ess.snspowder.powgen.data.powgen_tutorial_calibration_file#

ess.snspowder.powgen.data.powgen_tutorial_calibration_file(*, small=False)[source]#

Return the path to the POWGEN calibration file.

Parameters:

small (bool, default: False) –

If True, return a smaller file for unit tests. The small version of the file was created using the following code, which keeps only 7 columns out of 154 (154 / 7 = 22):

```python import scipp as sc

fname = ‘PG3_FERNS_d4832_2011_08_24_spectrum.h5’ dg = sc.io.load_hdf5(fname)

sizes = {“bank”: 23, “column”: 154, “row”: 7}

def foldme(x, dim):
return x.fold(dim=dim, sizes=sizes)[‘column’, ::22].flatten(

dims=list(sizes.keys()), to=dim)

small = sc.Dataset(

data={k: foldme(a, ‘spectrum’) for k, a in ds.items()}, coords={k: foldme(c, ‘spectrum’) for k, c in ds.coords.items()}

) sc.io.save_hdf5(small, ‘TEST_PG3_FERNS_d4832_2011_08_24_spectrum.h5’) ```

Return type:

str