Individual custom markers and colorbar

Thanks, Ryan, this is (amost) exactly what I was looking for. Now, I get the markers and their colors right, but I still have two problems:
The markers have a black edges, that I cannot get rid of. I've tried

rect = Rectangle(..., ec=None)

and also

col.set=edgecolor(None)

and 'None', respectively, both with no effect whatsoever.

The second problem is, that I cannot get the colorbar to work.
I tried

sc = ax.add_collection(col)
plt.colorbar(sc)

and

plt.colobar(col)

both do not work.
Any Ideas how to fix those two issues?

Thanks,

-Hackstein

···

Message: 4
Date: Thu, 25 Apr 2013 19:44:23 -0400
From: Ryan Nelson <rnelsonchem@...287...>
Subject: Re: [Matplotlib-users] Individual custom markers and colorbar
To: matplotlib-users@lists.sourceforge.net
Message-ID: <5179BFD7.7060106@...287...>
Content-Type: text/plain; charset="iso-8859-1"

Hackstein,

Unfortunately, I'm not sure of an 'elegant' way to do what your asking
with a single call to scatter. Others may know a better way. However,
you can use rectangle patches and patch collections. (Requires a bit
more code than scatter but is ultimately more flexible.)

I think the example below does what you need, but with random numbers.

Hope it helps a little.

Ryan

#######################
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection

n = 100

# Get your xy data points, which are the centers of the rectangles.
xy = np.random.rand(n,2)

# Set a fixed height
height = 0.02
# The variable widths of the rectangles
widths = np.random.rand(n)*0.1

# Get a color map and color values (normalized between 0 and 1)
cmap = plt.cm.jet
colors = np.random.rand(n)

rects = []
for p, w, c in zip(xy, widths, colors):
    xpos = p[0] - w/2 # The x position will be half the width from the
center
    ypos = p[1] - height/2 # same for the y position, but with height
    rect = Rectangle( (xpos, ypos), w, height ) # Create a rectangle
    rects.append(rect) # Add the rectangle patch to our list

# Create a collection from the rectangles
col = PatchCollection(rects)
# set the alpha for all rectangles
col.set_alpha(0.3)
# Set the colors using the colormap
col.set_facecolor( cmap(colors) )

# Make a figure and add the collection to the axis.
ax = plt.subplot(111)
ax.add_collection(col)
plt.show()

###############################

On 4/24/2013 5:35 PM, Hackstein wrote:

Hi all,

I am trying to get a scatter plot using a colormap. Additionally, I
need to define every marker for every data point individually -- each
being a rectangle with fixed height but varying width as a function of
the y-value. X and y being the data coordinates, z being a number to
be color coded with the colormap.

Ideally, I would like to create a list of width and height values for
each data point and tell the scatter plot to use those.

So far I got colormapped data with custom markers (simplified):

[code]

import numpy as np

import matplotlib.pyplot as plt

from pylab import *

x = y = [1,2,3,4,5]

z = [2,4,6,8,10]

colors = cm.gnuplot2

verts_vec = list(zip([-10.,10.,10.,-10.],[-5.,-5.,5.,5.]))

fig = plt.figure(1, figsize=(14.40, 9.00))

ax = fig.add_subplot(1,1,1)

sc = ax.scatter(x, y, c=np.asarray(z), marker=None, edgecolor='None',
verts=verts_vec, cmap=colors, alpha=1.)

plt.colorbar(sc, orientation='horizontal')

plt.savefig('test.png', dpi=200)

plt.close(1)

[/code]

But I need to define a marker size for each point, and I also need to
do that in axis scale values, not in points.

I imagine giving verts a list of N*2 tuples instead of 2 tuples, N
being len(x), to define N individual markers.

But when doing that I get the error that vertices.ndim==2.

A less elegant way would be to plot every data point in an individual
scatter plot function, using a for-loop iterating over all data
points. Then, however, I see no way to apply a colormap and colorbar.

What is the best way to accomplish that then?

