# Display displacement field with SimpleITK
**URL:** https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078
**Category:** Beginner Questions
**Created:** [April 26, 2021, 3:38pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078 "2021-04-26T15:38:15Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@Arthur\_Masson](https://discourse.itk.org/u/Arthur_Masson)
#### Post date: [April 26, 2021, 3:38pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/1 "2021-04-26T15:38:15Z")
How could I display a displacement field (in physical space) with arrows on an image slice with SimpleITK ?
I tried using quiver in matplotlib, but I had troubles with the physical to voxel space conversions.
Is there any example available somewhere ?
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### Author:  [@zivy](https://discourse.itk.org/u/zivy)
#### Post date: [April 26, 2021, 3:51pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/2 "2021-04-26T15:51:54Z")
Hello @Arthur_Masson,
SimpleITK is not the tool for this, it has minimal visualization related functionality.
I highly recommend saving the transformation to file and using 3D slicer to do the visualization. Slicer has a very nice module for [visualization of transformations](https://www.slicer.org/wiki/Documentation/4.10/Modules/Transforms).
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### Author:  [@Arthur\_Masson](https://discourse.itk.org/u/Arthur_Masson)
#### Post date: [April 27, 2021, 7:48am UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/3 "2021-04-27T07:48:42Z")
Thanks @zivy ! But I am looking for a method to generate those visualization images programmatically ; to generate a report comparing many different displacement fields.
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### Author:  [@zivy](https://discourse.itk.org/u/zivy)
#### Post date: [April 27, 2021, 12:48pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/4 "2021-04-27T12:48:56Z")
Hi @Arthur_Masson,
Got it. For direct visualization, possibly try the [mplot3D quiver](https://matplotlib.org/stable/gallery/mplot3d/quiver3d.html?highlight=quiver) or look into using [vtk](https://pypi.org/project/vtk/).
Another possibility, which is indirect, would be to visualize the Jacobian determinant image of the displacement field (contraction\<1, expansion\>1, no change in volume=1). The relevant filters are [DisplacementFieldJacobianDeterminantFilter](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1DisplacementFieldJacobianDeterminantFilter.html) and for color, map the result through the [ScalarToRGBColormapImageFilter](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1ScalarToRGBColormapImageFilter.html).
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### Author:  [@dchen](https://discourse.itk.org/u/dchen)
#### Post date: [April 27, 2021, 1:52pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/5 "2021-04-27T13:52:57Z")
You should be able to script Slicer to generate renderings.
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### Author:  [@Arthur\_Masson](https://discourse.itk.org/u/Arthur_Masson)
#### Post date: [April 27, 2021, 2:07pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/6 "2021-04-27T14:07:31Z")
Thanks zivy and dchen!
I ended up using the following script:
```
flair1_path = data_path + 'flair.nii.gz'
df_path = data_path + 'df.nii.gz'
image = sitk.ReadImage(flair1_path)
image_data = sitk.GetArrayFromImage(image)
slice_index = image_data.shape[0]//2
image_slice = image_data[slice_index,:,:][::-1,::-1]
spacing = image.GetSpacing()
size = image.GetSize()
# # extent = (left, right, bottom, top)
extent = (0, size[0] * spacing[0], size[1] * spacing[1], 0)
plt.figure(figsize=(20,20))
t=plt.imshow(image_slice,extent=extent,interpolation=None)
t.set_cmap("gray")
df = sitk.ReadImage(df_path)
df_data = sitk.GetArrayFromImage(df)
slice_index = df_data.shape[0]//2
df_slice = df_data[slice_index,:,:,:]
orientation = df.GetDirection()
spacing = df.GetSpacing()
orientation = np.array(orientation).reshape((3,3))
voxel_to_physical = ( spacing * np.identity(3) ) @ orientation
physical_to_voxel = np.linalg.inv(voxel_to_physical)
# for i in range(df_slice.shape[0]):
# for j in range(df_slice.shape[1]):
# p = physical_to_voxel @ df_slice[i,j]
# df_slice[i,j] = p
x = df_slice[:,:,0][::-1,::-1]
y = -df_slice[:,:,1][::-1,::-1]
coordsX = np.arange(0, size[0] * spacing[0], size[0] * spacing[0] / float(image_data.shape[2]) )
coordsY = np.arange(0, size[1] * spacing[1], size[1] * spacing[1] / float(image_data.shape[1]) )
ic(image_slice.shape)
ic(df_slice.shape)
ic(image_data.shape[2])
ic(image_data.shape[1])
ic(x.shape)
ic(coordsX.shape)
ic(coordsY.shape)
ic(size[0] * spacing[0])
ic(size[0] * spacing[0] / float(image_data.shape[2]))
coordsX, coordsY = np.meshgrid(coordsX, coordsY)
M = np.sqrt(x*x+y*y)
qq=plt.quiver(coordsX, coordsY, x, y, M, cmap=plt.cm.jet, units='x', scale=1)
plt.axis('off')
plt.show()
```
I was confused by the physical to voxel space conversion ; and the numpy to simpleITK / matlab ordering conversion.
I am surprised that, when generating the displacement field, `demons.SetUseImageSpacing(True)` does not seem to make any difference (the generated field is the same with `demons.SetUseImageSpacing(True)` and `demons.SetUseImageSpacing(False)`), and that I got better results without converting to voxel space.
---
### Author:  [@Arthur\_Masson](https://discourse.itk.org/u/Arthur_Masson)
#### Post date: [April 27, 2021, 2:54pm UTC](https://discourse.itk.org/t/display-displacement-field-with-simpleitk/4078/7 "2021-04-27T14:54:02Z")
I asked [a new question](https://discourse.itk.org/t/fastsymmetricforcesdemonsregistrationfilter-setuseimagespacing-not-working/4080) about the `FastSymmetricForcesDemonsRegistrationFilter.SetUseImageSpacing()` problem.