def _fits_array_writer(validator, _, instance, schema):
if instance is None:
return
instance = np.asanyarray(instance)
if not len(instance.shape):
return
if 'ndim' in schema:
ndarray.validate_ndim(validator, schema['ndim'], instance, schema)
if 'max_ndim' in schema:
ndarray.validate_max_ndim(validator, schema['max_ndim'], instance, schema)
if 'dtype' in schema:
ndarray.validate_dtype(validator, schema['dtype'], instance, schema)
hdu_name = _get_hdu_name(schema)
_assert_non_primary_hdu(hdu_name)
if instance.dtype.names is not None:
hdu_type = fits.BinTableHDU
else:
hdu_type = fits.ImageHDU
index = getattr(validator, 'sequence_index', None)
hdu = _get_or_make_hdu(validator.hdulist, hdu_name, index=index, hdu_type=hdu_type)
hdu.data = instance
def _fits_array_writer(validator, _, instance, schema):
if instance is None:
return
instance = np.asanyarray(instance)
if not len(instance.shape):
return
if 'ndim' in schema:
ndarray.validate_ndim(validator, schema['ndim'], instance, schema)
if 'max_ndim' in schema:
ndarray.validate_max_ndim(validator, schema['max_ndim'], instance, schema)
if 'dtype' in schema:
ndarray.validate_dtype(validator, schema['dtype'], instance, schema)
hdu_name = _get_hdu_name(schema)
_assert_non_primary_hdu(hdu_name)
index = getattr(validator, 'sequence_index', 0)
hdu_type = _get_hdu_type(hdu_name, schema=schema, value=instance)
hdu = _get_or_make_hdu(validator.hdulist, hdu_name,
index=index, hdu_type=hdu_type)
hdu.data = instance
hdu.ver = index + 1
def _fits_array_writer(validator, _, instance, schema):
if instance is None:
return
instance = np.asanyarray(instance)
if not len(instance.shape):
return
if 'ndim' in schema:
ndarray.validate_ndim(validator, schema['ndim'], instance, schema)
if 'max_ndim' in schema:
ndarray.validate_max_ndim(validator, schema['max_ndim'], instance,
schema)
if 'dtype' in schema:
ndarray.validate_dtype(validator, schema['dtype'], instance, schema)
hdu_name = _get_hdu_name(schema)
_assert_non_primary_hdu(hdu_name)
index = getattr(validator, 'sequence_index', 0)
hdu_type = _get_hdu_type(hdu_name, schema=schema, value=instance)
hdu = _get_or_make_hdu(validator.hdulist,
hdu_name,
index=index,
hdu_type=hdu_type)
hdu.data = instance
hdu.ver = index + 1
def _fits_array_writer(validator, _, instance, schema):
if instance is None:
return
instance = np.asarray(instance)
if not len(instance.shape):
return
if 'ndim' in schema:
ndarray.validate_ndim(validator, schema['ndim'], instance, schema)
if 'max_ndim' in schema:
ndarray.validate_max_ndim(validator, schema['max_ndim'], instance,
schema)
if 'dtype' in schema:
ndarray.validate_dtype(validator, schema['dtype'], instance, schema)
hdu_name = _get_hdu_name(schema)
_assert_non_primary_hdu(hdu_name)
if instance.dtype.names is not None:
hdu_type = fits.BinTableHDU
else:
hdu_type = fits.ImageHDU
index = getattr(validator, 'sequence_index', None)
hdu = _get_or_make_hdu(validator.hdulist,
hdu_name,
index=index,
hdu_type=hdu_type)
hdu.data = instance
