ai-content-maker/.venv/Lib/site-packages/fontTools/varLib/avarPlanner.py

from fontTools.ttLib import newTable
from fontTools.ttLib.tables._f_v_a_r import Axis as fvarAxis
from fontTools.pens.areaPen import AreaPen
from fontTools.pens.basePen import NullPen
from fontTools.pens.statisticsPen import StatisticsPen
from fontTools.varLib.models import piecewiseLinearMap, normalizeValue
from fontTools.misc.cliTools import makeOutputFileName
import math
import logging
from pprint import pformat

__all__ = [
    "planWeightAxis",
    "planWidthAxis",
    "planSlantAxis",
    "planOpticalSizeAxis",
    "planAxis",
    "sanitizeWeight",
    "sanitizeWidth",
    "sanitizeSlant",
    "measureWeight",
    "measureWidth",
    "measureSlant",
    "normalizeLinear",
    "normalizeLog",
    "normalizeDegrees",
    "interpolateLinear",
    "interpolateLog",
    "processAxis",
    "makeDesignspaceSnippet",
    "addEmptyAvar",
    "main",
]

log = logging.getLogger("fontTools.varLib.avarPlanner")

WEIGHTS = [
    50,
    100,
    150,
    200,
    250,
    300,
    350,
    400,
    450,
    500,
    550,
    600,
    650,
    700,
    750,
    800,
    850,
    900,
    950,
]

WIDTHS = [
    25.0,
    37.5,
    50.0,
    62.5,
    75.0,
    87.5,
    100.0,
    112.5,
    125.0,
    137.5,
    150.0,
    162.5,
    175.0,
    187.5,
    200.0,
]

SLANTS = list(math.degrees(math.atan(d / 20.0)) for d in range(-20, 21))

SIZES = [
    5,
    6,
    7,
    8,
    9,
    10,
    11,
    12,
    14,
    18,
    24,
    30,
    36,
    48,
    60,
    72,
    96,
    120,
    144,
    192,
    240,
    288,
]


SAMPLES = 8


def normalizeLinear(value, rangeMin, rangeMax):
    """Linearly normalize value in [rangeMin, rangeMax] to [0, 1], with extrapolation."""
    return (value - rangeMin) / (rangeMax - rangeMin)


def interpolateLinear(t, a, b):
    """Linear interpolation between a and b, with t typically in [0, 1]."""
    return a + t * (b - a)


def normalizeLog(value, rangeMin, rangeMax):
    """Logarithmically normalize value in [rangeMin, rangeMax] to [0, 1], with extrapolation."""
    logMin = math.log(rangeMin)
    logMax = math.log(rangeMax)
    return (math.log(value) - logMin) / (logMax - logMin)


def interpolateLog(t, a, b):
    """Logarithmic interpolation between a and b, with t typically in [0, 1]."""
    logA = math.log(a)
    logB = math.log(b)
    return math.exp(logA + t * (logB - logA))


def normalizeDegrees(value, rangeMin, rangeMax):
    """Angularly normalize value in [rangeMin, rangeMax] to [0, 1], with extrapolation."""
    tanMin = math.tan(math.radians(rangeMin))
    tanMax = math.tan(math.radians(rangeMax))
    return (math.tan(math.radians(value)) - tanMin) / (tanMax - tanMin)


def measureWeight(glyphset, glyphs=None):
    """Measure the perceptual average weight of the given glyphs."""
    if isinstance(glyphs, dict):
        frequencies = glyphs
    else:
        frequencies = {g: 1 for g in glyphs}

    wght_sum = wdth_sum = 0
    for glyph_name in glyphs:
        if frequencies is not None:
            frequency = frequencies.get(glyph_name, 0)
            if frequency == 0:
                continue
        else:
            frequency = 1

        glyph = glyphset[glyph_name]

        pen = AreaPen(glyphset=glyphset)
        glyph.draw(pen)

