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[param] indexing routine simplified
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1 changed files with 0 additions and 25 deletions
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@ -143,31 +143,6 @@ class Param(Parameterizable, ObsAr):
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return self._raveled_index()
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#===========================================================================
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# Index recreation
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#===========================================================================
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def _expand_index(self, slice_index=None):
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# this calculates the full indexing arrays from the slicing objects given by get_item for _real..._ attributes
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# it basically translates slices to their respective index arrays and turns negative indices around
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# it tells you in the second return argument if it has only seen arrays as indices
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if slice_index is None:
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slice_index = self._current_slice_
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def f(a):
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a, b = a
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if isinstance(a, numpy.ndarray) and a.dtype == bool:
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raise ValueError, "Boolean indexing not implemented, use Param[np.where(index)] to index by boolean arrays!"
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if a not in (slice(None), Ellipsis):
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if isinstance(a, slice):
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start, stop, step = a.indices(b)
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return numpy.r_[start:stop:step]
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elif isinstance(a, (list, numpy.ndarray, tuple)):
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a = numpy.asarray(a, dtype=int)
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a[a < 0] = b + a[a < 0]
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elif a < 0:
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a = b + a
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return numpy.r_[a]
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return numpy.r_[:b]
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return itertools.imap(f, itertools.izip_longest(slice_index[:self._realndim_], self._realshape_, fillvalue=slice(self.size)))
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#===========================================================================
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# Constrainable
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#===========================================================================
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def _ensure_fixes(self):
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