I have three 2d arrays: X,Y,Z, which contain irregular 3d points coordinate,respectively.And another 2d array data, which contains the values on those points.
What I want to do is to display this data in 3d space , with 0 value part masked out.Much like this one:
In matlab, I can use function fill3 to achieve this, but how can I plot the same kind of picture in matplotlib or mayavi ? I have tried to use mask array ,plot_surface and colorface together, as the example here:
Plotting a masked surface plot using python, numpy and matplotlib
and it worked, the result is the link below:
but that is really really slow, and will cost too much time. Is there a better way?
Well, today I find out an alternative way to solve the problem. Except using plot_surface, I choose to use scatter3D,
the core code is some what like this
aa=np.shape(X)[0]
bb=np.shape(X)[1]
x=X.reshape(aa*bb)
y=Y.reshape(aa*bb)
z=Z.reshape(aa*bb)
data=data.reshape(aa*bb)
x1=[]
y1=[]
z1=[]
da1=[]
for i in range(aa*bb):
if data[i]>0:
x1.append(x[i])
y1.append(y[i])
z1.append(z[i])
da1.append(data[i])
my_cmap=cm.jet
my_cmap.set_over('c')
my_cmap.set_under('m')
N=da1/max(da1)
fig=plt.figure()
ax=fig.add_subplot(111,projection='3d')
ax.scatter3D(x1,y1,z1,s=6,alpha=0.8,marker=',',facecolors=my_cmap(N),lw=0)
and the result is like this:
this doesn't really solve the problem, but it is a nice substitution.
I'll keep waiting for more answers.
Related
I have data that I would like to save as png's. I need to keep the exact pixel dimensions - I don't want any inter-pixel interpolation, smoothing, or up/down sizing, etc. I do want to use a colormap, though (and mayber some other features of matplotlib's imshow). As I see it there are a couple ways I could do this:
1) Manually roll my own colormapping. (I'd rather not do this)
2) Figure out how to make sure the pixel dimenensions of the image in the figure produced by imshow are exactly correct, and then extract just the image portion of the figure for saving.
3) Use some other method which will directly give me a color mapped array (i.e. my NxN grayscale array -> NxNx3 array, using one of matplotlibs colormaps). Then save it using another png save method such as scipy.misc.imsave.
How can I do one of the above? (Or another alternate)
My problem arose when I was just saving the figure directly using savefig, and realized that I couldn't zoom into details. Upscaling wouldn't solve the problem, since the blurring between pixels is exactly one of the things I'm looking for - and the pixel size has a physical meaning.
EDIT:
Example:
import numpy as np
import matplotlib.pyplot as plt
X,Y = np.meshgrid(np.arange(-50.0,50,.1), np.arange(-50.0,50,.1))
Z = np.abs(np.sin(2*np.pi*(X**2+Y**2)**.5))/(1+(X/20)**2+(Y/20)**2)
plt.imshow(Z,cmap='inferno', interpolation='nearest')
plt.savefig('colormapeg.png')
plt.show()
Note zooming in on the interactive figure gives you a very different view then trying to zoom in on the saved figure. I could up the resolution of the saved figure - but that has it's own problems. I really just need the resolution fixed.
It seems you are looking for plt.imsave().
In this case,
plt.imsave("filename.png", Z, cmap='inferno')
I'm constructing a graph plot in Julia and need to color each edge of the graph differently, based on some weighting factor. I can't find a way to get a specific RGB (or HSV, it doesn't matter) value from a colormap. Let's say I'd like to get the RGB value on 'jet' that would correspond to a data value of n on imshow plot.
In python, I would just use jet(n), where n is the value along the colormap in which I am interested. PyPlot in Julia doesn't seem to have wrapped this functionality. I've also already tried indexing into the cmap object returned from get_cmap(). Any advice?
I'm stumped, so even an approximate solution would help. Thanks!
Maybe you can look at the Colors.jl package (https://github.com/JuliaGraphics/Colors.jl):
using Colors
palette = colormap("Oranges", 100)
Then you can access each color with palette[n]. Or are you using PyCall? A code describing what you're trying to do would help.
I have some data defined on a sphere (a sphere not the earth): is it possible with Python 2.6 and matplotlib to draw them on map (of the type of Mercator map) "automatically" or do I have to project the data?
Edit: All of my data are lat-long.
It really depends on what you have and what you want: x-y and/or lat-lon? It looks like your question is similar to a problem I had and more-or-less answered:
matplotlib and apect ratio of geographical-data plots
Consider using set_aspect(), using the reciprocal of the mean latitude of your data.
See matplotlib and apect ratio of geographical-data plots for a working example.
In an answer to an earlier question of mine regarding fixing the colorspace for scatter images of 4D data, Tom10 suggested plotting values as symbols in order to double-check my data. An excellent idea. I've run some similar demos in the past, but I can't for the life of me find the demo I remember being quite simple.
So, what's the easiest way to plot numerical values as the symbol in a scatter plot instead of 'o' for example? Tom10 suggested plt.txt(x,y,value)- and that is the implementation used in a number of examples. I however wonder if there's an easy way to evaluate "value" from my array of numbers? Can one simply say: str(valuearray) ?
Do you need a loop to evaluate the values for plotting as suggested in the matplotlib demo section for 3D text scatter plots?
Their example produces:
(source: sourceforge.net)
However, they're doing something fairly complex in evaluating the locations as well as changing text direction based on data. So, is there a cute way to plot x,y,C data (where C is a value often taken as the color in the plot data- but instead I wish to make the symbol)?
Again, I think we have a fair answer to this- I just wonder if there's an easier way?
The easiest way I've seen to do this is:
for x, y, val in zip(x_array, y_array, val_array):
plt.text(x, y, val)
Also, btw, you suggested using str(valarray), and this, as you may have noticed doesn't work. To convert an array of numbers to a sequence of strings you could use
valarray.astype(str)
to get a numpy array, or,
[str(v) for v in valarray]
to get a Python list. But even with valarray as a proper sequence of strings, plt.text won't iterate over it's inputs.
In GNU Octave you can make a picture where different colors represent different values in a matrix. You can also add a colorbar, which shows what color corresponds to what value.
Is it possible to somehow add units to the values shown in the colorbar? Instead of saying “0.36” it would say “0.36 V/nm”? I know this is possible in Matlab, but I can’t figure out how to do it in Octave. Any good workarounds?
I assume someone here will mention that I should use matplotlib instead (that usually happens). How would you accomplish the same thing with that?
The matplotlib answer (using pylab) is
imshow(random((20,20)))
colorbar(format='%.2f V/nm')
In Octave it seems that the following works (but I'm no Octave expert so maybe there's a better way):
c=colorbar();
labels = {};
for v=get(c,'ytick'), labels{end+1} = sprintf('%.2f V/nm',v); end
set(c,'yticklabel',labels);