        mult = glyph.width * frequency
        wght_sum += mult * abs(pen.value)
        wdth_sum += mult

    return wght_sum / wdth_sum


def measureWidth(glyphset, glyphs=None):
    """Measure the average width of the given glyphs."""
    if isinstance(glyphs, dict):
        frequencies = glyphs
    else:
        frequencies = {g: 1 for g in glyphs}

    wdth_sum = 0
    freq_sum = 0
    for glyph_name in glyphs:
        if frequencies is not None:
            frequency = frequencies.get(glyph_name, 0)
            if frequency == 0:
                continue
        else:
            frequency = 1

        glyph = glyphset[glyph_name]

        pen = NullPen()
        glyph.draw(pen)

        wdth_sum += glyph.width * frequency
        freq_sum += frequency

    return wdth_sum / freq_sum


def measureSlant(glyphset, glyphs=None):
    """Measure the perceptual average slant angle of the given glyphs."""
    if isinstance(glyphs, dict):
        frequencies = glyphs
    else:
        frequencies = {g: 1 for g in glyphs}

    slnt_sum = 0
    freq_sum = 0
    for glyph_name in glyphs:
        if frequencies is not None:
            frequency = frequencies.get(glyph_name, 0)
            if frequency == 0:
                continue
        else:
            frequency = 1

        glyph = glyphset[glyph_name]

        pen = StatisticsPen(glyphset=glyphset)
        glyph.draw(pen)

        mult = glyph.width * frequency
        slnt_sum += mult * pen.slant
        freq_sum += mult

    return -math.degrees(math.atan(slnt_sum / freq_sum))


def sanitizeWidth(userTriple, designTriple, pins, measurements):
    """Sanitize the width axis limits."""

    minVal, defaultVal, maxVal = (
        measurements[designTriple[0]],
        measurements[designTriple[1]],
        measurements[designTriple[2]],
    )

    calculatedMinVal = userTriple[1] * (minVal / defaultVal)
    calculatedMaxVal = userTriple[1] * (maxVal / defaultVal)

    log.info("Original width axis limits: %g:%g:%g", *userTriple)
    log.info(
        "Calculated width axis limits: %g:%g:%g",
        calculatedMinVal,
        userTriple[1],
        calculatedMaxVal,
    )

    if (
        abs(calculatedMinVal - userTriple[0]) / userTriple[1] > 0.05
        or abs(calculatedMaxVal - userTriple[2]) / userTriple[1] > 0.05
    ):
        log.warning("Calculated width axis min/max do not match user input.")
        log.warning(
            "  Current width axis limits: %g:%g:%g",
            *userTriple,
        )
        log.warning(
            "  Suggested width axis limits: %g:%g:%g",
            calculatedMinVal,
            userTriple[1],
            calculatedMaxVal,
        )

        return False

    return True


def sanitizeWeight(userTriple, designTriple, pins, measurements):
    """Sanitize the weight axis limits."""

    if len(set(userTriple)) < 3:
        return True

    minVal, defaultVal, maxVal = (
        measurements[designTriple[0]],
        measurements[designTriple[1]],
        measurements[designTriple[2]],
    )

    logMin = math.log(minVal)
    logDefault = math.log(defaultVal)
    logMax = math.log(maxVal)

    t = (userTriple[1] - userTriple[0]) / (userTriple[2] - userTriple[0])
    y = math.exp(logMin + t * (logMax - logMin))
    t = (y - minVal) / (maxVal - minVal)
    calculatedDefaultVal = userTriple[0] + t * (userTriple[2] - userTriple[0])

    log.info("Original weight axis limits: %g:%g:%g", *userTriple)
    log.info(
        "Calculated weight axis limits: %g:%g:%g",
        userTriple[0],
        calculatedDefaultVal,
        userTriple[2],
    )

    if abs(calculatedDefaultVal - userTriple[1]) / userTriple[1] > 0.05:
        log.warning("Calculated weight axis default does not match user input.")

