def to_sherpa_data2d(self, dstype='Data2D'):
"""
Convert image to `~sherpa.data.Data2D` or `~sherpa.data.Data2DInt` class.
Parameters
----------
dstype : {'Data2D', 'Data2DInt'}
Sherpa data type.
"""
from sherpa.data import Data2D, Data2DInt
if dstype == 'Data2D':
coordinates = self.coordinates(mode='center')
x = coordinates.data.lon.degree
y = coordinates.data.lat.degree
return Data2D(self.name, x.ravel(), y.ravel(), self.data.ravel(),
self.data.shape)
elif dstype == 'Data2DInt':
coordinates = self.coordinates(mode='edges')
x = coordinates.data.lon
y = coordinates.data.lat
xlo, xhi = x[:-1], x[1:]
ylo, yhi = y[:-1], y[1:]
return Data2DInt(self.name, xlo.ravel(), xhi.ravel(), ylo.ravel(),
yhi.ravel(), self.data.ravel(), self.data.shape)
else:
raise ValueError('Invalid sherpa data type.')
def test_data2d_int_wrong_y_array_size(array_sizes_fixture):
x0, x1, dx, y = array_sizes_fixture
with pytest.raises(TypeError):
Data2DInt('name',
x0.flatten(),
x0.flatten(),
x1.flatten(),
x1.flatten(),
y,
staterror=numpy.sqrt(y).flatten())
def make_data(data_class):
"""Create a test data object of the given class.
Using a string means it is easier to support the various PHA
"types" - eg basic, grouping, grouping+quality.
"""
x0 = np.asarray([1, 3, 7, 12])
y = np.asarray([2, 3, 4, 5])
if data_class == "1d":
return Data1D('x1', x0, y)
if data_class == "1dint":
return Data1DInt('xint1', x0, np.asarray([3, 5, 8, 15]), y)
chans = np.arange(1, 5)
if data_class == "pha":
return DataPHA('pha', chans, y)
# We want to provide PHA tests that check out the grouping and
# quality handling (but it is not worth trying all different
# variants), so we have "grp" for grouping and no quality [*], and
# "qual" for grouping and quality.
#
# [*] by which I mean we have not called ignore_bad, not that
# there is no quality array.
#
grp = np.asarray([1, -1, 1, 1])
qual = np.asarray([0, 0, 2, 0])
pha = DataPHA('pha', chans, y, grouping=grp, quality=qual)
if data_class == "grp":
return pha
if data_class == "qual":
pha.ignore_bad()
return pha
x0 = np.asarray([1, 2, 3] * 2)
x1 = np.asarray([1, 1, 1, 2, 2, 2])
y = np.asarray([2, 3, 4, 5, 6, 7])
if data_class == "2d":
return Data2D('x2', x0, x1, y, shape=(2, 3))
if data_class == "2dint":
return Data2DInt('xint2', x0, x1, x0 + 1, x1 + 1, y, shape=(2, 3))
if data_class == "img":
return DataIMG('img', x0, x1, y, shape=(2, 3))
if data_class == "imgint":
return DataIMGInt('imgi', x0, x1, x0 + 1, x1 + 1, y, shape=(2, 3))
assert False
def test_data2d_int_eval_model_to_fit(array_sizes_fixture):
from sherpa.fit import Fit
from sherpa.optmethods import LevMar
from sherpa.stats import Chi2
from sherpa.models import Gauss2D
x0, x1, dx, y = array_sizes_fixture
data2 = Data2DInt('name', x0.flatten(), x0.flatten() + dx, x1.flatten(), x1.flatten() + dx, y.flatten(),
staterror=numpy.sqrt(y).flatten())
model2 = Gauss2D()
fitter = Fit(data2, model2, Chi2(), LevMar())
fitter.fit() # Failed in Sherpa 4.11.0
def to_sherpa_data2d(self, dstype='Data2D'):
"""
Convert sky map to `~sherpa.data.Data2D` or `~sherpa.data.Data2DInt` class.
Parameter
---------
dstype : {'Data2D', 'Data2DInt'}
Sherpa data type.
