sncosmo.select_data¶
- sncosmo.select_data(data, index)[source]¶
Convenience function for indexing photometric data with covariance.
This is like
data[index]
on an astropy Table, but handles covariance columns correctly.- Parameters:
- data
Table
Table of photometric data.
- indexslice or array or int
Row selection to apply to table.
- data
- Returns:
Examples
We have a small table of photometry with a covariance column and we want to select some rows based on a mask:
>>> data = Table([[1., 2., 3.], ... ['a', 'b', 'c'], ... [[1.1, 1.2, 1.3], ... [2.1, 2.2, 2.3], ... [3.1, 3.2, 3.3]]], ... names=['time', 'x', 'cov']) >>> mask = np.array([True, True, False])
Selecting directly on the table, the covariance column is not sliced in each row: it has shape (2, 3) when it should be (2, 2):
>>> data[mask] <Table length=2> time x cov [3] float64 str1 float64 ------- ---- ---------- 1.0 a 1.1 .. 1.3 2.0 b 2.1 .. 2.3
Using
select_data
solves this:>>> sncosmo.select_data(data, mask) <Table length=2> time x cov [2] float64 str1 float64 ------- ---- ---------- 1.0 a 1.1 .. 1.2 2.0 b 2.1 .. 2.2