I am plotting a contourmap. When first plotting I noticed I had my axes wrong. So I switched the axes and noticed that the structure of both plots is different. On the first plot the axes and assignments are correct, but the structure is messy. On the second plot it is the other way around.
Since it's a square matrix I don't see why there should be a sampling issue.
Transposing the matrix with z-values or the meshgrid of x and y does not help either. Whatever way I plot x and y correctly it keeps looking messy.
Does anybody here know any more ideas which I can try or what might solve it?
The problem was the sampling. Although the arrays have the same size, the stepsize in the plot is not equal for x and y axis.
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My goal is to create a 3d plot of the field inside a Paul trap. I've been trying to do this 3D plot without any success. My problem is that I have a 3D matrix that represents the potential everywhere in space, but I haven't found a way to plot it as a contour or color map.
All the options I saw required me to create a meshgrid of x and y and then plot z as a function of x and y, which isn't what I need because the potential depends on all 3 coordinates. Does anyone know of a function to plot in such a way, or at least a way to trick other functions into doing what I need?
Thank you in advance!
I'm plotting a Matrix with contourf, the Matrix is 883x883, the problem is that when plotting it the axis in the plots go from 0 to 883, but I would like to give it another values, more exactly, I'd like it to go from -20 to 20. How can I set that? I am very new in python, so I'd appreciate your help.
When you use contourf, you can provide the location of your data points using the optional X and Y arguments. This will only work as expected if your data is structured, meaning if you can generate a grid made of rectangles for which the nodes would represent the location of your data points. If this is not the case, then I would suggest using a triangulation and provide it to tricontourf.
Is there a way to let matplotlib know to recompute the optimal bounds of a plot?
My problem is that, I am manually computing a bunch of boxplots, putting them at various locations in a plot. By the end, some boxplots extend beyond the plot frame. I could hard-code some xlim and ylim's for now, but I want a more general solution.
What I was thinking was a feature where you say "ok plt I am done plotting, now please adjust the bounds so that all my data is nicely within the bounds".
Is this possible?
EDIT:
The answer is yes.
Follow-up question: Can this be done for the ticks as well?
You want to use matplotlib's automatic axis scaling. You can do this with either axes.axis with the "auto" input or axes.set_autoscale_on
ax.axis('auto')
ax.set_autoscale_on()
If you want to auto-scale only the x or y axis, you can use set_autoscaley_on or set_autoscalex_on.
In a standard 3D python plot, each data point is, by default, represented as a sphere in 3D. For the data I'm plotting, the z-axis is very sensitive, while the x and y axes are very general, so is there a way to make each point on the scatter plot spread out over the x and y direction as it normally would with, for example, s=500, but not spread at all along the z-axis? Ideally this would look like a set of stacked discs, rather than overlapping spheres.
Any ideas? I'm relatively new to python and I don't know if there's a way to make custom data points like this with a scatter plot.
I actually was able to do this using the matplotlib.patches library, creating a patch for every data point, and then making it whatever shape I wanted with the help of mpl_toolkits.mplot3d.art3d.
You might look for something called "jittering". Take a look at
Matplotlib: avoiding overlapping datapoints in a "scatter/dot/beeswarm" plot
It works by adding random noise to your data.
Another way might be to reduce the variance of the data on your z-axis (e.g. applying a log-function) or adjusting the scale. You could do that with ax.set_zscale("log"). It is documented here http://matplotlib.org/mpl_toolkits/mplot3d/api.html#mpl_toolkits.mplot3d.axes3d.Axes3D.set_zscale
I'm using this code to plot a cumulative frequency plot:
lot = ocum.plot(x='index', y='cdf', yticks=np.arange(0.0, 1.05, 0.1))
plot.set_xlabel("Data usage")`
plot.set_ylabel("CDF")
fig = plot.get_figure()
fig.savefig("overall.png")
How it appears as follows and is very crowded around the initial part. This is due to my data spread. How can I make it more clear? (uploading to postimg because I don't have enough reputation points)
http://postimg.org/image/ii5z4czld/
I hope that I understood what you want: give more space to the visualization of the "CDF" development for smaller "data usage" values, right? Typically, you would achieve this by changing your X axis scale from linear to logarithmic. Head over to Plot logarithmic axes with matplotlib in python for seeing different ways to achieve that. The simplest might be, in your case, to replace plot() with semilogx().