        log.warning(
            "  Current weight axis limits: %g:%g:%g",
            *userTriple,
        )

        log.warning(
            "  Suggested weight axis limits, changing default: %g:%g:%g",
            userTriple[0],
            calculatedDefaultVal,
            userTriple[2],
        )

        t = (userTriple[2] - userTriple[0]) / (userTriple[1] - userTriple[0])
        y = math.exp(logMin + t * (logDefault - logMin))
        t = (y - minVal) / (defaultVal - minVal)
        calculatedMaxVal = userTriple[0] + t * (userTriple[1] - userTriple[0])
        log.warning(
            "  Suggested weight axis limits, changing maximum: %g:%g:%g",
            userTriple[0],
            userTriple[1],
            calculatedMaxVal,
        )

        t = (userTriple[0] - userTriple[2]) / (userTriple[1] - userTriple[2])
        y = math.exp(logMax + t * (logDefault - logMax))
        t = (y - maxVal) / (defaultVal - maxVal)
        calculatedMinVal = userTriple[2] + t * (userTriple[1] - userTriple[2])
        log.warning(
            "  Suggested weight axis limits, changing minimum: %g:%g:%g",
            calculatedMinVal,
            userTriple[1],
            userTriple[2],
        )

        return False

    return True


def sanitizeSlant(userTriple, designTriple, pins, measurements):
    """Sanitize the slant axis limits."""

    log.info("Original slant axis limits: %g:%g:%g", *userTriple)
    log.info(
        "Calculated slant axis limits: %g:%g:%g",
        measurements[designTriple[0]],
        measurements[designTriple[1]],
        measurements[designTriple[2]],
    )

    if (
        abs(measurements[designTriple[0]] - userTriple[0]) > 1
        or abs(measurements[designTriple[1]] - userTriple[1]) > 1
        or abs(measurements[designTriple[2]] - userTriple[2]) > 1
    ):
        log.warning("Calculated slant axis min/default/max do not match user input.")
        log.warning(
            "  Current slant axis limits: %g:%g:%g",
            *userTriple,
        )
        log.warning(
            "  Suggested slant axis limits: %g:%g:%g",
            measurements[designTriple[0]],
            measurements[designTriple[1]],
            measurements[designTriple[2]],
        )

        return False

    return True


def planAxis(
    measureFunc,
    normalizeFunc,
    interpolateFunc,
    glyphSetFunc,
    axisTag,
    axisLimits,
    values,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitizeFunc=None,
):
    """Plan an axis.

    measureFunc: callable that takes a glyphset and an optional
    list of glyphnames, and returns the glyphset-wide measurement
    to be used for the axis.

    normalizeFunc: callable that takes a measurement and a minimum
    and maximum, and normalizes the measurement into the range 0..1,
    possibly extrapolating too.

    interpolateFunc: callable that takes a normalized t value, and a
    minimum and maximum, and returns the interpolated value,
    possibly extrapolating too.

    glyphSetFunc: callable that takes a variations "location" dictionary,
    and returns a glyphset.

    axisTag: the axis tag string.

    axisLimits: a triple of minimum, default, and maximum values for
    the axis. Or an `fvar` Axis object.

    values: a list of output values to map for this axis.

    samples: the number of samples to use when sampling. Default 8.

    glyphs: a list of glyph names to use when sampling. Defaults to None,
    which will process all glyphs.

    designLimits: an optional triple of minimum, default, and maximum values
    represenging the "design" limits for the axis. If not provided, the
    axisLimits will be used.

    pins: an optional dictionary of before/after mapping entries to pin in
    the output.

