GenericModel#

class sunkit_dem.GenericModel(

data,

kernel,

temperature_bin_edges: Unit('K'),

kernel_temperatures=None,

**kwargs,

)[source]#

Bases: BaseModel

Base class for implementing a differential emission measure model

Parameters:

data (NDCollection)
kernel (dict) – Quantity objects containing the kernels of each response. The keys should correspond to those in data.
temperature_bin_edges (Quantity) – Edges of the temperature bins in which the DEM is computed. The rightmost edge is included. The kernel is evaluated at the bin centers. The bin widths must be equal in log10.

Attributes Summary

`combined_mask`	Combined mask of all members of `data`.
`data`
`data_matrix`
`kernel`
`kernel_matrix`
`temperature_bin_centers`
`temperature_bin_widths`
`uncertainty_matrix`

Methods Summary

fit(*args, **kwargs)

Apply inversion procedure to data.

Attributes Documentation

combined_mask#: Combined mask of all members of data. Will be True if any member is masked. This is propagated to the final DEM result

Methods Documentation

fit(*args, **kwargs)[source]#

Apply inversion procedure to data.

Returns:: dem – Differential emission measure as a function of temperature. The temperature axis is evenly spaced in \(\log{T}\). The number of dimensions depend on the input data.
Return type:: NDCube