Accessing and Plotting Meshes

Setup

Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).



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!pip install -I "phoebe>=2.2,<2.3"

As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.



In [1]:

    
%matplotlib inline



In [2]:

    
import phoebe

logger = phoebe.logger()

b = phoebe.default_binary()

The 'Mesh' Dataset

You must create a mesh dataset and specify the times and columns which you'd like exposed. For more information, see the tutorial on the MESH dataset.

The mesh will be exposed at the times specified by the compute_times Parameter, as well as any times referenced by the include_times SelectParameter.

So let's add an LC and MESH datasets.



In [3]:

    
b.add_dataset('lc', times=phoebe.linspace(0,1,6))









    Out[3]:





<ParameterSet: 20 parameters | contexts: dataset, compute, constraint>



In [4]:

    
b.add_dataset('mesh')









    Out[4]:





<ParameterSet: 7 parameters | contexts: dataset, compute, constraint>

NEW in PHOEBE 2.2: Unlike other datasets, the mesh dataset cannot accept actual observations, so there is no times parameter, only the compute_times and compute_phases parameters. For more details on these, see the Compute Times & Phases tutorial.



In [5]:

    
print(b.get_parameter(qualifier='compute_times', kind='mesh'))









    



Parameter: compute_times@mesh01@dataset
                       Qualifier: compute_times
                     Description: Times to use during run_compute.
                           Value: [] d
                  Constrained by: 
                      Constrains: compute_phases@mesh01@dataset
                      Related to: period@binary@component, compute_phases@mesh01@dataset



In [6]:

    
print(b.get_parameter(qualifier='include_times', kind='mesh'))









    



Parameter: include_times@mesh01@dataset
                       Qualifier: include_times
                     Description: append to compute_times from the following datasets/time standards
                           Value: []
                         Choices: lc01, t0_perpass@binary, t0_supconj@binary, t0_ref@binary, t0@system

Note that we can manually set the times of the mesh AND/OR reference the times for existing non-mesh datasets (such as the light curve we just added) as well as any of the various t0s in the system.



In [7]:

    
b.set_value('compute_times', kind='mesh', value=[10])



In [8]:

    
b.set_value('include_times', kind='mesh', value=['lc01'])



In [9]:

    
b.run_compute()









    Out[9]:





<ParameterSet: 60 parameters | kinds: mesh, lc>



In [10]:

    
print(b.filter(kind='mesh', context='model').times)









    



['00.000000', '00.200000', '00.400000', '00.600000', '00.800000', '01.000000', '10.000000']

By default, the mesh only exposes the geometric columns of the triangles, in both plane-of-sky and roche coordinates.



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print(b.filter(kind='mesh', context='model').qualifiers)









    



['times', 'uvw_elements', 'uvw_normals', 'xyz_elements', 'xyz_normals']

But we can also specify other columns to be included (by setting the columns SelectParameter before calling run_compute)



In [13]:

    
print(b.get_parameter(qualifier='columns', kind='mesh', context='dataset'))









    



Parameter: columns@mesh01@dataset
                       Qualifier: columns
                     Description: columns to expose within the mesh
                           Value: []
                         Choices: volume, xs, ys, zs, vxs, vys, vzs, nxs, nys, nzs, us, vs, ws, vus, vvs, vws, nus, nvs, nws, areas, loggs, teffs, rprojs, mus, visibilities, visible_centroids, rs, intensities@lc01, normal_intensities@lc01, abs_intensities@lc01, abs_normal_intensities@lc01, boost_factors@lc01, ldint@lc01, pblum_ext@lc01, abs_pblum_ext@lc01, ptfarea@lc01



In [14]:

    
b.set_value('columns', value=['teffs'])



In [15]:

    
b.run_compute()









    



Sat, 08 Jun 2019 11:57 BUNDLE       WARNING overwriting model: latest






    Out[15]:





<ParameterSet: 74 parameters | kinds: mesh, lc>



In [16]:

    
print(b.filter(kind='mesh', context='model').qualifiers)









    



['times', 'uvw_elements', 'uvw_normals', 'xyz_elements', 'xyz_normals', 'teffs']



In [17]:

    
print(b.get_value('teffs', time=0.0, component='primary'))









    



[6026.91748731 6026.97665997 6026.91260356 ... 5993.51016065 5993.2855728
 5994.18366387]

Any of the exposed columns are then available for plotting the mesh, via b.plot.



In [18]:

    
afig, mplfig = b.plot(kind='mesh', time=0.2, fc='teffs', ec='none', show=True)

Additionally, if we know that we only want to expose (and plot) the mesh in plane-of-sky, we can save some computation time by ommitting roche coordinates when computing the model. This is done via the coordinates SelectParameter.



In [19]:

    
print(b.get_parameter(qualifier='coordinates', kind='mesh', context='dataset'))









    



Parameter: coordinates@mesh01@dataset
                       Qualifier: coordinates
                     Description: coordinates to expose the mesh.  uvw (plane of sky) and/or xyz (roche)
                           Value: ['xyz', 'uvw']
                         Choices: xyz, uvw



In [20]:

    
b.set_value('coordinates', value=['uvw'])



In [21]:

    
b.run_compute()









    



Sat, 08 Jun 2019 11:57 BUNDLE       WARNING overwriting model: latest






    Out[21]:





<ParameterSet: 46 parameters | kinds: mesh, lc>



In [22]:

    
print(b.filter(kind='mesh', context='model').qualifiers)









    



['times', 'uvw_elements', 'uvw_normals', 'teffs']



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