    sanitizeFunc: an optional callable to call to sanitize the axis limits.
    """

    if isinstance(axisLimits, fvarAxis):
        axisLimits = (axisLimits.minValue, axisLimits.defaultValue, axisLimits.maxValue)
    minValue, defaultValue, maxValue = axisLimits

    if samples is None:
        samples = SAMPLES
    if glyphs is None:
        glyphs = glyphSetFunc({}).keys()
    if pins is None:
        pins = {}
    else:
        pins = pins.copy()

    log.info(
        "Axis limits min %g / default %g / max %g", minValue, defaultValue, maxValue
    )
    triple = (minValue, defaultValue, maxValue)

    if designLimits is not None:
        log.info("Axis design-limits min %g / default %g / max %g", *designLimits)
    else:
        designLimits = triple

    if pins:
        log.info("Pins %s", sorted(pins.items()))
    pins.update(
        {
            minValue: designLimits[0],
            defaultValue: designLimits[1],
            maxValue: designLimits[2],
        }
    )

    out = {}
    outNormalized = {}

    axisMeasurements = {}
    for value in sorted({minValue, defaultValue, maxValue} | set(pins.keys())):
        glyphset = glyphSetFunc(location={axisTag: value})
        designValue = pins[value]
        axisMeasurements[designValue] = measureFunc(glyphset, glyphs)

    if sanitizeFunc is not None:
        log.info("Sanitizing axis limit values for the `%s` axis.", axisTag)
        sanitizeFunc(triple, designLimits, pins, axisMeasurements)

    log.debug("Calculated average value:\n%s", pformat(axisMeasurements))

    for (rangeMin, targetMin), (rangeMax, targetMax) in zip(
        list(sorted(pins.items()))[:-1],
        list(sorted(pins.items()))[1:],
    ):
        targetValues = {w for w in values if rangeMin < w < rangeMax}
        if not targetValues:
            continue

        normalizedMin = normalizeValue(rangeMin, triple)
        normalizedMax = normalizeValue(rangeMax, triple)
        normalizedTargetMin = normalizeValue(targetMin, designLimits)
        normalizedTargetMax = normalizeValue(targetMax, designLimits)

        log.info("Planning target values %s.", sorted(targetValues))
        log.info("Sampling %u points in range %g,%g.", samples, rangeMin, rangeMax)
        valueMeasurements = axisMeasurements.copy()
        for sample in range(1, samples + 1):
            value = rangeMin + (rangeMax - rangeMin) * sample / (samples + 1)
            log.debug("Sampling value %g.", value)
            glyphset = glyphSetFunc(location={axisTag: value})
            designValue = piecewiseLinearMap(value, pins)
            valueMeasurements[designValue] = measureFunc(glyphset, glyphs)
        log.debug("Sampled average value:\n%s", pformat(valueMeasurements))

        measurementValue = {}
        for value in sorted(valueMeasurements):
            measurementValue[valueMeasurements[value]] = value

        out[rangeMin] = targetMin
        outNormalized[normalizedMin] = normalizedTargetMin
        for value in sorted(targetValues):
            t = normalizeFunc(value, rangeMin, rangeMax)
            targetMeasurement = interpolateFunc(
                t, valueMeasurements[targetMin], valueMeasurements[targetMax]
            )
            targetValue = piecewiseLinearMap(targetMeasurement, measurementValue)
            log.debug("Planned mapping value %g to %g." % (value, targetValue))
            out[value] = targetValue
            valueNormalized = normalizedMin + (value - rangeMin) / (
                rangeMax - rangeMin
            ) * (normalizedMax - normalizedMin)
            outNormalized[valueNormalized] = normalizedTargetMin + (
                targetValue - targetMin
            ) / (targetMax - targetMin) * (normalizedTargetMax - normalizedTargetMin)
        out[rangeMax] = targetMax
        outNormalized[normalizedMax] = normalizedTargetMax

    log.info("Planned mapping for the `%s` axis:\n%s", axisTag, pformat(out))
    log.info(
        "Planned normalized mapping for the `%s` axis:\n%s",
        axisTag,
        pformat(outNormalized),
    )

    if all(abs(k - v) < 0.01 for k, v in outNormalized.items()):
        log.info("Detected identity mapping for the `%s` axis. Dropping.", axisTag)
        out = {}
        outNormalized = {}

    return out, outNormalized


def planWeightAxis(
    glyphSetFunc,
    axisLimits,
    weights=None,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitize=False,
):
    """Plan a weight (`wght`) axis.

    weights: A list of weight values to plan for. If None, the default
    values are used.

