def _create_plot_component():
# Create some data
numpts = 500
x1 = random(numpts)
y1 = random(numpts)
x2 = x1 + standard_normal(numpts) * 0.05
y2 = y1 + standard_normal(numpts) * 0.05
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", column_stack([x1, x2]).reshape(-1))
pd.set_data("value", column_stack([y1, y2]).reshape(-1))
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="segment",
color="forestgreen",
line_width=2,
line_style='dash',
alpha=0.7,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Segment Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 1000
x = numpy.arange(0, numpts)
y = numpy.random.random(numpts)
marker_size = numpy.random.normal(4.0, 4.0, numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
marker="circle",
index_sort="ascending",
color=(1.0, 0.0, 0.74, 0.4),
marker_size=marker_size,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
index, vals = _create_data(20)
# Create a plot data object and give it this data
pd = ArrayPlotData(index = index,
values = vals)
# Create the plot
plot = Plot(pd)
plot.stacked_bar_plot(("index", "values"),
color = ["red", "yellow", "green", "blue"],
outline_color = "lightgray",)
# Tweak some of the plot properties
plot.title = "Stacked Bar Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 5000
x = sort(random(numpts))
y = random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
index, sorted_vals = _create_data(200)
# Create a plot data obect and give it this data
pd = ArrayPlotData(index = index,
min = sorted_vals[0],
bar_min = sorted_vals[1],
average = sorted_vals[2],
bar_max = sorted_vals[3],
max = sorted_vals[4])
# Create the plot
plot = Plot(pd)
plot.candle_plot(("index", "min", "bar_min", "average", "bar_max", "max"),
color = "lightgray",
bar_line_color = "black",
stem_color = "blue",
center_color = "red",
center_width = 2)
# Tweak some of the plot properties
plot.title = "Candlestick Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
index, sorted_vals = _create_data(200)
# Create a plot data obect and give it this data
pd = ArrayPlotData(index = index,
min = sorted_vals[0],
bar_min = sorted_vals[1],
average = sorted_vals[2],
bar_max = sorted_vals[3],
max = sorted_vals[4])
# Create the plot
plot = Plot(pd)
plot.candle_plot(("index", "min", "bar_min", "average", "bar_max", "max"),
color = "lightgray",
bar_line_color = "black",
stem_color = "blue",
center_color = "red",
center_width = 2)
# Tweak some of the plot properties
plot.title = "Candlestick Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _fuel_cycle_plot_component(x, y, x_name, y_name):
# Create some data
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="line",
marker="circle",
index_sort="ascending",
color="red",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Fuel Cycle Plot"
plot.line_width = 0.5
plot.padding = 100
plot.x_axis.title = x_name
plot.x_axis.title_font = "Roman 16"
plot.x_axis.tick_label_font = "Roman 12"
plot.y_axis.title = y_name
plot.y_axis.title_font = "Roman 16"
plot.y_axis.tick_label_font = "Roman 12"
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 5000
x = sort(random(numpts))
y = random(numpts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
marker="circle",
index_sort="ascending",
color="orange",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component(self):
""" Creates the plot component of the to be used in the FeatureScatter
instance.
