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Remove FluxPointsDataset chi2assym option #2645

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Dec 1, 2019
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Remove FluxPointsDataset chi2assym option #2645

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5237114
Remove FluxPointsDataset chi2assym option
cdeil Dec 1, 2019
1ca8283
Fix tutorials/sed_fitting_gammacat_fermi.ipynb
cdeil Dec 1, 2019
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41 changes: 4 additions & 37 deletions gammapy/spectrum/flux_point.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1155,8 +1155,6 @@ class FluxPointsDataset(Dataset):
Flux points.
mask_fit : `numpy.ndarray`
Mask to apply for fitting
likelihood : {"chi2", "chi2assym"}
Likelihood function to use for the fit.
mask_safe : `numpy.ndarray`
Mask defining the safe data range.

Expand All @@ -1180,10 +1178,11 @@ class FluxPointsDataset(Dataset):
print(result.parameters.to_table())
"""

likelihood_type = "chi2"
tag = "FluxPointsDataset"

def __init__(
self, models, data, mask_fit=None, likelihood="chi2", mask_safe=None, name=""
self, models, data, mask_fit=None, mask_safe=None, name=""
):
self.data = data
self.mask_fit = mask_fit
Expand All @@ -1197,14 +1196,6 @@ def __init__(

self.mask_safe = mask_safe

if likelihood in ["chi2", "chi2assym"]:
self.likelihood_type = likelihood
else:
raise ValueError(
f"Invalid likelihood: {likelihood!r}."
" Choose either 'chi2' or 'chi2assym'."
)

@property
def models(self):
return self._models
Expand Down Expand Up @@ -1285,7 +1276,6 @@ def from_dict(cls, data, components, models):
data=FluxPoints(table),
mask_fit=mask_fit,
mask_safe=mask_safe,
likelihood=data["likelihood"],
)

def to_dict(self, filename=""):
Expand All @@ -1299,7 +1289,6 @@ def to_dict(self, filename=""):
"name": self.name,
"type": self.tag,
"models": models,
"likelihood": self.likelihood_type,
"filename": str(filename),
}

Expand Down Expand Up @@ -1349,26 +1338,13 @@ def __str__(self):
str_ += "\t \t {:23}: {:.2f} {} \n".format(
par.name, par.value, par.unit
)
str_ += "\t{:32}: {}\n".format("Likelihood type", self.likelihood_type)
str_ += "\t{:32}: {:.2f}\n".format("Likelihood value", self.stat_sum())
return str_

def data_shape(self):
"""Shape of the flux points data (tuple)."""
return self.data.e_ref.shape

@staticmethod
def _stat_chi2(data, model, sigma):
return ((data - model) / sigma).to_value("") ** 2

@staticmethod
def _stat_chi2_assym(data, model, sigma_n, sigma_p):
"""Assymetric chi2 statistics for a list of flux points and model."""
is_p = model > data
sigma = sigma_n
sigma[is_p] = sigma_p[is_p]
return FluxPointsDataset._stat_chi2(data, model, sigma)

def flux_pred(self):
"""Compute predicted flux."""
flux = 0.0
Expand All @@ -1380,17 +1356,8 @@ def stat_array(self):
"""Fit statistic array."""
model = self.flux_pred()
data = self.data.table["dnde"].quantity

if self.likelihood_type == "chi2":
sigma = self.data.table["dnde_err"].quantity
return self._stat_chi2(data, model, sigma)
elif self.likelihood_type == "chi2assym":
sigma_n = self.data.table["dnde_errn"].quantity
sigma_p = self.data.table["dnde_errp"].quantity
return self._stat_chi2_assym(data, model, sigma_n, sigma_p)
else:
# TODO: add fit statistic profiles
pass
sigma = self.data.table["dnde_err"].quantity
return ((data - model) / sigma).to_value("") ** 2

