2nd try: dispersion normalize y-ranges around median
In the dispersion swing calcs, use the series median from the in-view data to determine swing proportions to apply on each "minor curve" (series with lesser dispersion the one with the greatest). Track the major `Viz` as before by max dispersion. Apply the dispersion swing proportions to each minor curve-series in a third loop/pass of all overlay groups: this ensures all overlays are dispersion normalized in their ranges but, minor curves are currently (vertically) centered (vs. the major) via their medians. There is a ton of commented code from attempts to try and vertically align minor curves to the major via the "first datum" in-view/available. This still needs work and we may want to offer it as optional. Also adds logic to allow skipping margin adjustments in `._set_yrange()` if you pass `range_margin=None`.log_linearized_curve_overlays
parent
dfc35253ea
commit
52ac1053aa
piker/ui
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@ -737,7 +737,7 @@ class ChartView(ViewBox):
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# NOTE: this value pairs (more or less) with L1 label text
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# height offset from from the bid/ask lines.
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range_margin: float = 0.09,
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range_margin: float | None = 0.09,
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bars_range: Optional[tuple[int, int, int, int]] = None,
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@ -811,15 +811,16 @@ class ChartView(ViewBox):
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ylow, yhigh = yrange
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# view margins: stay within a % of the "true range"
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diff = yhigh - ylow
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ylow = max(
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ylow - (diff * range_margin),
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0,
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)
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yhigh = min(
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yhigh + (diff * range_margin),
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yhigh * (1 + range_margin),
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)
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if range_margin is not None:
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diff = yhigh - ylow
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ylow = max(
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ylow - (diff * range_margin),
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0,
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)
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yhigh = min(
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yhigh + (diff * range_margin),
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yhigh * (1 + range_margin),
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)
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# XXX: this often needs to be unset
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# to get different view modes to operate
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@ -979,12 +980,194 @@ class ChartView(ViewBox):
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# print(f'adding {viz.name} to overlay')
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mxmn_groups[viz.name] = out
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pi.vb._set_yrange(yrange=yrange)
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profiler(
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f'{viz.name}@{chart_name} `Viz.plot.vb._set_yrange()`'
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else:
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pi.vb._set_yrange(yrange=yrange)
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profiler(
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f'{viz.name}@{chart_name} `Viz.plot.vb._set_yrange()`'
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)
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profiler(f'<{chart_name}>.interact_graphics_cycle({name})')
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# proportional group auto-scaling per overlay set.
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# -> loop through overlays on each multi-chart widget
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# and scale all y-ranges based on autoscale config.
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# -> for any "group" overlay we want to dispersion normalize
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# and scale minor charts onto the major chart: the chart
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# with the most dispersion in the set.
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major_mx: float = 0
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major_mn: float = float('inf')
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mx_up_rng: float = 0
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mn_down_rng: float = 0
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mx_disp: float = 0
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start_datums: dict[
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ViewBox,
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tuple[
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Viz,
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float, # y start
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float, # y min
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float, # y max
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float, # y median
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slice, # in-view array slice
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],
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] = {}
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max_start: float = 0
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major_viz: Viz = None
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for viz_name, out in mxmn_groups.items():
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(
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ixrng,
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read_slc,
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(ymn, ymx),
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) = out
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x_start = ixrng[0]
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max_start = max(x_start, max_start)
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# determine start datum in view
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viz = chart._vizs[viz_name]
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arr = viz.shm.array
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in_view = arr[read_slc]
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row_start = arr[read_slc.start - 1]
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# row_stop = arr[read_slc.stop - 1]
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if viz.is_ohlc:
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y_median = np.median(in_view['close'])
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y_start = row_start['open']
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else:
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y_median = np.median(in_view[viz.name])
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y_start = row_start[viz.name]
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# y_stop = row_stop[viz.name]
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start_datums[viz.plot.vb] = (
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viz,
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y_start,
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ymn,
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ymx,
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y_median,
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read_slc,
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)
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# if 'dolla_vlm' in viz.name:
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# compute directional (up/down) y-range % swing/dispersion
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y_ref = y_median
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up_rng = (ymx - y_ref) / y_ref
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down_rng = (ymn - y_ref) / y_ref
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disp = abs(ymx - ymn) / y_ref
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# track the "major" curve as the curve with most
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# dispersion.
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if disp > mx_disp:
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major_viz = viz
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mx_disp = disp
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major_mn = ymn
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major_mx = ymx
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mx_up_rng = max(mx_up_rng, up_rng)
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mn_down_rng = min(mn_down_rng, down_rng)
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print(
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f'{viz.name}@{chart_name} group mxmn calc\n'
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f'y_start: {y_start}\n'
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f'ymn: {ymn}\n'
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f'ymx: {ymx}\n'
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f'mx_disp: {mx_disp}\n'
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f'up %: {up_rng * 100}\n'
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f'down %: {down_rng * 100}\n'
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f'mx up %: {mx_up_rng * 100}\n'
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f'mn down %: {mn_down_rng * 100}\n'
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)
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for (
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view,
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(
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viz,
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y_start,
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y_min,
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y_max,
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y_median,
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read_slc,
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)
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) in start_datums.items():
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# TODO: just use y_min / y_max directly for the major
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# `Viz` instead of the below calc since it should be the
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# same output..
