# This file is part of h5py, a Python interface to the HDF5 library. # # http://www.h5py.org # # Copyright 2008-2013 Andrew Collette and contributors # # License: Standard 3-clause BSD; see "license.txt" for full license terms # and contributor agreement. """ Implements support for HDF5 dimension scales. """ import warnings from .. import h5ds from ..h5py_warnings import H5pyDeprecationWarning from . import base from .base import phil, with_phil from .dataset import Dataset class DimensionProxy(base.CommonStateObject): """ Represents an HDF5 "dimension". """ @property @with_phil def label(self): """ Get or set the dimension scale label """ #return h5ds.get_label(self._id, self._dimension) # Produces a segfault for a non-existent label (Fixed in hdf5-1.8.8). # Here is a workaround: try: dset = Dataset(self._id) return dset.attrs['DIMENSION_LABELS'][self._dimension] except (KeyError, IndexError): return '' @label.setter @with_phil def label(self, val): # pylint: disable=missing-docstring h5ds.set_label(self._id, self._dimension, self._e(val)) @with_phil def __init__(self, id_, dimension): self._id = id_ self._dimension = dimension @with_phil def __hash__(self): return hash((type(self), self._id, self._dimension)) @with_phil def __eq__(self, other): return hash(self) == hash(other) @with_phil def __iter__(self): for k in self.keys(): yield k @with_phil def __len__(self): return h5ds.get_num_scales(self._id, self._dimension) @with_phil def __getitem__(self, item): if isinstance(item, int): scales = [] h5ds.iterate(self._id, self._dimension, scales.append, 0) return Dataset(scales[item]) else: def f(dsid): """ Iterate over scales to find a matching name """ if h5ds.get_scale_name(dsid) == self._e(item): return dsid res = h5ds.iterate(self._id, self._dimension, f, 0) if res is None: raise KeyError(item) return Dataset(res) def attach_scale(self, dset): """ Attach a scale to this dimension. Provide the Dataset of the scale you would like to attach. """ with phil: h5ds.attach_scale(self._id, dset.id, self._dimension) def detach_scale(self, dset): """ Remove a scale from this dimension. Provide the Dataset of the scale you would like to remove. """ with phil: h5ds.detach_scale(self._id, dset.id, self._dimension) def items(self): """ Get a list of (name, Dataset) pairs with all scales on this dimension. """ with phil: scales = [] # H5DSiterate raises an error if there are no dimension scales, # rather than iterating 0 times. See #483. if len(self) > 0: h5ds.iterate(self._id, self._dimension, scales.append, 0) return [ (self._d(h5ds.get_scale_name(x)), Dataset(x)) for x in scales ] def keys(self): """ Get a list of names for the scales on this dimension. """ with phil: return [key for (key, _) in self.items()] def values(self): """ Get a list of Dataset for scales on this dimension. """ with phil: return [val for (_, val) in self.items()] @with_phil def __repr__(self): if not self._id: return "" return ('<"%s" dimension %d of HDF5 dataset at %s>' % (self.label, self._dimension, id(self._id))) class DimensionManager(base.CommonStateObject): """ Represents a collection of dimension associated with a dataset. Like AttributeManager, an instance of this class is returned when accessing the ".dims" property on a Dataset. """ @with_phil def __init__(self, parent): """ Private constructor. """ self._id = parent.id @with_phil def __getitem__(self, index): """ Return a Dimension object """ if index > len(self) - 1: raise IndexError('Index out of range') return DimensionProxy(self._id, index) @with_phil def __len__(self): """ Number of dimensions associated with the dataset. """ return self._id.rank @with_phil def __iter__(self): """ Iterate over the dimensions. """ for i in range(len(self)): yield self[i] @with_phil def __repr__(self): if not self._id: return "" return "" % id(self._id) def create_scale(self, dset, name=''): """ Create a new dimension, from an initial scale. Provide the dataset and a name for the scale. """ warnings.warn("other_ds.dims.create_scale(ds, name) is deprecated. " "Use ds.make_scale(name) instead.", H5pyDeprecationWarning, stacklevel=2, ) dset.make_scale(name)