diff options
Diffstat (limited to 'numpy/lib/recfunctions.py')
| -rw-r--r-- | numpy/lib/recfunctions.py | 68 |
1 files changed, 50 insertions, 18 deletions
diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py index 6e257bb3f..40060b41a 100644 --- a/numpy/lib/recfunctions.py +++ b/numpy/lib/recfunctions.py @@ -72,7 +72,7 @@ def recursive_fill_fields(input, output): current = input[field] except ValueError: continue - if current.dtype.names: + if current.dtype.names is not None: recursive_fill_fields(current, output[field]) else: output[field][:len(current)] = current @@ -139,11 +139,11 @@ def get_names(adtype): names = adtype.names for name in names: current = adtype[name] - if current.names: + if current.names is not None: listnames.append((name, tuple(get_names(current)))) else: listnames.append(name) - return tuple(listnames) or None + return tuple(listnames) def get_names_flat(adtype): @@ -176,9 +176,9 @@ def get_names_flat(adtype): for name in names: listnames.append(name) current = adtype[name] - if current.names: + if current.names is not None: listnames.extend(get_names_flat(current)) - return tuple(listnames) or None + return tuple(listnames) def flatten_descr(ndtype): @@ -215,8 +215,8 @@ def _zip_dtype(seqarrays, flatten=False): else: for a in seqarrays: current = a.dtype - if current.names and len(current.names) <= 1: - # special case - dtypes of 0 or 1 field are flattened + if current.names is not None and len(current.names) == 1: + # special case - dtypes of 1 field are flattened newdtype.extend(_get_fieldspec(current)) else: newdtype.append(('', current)) @@ -268,7 +268,7 @@ def get_fieldstructure(adtype, lastname=None, parents=None,): names = adtype.names for name in names: current = adtype[name] - if current.names: + if current.names is not None: if lastname: parents[name] = [lastname, ] else: @@ -281,7 +281,7 @@ def get_fieldstructure(adtype, lastname=None, parents=None,): elif lastname: lastparent = [lastname, ] parents[name] = lastparent or [] - return parents or None + return parents def _izip_fields_flat(iterable): @@ -435,7 +435,7 @@ def merge_arrays(seqarrays, fill_value=-1, flatten=False, if isinstance(seqarrays, (ndarray, np.void)): seqdtype = seqarrays.dtype # Make sure we have named fields - if not seqdtype.names: + if seqdtype.names is None: seqdtype = np.dtype([('', seqdtype)]) if not flatten or _zip_dtype((seqarrays,), flatten=True) == seqdtype: # Minimal processing needed: just make sure everythng's a-ok @@ -653,7 +653,7 @@ def rename_fields(base, namemapper): for name in ndtype.names: newname = namemapper.get(name, name) current = ndtype[name] - if current.names: + if current.names is not None: newdtype.append( (newname, _recursive_rename_fields(current, namemapper)) ) @@ -874,16 +874,35 @@ def _get_fields_and_offsets(dt, offset=0): scalar fields in the dtype "dt", including nested fields, in left to right order. """ + + # counts up elements in subarrays, including nested subarrays, and returns + # base dtype and count + def count_elem(dt): + count = 1 + while dt.shape != (): + for size in dt.shape: + count *= size + dt = dt.base + return dt, count + fields = [] for name in dt.names: field = dt.fields[name] - if field[0].names is None: - count = 1 - for size in field[0].shape: - count *= size - fields.append((field[0], count, field[1] + offset)) + f_dt, f_offset = field[0], field[1] + f_dt, n = count_elem(f_dt) + + if f_dt.names is None: + fields.append((np.dtype((f_dt, (n,))), n, f_offset + offset)) else: - fields.extend(_get_fields_and_offsets(field[0], field[1] + offset)) + subfields = _get_fields_and_offsets(f_dt, f_offset + offset) + size = f_dt.itemsize + + for i in range(n): + if i == 0: + # optimization: avoid list comprehension if no subarray + fields.extend(subfields) + else: + fields.extend([(d, c, o + i*size) for d, c, o in subfields]) return fields @@ -948,6 +967,12 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'): fields = _get_fields_and_offsets(arr.dtype) n_fields = len(fields) + if n_fields == 0 and dtype is None: + raise ValueError("arr has no fields. Unable to guess dtype") + elif n_fields == 0: + # too many bugs elsewhere for this to work now + raise NotImplementedError("arr with no fields is not supported") + dts, counts, offsets = zip(*fields) names = ['f{}'.format(n) for n in range(n_fields)] @@ -1039,6 +1064,9 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False, if arr.shape == (): raise ValueError('arr must have at least one dimension') n_elem = arr.shape[-1] + if n_elem == 0: + # too many bugs elsewhere for this to work now + raise NotImplementedError("last axis with size 0 is not supported") if dtype is None: if names is None: @@ -1051,7 +1079,11 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False, raise ValueError("don't supply both dtype and names") # sanity check of the input dtype fields = _get_fields_and_offsets(dtype) - dts, counts, offsets = zip(*fields) + if len(fields) == 0: + dts, counts, offsets = [], [], [] + else: + dts, counts, offsets = zip(*fields) + if n_elem != sum(counts): raise ValueError('The length of the last dimension of arr must ' 'be equal to the number of fields in dtype') |