FluxPointsDataset

class gammapy.datasets.FluxPointsDataset(models=None, data=None, mask_fit=None, mask_safe=None, name=None, meta_table=None)

Bases: gammapy.datasets.Dataset

Fit a set of flux points with a parametric model.

Parameters

modelsModels

Models (only spectral part needs to be set)

dataFluxPoints

Flux points.

mask_fitnumpy.ndarray

Mask to apply for fitting

mask_safenumpy.ndarray

Mask defining the safe data range. By default upper limit values are excluded.

meta_tableTable

Table listing information on observations used to create the dataset. One line per observation for stacked datasets.

Examples

Load flux points from file and fit with a power-law model:

from gammapy.modeling import Fit
from gammapy.modeling.models import PowerLawSpectralModel, SkyModel
from gammapy.estimators import FluxPoints
from gammapy.datasets import FluxPointsDataset

filename = "$GAMMAPY_DATA/tests/spectrum/flux_points/diff_flux_points.fits"
flux_points = FluxPoints.read(filename)

model = SkyModel(spectral_model=PowerLawSpectralModel())

dataset = FluxPointsDataset(model, flux_points)
fit = Fit()
result = fit.run([dataset])
print(result)
print(result.parameters.to_table())

Note: In order to reproduce the example you need the tests datasets folder. You may download it with the command gammapy download datasets --tests --out $GAMMAPY_DATA

Attributes Summary

gti	Good time interval info (GTI)
mask	Combined fit and safe mask
models
name
stat_type
tag

Methods Summary

copy([name])	A deep copy.
data_shape()	Shape of the flux points data (tuple).
flux_pred()	Compute predicted flux.
from_dict(data, **kwargs)	Create flux point dataset from dict.
plot_fit([ax_spectrum, ax_residuals, …])	Plot flux points, best fit model and residuals in two panels.
plot_residuals([ax, method])	Plot flux point residuals.
plot_spectrum([ax, kwargs_fp, kwargs_model])	Plot spectrum including flux points and model.
residuals([method])	Compute the flux point residuals ().
stat_array()	Fit statistic array.
stat_sum()	Total statistic given the current model parameters.
to_dict()	Convert to dict for YAML serialization.
write(filename[, overwrite])	Write flux point dataset to file.

Attributes Documentation

gti

Good time interval info (GTI)

mask

Combined fit and safe mask

models

name

stat_type = 'chi2'

tag = 'FluxPointsDataset'

Methods Documentation

copy(name=None)

A deep copy.

Parameters

namestr

Name of the copied dataset

Returns

datasetDataset

Copied datasets.

data_shape()

Shape of the flux points data (tuple).

flux_pred()

Compute predicted flux.

classmethod from_dict(data, **kwargs)

Create flux point dataset from dict.

Parameters

datadict

Dict containing data to create dataset from.

Returns

datasetFluxPointsDataset

Flux point datasets.

plot_fit(ax_spectrum=None, ax_residuals=None, kwargs_spectrum=None, kwargs_residuals=None)

Plot flux points, best fit model and residuals in two panels.

Calls plot_spectrum and plot_residuals.

Parameters

ax_spectrumAxes

Axes to plot flux points and best fit model on.

ax_residualsAxes

Axes to plot residuals on.

kwargs_spectrumdict

Keyword arguments passed to plot_spectrum.

kwargs_residualsdict

Keyword arguments passed to plot_residuals.

Returns

ax_spectrum, ax_residualsAxes

Flux points, best fit model and residuals plots.

plot_residuals(ax=None, method='diff', **kwargs)

Plot flux point residuals.

Parameters

axAxes

Axes to plot on.

method{“diff”, “diff/model”}

Normalization used to compute the residuals, see FluxPointsDataset.residuals.

**kwargsdict

Keyword arguments passed to errorbar.

Returns

axAxes

Axes object.

plot_spectrum(ax=None, kwargs_fp=None, kwargs_model=None)

Plot spectrum including flux points and model.

Parameters

axAxes

Axes to plot on.

kwargs_fpdict

Keyword arguments passed to gammapy.estimators.FluxPoints.plot.

kwargs_modeldict

Keyword arguments passed to gammapy.modeling.models.SpectralModel.plot and gammapy.modeling.models.SpectralModel.plot_error.

Returns

axAxes

Axes object.

residuals(method='diff')

Compute the flux point residuals ().

Parameters

method: {“diff”, “diff/model”}

Method used to compute the residuals. Available options are:

• diff (default): data - model

• diff/model: (data - model) / model

Returns

residualsndarray

Residuals array.

stat_array()

Fit statistic array.

stat_sum()

Total statistic given the current model parameters.

to_dict()

Convert to dict for YAML serialization.

write(filename, overwrite=True, **kwargs)

Write flux point dataset to file.

Parameters

filenamestr

Filename to write to.

overwritebool

Overwrite existing file.

**kwargsdict

Keyword arguments passed to write.