Thanks,

-Hackstein

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Thanks, Ryan, this is (amost) exactly what I was looking for. Now, I get the markers and their colors right, but I still have two problems:
The markers have a black edges, that I cannot get rid of. I’ve tried

rect = Rectangle(…, ec=None)

and also

col.set=edgecolor(None)

I think that you have to use the string ‘none’ instead of None type. The latter is used to use the default value for the variable (in you case black).

cheers
Francesco

···

Il giorno 26/apr/2013 13:16, “Hackstein” <news.hackstein@…361…> ha scritto:

and ‘None’, respectively, both with no effect whatsoever.

The second problem is, that I cannot get the colorbar to work.
I tried

sc = ax.add_collection(col)
plt.colorbar(sc)

and

plt.colobar(col)

both do not work.
Any Ideas how to fix those two issues?

Thanks,

-Hackstein

Message: 4
Date: Thu, 25 Apr 2013 19:44:23 -0400
From: Ryan Nelson <rnelsonchem@…287…>
Subject: Re: [Matplotlib-users] Individual custom markers and colorbar
To: matplotlib-users@lists.sourceforge.net
Message-ID: <5179BFD7.7060106@…287…>
Content-Type: text/plain; charset=“iso-8859-1”

Hackstein,

Unfortunately, I’m not sure of an ‘elegant’ way to do what your asking
with a single call to scatter. Others may know a better way. However,
you can use rectangle patches and patch collections. (Requires a bit
more code than scatter but is ultimately more flexible.)

I think the example below does what you need, but with random numbers.

Hope it helps a little.

Ryan

#######################
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection

n = 100

Get your xy data points, which are the centers of the rectangles.

xy = np.random.rand(n,2)

Set a fixed height

height = 0.02

The variable widths of the rectangles

widths = np.random.rand(n)*0.1

Get a color map and color values (normalized between 0 and 1)

cmap = plt.cm.jet
colors = np.random.rand(n)

rects = []
for p, w, c in zip(xy, widths, colors):
xpos = p[0] - w/2 # The x position will be half the width from the
center
ypos = p[1] - height/2 # same for the y position, but with height
rect = Rectangle( (xpos, ypos), w, height ) # Create a rectangle
rects.append(rect) # Add the rectangle patch to our list

Create a collection from the rectangles

col = PatchCollection(rects)

set the alpha for all rectangles

col.set_alpha(0.3)

Set the colors using the colormap

col.set_facecolor( cmap(colors) )

Make a figure and add the collection to the axis.

ax = plt.subplot(111)
ax.add_collection(col)
plt.show()

###############################

On 4/24/2013 5:35 PM, Hackstein wrote:

Hi all,

I am trying to get a scatter plot using a colormap. Additionally, I
need to define every marker for every data point individually – each
being a rectangle with fixed height but varying width as a function of
the y-value. X and y being the data coordinates, z being a number to
be color coded with the colormap.

Ideally, I would like to create a list of width and height values for
each data point and tell the scatter plot to use those.

So far I got colormapped data with custom markers (simplified):


> >> import numpy as np
> >>
> >> import matplotlib.pyplot as plt
> >>
> >> from pylab import *
> >>
> >> x = y = [1,2,3,4,5]
> >>
> >> z = [2,4,6,8,10]
> >>
> >> colors = cm.gnuplot2
> >>
> >> verts_vec = list(zip([-10.,10.,10.,-10.],[-5.,-5.,5.,5.]))
> >>
> >> fig = plt.figure(1, figsize=(14.40, 9.00))
> >>
> >> ax = fig.add_subplot(1,1,1)
> >>
> >> sc = ax.scatter(x, y, c=np.asarray(z), marker=None, edgecolor='None',
> >> verts=verts_vec, cmap=colors, alpha=1.)
> >>
> >> plt.colorbar(sc, orientation='horizontal')
> >>
> >> plt.savefig('test.png', dpi=200)
> >>
> >> plt.close(1)
> >>

But I need to define a marker size for each point, and I also need to
do that in axis scale values, not in points.

