def clean(x, y, series, color=None, label=None, size=None, alpha=None):
"""
Create a joint scatter / line plot.
.. image:: scatterline.png
Parameters
----------
x, y : array-like, each (n,)
Input data for scatter plot as x,y coordinates
t : array-like
Input data for line plot
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set point colors
label : array-like, optional, singleton or (n,)
Single integer or array to set point colors via group labels
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
"""
points = vecs_to_points(x, y)
series = array_to_lines(series)
outdict = {'points': points, 'series': series}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
return outdict
def clean(x, y, series, color=None, label=None, size=None, alpha=None):
"""
Create a joint scatter / line plot.
.. image:: scatterline.png
Parameters
----------
x, y : array-like, each (n,)
Input data for scatter plot as x,y coordinates
t : array-like
Input data for line plot
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set point colors
label : array-like, optional, singleton or (n,)
Single integer or array to set point colors via group labels
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
"""
points = vecs_to_points(x, y)
series = array_to_lines(series)
outdict = {'points': points, 'series': series}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
return outdict
def clean(x, y, conn, values=None, labels=None,color=None, group=None, colormap=None, size=None):
"""
Create a node-link graph from spatial points and their connectivity.
.. image:: graph.png
Parameters
----------
x,y : array-like, each (n,)
Input data for nodes (x,y coordinates)
conn : array-like, (n,n) or (n,3) or (n,2)
Input connectivity data as either a matrix or a list of links.
Matrix can be binary or continuous valued. Links should contain
either 2 elements per link (source, target),
or 3 elements (source, target, value).
values : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
labels : array-like, optional, (n,)
Array of text labels to set tooltips
color : array-like, optional, singleton or (n,) or (n,3)
Single rgb value or array to set node colors
group : array-like, optional, singleton or (n,)
Single integer or array to set node colors via group assignment
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set node sizes
tooltips : boolean, optional, default=True
Whether to show tooltips
zoom : boolean, optional, default=True
Whether to allow zooming
brush : boolean, optional, default=True
Whether to support brushing
"""
links = parse_links(conn)
nodes = vecs_to_points(x, y)
outdict = {'links': links, 'nodes': nodes}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, group, 'group')
outdict = add_property(outdict, values, 'values')
outdict = add_property(outdict, labels, 'labels')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
return outdict
def clean(x, y, conn, values=None, labels=None,color=None, group=None, colormap=None, size=None):
"""
Create a node-link graph from spatial points and their connectivity.
.. image:: graph.png
Parameters
----------
x,y : array-like, each (n,)
Input data for nodes (x,y coordinates)
conn : array-like, (n,n) or (n,3) or (n,2)
Input connectivity data as either a matrix or a list of links.
Matrix can be binary or continuous valued. Links should contain
either 2 elements per link (source, target),
or 3 elements (source, target, value).
values : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
labels : array-like, optional, (n,)
Array of text labels to set tooltips
color : array-like, optional, singleton or (n,) or (n,3)
Single rgb value or array to set node colors
group : array-like, optional, singleton or (n,)
Single integer or array to set node colors via group assignment
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set node sizes
tooltips : boolean, optional, default=True
Whether to show tooltips
zoom : boolean, optional, default=True
Whether to allow zooming
brush : boolean, optional, default=True
Whether to support brushing
"""
links = parse_links(conn)
nodes = vecs_to_points(x, y)
outdict = {'links': links, 'nodes': nodes}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, group, 'group')
outdict = add_property(outdict, values, 'values')
outdict = add_property(outdict, labels, 'labels')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
return outdict
def clean(x,
y,
color=None,
label=None,
value=None,
colormap=None,
size=None,
alpha=None,
xaxis=None,
yaxis=None):
"""
Plot two-dimensional data as points.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
label : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
alpha : array-like, optional, singleton or (n,)
Single alpha value or array to set fill and stroke opacity
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, value, 'value')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x,
y,
conn,
color=None,
label=None,
value=None,
colormap=None,
size=None,
imagedata=None):
"""
Create a node-link graph from spatial points and their connectivity.
.. image:: graph.png
Parameters
----------
x,y : array-like, each (n,)
Input data for nodes (x,y coordinates)
conn : array-like, (n,n) or (n,3) or (n,2)
Input connectivity data as either a matrix or a list of links.
Matrix can be binary or continuous valued. Links should contain
either 2 elements per link (source, target),
or 3 elements (source, target, value).
color : array-like, optional, singleton or (n,) or (n,3)
Single rgb value or array to set node colors
label : array-like, optional, singleton or (n,)
Single integer or array to set node colors via group labels
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set node sizes
"""
links = parse_links(conn)
nodes = vecs_to_points(x, y)
outdict = {'links': links, 'nodes': nodes}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, value, 'value')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
if imagedata is not None:
images = array_to_im(imagedata)
outdict['images'] = images
return outdict
def clean(x, y, values=None, labels=None, group=None, color=None, colormap=None, size=None, xaxis=None, yaxis=None):
"""
Create a streaming scatter plot of x and y.
Plotting once returns a visualization on which 'append' can be called to add new data
in a streaming fashion. The opacity of old and new data is automatically set
to highlight the most recent data and fade old data away.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
values : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
labels : array-like, optional, (n,)
Array of text labels to set tooltips
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
group : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, group, 'group')
outdict = add_property(outdict, values, 'values')
outdict = add_property(outdict, labels, 'labels')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x, y, color=None, label=None, value=None, colormap=None, size=None, xaxis=None, yaxis=None):
"""
Create a streaming scatter plot of x and y.
