Unable to plot the results in matplotlib after extracting the co-ordinates and the corresponding attributes.

[vavachan]

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• I used the GitHub search to find a similar question and didn't find it.
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Sample Code What is the problem, question, or error?

Write a short description telling me what you are doing, what you expect to happen, and what is currently happening.

# I read the a vti file 
import pyvista as pv
data = pv.read(file)

# this gives me what I expect to see. 
SLICE=data.slice(normal=[0,0,1],origin=[45,15,30])
SLICE.plot(scalars='geometry',style='points',point_size=20,cpos='xy') # output attached as Fig 1.  


# However, if I extract the data and plot
fig,ax = plt.subplots(1,1)
data=pv.read(file)
SLICE=data.slice(normal=[0,0,1],origin=[45,15,30])
xy=SLICE.points[:,0:2]
geo_data=SLICE['geometry']

x_plot=np.arange(xy[:,0].min(),xy[:,0].max()+1)
y_plot=np.arange(xy[:,1].min(),xy[:,1].max()+1)

geo_data=np.transpose(geo_data.reshape(x_plot.shape[0],y_plot.shape[0]))

cf=ax.pcolormesh(x_plot,y_plot,geo_data)

fig.colorbar(cf) # this doesn't show the result correctly. fig attached as Fig 2

Description

Fig 1

Fig 2

My questions

Why are the outputs different ?

How to do this correctly?

I followed this example

pyvista/pyvista-support#70

The data used there, mesh = pv.examples.load_uniform() works correctly with my matplotlib code. So I suspect the issue is with my dataset?

HeatEquation_iT0000000iC00004.vti.zip

System Information

--------------------------------------------------------------------------------
  Date: Wed Mar 27 09:58:01 2024 EDT

                OS : Darwin
            CPU(s) : 14
           Machine : arm64
      Architecture : 64bit
               RAM : 36.0 GiB
       Environment : Jupyter
       File system : apfs
        GPU Vendor : Apple
      GPU Renderer : Apple M3 Max
       GPU Version : 4.1 Metal - 88
  MathText Support : True

  Python 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:54:21)
  [Clang 16.0.6 ]

           pyvista : 0.43.4
               vtk : 9.2.6
             numpy : 1.26.4
        matplotlib : 3.8.3
            scooby : 0.9.2
             pooch : 1.8.1
            pillow : 10.2.0
           IPython : 8.22.2
        ipywidgets : 8.1.2
        jupyterlab : 4.1.5
             trame : 3.5.4
      trame_client : 2.16.4
      trame_server : 2.17.2
         trame_vtk : 2.8.5
     trame_vuetify : 2.4.3
      nest_asyncio : 1.6.0
--------------------------------------------------------------------------------

Screenshots

No response

[vavachan]

I have made some progress on understanding this,

Changing

geo_data=np.transpose(geo_data.reshape(x_plot.shape[0],y_plot.shape[0]))

to

geo_data=(geo_data.reshape(y_plot.shape[0],x_plot.shape[0]))

Gives the correct result.

But I am now faced with another Issue.

My data actually consists of 8 blocks.

Archive.zip

I can plot the individual blocks as mentioned above. However, when I combine all of them using

data = pv.read(file)
combined = data.combine()

xy=combined.slice(normal=[0,0,1]).points[:,0:2]
geo_data=combined.slice(normal=[0,0,1])['geometry']

x_plot=np.arange(xy[:,0].min(),xy[:,0].max()+1)
y_plot=np.arange(xy[:,1].min(),xy[:,1].max()+1)

geo_data=(geo_data.reshape(y_plot.shape[0],x_plot.shape[0]))
cf=ax.pcolormesh(x_plot,y_plot,geo_data)

fig.colorbar(cf)

gives wrong result.