"""
x = np.zeros(len(self.data))
y = np.zeros(len(self.data))
c = np.zeros(len(self.data))
for i, (coord, count) in enumerate(self.data.items()):
x[i], y[i] = coord
c[i] = count
c = np.log2(c)
pd = ArrayPlotData()
pd.set_data("x", x)
pd.set_data("y", y)
pd.set_data("color", c)
cm = Map(DataRange1D(low=-c.max() / 2, high=c.max()))
plot = Plot(pd)
plot.plot(("x", "y", "color"),
type="cmap_scatter",
name="my_plot",
marker="dot",
index_sort="ascending",
color_mapper=cm,
marker_size=2,
bgcolor=0xF7F7F7,
)
plot.title = "Scatter Plot With Lasso Selection"
plot.line_width = 1
plot.padding = 50
my_plot = plot.plots["my_plot"][0]
my_plot.data = self.data
my_plot.out_file = self.out_file
my_plot.label = self.label
lasso_selection = FeatureLasso(component=my_plot,
selection_datasource=my_plot.index,
drag_button="left")
my_plot.tools.append(lasso_selection)
my_plot.tools.append(BetterZoom(my_plot, zoom_factor=1.2))
my_plot.tools.append(PanTool(my_plot, drag_button="right"))
my_plot.tools.append(ScatterInspector(my_plot))
lasso_overlay = LassoOverlay(lasso_selection=lasso_selection,
component=my_plot,
selection_fill_color=0xEF8A62)
my_plot.overlays.append(lasso_overlay)
my_plot.overlays.append(ScatterInspectorOverlay(my_plot,
hover_marker_size=4))
return plot
def _create_plot_component():
# Create some data
npts = 100
x = sort(random(npts))
y = random(npts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
pd.set_data("value2", y * 2)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="slategray",
marker_size=6,
bgcolor="white")
plot.plot(("index", "value2"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="red",
marker_size=6,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot With Selection"
plot.line_width = 1
plot.padding = 50
# Right now, some of the tools are a little invasive, and we need the
# actual ScatterPlot object to give to them
my_plot = plot.plots["my_plot"][0]
# Attach some tools to the plot
my_plot.tools.append(
ScatterInspector(my_plot,
selection_mode="toggle",
persistent_hover=False))
my_plot.overlays.append(
ScatterInspectorOverlay(my_plot,
hover_color="transparent",
hover_marker_size=10,
hover_outline_color="purple",
hover_line_width=2,
selection_marker_size=8,
selection_color="lawngreen"))
my_plot.tools.append(PanTool(my_plot))
my_plot.overlays.append(ZoomTool(my_plot, drag_button="right"))
return plot
def _create_plot_component():
# Create some data
numpts = 1000
x = numpy.arange(0, numpts)
y = numpy.random.random(numpts)
marker_size = numpy.random.normal(4.0, 4.0, numpts)
color = numpy.random.random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Because this is a non-standard renderer, we can't call plot.plot, which
# sets up the array data sources, mappers and default index/value ranges.
# So, its gotta be done manually for now.
index_ds = ArrayDataSource(x)
value_ds = ArrayDataSource(y)
color_ds = ArrayDataSource(color)
# Create the plot
plot = Plot(pd)
plot.index_range.add(index_ds)
plot.value_range.add(value_ds)
# Create the index and value mappers using the plot data ranges
imapper = LinearMapper(range=plot.index_range)
vmapper = LinearMapper(range=plot.value_range)
# Create the scatter renderer
scatter = ColormappedScatterPlot(
index=index_ds,
value=value_ds,
color_data=color_ds,
color_mapper=jet(range=DataRange1D(
low=0.0, high=1.0)),
fill_alpha=0.4,
index_mapper=imapper,
value_mapper=vmapper,
marker='circle',
marker_size=marker_size)
# Append the renderer to the list of the plot's plots
plot.add(scatter)
plot.plots['var_size_scatter'] = [scatter]
# Tweak some of the plot properties
plot.title = "Variable Size and Color Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 1000
x = numpy.arange(0, numpts)
y = numpy.random.random(numpts)
marker_size = numpy.random.normal(4.0, 4.0, numpts)
color = numpy.random.random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Because this is a non-standard renderer, we can't call plot.plot, which
