx.value_range
plot_jitter_spec_dfe = Plot(plotdata)
plot_jitter_spec_dfe.plot(('f_MHz_dfe', 'jitter_spectrum_dfe'), type="line", color="blue", name="Total")
plot_jitter_spec_dfe.plot(('f_MHz_dfe', 'jitter_ind_spectrum_dfe'), type="line", color="red", name="Data Independent")
plot_jitter_spec_dfe.plot(('f_MHz_dfe', 'thresh_dfe'), type="line", color="magenta", name="Pj Threshold")
plot_jitter_spec_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_jitter_spec_dfe.index_axis.title = "Frequency (MHz)"
plot_jitter_spec_dfe.value_axis.title = "|FFT(TIE)| (dBui)"
plot_jitter_spec_dfe.tools.append(PanTool(plot_jitter_spec_dfe, constrain=True, constrain_key=None, constrain_direction='x'))
zoom_jitter_spec_dfe = ZoomTool(plot_jitter_spec_dfe, tool_mode="range", axis='index', always_on=False)
plot_jitter_spec_dfe.overlays.append(zoom_jitter_spec_dfe)
plot_jitter_spec_dfe.legend.visible = True
plot_jitter_spec_dfe.legend.align = 'lr'
plot_jitter_spec_dfe.value_range = plot_jitter_spec_tx.value_range
container_jitter_spec = GridPlotContainer(shape=(2,2))
container_jitter_spec.add(plot_jitter_spec_chnl)
container_jitter_spec.add(plot_jitter_spec_tx)
container_jitter_spec.add(plot_jitter_spec_ctle)
container_jitter_spec.add(plot_jitter_spec_dfe)
self.plots_jitter_spec = container_jitter_spec
# - Bathtub Curves tab
plot_bathtub_chnl = Plot(plotdata)
plot_bathtub_chnl.plot(("jitter_bins", "bathtub_chnl"), type="line", color="blue")
plot_bathtub_chnl.value_range.high_setting = 0
plot_bathtub_chnl.value_range.low_setting = -18
plot_bathtub_chnl.value_axis.tick_interval = 3
plot_bathtub_chnl.title = "Channel"
plot_bathtub_chnl.index_axis.title = "Time (ps)"
plot_bathtub_chnl.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_tx = Plot(plotdata)
plot_bathtub_tx.plot(("jitter_bins", "bathtub_tx"), type="line", color="blue")
plot_bathtub_tx.value_range.high_setting = 0
plot_bathtub_tx.value_range.low_setting = -18
plot_bathtub_tx.value_axis.tick_interval = 3
plot_bathtub_tx.title = "Channel + Tx Preemphasis (Noise added here.)"
plot_bathtub_tx.index_axis.title = "Time (ps)"
plot_bathtub_tx.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_ctle = Plot(plotdata)
plot_bathtub_ctle.plot(("jitter_bins", "bathtub_ctle"), type="line", color="blue")
plot_bathtub_ctle.value_range.high_setting = 0
plot_bathtub_ctle.value_range.low_setting = -18
plot_bathtub_ctle.value_axis.tick_interval = 3
plot_bathtub_ctle.title = "Channel + Tx Preemphasis + CTLE"
plot_bathtub_ctle.index_axis.title = "Time (ps)"
plot_bathtub_ctle.value_axis.title = "Log10(P(Transition occurs inside.))"
plot_bathtub_dfe = Plot(plotdata)
plot_bathtub_dfe.plot(("jitter_bins", "bathtub_dfe"), type="line", color="blue")
plot_bathtub_dfe.value_range.high_setting = 0
plot_bathtub_dfe.value_range.low_setting = -18
plot_bathtub_dfe.value_axis.tick_interval = 3
plot_bathtub_dfe.title = "Channel + Tx Preemphasis + CTLE + DFE"
plot_bathtub_dfe.index_axis.title = "Time (ps)"
plot_bathtub_dfe.value_axis.title = "Log10(P(Transition occurs inside.))"
container_bathtub = GridPlotContainer(shape=(2,2))
container_bathtub.add(plot_bathtub_chnl)
container_bathtub.add(plot_bathtub_tx)
container_bathtub.add(plot_bathtub_ctle)
container_bathtub.add(plot_bathtub_dfe)
self.plots_bathtub = container_bathtub
update_eyes(self)
return
def _create_plot_component():
army_lat = np.column_stack([army['start_lat'],
army['end_lat']]).reshape(-1)
army_lon = np.column_stack([army['start_lon'],
army['end_lon']]).reshape(-1)
plot_data = ArrayPlotData(
army_lon=army_lon,
army_lat=army_lat,
army_size=army['size'],
army_color=army['direction'] * army["group"],
towns_lat=towns['lat'],
towns_lon=towns['lon'],
towns=towns['town'],
temp_lon=temperatures['lon'],
temp=temperatures['temp'],
temp_date=temperatures['date'],
)
map_plot = Plot(plot_data)
map_plot.x_grid = None
map_plot.y_grid = None
map_plot.x_axis.orientation = 'top'
map_plot.x_axis.title = 'Longitude'
map_plot.y_axis.title = 'Latitude'
map_plot.title = "Minard's Map of Napoleon's Russian Campaign"
map_plot._title.overlay_position = "inside top"
map_plot._title.hjustify = "left"
map_plot._title.vjustify = "bottom"
map_plot.plot(
("army_lon", "army_lat", "army_color", "army_size"),
type="cmap_segment",
name="my_plot",
color_mapper=viridis,
border_visible=True,
bgcolor="white",
size_min=1.0,
size_max=128.0,
)
map_plot.plot(
("towns_lon", "towns_lat"),
type="scatter",
)
map_plot.plot(
("towns_lon", "towns_lat", "towns"),
type="text",
text_margin=4,
h_position='right',
text_offset=(4, 0),
)
map_plot.plot_1d(
('temp_lon'),
type='line_scatter_1d',
alpha=0.5,
line_style='dot',
)
map_plot.index_range.high_setting = 38
map_plot.index_range.low_setting = 23
map_plot.value_range.high_setting = 56.0
map_plot.value_range.low_setting = 53.5
map_plot.tools.extend([
PanTool(map_plot),
ZoomTool(map_plot),
])
temp_plot = Plot(plot_data, height=100)
temp_plot.index_range = map_plot.index_range
temp_plot.x_grid = None
temp_plot.x_axis = None