I imagine giving verts a list of N*2 tuples instead of 2 tuples, N
being len(x), to define N individual markers.

But when doing that I get the error that vertices.ndim==2.

A less elegant way would be to plot every data point in an individual
scatter plot function, using a for-loop iterating over all data
points. Then, however, I see no way to apply a colormap and colorbar.

What is the best way to accomplish that then?

Thanks,

-Hackstein


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Thanks, Francesco, but I already tried for both and that doesn’t work either.

Cheers,

···

Am 26.04.2013 um 14:07 schrieb Francesco Montesano <franz.bergesund@…287…>:

Il giorno 26/apr/2013 13:16, “Hackstein” <news.hackstein@…361…> ha scritto:

Thanks, Ryan, this is (amost) exactly what I was looking for. Now, I get the markers and their colors right, but I still have two problems:
The markers have a black edges, that I cannot get rid of. I’ve tried

rect = Rectangle(…, ec=None)

and also

col.set=edgecolor(None)

I think that you have to use the string ‘none’ instead of None type. The latter is used to use the default value for the variable (in you case black).

cheers
Francesco

and ‘None’, respectively, both with no effect whatsoever.

The second problem is, that I cannot get the colorbar to work.
I tried

sc = ax.add_collection(col)
plt.colorbar(sc)

and

plt.colobar(col)

both do not work.
Any Ideas how to fix those two issues?

Thanks,

-Hackstein

Message: 4
Date: Thu, 25 Apr 2013 19:44:23 -0400
From: Ryan Nelson <rnelsonchem@…287…>
Subject: Re: [Matplotlib-users] Individual custom markers and colorbar
To: matplotlib-users@lists.sourceforge.net
Message-ID: <5179BFD7.7060106@…287…>
Content-Type: text/plain; charset=“iso-8859-1”

Hackstein,

Unfortunately, I’m not sure of an ‘elegant’ way to do what your asking
with a single call to scatter. Others may know a better way. However,
you can use rectangle patches and patch collections. (Requires a bit
more code than scatter but is ultimately more flexible.)

I think the example below does what you need, but with random numbers.

Hope it helps a little.

Ryan

#######################
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection

n = 100

Get your xy data points, which are the centers of the rectangles.

xy = np.random.rand(n,2)

Set a fixed height

height = 0.02

The variable widths of the rectangles

widths = np.random.rand(n)*0.1

Get a color map and color values (normalized between 0 and 1)

cmap = plt.cm.jet
colors = np.random.rand(n)

rects = []
for p, w, c in zip(xy, widths, colors):
xpos = p[0] - w/2 # The x position will be half the width from the
center
ypos = p[1] - height/2 # same for the y position, but with height
rect = Rectangle( (xpos, ypos), w, height ) # Create a rectangle
rects.append(rect) # Add the rectangle patch to our list

Create a collection from the rectangles

col = PatchCollection(rects)

set the alpha for all rectangles

col.set_alpha(0.3)

Set the colors using the colormap

col.set_facecolor( cmap(colors) )

Make a figure and add the collection to the axis.

ax = plt.subplot(111)
ax.add_collection(col)
plt.show()

###############################

On 4/24/2013 5:35 PM, Hackstein wrote:

Hi all,

I am trying to get a scatter plot using a colormap. Additionally, I
need to define every marker for every data point individually – each
being a rectangle with fixed height but varying width as a function of
the y-value. X and y being the data coordinates, z being a number to
be color coded with the colormap.

Ideally, I would like to create a list of width and height values for
each data point and tell the scatter plot to use those.