# sets up the array data sources, mappers and default index/value ranges.
# So, its gotta be done manually for now.
index_ds = ArrayDataSource(x)
value_ds = ArrayDataSource(y)
color_ds = ArrayDataSource(color)
# Create the plot
plot = Plot(pd)
plot.index_range.add(index_ds)
plot.value_range.add(value_ds)
# Create the index and value mappers using the plot data ranges
imapper = LinearMapper(range=plot.index_range)
vmapper = LinearMapper(range=plot.value_range)
# Create the scatter renderer
scatter = ColormappedScatterPlot(
index=index_ds,
value=value_ds,
color_data=color_ds,
color_mapper=jet(range=DataRange1D(low=0.0, high=1.0)),
fill_alpha=0.4,
index_mapper = imapper,
value_mapper = vmapper,
marker='circle',
marker_size=marker_size)
# Append the renderer to the list of the plot's plots
plot.add(scatter)
plot.plots['var_size_scatter'] = [scatter]
# Tweak some of the plot properties
plot.title = "Variable Size and Color Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
npts = 200
x = sort(random(npts))
y = random(npts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="red",
marker_size=4,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot With Rectangular Selection"
plot.line_width = 1
plot.padding = 50
# Right now, some of the tools are a little invasive, and we need the
# actual ScatterPlot object to give to them
my_plot = plot.plots["my_plot"][0]
# Attach some tools to the plot
rect_selection = RectangularSelection(
component=my_plot,
selection_datasource=my_plot.index,
drag_button="left",
metadata_name='selections',
)
my_plot.tools.append(rect_selection)
my_plot.tools.append(ScatterInspector(my_plot, selection_mode='toggle'))
my_plot.active_tool = rect_selection
lasso_overlay = LassoOverlay(lasso_selection=rect_selection,
component=my_plot)
my_plot.overlays.append(lasso_overlay)
scatter_overlay = ScatterInspectorOverlay(
component=my_plot,
selection_color='cornflowerblue',
selection_marker_size=int(my_plot.marker_size) + 3,
selection_marker='circle')
my_plot.overlays.append(scatter_overlay)
return plot
def _create_plot_component():
# Create some data
numpts = 5000
x = sort(np.random.random(numpts))
y = np.random.random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Generate Random marker and outline colors
# The arrays must be RGBA color tuples. Create the appropriate arrays.
col_array=np.zeros(len(x),dtype=('f8,f8,f8,f8'))
outline_col_array=np.zeros(len(x),dtype=('f8,f8,f8,f8'))
colors=[]
for i in range(len(x)):
colors.append(random.choice(enable.colors.color_table.keys()))
for idx, color in enumerate(colors):
col_array[idx] = enable.colors.color_table[color]
colors=[]
for i in range(len(x)):
colors.append(random.choice(enable.colors.color_table.keys()))
for idx, color in enumerate(colors):
outline_col_array[idx] = enable.colors.color_table[color]
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
marker="circle",
index_sort="ascending",
color=col_array,
marker_size=3,
outline_color = outline_col_array,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
npts = 100
x = sort(random(npts))
y = random(npts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="slategray",
marker_size=6,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot With Selection"
plot.line_width = 1
plot.padding = 50
# Right now, some of the tools are a little invasive, and we need the
# actual ScatterPlot object to give to them
my_plot = plot.plots["my_plot"][0]
# Attach some tools to the plot
my_plot.tools.append(ScatterInspector(my_plot, selection_mode="toggle",
persistent_hover=False))
my_plot.overlays.append(
ScatterInspectorOverlay(my_plot,
hover_color = "transparent",
hover_marker_size = 10,
hover_outline_color = "purple",
hover_line_width = 2,
selection_marker_size = 8,
selection_color = "lawngreen")
)
my_plot.tools.append(PanTool(my_plot))
my_plot.overlays.append(ZoomTool(my_plot, drag_button="right"))
return plot
def _plot_default(self):
# Create the plot
plot = Plot(self.dataset)
plot.plot(("index", "value"),
type="scatter",
marker='circle',
color='blue')
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
return plot
def _create_plot_component():
# Create some data
npts = 2000
x = sort(random(npts))
y = random(npts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="red",
marker_size=4,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot With Lasso Selection"
plot.line_width = 1
plot.padding = 50
# Right now, some of the tools are a little invasive, and we need the
# actual ScatterPlot object to give to them
my_plot = plot.plots["my_plot"][0]
# Attach some tools to the plot
lasso_selection = LassoSelection(component=my_plot,
selection_datasource=my_plot.index,
drag_button="left")
#drag_button="right")
my_plot.active_tool = lasso_selection
my_plot.tools.append(ScatterInspector(my_plot))
lasso_overlay = LassoOverlay(lasso_selection=lasso_selection,
