I am using matplotlib for visualisation. I need 3d visualisation and also the animations in my visualisation. I have searched about the 3d visualisation and animation in matplotlib but get nothing useful information. Is it possible or not to use matplotlib for 3d visuallisation and animations. What are the links that I can study about it ?
Animation and 3D plot are available on mplot3d library. Take a look at wire3d_animation and mayavi Animation.
Here is what I, probably most of people, use for python numpy plotting.
For 2D figure plotting, use matplotlib.
For 3D surface and volume plotting, use mayavi.
Both of them come with their own approaches of animating plots. Nevertheless, moviepy is a great alternative approach.
Related
I can zoom when i use a 2d plot using the area selection tool with the mouse on the plot, but when i want to do the same on a 3d plot, the 3d plot is rotated.
Is this not possible in 3d mode or do i just use the wrong mouse button / keys?
I used the jupyter notebook with %matplotlib widget, after installing ipympl and restarting jupyter notebook.
Î tried it with qt5, but the zoom in the 3d plots is not possible, or at least i dont know how to do it.
I have to visualize the interactive 3D plot on tensorboard. Can the tensorboard visualize this or is there any way to display this on tensorboard.
Thank you.
Yes, you can use the mesh plugin on TensorBoard. It'll allow you to create a visualization similar to those found on Three.js . You pass in the vertices, colors, and faces of the 3D data and TensorBoard will create a 3D interactive visualization. There are other options such as projections but those are mainly used for embeddings.
My pandas data frame has two columns: category and duration. And
I use the following code to make a box plot of all data points.
import matplotlib.pyplot as plt
plt.boxplot(df.duration)
plt.show()
However, if I want one box fore each category, how do I modify the above code? Thanks!
In addition to Wen's answer, which is spot on, you might want to check out the seaborn library. It was made to do this kind of plot.
Seaborn is a Python visualization library based on matplotlib. It
provides a high-level interface for drawing attractive statistical
graphics.
Check the documentation for boxplots
Draw a box plot to show distributions with respect to categories.
sns.boxplot(data=df, x='category', y='duration')
We can do it with pandas
#df=pd.DataFrame({'category':list('aacde'),'duration':[1,3,2,3,4]}) sample data
df.assign(index=df.groupby('category').cumcount()).pivot('index','category','duration').plot(kind='box')
Cartopy seems like a great tool for Geoscience, but it appears to lack a method for plotting vector data on a map together with their error ellipses. Is there a straightforward way to add error ellipses centered on the tips of vector data?
Cartopy inherits all its vector plotting functionality from matplotlib. Cartopy provides a way to project the vectors, but they are drawn by matplotlib. I haven't heard of a feature you describe in matplotlib, so I'm afraid the answer is probably no.
I want to create a contour plot with matlibplot and generate a shapefile from it so that I can use it in QGIS to display it.
Though it is possible to plot a map with matplotlib and then overlay with my contour plot, the choices of map sources are limited. It would be easier to export the contour plot in a shapefile and loaded in QGIS with a customized map.
Thanks!
There is a contour plugin available in QGIS, and it is based on the contouring functions of matplotlib. It's still a little bit buggy but hopefully that will be corrected in the future.