Drop all "pixel width" refs (`px_width`) from m4 impl
parent
f67fd11a29
commit
df1c89e811
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@ -138,51 +138,20 @@ def ohlc_flatten(
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return x, flat
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def ohlc_to_m4_line(
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ohlc: np.ndarray,
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px_width: int,
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downsample: bool = False,
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uppx: Optional[float] = None,
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pretrace: bool = False,
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) -> tuple[np.ndarray, np.ndarray]:
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'''
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Convert an OHLC struct-array to a m4 downsampled 1-d array.
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'''
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xpts, flat = ohlc_flatten(
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ohlc,
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use_mxmn=pretrace,
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)
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if downsample:
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bins, x, y = ds_m4(
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xpts,
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flat,
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px_width=px_width,
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uppx=uppx,
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# log_scale=bool(uppx)
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)
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x = np.broadcast_to(x[:, None], y.shape)
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x = (x + np.array([-0.43, 0, 0, 0.43])).flatten()
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y = y.flatten()
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return x, y
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else:
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return xpts, flat
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def ds_m4(
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x: np.ndarray,
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y: np.ndarray,
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# units-per-pixel-x(dimension)
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uppx: float,
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# XXX: troll zone / easter egg..
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# want to mess with ur pal, pass in the actual
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# pixel width here instead of uppx-proper (i.e. pass
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# in our ``pg.GraphicsObject`` derivative's ``.px_width()``
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# gto mega-trip-out ur bud). Hint, it used to be implemented
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# (wrongly) using "pixel width", so check the git history ;)
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# this is the width of the data in view
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# in display-device-local pixel units.
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px_width: int,
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uppx: Optional[float] = None,
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xrange: Optional[float] = None,
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# log_scale: bool = True,
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) -> tuple[int, np.ndarray, np.ndarray]:
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'''
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@ -209,29 +178,8 @@ def ds_m4(
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# "i didn't show it in the sample code, but it's accounted for
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# in the start and end indices and number of bins"
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# optionally log-scale down the "supposed pxs on screen"
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# as the units-per-px (uppx) get's large.
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# if log_scale:
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# assert uppx, 'You must provide a `uppx` value to use log scaling!'
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# # uppx = uppx * math.log(uppx, 2)
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# # scaler = 2**7 / (1 + math.log(uppx, 2))
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# scaler = round(
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# max(
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# # NOTE: found that a 16x px width brought greater
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# # detail, likely due to dpi scaling?
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# # px_width=px_width * 16,
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# 2**7 / (1 + math.log(uppx, 2)),
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# 1
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# )
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# )
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# px_width *= scaler
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# else:
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# px_width *= 16
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# should never get called unless actually needed
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assert px_width > 1 and uppx > 0
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assert uppx > 1
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# NOTE: if we didn't pre-slice the data to downsample
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# you could in theory pass these as the slicing params,
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@ -248,16 +196,9 @@ def ds_m4(
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# uppx *= max(4 / (1 + math.log(uppx, 2)), 1)
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pxw = math.ceil(xrange / uppx)
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# px_width = math.ceil(px_width)
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# ratio of indexed x-value to width of raster in pixels.
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# this is more or less, uppx: units-per-pixel.
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# w = xrange / float(px_width)
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# uppx = uppx * math.log(uppx, 2)
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# w2 = px_width / uppx
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# scale up the width as the uppx get's large
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w = uppx # * math.log(uppx, 666)
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# scale up the frame "width" directly with uppx
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w = uppx
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# ensure we make more then enough
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# frames (windows) for the output pixel
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@ -276,9 +217,7 @@ def ds_m4(
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# print(
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# f'uppx: {uppx}\n'
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# f'xrange: {xrange}\n'
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# f'px_width: {px_width}\n'
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# f'pxw: {pxw}\n'
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# f'WTF w:{w}, w2:{w2}\n'
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# f'frames: {frames}\n'
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# )
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assert frames >= (xrange / uppx)
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@ -41,7 +41,6 @@ from ._compression import (
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def xy_downsample(
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x,
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y,
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px_width,
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uppx,
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x_spacer: float = 0.5,
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@ -54,9 +53,7 @@ def xy_downsample(
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bins, x, y = ds_m4(
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x,
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y,
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px_width=px_width,
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uppx=uppx,
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# log_scale=bool(uppx)
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uppx,
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)
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# flatten output to 1d arrays suitable for path-graphics generation.
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