"""
from sherpa.data import Data2D, Data2DInt
if dstype == 'Data2D':
x, y = self.coordinates('galactic', mode='center')
return Data2D(self.name, x.ravel(), y.ravel(), self.data.ravel(),
self.data.shape)
elif dstype == 'Data2DInt':
x, y = self.coordinates('galactic', mode='edges')
xlo, xhi = x[:-1], x[1:]
ylo, yhi = y[:-1], y[1:]
return Data2DInt(self.name, xlo.ravel(), xhi.ravel(), ylo.ravel(),
yhi.ravel(), self.data.ravel(), self.data.shape)
else:
raise ValueError('Invalid sherpa data type.')
def _make_dataset(n_dim, x, y, z=None, xbinsize=None, ybinsize=None, err=None, bkg=None, bkg_scale=1, n=0):
"""
Parameters
----------
n_dim: int
Used to veirfy required number of dimentions.
x : array
input coordinates
y : array
input coordinates
z : array (optional)
input coordinatesbkg
xbinsize : array (optional)
an array of errors in x
ybinsize : array (optional)
an array of errors in y
err : array (optional)
an array of errors in z
n : int
used in error reporting
Returns
-------
_data: a sherpa dataset
"""
if (z is None and n_dim > 1) or (z is not None and n_dim == 1):
raise ValueError("Model and data dimentions don't match in dataset %i" % n)
if z is None:
assert x.shape == y.shape, "shape of x and y don't match in dataset %i" % n
else:
z = np.asarray(z)
assert x.shape == y.shape == z.shape, "shapes x,y and z don't match in dataset %i" % n
if xbinsize is not None:
xbinsize = np.array(xbinsize)
assert x.shape == xbinsize.shape, "x's and xbinsize's shapes do not match in dataset %i" % n
if z is not None and err is not None:
err = np.array(err)
assert z.shape == err.shape, "z's and err's shapes do not match in dataset %i" % n
if ybinsize is not None:
ybinsize = np.array(ybinsize)
assert y.shape == ybinsize.shape, "y's and ybinsize's shapes do not match in dataset %i" % n
else:
if err is not None:
err = np.array(err)
assert y.shape == err.shape, "y's and err's shapes do not match in dataset %i" % n
if xbinsize is not None:
bs = xbinsize / 2.0
if z is None:
if xbinsize is None:
if err is None:
if bkg is None:
data = Data1D("wrapped_data", x=x, y=y)
else:
data = Data1DBkg("wrapped_data", x=x, y=y, bkg=bkg, bkg_scale=bkg_scale)
else:
if bkg is None:
data = Data1D("wrapped_data", x=x, y=y, staterror=err)
else:
data = Data1DBkg("wrapped_data", x=x, y=y, staterror=err, bkg=bkg, bkg_scale=bkg_scale)
else:
if err is None:
if bkg is None:
data = Data1DInt("wrapped_data", xlo=x - bs, xhi=x + bs, y=y)
else:
data = Data1DIntBkg("wrapped_data", xlo=x - bs, xhi=x + bs, y=y, bkg=bkg, bkg_scale=bkg_scale)
else:
if bkg is None:
data = Data1DInt("wrapped_data", xlo=x - bs, xhi=x + bs, y=y, staterror=err)
else:
data = Data1DIntBkg("wrapped_data", xlo=x - bs, xhi=x + bs, y=y, staterror=err, bkg=bkg, bkg_scale=bkg_scale)
else:
if xbinsize is None and ybinsize is None:
if err is None:
if bkg is None:
data = Data2D("wrapped_data", x0=x, x1=y, y=z)
else:
data = Data2DBkg("wrapped_data", x0=x, x1=y, y=z, bkg=bkg, bkg_scale=bkg_scale)
else:
if bkg is None:
data = Data2D("wrapped_data", x0=x, x1=y, y=z, staterror=err)
else:
data = Data2DBkg("wrapped_data", x0=x, x1=y, y=z, staterror=err, bkg=bkg, bkg_scale=bkg_scale)
elif xbinsize is not None and ybinsize is not None:
ys = ybinsize / 2.0
if err is None:
if bkg is None:
data = Data2DInt("wrapped_data", x0lo=x - bs, x0hi=x + bs, x1lo=y - ys, x1hi=y + ys, y=z)
else:
data = Data2DIntBkg("wrapped_data", x0lo=x - bs, x0hi=x + bs, x1lo=y - ys, x1hi=y + ys, y=z, bkg=bkg, bkg_scale=bkg_scale)
else:
if bkg is None:
data = Data2DInt("wrapped_data", x0lo=x - bs, x0hi=x + bs, x1lo=y - ys, x1hi=y + ys, y=z, staterror=err)
else:
data = Data2DIntBkg("wrapped_data", x0lo=x - bs, x0hi=x + bs, x1lo=y - ys, x1hi=y + ys, y=z, staterror=err, bkg=bkg, bkg_scale=bkg_scale)
else:
raise ValueError("Set xbinsize and ybinsize, or set neither!")
return data