path: root/lulua/plot.py

# Copyright (c) 2019 lulua contributors
# 
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# 
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
# 
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.

import sys, argparse, json, unicodedata, pickle, logging, math
from operator import itemgetter

from .layout import *
from .keyboard import defaultKeyboards
from .util import limit, displayText
from .writer import Writer
from .carpalx import Carpalx, models

def setPlotStyle (p):
    """ Set common plot styles """

    # Suppress warnings from bokeh if the legend is empty.
    if p.legend:
        p.legend.location = "top_left"
        # Hide glyph on click on legend
        p.legend.click_policy = "hide"
        p.legend.label_text_font = 'IBM Plex Sans Arabic'
        p.legend.border_line_color = None
        p.legend.background_fill_color = None
        p.legend.inactive_fill_color = 'black'
        p.legend.inactive_fill_alpha = 0.1

    # no border fill
    p.border_fill_color = None
    p.background_fill_alpha = 0.5

def letterfreq (args):
    """ Map key combinations to their text, bin it and plot sorted distribution """

    from bokeh.plotting import figure
    from bokeh.models import ColumnDataSource, LinearAxis, Range1d
    from bokeh.embed import json_item

    # show unicode class "letters other" only
    whitelistCategory = {'Lo'}

    stats = pickle.load (sys.stdin.buffer)

    # XXX: add layout to stats?
    keyboard = defaultKeyboards['ibmpc105']
    layout = defaultLayouts[args.layout].specialize (keyboard)


    # letter-based binning, in case multiple buttons are mapped to the same
    # letter.
    binned = defaultdict (int)
    for k, v in stats['simple'].combinations.items ():
        # assuming multiple characters have the same category
        text = layout.getText (k)
        category = unicodedata.category (text[0])
        if category in whitelistCategory:
            binned[text] += v
    combinationTotal = sum (binned.values ())
    logging.info (f'total binned combinations {combinationTotal}')

    xdata = []
    xlabel = []
    ydata = []
    ydataAbs = []
    ydataCumAbs = []
    ydataCumRel = []

    cumSum = combinationTotal
    for i, (k, v) in enumerate (sorted (binned.items (), key=itemgetter (1))):
        xdata.append (i)
        xlabel.append (k)
        ydata.append (v/combinationTotal)
        ydataAbs.append (v)

        # cumulative
        ydataCumAbs.append (cumSum)
        ydataCumRel.append (cumSum/combinationTotal)
        cumSum -= v

    source = ColumnDataSource(data=dict(x=xdata, letters=xlabel, rel=ydata, abs=ydataAbs, cum=ydataCumAbs, cumRel=ydataCumRel))
    p = figure(
            plot_width=1000,
            plot_height=500,
            x_range=xlabel,
            y_range=(0, 1),
            sizing_mode='scale_both',
            tooltips=[('frequency', '@rel'), ('cumulative', '@cumRel'), ('count', '@abs')],
            )
    p.line ('letters', 'cumRel', source=source, line_width=2)

    p.extra_y_ranges = {"single": Range1d (0, max (ydata))}
    p.vbar(x='letters', width=0.5, top='rel', color="#dc322f", source=source, y_range_name='single')
    p.add_layout(LinearAxis(y_range_name="single"), 'right')

    setPlotStyle (p)
    # styling
    p.xgrid.grid_line_color = None
    for axis, size, font in ((p.xaxis, '1.5em', 'IBM Plex Sans Arabic'), (p.yaxis, '1em', 'IBM Plex Sans')):
        axis.major_label_text_font_size = size
        axis.major_label_text_font = font

    json.dump (json_item (p), sys.stdout)

    return 0

def triadfreq (args):
    """ Dump triad frequency stats to stdout """
    sorter = dict (
        weight=lambda x: x['weight'],
        effort=lambda x: x['effort'].effort,
        # increase impact of extremely “bad” triads using math.pow
        combined=lambda x: (x['weight']/weightSum)*math.pow (x['effort'].effort, 2)
        )
    def noLimit (l, n):
        yield from l
    limiter = limit if args.limit > 0 else noLimit

    stats = pickle.load (sys.stdin.buffer)

    # XXX: add layout to stats?
    keyboard = defaultKeyboards['ibmpc105']
    layout = defaultLayouts[args.layout].specialize (keyboard)
    writer = Writer (layout)

    # letter-based binning, in case multiple buttons are mapped to the same
    # letter.
    binned = defaultdict (lambda: dict (weight=0, effort=Carpalx (models['mod01'], writer), textTriad=None))
    weightSum = 0
    for triad, weight in stats['triads'].triads.items ():
        textTriad = tuple (layout.getText (t) for t in triad)
        data = binned[textTriad]
        data['weight'] += weight
        data['effort'].addTriad (triad, weight)
        data['textTriad'] = textTriad
        data['layers'] = tuple (layout.modifierToLayer (x.modifier)[0] for x in triad)
        weightSum += weight

    # triads that contribute to x% of the weight
    topTriads = list ()
    topTriadsWeight = 0
    for data in sorted (binned.values (), key=lambda x: x['weight'], reverse=True):
        if topTriadsWeight < weightSum*args.cutoff:
            topTriads.append (data)
            topTriadsWeight += data['weight']

    logging.info (f'{len (topTriads)}/{len (stats["triads"].triads)} triads '
            f'contribute to {args.cutoff*100}% of the typing')

    # final output
    sortByEffort = sorted (iter (topTriads), key=sorter[args.sort], reverse=args.reverse)
    for data in limiter (sortByEffort, args.limit):
        print (''.join (map (displayText, data['textTriad'])), data['weight'], data['effort'].effort)

    return 0

def triadEffortData (args):
    """
    Plot cumulated triad frequency vs cumulative effort.

