How can I set the colorbar limits for a yt.SlicePlot using set_cmap?

Question

I am totally new to Python and I am totally lost. My supervisor helped me to generate a script to see some slices of a 3D velocity model:

import numpy as np
import matplotlib.pyplot as plt
import yt
from yt.units import km

#Import et reshape data
d = np.genfromtxt('velocity_model.txt', delimiter=' ')
nd=22
nx=131
vel = d[:,3].reshape(nd,nx,nx)
lat = d[:,0].reshape(nd,nx,nx)
lon = d[:,1].reshape(nd,nx,nx)
dep = d[:,2].reshape(nd,nx,nx)
# When this is read into YT, depth increases along x axis, longitude increases along y axis and latitude increases along z axis, need to swap x and z and then flip z
dep=dep.swapaxes(0,2) # swap first and third dimensions: gives lon (x), lat (y), depth (z)
vel=vel.swapaxes(0,2) # swap first and third dimensions: 
lat=lat.swapaxes(0,2) # swap first and third dimensions: 
lon=lon.swapaxes(0,2) # swap first and third dimensions: 
dep=dep[:,:,::-1] # reverse z direction
vel=vel[:,:,::-1] # swap first and 2nd dimensions: 
lat=lat[:,:,::-1] # swap first and 2nd dimensions: 
lon=lon[:,:,::-1] # swap first and 2nd dimensions: 
xmin=0
xmax=289
ymin=0
ymax=289
zmin=-100
zmax=5

#Entrer dans YT
data=dict(velocity=(vel,'km/s'),latitude=(lat,'deg'),longitude=(lon,'deg'),depth=(dep,'km'))
bbox = np.array([[xmin,xmax], [ymin,ymax], [zmin,zmax]])
ds=yt.load_uniform_grid(data,vel.shape, length_unit='km', bbox=bbox)

#Off-Axis Slice
for key in ['latitude','longitude','depth','velocity'] :
     L = [0,0,1] # cutting plane=z
     slicepos=-50
     c = [(xmax-xmin)/2, (ymax-ymin)/2, slicepos]
     cut = yt.SlicePlot(ds, L, key,origin='native',center=c) #, width=(200,90,'km'))
     cut.set_log(key, False)
     cut.annotate_text([0.5,0.9],'z={:d} km'.format(slicepos),coord_system='axis')
     cut.set_cmap(field='velocity',cmap='jet_r')
     cut.save()

With this script, I would like to fix the colorbar, because for each image this one change, and it's not easy to interpret like this.

I tried to add limits like this:

h=colorbar
h.Limits = [5 9]
cut.set_cmap(field='velocity',cmap='jet_r', h)

But it's not the good way. Does someone have an idea? I saw lot of things but not for cmap.

Answer 1

You're looking for the set_zlim function:

http://yt-project.org/doc/reference/api/generated/yt.visualization.plot_window.AxisAlignedSlicePlot.set_zlim.html

The set_cmap function just allows you to choose which colormap you want, it does not allow you to set the colormap range. You need to use set_zlim for that. Here's an example, using one of the sample datasets from http://yt-project.org/data :

import yt
ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
plot = yt.SlicePlot(ds, 2, 'density')
plot.set_cmap('density', 'viridis')
plot.set_zlim('density', 1e-28, 1e-25)

This produces the following image:

Answer 2

This is really a question about the yt visualization library rather than matplotlib per se - I've edited the title and tags to reflect this.

I have never come across yt before, but based on the official documentation for yt.SlicePlot , it seems that cut will either be an AxisAlignedSlicePlot or an OffAxisSlicePlot object. Both of these classes have a .set_zlim() method that seems to do what you want:

AxisAlignedSlicePlot.set_zlim(*args, **kwargs)

set the scale of the colormap

Parameters:

• field : string

  the field to set a colormap scale if field == 'all', applies to all plots.

• zmin : float

  the new minimum of the colormap scale. If 'min', will set to the minimum value in the current view.

• zmax : float

  the new maximum of the colormap scale. If 'max', will set to the maximum value in the current view.

Other Parameters:

• dynamic_range : float (default: None)

  The dynamic range of the image. If zmin == None, will set zmin = zmax / dynamic_range If zmax == None, will set zmax = zmin * dynamic_range. When dynamic_range is specified, defaults to setting zmin = zmax / dynamic_range.

In other words, you could probably use:

cut.set_zlim(field='velocity', zmin=5, zmax=9)