component=my_plot)
my_plot.overlays.append(lasso_overlay)
# Uncomment this if you would like to see incremental updates:
#lasso_selection.incremental_select = True
return plot
def _create_plot_component():
# Create some data
npts = 2000
x = sort(random(npts))
y = random(npts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="circle",
index_sort="ascending",
color="red",
marker_size=4,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter Plot With Lasso Selection"
plot.line_width = 1
plot.padding = 50
# Right now, some of the tools are a little invasive, and we need the
# actual ScatterPlot object to give to them
my_plot = plot.plots["my_plot"][0]
# Attach some tools to the plot
lasso_selection = LassoSelection(component=my_plot,
selection_datasource=my_plot.index,
drag_button="left")
#drag_button="right")
my_plot.active_tool = lasso_selection
my_plot.tools.append(ScatterInspector(my_plot))
lasso_overlay = LassoOverlay(lasso_selection=lasso_selection,
component=my_plot)
my_plot.overlays.append(lasso_overlay)
# Uncomment this if you would like to see incremental updates:
#lasso_selection.incremental_select = True
return plot
def _plot_default(self):
# Create the plot
plot = Plot(self.dataset)
plot.plot(
("index", "value"),
type="scatter",
marker='circle',
color='blue'
)
# Tweak some of the plot properties
plot.title = "Scatter Plot"
plot.line_width = 0.5
plot.padding = 50
return plot
def _create_plot_component():
# Create some data
numpts = 300
x = sort(random(numpts))
y = random(numpts)
# create a custom marker
marker = make_custom_marker()
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
marker="custom",
custom_symbol=marker,
index_sort="ascending",
color="orange",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Scatter plot with custom markers"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 1000
x = sort(random(numpts))
y = random(numpts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="square",
index_sort="ascending",
color="lightblue",
outline_color="none",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Click to add points, press Enter to finalize selection"
plot.padding = 50
plot.line_width = 1
# Attach some tools to the plot
pan = PanTool(plot, drag_button="right", constrain_key="shift")
plot.tools.append(pan)
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
plot.overlays.append(MyLineDrawer(plot))
return plot
def _create_plot_component():
# Create some data
numpts = 1000
x = sort(random(numpts))
y = random(numpts)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="scatter",
name="my_plot",
marker="square",
index_sort="ascending",
color="lightblue",
outline_color="none",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Click to add points, press Enter to finalize selection"
plot.padding = 50
plot.line_width = 1
# Attach some tools to the plot
pan = PanTool(plot, drag_button="right", constrain_key="shift")
plot.tools.append(pan)
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
plot.overlays.append(MyLineDrawer(plot))
return plot
def _create_plot_component():
# Create some data
numpts = 50
x = sort(random(numpts))
y = random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd, use_backbuffer=True, auto_grid=False)
plot.plot_1d(
'index',
type='line_scatter_1d',
orientation='h',
color='lightgrey',
line_style='dot',
)
plot.plot_1d(
'index',
type='scatter_1d',
orientation='h',
marker='plus',
alignment='bottom'
)
plot.plot_1d(
'value',
type='line_scatter_1d',
orientation='v',
color='lightgrey',
line_style='dot',
)
plot.plot_1d(
'value',
type='scatter_1d',
orientation='v',
marker='plus',
alignment='left'
)
plot.plot(("index", "value"),
type="scatter",
marker="square",
index_sort="ascending",
color="orange",
marker_size=3, #randint(1,5, numpts),
bgcolor="white",
use_backbuffer=True)
# Tweak some of the plot properties
plot.title = "1D Scatter Plots"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component():
# Create some data
numpts = 50
x = sort(random(numpts))
y = random(numpts)
# Create a plot data object and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd, use_backbuffer=True, auto_grid=False)
plot.plot_1d(
'index',
type='line_scatter_1d',
orientation='h',
color='lightgrey',
line_style='dot', )
plot.plot_1d(
'index',
type='scatter_1d',
orientation='h',
marker='plus',
alignment='bottom')
plot.plot_1d(
'value',
type='line_scatter_1d',
orientation='v',
color='lightgrey',
line_style='dot', )
plot.plot_1d(
'value',
type='scatter_1d',
orientation='v',
marker='plus',
alignment='left')
plot.plot(
("index", "value"),
type="scatter",
marker="square",
index_sort="ascending",
color="orange",
marker_size=3, #randint(1,5, numpts),
bgcolor="white",
use_backbuffer=True)
# Tweak some of the plot properties
plot.title = "1D Scatter Plots"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
