Go back to hard-coded index field
Turns out https://github.com/numba/numba/issues/8622 is real and the suggested `numba.literally` hack doesn't seem to work..pre_viz_calls
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6ec113659b
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@ -26,15 +26,20 @@ from typing import (
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import msgspec
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import numpy as np
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from numpy.lib import recfunctions as rfn
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from numba import njit, float64, int64 # , optional
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# import pyqtgraph as pg
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# from PyQt5 import QtGui
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# from PyQt5.QtCore import QLineF, QPointF
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from numba import (
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types,
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njit,
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float64,
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int64,
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optional,
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)
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from numba.core.types.misc import StringLiteral
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# from numba.extending import as_numba_type
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from ._sharedmem import (
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ShmArray,
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)
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# from .._profile import pg_profile_enabled, ms_slower_then
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# from ._source import numba_ohlc_dtype
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from ._compression import (
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ds_m4,
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)
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@ -514,11 +519,17 @@ class OHLCBarsFmtr(IncrementalFormatter):
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@staticmethod
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@njit(
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# TODO: for now need to construct this manually for readonly
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# NOTE: need to construct this manually for readonly
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# arrays, see https://github.com/numba/numba/issues/4511
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# ntypes.tuple((float64[:], float64[:], float64[:]))(
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# numba_ohlc_dtype[::1], # contiguous
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# (
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# types.Array(
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# numba_ohlc_dtype,
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# 1,
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# 'C',
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# readonly=True,
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# ),
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# int64,
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# types.unicode_type,
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# optional(float64),
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# ),
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nogil=True
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@ -527,7 +538,7 @@ class OHLCBarsFmtr(IncrementalFormatter):
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data: np.ndarray,
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start: int64,
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bar_gap: float64 = 0.43,
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index_field: str = 'index',
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# index_field: str,
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) -> tuple[
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np.ndarray,
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@ -540,8 +551,10 @@ class OHLCBarsFmtr(IncrementalFormatter):
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'''
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size = int(data.shape[0] * 6)
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# XXX: see this for why the dtype might have to be defined outside
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# the routine.
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# https://github.com/numba/numba/issues/4098#issuecomment-493914533
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x = np.zeros(
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# data,
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shape=size,
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dtype=float64,
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)
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@ -559,7 +572,8 @@ class OHLCBarsFmtr(IncrementalFormatter):
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high = q['high']
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low = q['low']
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close = q['close']
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index = float64(q[index_field])
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# index = float64(q[index_field])
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index = float64(q['index'])
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istart = i * 6
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istop = istart + 6
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@ -615,8 +629,8 @@ class OHLCBarsFmtr(IncrementalFormatter):
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x, y, c = self.path_arrays_from_ohlc(
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array,
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start,
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# self.index_field,
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bar_gap=w,
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index_field=self.index_field,
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)
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return x, y, c
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