Plotting once returns a visualization on which 'append' can be called to add new data
in a streaming fashion. The opacity of old and new data is automatically set
to highlight the most recent data and fade old data away.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
label : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, value, 'value')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x, y, conn, color=None, label=None, value=None, colormap=None, size=None, imagedata=None):
"""
Create a node-link graph from spatial points and their connectivity.
.. image:: graph.png
Parameters
----------
x,y : array-like, each (n,)
Input data for nodes (x,y coordinates)
conn : array-like, (n,n) or (n,3) or (n,2)
Input connectivity data as either a matrix or a list of links.
Matrix can be binary or continuous valued. Links should contain
either 2 elements per link (source, target),
or 3 elements (source, target, value).
color : array-like, optional, singleton or (n,) or (n,3)
Single rgb value or array to set node colors
label : array-like, optional, singleton or (n,)
Single integer or array to set node colors via group labels
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set node sizes
"""
links = parse_links(conn)
nodes = vecs_to_points(x, y)
outdict = {'links': links, 'nodes': nodes}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, value, 'value')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
if imagedata is not None:
images = array_to_im(imagedata)
outdict['images'] = images
return outdict
def clean(x, y, color=None, label=None, value=None, colormap=None, size=None, alpha=None, xaxis=None, yaxis=None):
"""
Plot two-dimensional data as points.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
label : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
alpha : array-like, optional, singleton or (n,)
Single alpha value or array to set fill and stroke opacity
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, value, 'value')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x, y, color=None, label=None, value=None, colormap=None, size=None, xaxis=None, yaxis=None):
"""
Create a streaming scatter plot of x and y.
Plotting once returns a visualization on which 'append' can be called to add new data
in a streaming fashion. The opacity of old and new data is automatically set
to highlight the most recent data and fade old data away.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
label : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
value : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {"points": points}
outdict = add_property(outdict, color, "color")
outdict = add_property(outdict, label, "label")
outdict = add_property(outdict, value, "value")
outdict = add_property(outdict, colormap, "colormap")
outdict = add_property(outdict, size, "size")
outdict = add_property(outdict, xaxis, "xaxis")
outdict = add_property(outdict, yaxis, "yaxis")
return outdict
def clean(x, y, color=None, label=None, size=None, xaxis=None, yaxis=None):
"""
Create a streaming scatter plot of x and y.
Plotting once returns a visualization on which 'append' can be called to add new data
in a streaming fashion. The opacity of old and new data is automatically set
to highlight the most recent data and fade old data away.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
label : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x, y, matrix, color=None, label=None, size=None, imagedata=None):
"""
Create a node-link graph with bundled edges.
.. image:: graphbundled.png
Parameters
----------
x,y : array-like, each (n,)
Input data for nodes (x,y coordinates)
matrix : array, (n,n)
Input data with connectivity matrix. Can be binary or continuous-valued
(for weighted edges).
color : array-like, optional, singleton or (n,) or (n,3)
Single rgb value or array to set node colors
label : array-like, optional, singleton or (n,)
Single integer or array to set node colors via group labels
size : array-like, optional, singleton or (n,)
Single size or array to set node sizes
"""
points = vecs_to_points(x, y)
links = mat_to_links(matrix)
outdict = {'links': links, 'nodes': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, label, 'label')
outdict = add_property(outdict, size, 'size')
if imagedata is not None:
images = array_to_im(imagedata)
outdict['images'] = images
return outdict
def clean(x, y, labels=None, values=None, color=None, group=None, colormap=None,
size=None, alpha=None, xaxis=None, yaxis=None):
"""
Plot two-dimensional data as points.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
values : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
labels : array-like, optional, (n,)
Array of text labels to set tooltips
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
group : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
alpha : array-like, optional, singleton or (n,)
Single alpha value or array to set fill and stroke opacity
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
tooltips : boolean, optional, default=True
Whether to show tooltips
zoom : boolean, optional, default=True
Whether to allow zooming
brush : boolean, optional, default=True
Whether to support brushing
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, group, 'group')
outdict = add_property(outdict, labels, 'labels')
outdict = add_property(outdict, values, 'values')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
def clean(x, y, labels=None, values=None, color=None, group=None, colormap=None,
size=None, alpha=None, xaxis=None, yaxis=None):
"""
Plot two-dimensional data as points.
.. image:: scatter.png
Parameters
----------
x, y : array-like, each (n,)
Input data
values : array-like, optional, singleton or (n,)
Values to set node colors via a linear scale
labels : array-like, optional, (n,)
Array of text labels to set tooltips
color : array-like, optional, singleton or (n,3)
Single rgb value or array to set colors
group : array-like, optional, singleton or (n,)
Single integer or array to set colors via groups
colormap : string
Specification of color map, only colorbrewer types supported
size : array-like, optional, singleton or (n,)
Single size or array to set point sizes
alpha : array-like, optional, singleton or (n,)
Single alpha value or array to set fill and stroke opacity
xaxis : str, optional, default = None
Label for x-axis
yaxis : str, optional, default = None
Label for y-axis
tooltips : boolean, optional, default=True
Whether to show tooltips
zoom : boolean, optional, default=True
Whether to allow zooming
brush : boolean, optional, default=True
Whether to support brushing
"""
points = vecs_to_points(x, y)
outdict = {'points': points}
outdict = add_property(outdict, color, 'color')
outdict = add_property(outdict, group, 'group')
outdict = add_property(outdict, labels, 'labels')
outdict = add_property(outdict, values, 'values')
outdict = add_property(outdict, colormap, 'colormap')
outdict = add_property(outdict, size, 'size')
outdict = add_property(outdict, alpha, 'alpha')
outdict = add_property(outdict, xaxis, 'xaxis')
outdict = add_property(outdict, yaxis, 'yaxis')
return outdict