def residuals(self, method="diff"):
"""Compute the flux point residuals ().
Expand Down
40 changes: 19 additions & 21 deletions tutorials/sed_fitting_gammacat_fermi.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,7 @@
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from astropy import units as u\n",
"from gammapy.modeling.models import (\n",
" PowerLawSpectralModel,\n",
Expand All @@ -61,11 +62,7 @@
" SkyModel,\n",
")\n",
"from gammapy.spectrum import FluxPointsDataset, FluxPoints\n",
"from gammapy.catalog import (\n",
" SourceCatalog3FGL,\n",
" SourceCatalogGammaCat,\n",
" SourceCatalog3FHL,\n",
")\n",
"from gammapy.catalog import SOURCE_CATALOGS\n",
"from gammapy.modeling import Fit"
]
},
Expand All @@ -84,11 +81,9 @@
"metadata": {},
"outputs": [],
"source": [
"fermi_3fgl = SourceCatalog3FGL()\n",
"fermi_3fhl = SourceCatalog3FHL()\n",
"gammacat = SourceCatalogGammaCat(\n",
" \"$GAMMAPY_DATA/catalogs/gammacat/gammacat.fits.gz\"\n",
")"
"catalog_3fgl = SOURCE_CATALOGS[\"3fgl\"]()\n",
"catalog_3fhl = SOURCE_CATALOGS[\"3fhl\"]()\n",
"catalog_gammacat = SOURCE_CATALOGS[\"gamma-cat\"]()"
]
},
{
Expand All @@ -97,9 +92,9 @@
"metadata": {},
"outputs": [],
"source": [
"source_gammacat = gammacat[\"HESS J1507-622\"]\n",
"source_fermi_3fgl = fermi_3fgl[\"3FGL J1506.6-6219\"]\n",
"source_fermi_3fhl = fermi_3fhl[\"3FHL J1507.9-6228e\"]"
"source_fermi_3fgl = catalog_3fgl[\"3FGL J1506.6-6219\"]\n",
"source_fermi_3fhl = catalog_3fhl[\"3FHL J1507.9-6228e\"]\n",
"source_gammacat = catalog_gammacat[\"HESS J1507-622\"]"
]
},
{
Expand Down Expand Up @@ -153,13 +148,18 @@
"metadata": {},
"outputs": [],
"source": [
"# stack flux point tables\n",
"# Stack flux point tables\n",
"flux_points = FluxPoints.stack(\n",
" [flux_points_gammacat, flux_points_3fhl, flux_points_3fgl]\n",
")\n",
"\n",
"# drop the flux upper limit values\n",
"flux_points = flux_points.drop_ul()"
"t = flux_points.table\n",
"t[\"dnde_err\"] = 0.5 * (t[\"dnde_errn\"] + t[\"dnde_errp\"])\n",
"\n",
"# Remove upper limit points, where `dnde_errn = nan`\n",
"is_ul = np.isfinite(t[\"dnde_err\"])\n",
"flux_points = FluxPoints(t[is_ul])\n",
"flux_points"
]
},
{
Expand Down Expand Up @@ -196,7 +196,7 @@
"metadata": {},
"outputs": [],
"source": [
"dataset_pwl = FluxPointsDataset(model, flux_points, likelihood=\"chi2assym\")\n",
"dataset_pwl = FluxPointsDataset(model, flux_points)\n",
"fitter = Fit([dataset_pwl])\n",
"result_pwl = fitter.run()"
]
Expand Down Expand Up @@ -286,7 +286,7 @@
"metadata": {},
"outputs": [],
"source": [
"dataset_ecpl = FluxPointsDataset(model, flux_points, likelihood=\"chi2assym\")\n",
"dataset_ecpl = FluxPointsDataset(model, flux_points)\n",
"fitter = Fit([dataset_ecpl])\n",
"result_ecpl = fitter.run()\n",
"print(ecpl)"
Expand Down Expand Up @@ -342,9 +342,7 @@
"metadata": {},
"outputs": [],
"source": [
"dataset_log_parabola = FluxPointsDataset(\n",
" model, flux_points, likelihood=\"chi2assym\"\n",
")\n",
"dataset_log_parabola = FluxPointsDataset(model, flux_points)\n",
"fitter = Fit([dataset_log_parabola])\n",
"result_log_parabola = fitter.run()\n",
"print(log_parabola)"
Expand Down