temp_plot.y_axis.orientation = 'right'
temp_plot.y_axis.title = u'Temp (°Re)'
temp_plot.plot(
('temp_lon', 'temp'),
type='line',
)
temp_plot.plot_1d(
('temp_lon'),
type='line_scatter_1d',
alpha=0.5,
line_style='dot',
)
temp_plot.plot_1d(
('temp_lon', 'temp_date'),
type='textplot_1d',
alpha=0.5,
line_style='dot',
alignment='bottom',
)
temp_plot.value_range.high_setting = 5
temp_plot.value_range.low_setting = -35
container = VPlotContainer(temp_plot, map_plot)
container.spacing = 0
map_plot.padding_bottom = 0
map_plot.padding_left = 70
map_plot.padding_right = 70
map_plot.padding_top = 50
temp_plot.padding_top = 0
temp_plot.padding_bottom = 15
temp_plot.padding_right = 70
temp_plot.padding_left = 70
temp_plot.height = 100
temp_plot.resizable = 'h'
return container
def create_hplot(self, key=None, mini=False):
if mini:
hpc = HPlotContainer(bgcolor='darkgrey',
height=MINI_HEIGHT,
resizable='h',
padding=0)
else:
hpc = HPlotContainer(bgcolor='lightgrey',
padding=HPLOT_PADDING,
resizable='hv')
# make slice plot for showing intesity profile of main plot
#************************************************************
slice_plot = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
bgcolor='beige',
origin='top left')
slice_plot.x_axis.visible = False
slice_key = key + '_slice'
ydata_key = key + '_y'
slice_plot.plot((ydata_key, slice_key), name=slice_key)
# make main plot for editing depth lines
#************************************************************
main = Plot(
self.data,
border_visible=True,
bgcolor='beige',
origin='top left',
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
)
if mini:
main.padding = MINI_PADDING
# add intensity img to plot and get reference for line inspector
#************************************************************
img_plot = main.img_plot(key,
name=key,
xbounds=self.model.xbounds[key],
ybounds=self.model.ybounds[key],
colormap=self._cmap)[0]
# add line plots: use method since these may change
#************************************************************
self.update_line_plots(key, main, update=True)
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add vertical core lines to main plots and slices
#************************************************************
# save pos and distance in session dict for view info and control
for core in self.model.core_samples:
loc_index, loc, dist = self.model.core_info_dict[core.core_id]
# add boundarys to slice plot
ref_line = self.model.final_lake_depth
self.plot_core_depths(slice_plot, core, ref_line, loc_index)
# add positions to main plots
self.plot_core(main, core, ref_line, loc_index, loc)
# now add tools depending if it is a mini plot or not
#************************************************************
if mini:
# add range selection tool only
# first add a reference line to attach it to
reference = self.make_reference_plot()
main.add(reference)
# attache range selector to this plot
range_tool = RangeSelection(reference)
reference.tools.append(range_tool)
range_overlay = RangeSelectionOverlay(reference,
metadata_name="selections")
reference.overlays.append(range_overlay)
range_tool.on_trait_change(self._range_selection_handler,
"selection")
# add zoombox to mini plot
main.plot(('zoombox_x', 'zoombox_y'),
type='polygon',
face_color=ZOOMBOX_COLOR,
alpha=ZOOMBOX_ALPHA)
# add to hplot and dict
hpc.add(main)
self.hplot_dict['mini'] = hpc
else:
# add zoom tools
main.tools.append(PanTool(main))
zoom = ZoomTool(main, tool_mode='box', axis='both', alpha=0.5)
main.tools.append(zoom)
main.overlays.append(zoom)
main.value_mapper.on_trait_change(self.zoom_all_value, 'updated')
main.index_mapper.on_trait_change(self.zoom_all_index, 'updated')
# add line inspector and attach to freeze tool
#*********************************************
line_inspector = LineInspector(component=img_plot,
axis='index_x',
inspect_mode="indexed",
is_interactive=True,
write_metadata=True,
metadata_name='x_slice',
is_listener=True,
color="white")
img_plot.overlays.append(line_inspector)
self.inspector_freeze_tool.tool_set.add(line_inspector)
# add listener for changes to metadata made by line inspector
#************************************************************
img_plot.on_trait_change(self.metadata_changed, 'index.metadata')
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add clickable legend ; must update legend when depth_dict updated
#******************************************************************
legend = Legend(component=main,
padding=0,
align="ur",
font='modern 8')
legend_highlighter = LegendHighlighter(legend, drag_button="right")
legend.tools.append(legend_highlighter)
self.update_legend_plots(legend, main)
legend.visible = False
self.legend_dict[key] = [legend, legend_highlighter]
main.overlays.append(legend)
# add main and slice plot to hplot container and dict
#****************************************************
main.title = 'frequency = {} kHz'.format(key)
main.title_font = TITLE_FONT
hpc.add(main, slice_plot)
self.hplot_dict[key] = hpc
return hpc