So far I got colormapped data with custom markers (simplified):


> > >> import numpy as np
> > >>
> > >> import matplotlib.pyplot as plt
> > >>
> > >> from pylab import *
> > >>
> > >> x = y = [1,2,3,4,5]
> > >>
> > >> z = [2,4,6,8,10]
> > >>
> > >> colors = cm.gnuplot2
> > >>
> > >> verts_vec = list(zip([-10.,10.,10.,-10.],[-5.,-5.,5.,5.]))
> > >>
> > >> fig = plt.figure(1, figsize=(14.40, 9.00))
> > >>
> > >> ax = fig.add_subplot(1,1,1)
> > >>
> > >> sc = ax.scatter(x, y, c=np.asarray(z), marker=None, edgecolor='None',
> > >> verts=verts_vec, cmap=colors, alpha=1.)
> > >>
> > >> plt.colorbar(sc, orientation='horizontal')
> > >>
> > >> plt.savefig('test.png', dpi=200)
> > >>
> > >> plt.close(1)
> > >>

But I need to define a marker size for each point, and I also need to
do that in axis scale values, not in points.

I imagine giving verts a list of N*2 tuples instead of 2 tuples, N
being len(x), to define N individual markers.

But when doing that I get the error that vertices.ndim==2.

A less elegant way would be to plot every data point in an individual
scatter plot function, using a for-loop iterating over all data
points. Then, however, I see no way to apply a colormap and colorbar.

What is the best way to accomplish that then?

Thanks,

-Hackstein


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Hackstein,

Francesco's suggestion works for me.
col.set_edgecolor( 'none' )

You can also set the linewidth to be 0.
col.set_linewidth( 0 )

Colorbars in these cases can be more painful than you might like. You need to make a mappable object and pass that into a figure.colorbar call. Rather than try to explain it in detail, I've just pasted a modified version of my first script that should do what you need.

Glad we're getting closer.

Ryan

···

########################

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection

n = 100

# Get your xy data points, which are the centers of the rectangles.
xy = np.random.rand(n,2)

# Set a fixed height
height = 0.02
# The variable widths of the rectangles
widths = np.random.rand(n)*0.1

# Get a color map and make some colors
cmap = plt.cm.hsv
colors = np.random.rand(n)*10.
# Make a normalized array of colors
colors_norm = colors/colors.max()
# Here's where you have to make a ScalarMappable with the colormap
mappable = plt.cm.ScalarMappable(cmap=cmap)
# Give it your non-normalized color data
mappable.set_array(colors)

rects = []
for p, w in zip(xy, widths):
     xpos = p[0] - w/2 # The x position will be half the width from the center
     ypos = p[1] - height/2 # same for the y position, but with height
     rect = Rectangle( (xpos, ypos), w, height ) # Create a rectangle
     rects.append(rect) # Add the rectangle patch to our list

# Create a collection from the rectangles
col = PatchCollection(rects)
# set the alpha for all rectangles
col.set_alpha(0.3)
# Set the colors using the colormap
col.set_facecolor( cmap(colors_norm) )
# No lines
col.set_linewidth( 0 )
#col.set_edgecolor( 'none' )

# Make a figure and add the collection to the axis.
fig = plt.figure()
ax = fig.add_subplot(111)
ax.add_collection(col)
# Add your ScalarMappable to a figure colorbar
fig.colorbar(mappable)
plt.show()

########################

On 4/26/2013 7:15 AM, Hackstein wrote:

Thanks, Ryan, this is (amost) exactly what I was looking for. Now, I get the markers and their colors right, but I still have two problems:
The markers have a black edges, that I cannot get rid of. I've tried

rect = Rectangle(..., ec=None)

and also

col.set=edgecolor(None)

and 'None', respectively, both with no effect whatsoever.

The second problem is, that I cannot get the colorbar to work.
I tried

sc = ax.add_collection(col)
plt.colorbar(sc)

and

plt.colobar(col)

both do not work.
Any Ideas how to fix those two issues?

Thanks,

-Hackstein

Message: 4
Date: Thu, 25 Apr 2013 19:44:23 -0400
From: Ryan Nelson <rnelsonchem@...287...>
Subject: Re: [Matplotlib-users] Individual custom markers and colorbar
To: matplotlib-users@lists.sourceforge.net
Message-ID: <5179BFD7.7060106@...287...>
Content-Type: text/plain; charset="iso-8859-1"

Hackstein,

Unfortunately, I'm not sure of an 'elegant' way to do what your asking
with a single call to scatter. Others may know a better way. However,
you can use rectangle patches and patch collections. (Requires a bit
more code than scatter but is ultimately more flexible.)

