Files
catalyst/zipline/lib/_windowtemplate.pxi
T
2015-12-10 16:12:51 -05:00

107 lines
3.1 KiB
Cython

"""
Template for AdjustedArray windowed iterators.
This file is intended to be used by inserting it via a Cython include into a
file that's define a type symbol named `ctype` and string constant named
`dtype`.
See Also
--------
zipline.lib._floatwindow
zipline.lib._intwindow
zipline.lib._datewindow
"""
from numpy cimport ndarray
from numpy import asarray
ctypedef ctype[:, :] databuffer
cdef class AdjustedArrayWindow:
"""
An iterator representing a moving view over an AdjustedArray.
Concrete subtypes should subclass this and provide a `data` attribute for
specific types.
This object stores a copy of the data from the AdjustedArray over which
it's iterating. At each step in the iteration, it mutates its copy to
allow us to show different data when looking back over the array.
The arrays yielded by this iterator are always views over the underlying
data.
"""
cdef:
# ctype must be defined by the file into which this is being copied.
databuffer data
object viewtype
readonly Py_ssize_t window_length
Py_ssize_t anchor, max_anchor, next_adj
dict adjustments
list adjustment_indices
def __cinit__(self,
databuffer data not None,
object viewtype not None,
dict adjustments not None,
Py_ssize_t offset,
Py_ssize_t window_length):
self.data = data
self.viewtype = viewtype
self.adjustments = adjustments
self.adjustment_indices = sorted(adjustments, reverse=True)
self.window_length = window_length
self.anchor = window_length + offset
self.max_anchor = data.shape[0]
self.next_adj = self.pop_next_adj()
cdef pop_next_adj(self):
"""
Pop the index of the next adjustment to apply from self.adjustment_indices.
"""
if len(self.adjustment_indices) > 0:
return self.adjustment_indices.pop()
else:
return self.max_anchor
def __iter__(self):
return self
def __next__(self):
cdef:
ndarray out
object adjustment
Py_ssize_t start, anchor
anchor = self.anchor
if anchor > self.max_anchor:
raise StopIteration()
# Apply any adjustments that occured before our current anchor.
# Equivalently, apply any adjustments known **on or before** the date
# for which we're calculating a window.
while self.next_adj < anchor:
for adjustment in self.adjustments[self.next_adj]:
adjustment.mutate(self.data)
self.next_adj = self.pop_next_adj()
start = anchor - self.window_length
out = asarray(self.data[start:self.anchor]).view(self.viewtype)
out.setflags(write=False)
self.anchor += 1
return out
def __repr__(self):
return "<%s: window_length=%d, anchor=%d, max_anchor=%d, dtype=%r>" % (
type(self).__name__,
self.window_length,
self.anchor,
self.max_anchor,
self.viewtype,
)