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Added dm nondiag test #114

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Added dm nondiag test #114

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478eaf6
Added dm nondiag test
Jyvol Jun 15, 2021
53547f9
Update test_models.py
Jyvol Jun 21, 2021
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Update test_models.py
Jyvol Jun 22, 2021
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Jyvol Jun 22, 2021
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Jyvol Jun 22, 2021
874ced1
Nondiag fix
Jyvol Jun 23, 2021
e160403
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Jyvol Jul 14, 2021
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Jyvol Jul 14, 2021
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Jyvol Jul 15, 2021
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Jyvol Jul 20, 2021
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Jyvol Jul 22, 2021
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75 changes: 75 additions & 0 deletions tests/test_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,81 @@ def test_model_singlepsr_noise_dip_cusp(nodmx_psrs,caplog):
x0 = {pname:p.sample() for pname,p in zip(m.param_names, m.params)}
m.get_lnlikelihood(x0)

def test_model_singlepsr_noise_dm_nondiag(nodmx_psrs,caplog):
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# caplog.set_level(logging.CRITICAL)
mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='dmx_like')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='sq_exp')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='sq_exp_rfband')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='periodic')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='periodic_rfband')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_nondiag_kernel ='None')
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assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

def test_model_singlepsr_noise_dm_diag(nodmx_psrs,caplog):
# caplog.set_level(logging.CRITICAL)
mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_psd ='powerlaw')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_psd ='turnover')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_psd ='tprocess')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)

mn=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
dm_type='gp', dmgp_kernel ='diag',
dm_psd ='tprocess_adapt')
assert hasattr(mn,'get_lnlikelihood')
x0 = {pname:p.sample() for pname,p in zip(mn.param_names, mn.params)}
mn.get_lnlikelihood(x0)


def test_model_singlepsr_noise_chrom_nondiag(nodmx_psrs,caplog):
# caplog.set_level(logging.CRITICAL)
m=models.model_singlepsr_noise(nodmx_psrs[1], dm_var=True,
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