I think the example below does what you need, but with random numbers.

Hope it helps a little.

Ryan

#######################
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection

n = 100

# Get your xy data points, which are the centers of the rectangles.
xy = np.random.rand(n,2)

# Set a fixed height
height = 0.02
# The variable widths of the rectangles
widths = np.random.rand(n)*0.1

# Get a color map and color values (normalized between 0 and 1)
cmap = plt.cm.jet
colors = np.random.rand(n)

rects = []
for p, w, c in zip(xy, widths, colors):
     xpos = p[0] - w/2 # The x position will be half the width from the
center
     ypos = p[1] - height/2 # same for the y position, but with height
     rect = Rectangle( (xpos, ypos), w, height ) # Create a rectangle
     rects.append(rect) # Add the rectangle patch to our list

# Create a collection from the rectangles
col = PatchCollection(rects)
# set the alpha for all rectangles
col.set_alpha(0.3)
# Set the colors using the colormap
col.set_facecolor( cmap(colors) )

# Make a figure and add the collection to the axis.
ax = plt.subplot(111)
ax.add_collection(col)
plt.show()

###############################

On 4/24/2013 5:35 PM, Hackstein wrote:

Hi all,

I am trying to get a scatter plot using a colormap. Additionally, I
need to define every marker for every data point individually -- each
being a rectangle with fixed height but varying width as a function of
the y-value. X and y being the data coordinates, z being a number to
be color coded with the colormap.

Ideally, I would like to create a list of width and height values for
each data point and tell the scatter plot to use those.

So far I got colormapped data with custom markers (simplified):

[code]

import numpy as np

import matplotlib.pyplot as plt

from pylab import *

x = y = [1,2,3,4,5]

z = [2,4,6,8,10]

colors = cm.gnuplot2

verts_vec = list(zip([-10.,10.,10.,-10.],[-5.,-5.,5.,5.]))

fig = plt.figure(1, figsize=(14.40, 9.00))

ax = fig.add_subplot(1,1,1)

sc = ax.scatter(x, y, c=np.asarray(z), marker=None, edgecolor='None',
verts=verts_vec, cmap=colors, alpha=1.)

plt.colorbar(sc, orientation='horizontal')

plt.savefig('test.png', dpi=200)

plt.close(1)

[/code]

But I need to define a marker size for each point, and I also need to
do that in axis scale values, not in points.

I imagine giving verts a list of N*2 tuples instead of 2 tuples, N
being len(x), to define N individual markers.

But when doing that I get the error that vertices.ndim==2.

A less elegant way would be to plot every data point in an individual
scatter plot function, using a for-loop iterating over all data
points. Then, however, I see no way to apply a colormap and colorbar.

What is the best way to accomplish that then?

Thanks,

-Hackstein

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Notwithstanding these probably work (I haven't tried), my gut reaction would have been to color the edges the same as the face, although I don't know if you can give set_edgecolor the same cmap(colors_norm) argument.

-Sterling

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On Apr 26, 2013, at 5:30AM, Ryan Nelson wrote:

Hackstein,

Francesco's suggestion works for me.
col.set_edgecolor( 'none' )

You can also set the linewidth to be 0.
col.set_linewidth( 0 )

reaction would have been to color the edges the same as the face,
although I don't know if you can give set_edgecolor the same
cmap(colors_norm) argument.

  I think you can set the edgecolor equal to the string 'face' to make it use the facecolor.

···

On 2013-04-26 08:31, Sterling Smith wrote:
> Notwithstanding these probably work (I haven't tried), my gut
--
Brendan Barnwell
"Do not follow where the path may lead. Go, instead, where there is no path, and leave a trail."
    --author unknown