Drop log scaling support since uppx driven scaling seems way faster/better
parent
82b2d2ee3a
commit
ba0ba346ec
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@ -162,7 +162,7 @@ def ohlc_to_m4_line(
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flat,
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flat,
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px_width=px_width,
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px_width=px_width,
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uppx=uppx,
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uppx=uppx,
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log_scale=bool(uppx)
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# log_scale=bool(uppx)
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)
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)
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x = np.broadcast_to(x[:, None], y.shape)
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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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x = (x + np.array([-0.43, 0, 0, 0.43])).flatten()
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@ -182,7 +182,7 @@ def ds_m4(
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px_width: int,
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px_width: int,
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uppx: Optional[float] = None,
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uppx: Optional[float] = None,
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xrange: Optional[float] = None,
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xrange: Optional[float] = None,
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log_scale: bool = True,
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# log_scale: bool = True,
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) -> tuple[int, np.ndarray, np.ndarray]:
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) -> tuple[int, np.ndarray, np.ndarray]:
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'''
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'''
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@ -211,27 +211,27 @@ def ds_m4(
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# optionally log-scale down the "supposed pxs on screen"
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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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# as the units-per-px (uppx) get's large.
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if log_scale:
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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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# 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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# # uppx = uppx * math.log(uppx, 2)
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# scaler = 2**7 / (1 + 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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# scaler = round(
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max(
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# max(
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# NOTE: found that a 16x px width brought greater
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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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# # detail, likely due to dpi scaling?
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# px_width=px_width * 16,
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# # px_width=px_width * 16,
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2**7 / (1 + math.log(uppx, 2)),
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# 2**7 / (1 + math.log(uppx, 2)),
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1
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# 1
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)
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# )
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)
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# )
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# px_width *= scaler
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# px_width *= scaler
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# else:
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# else:
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# px_width *= 16
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# px_width *= 16
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assert px_width > 1 # width of screen in pxs?
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# should never get called unless actually needed
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assert uppx > 0
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assert px_width > 1 and uppx > 0
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# NOTE: if we didn't pre-slice the data to downsample
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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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# you could in theory pass these as the slicing params,
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@ -248,13 +248,13 @@ def ds_m4(
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# uppx *= max(4 / (1 + math.log(uppx, 2)), 1)
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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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pxw = math.ceil(xrange / uppx)
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px_width = math.ceil(px_width)
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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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# 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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# this is more or less, uppx: units-per-pixel.
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# w = xrange / float(px_width)
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# w = xrange / float(px_width)
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# uppx = uppx * math.log(uppx, 2)
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# uppx = uppx * math.log(uppx, 2)
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w2 = px_width / uppx
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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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# scale up the width as the uppx get's large
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w = uppx # * math.log(uppx, 666)
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w = uppx # * math.log(uppx, 666)
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@ -269,18 +269,18 @@ def ds_m4(
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# we have room for all output down-samples.
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# we have room for all output down-samples.
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pts_per_pixel, r = divmod(xrange, frames)
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pts_per_pixel, r = divmod(xrange, frames)
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if r:
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if r:
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while r:
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# while r:
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frames += 1
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frames += 1
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pts_per_pixel, r = divmod(xrange, frames)
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pts_per_pixel, r = divmod(xrange, frames)
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print(
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# print(
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f'uppx: {uppx}\n'
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# f'uppx: {uppx}\n'
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f'xrange: {xrange}\n'
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# f'xrange: {xrange}\n'
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f'px_width: {px_width}\n'
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# f'px_width: {px_width}\n'
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f'pxw: {pxw}\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'WTF w:{w}, w2:{w2}\n'
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f'frames: {frames}\n'
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# f'frames: {frames}\n'
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)
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# )
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assert frames >= (xrange / uppx)
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assert frames >= (xrange / uppx)
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# call into ``numba``
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# call into ``numba``
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