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https://github.com/wassname/catalyst.git
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fce97176d6
* Updated cython build scripts * Updated setup.py to to install catalyst package * Updated momentum example to use catalyst package * catalyst executable now supports loading pipelines from multiple bundles
162 lines
5.3 KiB
Cython
162 lines
5.3 KiB
Cython
"""
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Template for AdjustedArray windowed iterators.
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This file is intended to be used by inserting it via a Cython include into a
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file that's defined a type symbol named `databuffer` that can be used like a
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2-D numpy array.
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See Also
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--------
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catalyst.lib._floatwindow
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catalyst.lib._intwindow
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catalyst.lib._datewindow
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"""
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from numpy cimport ndarray
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from numpy import asanyarray, dtype, issubdtype
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class Exhausted(Exception):
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pass
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cdef class AdjustedArrayWindow:
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"""
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An iterator representing a moving view over an AdjustedArray.
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Concrete subtypes should subclass this and provide a `data` attribute for
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specific types.
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This object stores a copy of the data from the AdjustedArray over which
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it's iterating. At each step in the iteration, it mutates its copy to
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allow us to show different data when looking back over the array.
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The arrays yielded by this iterator are always views over the underlying
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data.
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The `rounding_places` attribute is an integer used to specify the number of
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decimal places to which the data should be rounded, given that the data is
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of dtype float. If `rounding_places` is None, no rounding occurs.
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"""
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cdef:
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# ctype must be defined by the file into which this is being copied.
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readonly databuffer data
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readonly dict view_kwargs
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readonly Py_ssize_t window_length
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Py_ssize_t anchor, max_anchor, next_adj
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Py_ssize_t perspective_offset
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object rounding_places
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dict adjustments
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list adjustment_indices
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ndarray output
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def __cinit__(self,
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databuffer data not None,
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dict view_kwargs not None,
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dict adjustments not None,
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Py_ssize_t offset,
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Py_ssize_t window_length,
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Py_ssize_t perspective_offset,
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object rounding_places):
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self.data = data
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self.view_kwargs = view_kwargs
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self.adjustments = adjustments
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self.adjustment_indices = sorted(adjustments, reverse=True)
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self.window_length = window_length
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self.anchor = window_length + offset - 1
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if perspective_offset > 1:
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# Limit perspective_offset to 1.
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# To support an offset greater than 1, work must be done to
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# ensure that adjustments are retrieved for the datetimes between
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# the end of the window and the vantage point defined by the
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# perspective offset.
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raise Exception("perspective_offset should not exceed 1, value "
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"is perspective_offset={0}".format(
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perspective_offset))
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self.perspective_offset = perspective_offset
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self.rounding_places = rounding_places
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self.max_anchor = data.shape[0]
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self.next_adj = self.pop_next_adj()
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self.output = None
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cdef pop_next_adj(self):
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"""
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Pop the index of the next adjustment to apply from self.adjustment_indices.
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"""
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if len(self.adjustment_indices) > 0:
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return self.adjustment_indices.pop()
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else:
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return self.max_anchor + self.perspective_offset
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def __iter__(self):
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return self
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def __next__(self):
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try:
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self._tick_forward(1)
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except Exhausted:
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raise StopIteration()
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self._update_output()
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return self.output
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def seek(self, Py_ssize_t target_anchor):
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cdef:
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Py_ssize_t anchor = self.anchor
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if target_anchor < anchor:
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raise Exception('Can not access data after window has passed.')
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if target_anchor == anchor:
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return self.output
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self._tick_forward(target_anchor - anchor)
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self._update_output()
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return self.output
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cdef inline _tick_forward(self, int N):
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cdef:
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object adjustment
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Py_ssize_t anchor = self.anchor
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Py_ssize_t target = anchor + N
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if target > self.max_anchor:
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raise Exhausted()
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# Apply any adjustments that occured before our current anchor.
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# Equivalently, apply any adjustments known **on or before** the date
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# for which we're calculating a window.
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while self.next_adj < target + self.perspective_offset:
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for adjustment in self.adjustments[self.next_adj]:
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adjustment.mutate(self.data)
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self.next_adj = self.pop_next_adj()
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self.anchor = target
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cdef inline _update_output(self):
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cdef:
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ndarray new_out
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Py_ssize_t anchor = self.anchor
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dict view_kwargs = self.view_kwargs
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new_out = asanyarray(self.data[anchor - self.window_length:anchor])
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if view_kwargs:
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new_out = new_out.view(**view_kwargs)
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if self.rounding_places is not None and \
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issubdtype(new_out.dtype, dtype('float64')):
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new_out = new_out.round(self.rounding_places)
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new_out.setflags(write=False)
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self.output = new_out
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def __repr__(self):
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return "<%s: window_length=%d, anchor=%d, max_anchor=%d, dtype=%r>" % (
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type(self).__name__,
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self.window_length,
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self.anchor,
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self.max_anchor,
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self.view_kwargs.get('dtype'),
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)
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