lsst.meas.algorithms.coaddBoundedField.CoaddBoundedField Class Reference

Public Member Functions
	evaluate (self, x, y=None)

Detailed Description

Definition at line 33 of file coaddBoundedField.py.

Member Function Documentation

evaluate()

lsst.meas.algorithms.coaddBoundedField.CoaddBoundedField.evaluate	(		self,
			x,
			y = None )

Evaluate the CoaddBoundedField.

This accepts either a Point2D or an array of x and y
positions.

When arrays are passed, this uses a vectorized version
of CoaddBoundedField::evaluate(). If the coadd bounded
field has throwOnMissing then this will return NaN
for missing values; otherwise it will return 0.0.

Parameters
----------
x : `lsst.geom.Point2D` or `np.ndarray`
    Array of x values.
y : `np.ndarray`, optional
    Array of y values.

Returns
-------
values : `float` or `np.ndarray`
    Evaluated value or array of values.

Definition at line 34 of file coaddBoundedField.py.

    def evaluate(self, x, y=None):
        """Evaluate the CoaddBoundedField.
 
        This accepts either a Point2D or an array of x and y
        positions.
 
        When arrays are passed, this uses a vectorized version
        of CoaddBoundedField::evaluate(). If the coadd bounded
        field has throwOnMissing then this will return NaN
        for missing values; otherwise it will return 0.0.
 
        Parameters
        ----------
        x : `lsst.geom.Point2D` or `np.ndarray`
            Array of x values.
        y : `np.ndarray`, optional
            Array of y values.
 
        Returns
        -------
        values : `float` or `np.ndarray`
            Evaluated value or array of values.
        """
        if isinstance(x, Point2D):
            return self._evaluate(x)
 
        _x = np.atleast_1d(x).ravel()
        _y = np.atleast_1d(y).ravel()
 
        if len(_x) != len(_y):
            raise ValueError("x and y arrays must be the same length.")
 
        ra, dec = self.getCoaddWcs().pixelToSkyArray(_x, _y)
 
        sums = np.zeros(len(_x))
        wts = np.zeros_like(sums)
 
        for elt in self.getElements():
            ix, iy = elt.wcs.skyToPixelArray(ra, dec)
            in_box = elt.field.getBBox().contains(ix, iy)
            if elt.validPolygon:
                in_box &= elt.validPolygon.contains(ix, iy)
            sums[in_box] += elt.weight*elt.field.evaluate(ix[in_box], iy[in_box])
            wts[in_box] += elt.weight
 
        good = (wts > 0)
        values = np.zeros(len(_x))
        values[good] = sums[good]/wts[good]
 
        if self.getThrowOnMissing():
            values[~good] = np.nan
 
        return values

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The documentation for this class was generated from the following file:

• /j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/meas_algorithms/g0603fd7c41+022847dfd1/python/lsst/meas/algorithms/coaddBoundedField.py