def clean(imagedata, coordinates=None, xy=None):
"""
Display an array as an image with polygonal regions and region drawing.
.. image:: image.png
Parameters
----------
imagedata : array-like
Image as a two dimensional (grayscale) or three dimensional (RGB) array.
coordinates : array-like
List of coordinates or list of list of coordinates. Assumes array indexing
(i.e. row/column), in the form [[r,c],[r,c]] for one region or
[[[r0,c0],[r0,c0]], [[r1,c1],[r1,c1]]] for multiple regions
xy : boolean, optional, default = None
Only if True treat coordinates as x/y positions instead of row/column indices
"""
if asarray(imagedata).ndim not in set((2, 3)):
raise Exception("Input must be two or three dimensional")
imgs = [array_to_im(imagedata)]
outdict = {"images": imgs}
outdict = add_property(outdict, coordinates, "coordinates", xy=xy)
return outdict
def clean(imagedata, coordinates=None, xy=None):
"""
Display an array as an image with polygonal regions and region drawing.
.. image:: image.png
Parameters
----------
imagedata : array-like
Image as a two dimensional (grayscale) or three dimensional (RGB) array.
coordinates : array-like
List of coordinates or list of list of coordinates. Assumes array indexing
(i.e. row/column), in the form [[r,c],[r,c]] for one region or
[[[r0,c0],[r0,c0]], [[r1,c1],[r1,c1]]] for multiple regions
xy : boolean, optional, default = None
Only if True treat coordinates as x/y positions instead of row/column indices
"""
if asarray(imagedata).ndim not in set((2, 3)):
raise Exception("Input must be two or three dimensional")
imgs = [array_to_im(imagedata)]
outdict = {'images': imgs}
outdict = add_property(outdict, coordinates, 'coordinates', xy=xy)
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, 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(imagedata):
"""
Display an array as an image.
.. image:: image.png
Parameters
----------
imagedata : array-like
Image as a two dimensional (grayscale) or three dimensional (RGB) array.
"""
if asarray(imagedata).ndim not in set((2, 3)):
raise Exception("Input must be two or three dimensional")
outdict = [array_to_im(imagedata)]
return {"images": outdict}
def clean(imagedata):
"""
Display an array as an image.
.. image:: image.png
Parameters
----------
imagedata : array-like
Image as a two dimensional (grayscale) or three dimensional (RGB) array.
"""
if asarray(imagedata).ndim not in set((2, 3)):
raise Exception("Input must be two or three dimensional")
outdict = [array_to_im(imagedata)]
return {'images': outdict}
def clean(imagedata):
"""
Display a collection of arrays as browsable images with thumbnails.
.. image:: gallery.png
Parameters
----------
imagedata : array-like, or list of array-like
Image or list of images as two dimensional (grayscale) or three dimensional (RGB) arrays.
"""
if isinstance(imagedata, ndarray):
imagedata = [imagedata]
outdict = [array_to_im(im) for im in imagedata]
return {"images": outdict}
def clean(imagedata):
"""
Display a collection of images as a three-dimensional volume.
.. image:: volume.png
Parameters
----------
imagedata : array-like, or list of array-like
Image or list of images as two dimensional (grayscale) or three dimensional (RGB) arrays.
"""
if isinstance(imagedata, ndarray):
imagedata = [imagedata]
outdict = [array_to_im(im) for im in imagedata]
return {"images": outdict}
def clean(imagedata):
"""
Display a collection of images as a three-dimensional volume.
.. image:: volume.png
Parameters
----------
imagedata : array-like, or list of array-like
Image or list of images as two dimensional (grayscale) or three dimensional (RGB) arrays.
"""
if isinstance(imagedata, ndarray):
imagedata = [imagedata]
outdict = [array_to_im(im) for im in imagedata]
return {'images': outdict}
def clean(imagedata):
"""
Display a collection of arrays as browsable images with thumbnails.
.. image:: gallery.png
Parameters
----------
imagedata : array-like, or list of array-like
Image or list of images as two dimensional (grayscale) or three dimensional (RGB) arrays.
"""
if isinstance(imagedata, ndarray):
imagedata = [imagedata]
outdict = [array_to_im(im) for im in imagedata]
return {'images': 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