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symn = y_median * (1 + mn_down_rng)
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symx = y_median * (1 + mx_up_rng)
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if not (viz is major_viz):
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# compute dispersion normed offsets at the start
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# index of the smaller dispersion curve.
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maj_viz_arr = major_viz.shm.array
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key = 'open' if viz.is_ohlc else viz.name
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# handle case where major (dispersion) curve has
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# a smaller domain then minor one(s).
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istart = read_slc.start
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if read_slc.start > maj_viz_arr.size:
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istart = 0
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maj_start_y = maj_viz_arr[istart][key]
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maj_start_offset = maj_start_y / major_mn
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maj_max_offset = major_mx / major_mn
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# XXX: or this?
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# maj_start_offset = (maj_start_y - major_mn) / major_mn
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# maj_max_offset = (major_mx - maj_start_y) / major_mn
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# XXX: or this?
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# major_disp_offset = (
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# (maj_viz_arr[istart][key] - major_mn)
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# /
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# major_mn
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# )
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# minor_disp_offset_mn = (
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# (y_start - y_min)
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# /
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# y_min
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# )
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# minor_disp_offset_mx = (
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# (ymx - y_start)
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# /
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# y_min
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# normed_disp_ratio = minor_disp_offset - major_disp_offset
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# adjust mxmn range to align curve start point in
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# the minor overlay with the major one.
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# symn = symn * (1 + normed_disp_ratio)
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# symx = symx * (1 + normed_disp_ratio)
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# symn = symn - (symn * normed_disp_ratio)
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# symx = symx - (symn * normed_disp_ratio)
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# symn = y_min * maj_start_offset
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# symx = y_min * maj_max_offset
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print(
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f'{view.name} APPLY group mxmn\n'
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# f'disp offset ratio diff %: {normed_disp_ratio}\n'
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# f'major disp offset %: {major_disp_offset}\n'
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# f'minor disp offset %: {minor_disp_offset}\n'
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f'y_start: {y_start}\n'
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f'mn_down_rng: {mn_down_rng * 100}\n'
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f'mx_up_rng: {mx_up_rng * 100}\n'
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f'scaled ymn: {symn}\n'
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f'scaled ymx: {symx}\n'
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f'scaled mx_disp: {mx_disp}\n'
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)
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view._set_yrange(
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yrange=(symn, symx),
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# range_margin=None,
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)
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# if 'mnq' in viz.name:
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# print(
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# f'AUTO-Y-RANGING: {viz.name}\n'
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# f'i_read_range: {i_read_range}\n'
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@ -995,76 +1178,15 @@ class ChartView(ViewBox):
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# view_xrange,
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# view_yrange,
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# ) = viz.plot.vb.viewRange()
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# view_ymx = view_yrange[1]
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# print(
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# f'{viz.name}@{chart_name}\n'
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# f' xRange -> {view_xrange}\n'
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# f' yRange -> {view_yrange}\n'
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# f' view y-max -> {view_ymx}\n'
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# )
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profiler(f'autoscaled overlays {chart_name}')
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profiler(f'<{chart_name}>.interact_graphics_cycle({name})')
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# proportional group auto-scaling per overlay set.
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# -> loop through overlays on each multi-chart widget
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# and scale all y-ranges based on autoscale config.
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group_mx: float = 0
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group_mn: float = 0
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mx_up_rng: float = 0
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mn_down_rng: float = 0
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start_datums: dict[ViewBox, float] = {}
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for viz_name, out in mxmn_groups.items():
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(
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ixrng,
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read_slc,
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(ymn, ymx),
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) = out
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# determine start datum in view
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viz = chart._vizs[viz_name]
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arr = viz.shm.array
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row_start = arr[read_slc.start - 1]
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# row_stop = arr[read_slc.stop - 1]
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if viz.is_ohlc:
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y_start = row_start['open']
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# y_stop = row_stop['close']
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else:
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y_start = row_start[viz.name]
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# y_stop = row_stop[viz.name]
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start_datums[viz.plot.vb] = (viz, y_start)
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# update max for group
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up_rng = (ymx - y_start) / y_start
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down_rng = (ymn - y_start) / y_start
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# compute directional (up/down) y-range % swing/dispersion
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mx_up_rng = max(mx_up_rng, up_rng)
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mn_down_rng = min(mn_down_rng, down_rng)
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# pis2ranges[pi] = (ymn, ymx)
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group_mx = max(group_mx, ymx)
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group_mn = min(group_mn, ymn)
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print(
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f'{viz.name}@{chart_name} group mxmn calc\n'
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f'ymn: {ymn}\n'
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f'ymx: {ymx}\n'
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f'down %: {mx_up_rng * 100}\n'
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f'up %: {mn_down_rng * 100}\n'
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)
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for view, (viz, ystart) in start_datums.items():
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ymn = ystart * (1 + mn_down_rng)
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ymx = ystart * (1 + mx_up_rng)
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print(
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f'{view.name} APPLY group mxmn\n'
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f'ystart: {ystart}\n'
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f'ymn: {ymn}\n'
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f'ymx: {ymx}\n'
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)
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view._set_yrange(yrange=(ymn, ymx))
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# if view_ymx != symx:
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# breakpoint()
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profiler.finish()
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Reference in New Issue