    More frequent triads should be easier to type and thus we expect an
    exponential distribution for optimized layouts and linear distribution
    for everything else.
    """

    import numpy as np

    stats = pickle.load (sys.stdin.buffer)

    # XXX: add layout to stats?
    keyboard = defaultKeyboards['ibmpc105']
    layout = defaultLayouts[args.layout].specialize (keyboard)
    writer = Writer (layout)

    # letter-based binning, in case multiple buttons are mapped to the same
    # letter.
    binned = defaultdict (lambda: dict (weight=0, effort=Carpalx (models['mod01'], writer), textTriad=None))
    weightSum = 0
    for triad, weight in stats['triads'].triads.items ():
        textTriad = tuple (layout.getText (t) for t in triad)
        data = binned[textTriad]
        data['weight'] += weight
        data['effort'].addTriad (triad, weight)
        data['textTriad'] = textTriad
        data['layers'] = tuple (layout.modifierToLayer (x.modifier)[0] for x in triad)
        weightSum += weight

    # Now bin into equally-sized buckets to reduce amount of data
    nBins = 200
    binWidth = weightSum//nBins
    cumulativeWeight = 0
    cumulativeEffort = 0
    x = []
    y = []
    for data in sorted (binned.values (), key=lambda x: x['weight'], reverse=True):
        cumulativeWeight += data['weight']
        cumulativeEffort += data['effort'].effort * data['weight']
        if not x or x[-1] + binWidth <= cumulativeWeight:
            x.append (cumulativeWeight)
            y.append (cumulativeEffort)
    x.append (cumulativeWeight)
    y.append (cumulativeEffort)

    x = np.true_divide (x, cumulativeWeight)
    y = np.true_divide (y, cumulativeEffort)

    pickle.dump (dict (x=x, y=y, layout=layout), sys.stdout.buffer, pickle.HIGHEST_PROTOCOL)

def triadEffortPlot (args):
    """ Plot concatenated pickled data from triadEffortData """

    from .stats import unpickleAll
    # Initializing bokeh is an expensive operation and this module is imported
    # alot, so only do it when necessary.
    from bokeh.palettes import Set3
    from bokeh.plotting import figure
    from bokeh.models import RadioButtonGroup, CustomJS,  Slope
    from bokeh.embed import json_item
    from bokeh.layouts import column

    p = figure(
            plot_width=1000,
            plot_height=500,
            sizing_mode='scale_both',
            x_range=(0, 1),
            y_range=(0, 1),
            output_backend="webgl",
            )
    data = list (unpickleAll (sys.stdin.buffer))
    colors = Set3[len(data)]
    lines = dict ()
    for o, color in zip (data, colors):
        name = o['layout'].name
        assert name not in lines
        lines[name] = p.line (o['x'], o['y'], line_width=1, color=color,
                legend_label=name, name=name)

    # color: base1
    slope = Slope(gradient=1, y_intercept=0,
            line_color='#93a1a1', line_dash='dashed', line_width=1)
    p.add_layout(slope)

    setPlotStyle (p)
    for axis, size, font in ((p.xaxis, '1em', 'IBM Plex Sans'), (p.yaxis, '1em', 'IBM Plex Sans')):
        axis.major_label_text_font_size = size
        axis.major_label_text_font = font

    LABELS = ["All", "Standard", "Usable"]
    visible = {
            0: list (lines.keys ()),
            1: ['ar-asmo663', 'ar-linux', 'ar-osx'],
            2: ['ar-lulua', 'ar-ergoarabic', 'ar-malas', 'ar-linux', 'ar-osx'],
            }
    ranges = {
            0: [(0, 1), (0, 1)],
            1: [(0, 0.5), (0, 0.4)],
            2: [(0, 0.5), (0, 0.4)],
            }
    presets = RadioButtonGroup (labels=LABELS, active=0)
    # Set visibility and x/yranges on click. Not sure if there’s a more pythonic way.
    presets.js_on_click(CustomJS(
            args=dict(lines=lines, plot=p, visible=visible, ranges=ranges),
            code="""
            for (const [k, line] of Object.entries (lines)) {
                line.visible = visible[this.active].includes (k);
            }
            const xrange = plot.x_range;
            xrange.start = ranges[this.active][0][0];
            xrange.end = ranges[this.active][0][1];
            const yrange = plot.y_range;
            yrange.start = ranges[this.active][1][0];
            yrange.end = ranges[this.active][1][1];
            """))

    json.dump (json_item (column (p, presets)), sys.stdout)

    return 0