color-mapping

I want to generate a heat map image of a floor. I have the following things: A black & white .png image of the floor A three column array stored in Matlab. -- The first two columns indicate the X & Y coordinates of the floorpan image -- The third coordinate denotes the "temperature" of that particular coordinate I want to generate a heat map of the floor that will show the "temperature" strength in those coordinates. However, I want to display the heat map on top of the floor plan so that the viewers can see which rooms lead to which "temperatures". Is there any software that does this job?

I have a simple scatter plot where each point has a color given by a value between 0 and 1 set to a chosen colormap. Here's a MWE of my code: import matplotlib.pyplot as plt import numpy as np import matplotlib.gridspec as gridspec x = np.random.randn(60) y = np.random.randn(60) z = [np.random.random() for _ in range(60)] fig = plt.figure() gs = gridspec.GridSpec(1, 2) ax0 = plt.subplot(gs[0, 0]) plt.scatter(x, y, s=20) ax1 = plt.subplot(gs[0, 1]) cm = plt.cm.get_cmap('RdYlBu_r') plt.scatter(x, y, s=20 ,c=z, cmap=cm) cbaxes = fig.add_axes([0.6, 0.12, 0.1, 0.02]) plt.colorbar(cax=cbaxes, ticks=

I would like to get a density distribution plot like this density http://www.nicolacarlon.it/out.png with the alpha channel instead of the blue channel like this density http://www.nicolacarlon.it/out2.png I found this code but it doesn't works :( theCM = cm.get_cmap() theCM._init() alphas = np.abs(np.linspace(-1.0, 1.0, theCM.N)) theCM._lut[:-3,-1] = alphas plt.imshow(img, cmap=theCM) plt.savefig("out.svg", transparent=True) This is a bug with the Colormap class of matplotlib. It exists in 0.99.x versions of matplotlib, but has been fixed as of 1.x. See the bug fix for a description of how it

I am plotting a histogram using plt.imshow(hist2d, norm = LogNorm(), cmap = gray) where hist2d is a matrix of histogram values. This works fine except for elements in hist2d that are zero. In particular, I obtain the following image but would like the white patches to be black. Thank you! tacaswell Here's an alternative method that does not require you to muck with your data by setting a rgb value for bad pixels. import copy data = np.arange(25).reshape((5,5)) my_cmap = copy.copy(matplotlib.cm.get_cmap('gray')) # copy the default cmap my_cmap.set_bad((0,0,0)) plt.imshow(data, norm=matplotlib

I have four dimensional data (x, y, z displacements; and respective voltages) which I wish to plot in a 3d scatterplot in python. I've gotten the 3d plot to render, but I want to have the colour of the points change using a colourmap, dependent upon the magnitude of the point's voltage. I've tried a few things, but can't seem to get it to work I'm getting the error ValueError: Cannot convert argument type <type 'numpy.ndarray'> to rgba array . I'm not sure exactly how to convert what I need to convert, so if anybody could please offer some help, I'd be most appreciative. My code is here: fig =

just want to check if it is possible to make a custom colormap with only 3 colors? (there is no need for gradient). Example: Data ranges from 0-100 , so 0-33 is one color, 34-67 is another color, and 68-100 is another color. Just use a colormap with three rows. Each row defines a color in terms of R, G, B components. A = randi(100,16,16); %// example data imagesc(A) %// display matrix as image colormap([1 0 0; 0 1 0; 0 0 1]) %// apply colormap colorbar %// show color bar This defines uniformly spaced thresholds between colors. If you need more control you need to have more than three rows,