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lc_generation [2023/01/04 11:44]
theoastro |
lc_generation [2023/06/02 17:05] (current)
theoastro |
| Note that the parameters vary from model to model - an overview can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/blob/c9f55663f27625ca7c3aa1b8d74dcb231ca060e7/nmma/em/model.py#L16|here]]. Some models such as ''Bu2019lm'' require to embed a SVD grid for light curve computation which can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/tree/main/svdmodels|here]]. With these, a light curve object can be instantiated as follows: | Note that the parameters vary from model to model - an overview can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/blob/c9f55663f27625ca7c3aa1b8d74dcb231ca060e7/nmma/em/model.py#L16|here]]. Some models such as ''Bu2019lm'' require to embed a SVD grid for light curve computation which can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/tree/main/svdmodels|here]]. With these, a light curve object can be instantiated as follows: |
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| t = np.arange(tmin=0.1, tmax=20.0 ,deltat=0.1) | tmin=0.1 |
| | tmax=20.0 |
| | deltat=0.1 |
| | t = np.arange(tmin, tmax, deltat) |
| lc_model = nmma.em.model.SVDLightCurveModel(model='Bu2019lm', sample_times = t, svd_path = "nmma/svdmodels/", parameter_conversion=None, mag_ncoeff=None, lbol_ncoeff=None) | lc_model = nmma.em.model.SVDLightCurveModel(model='Bu2019lm', sample_times = t, svd_path = "nmma/svdmodels/", parameter_conversion=None, mag_ncoeff=None, lbol_ncoeff=None) |
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