    This function simply calls planAxis with values=weights, and the appropriate
    arguments. See documenation for planAxis for more information.
    """

    if weights is None:
        weights = WEIGHTS

    return planAxis(
        measureWeight,
        normalizeLinear,
        interpolateLog,
        glyphSetFunc,
        "wght",
        axisLimits,
        values=weights,
        samples=samples,
        glyphs=glyphs,
        designLimits=designLimits,
        pins=pins,
        sanitizeFunc=sanitizeWeight if sanitize else None,
    )


def planWidthAxis(
    glyphSetFunc,
    axisLimits,
    widths=None,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitize=False,
):
    """Plan a width (`wdth`) axis.

    widths: A list of width values (percentages) to plan for. If None, the default
    values are used.

    This function simply calls planAxis with values=widths, and the appropriate
    arguments. See documenation for planAxis for more information.
    """

    if widths is None:
        widths = WIDTHS

    return planAxis(
        measureWidth,
        normalizeLinear,
        interpolateLinear,
        glyphSetFunc,
        "wdth",
        axisLimits,
        values=widths,
        samples=samples,
        glyphs=glyphs,
        designLimits=designLimits,
        pins=pins,
        sanitizeFunc=sanitizeWidth if sanitize else None,
    )


def planSlantAxis(
    glyphSetFunc,
    axisLimits,
    slants=None,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitize=False,
):
    """Plan a slant (`slnt`) axis.

    slants: A list slant angles to plan for. If None, the default
    values are used.

    This function simply calls planAxis with values=slants, and the appropriate
    arguments. See documenation for planAxis for more information.
    """

    if slants is None:
        slants = SLANTS

    return planAxis(
        measureSlant,
        normalizeDegrees,
        interpolateLinear,
        glyphSetFunc,
        "slnt",
        axisLimits,
        values=slants,
        samples=samples,
        glyphs=glyphs,
        designLimits=designLimits,
        pins=pins,
        sanitizeFunc=sanitizeSlant if sanitize else None,
    )


def planOpticalSizeAxis(
    glyphSetFunc,
    axisLimits,
    sizes=None,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitize=False,
):
    """Plan a optical-size (`opsz`) axis.

    sizes: A list of optical size values to plan for. If None, the default
    values are used.

    This function simply calls planAxis with values=sizes, and the appropriate
    arguments. See documenation for planAxis for more information.
    """

    if sizes is None:
        sizes = SIZES

    return planAxis(
        measureWeight,
        normalizeLog,
        interpolateLog,
        glyphSetFunc,
        "opsz",
        axisLimits,
        values=sizes,
        samples=samples,
        glyphs=glyphs,
        designLimits=designLimits,
        pins=pins,
    )


def makeDesignspaceSnippet(axisTag, axisName, axisLimit, mapping):
    """Make a designspace snippet for a single axis."""

    designspaceSnippet = (
        '    <axis tag="%s" name="%s" minimum="%g" default="%g" maximum="%g"'
        % ((axisTag, axisName) + axisLimit)
    )
    if mapping:
        designspaceSnippet += ">\n"
    else:
        designspaceSnippet += "/>"

    for key, value in mapping.items():
        designspaceSnippet += '      <map input="%g" output="%g"/>\n' % (key, value)

    if mapping:
        designspaceSnippet += "    </axis>"

    return designspaceSnippet


def addEmptyAvar(font):
    """Add an empty `avar` table to the font."""
    font["avar"] = avar = newTable("avar")
    for axis in fvar.axes:
        avar.segments[axis.axisTag] = {}


def processAxis(
    font,
    planFunc,
    axisTag,
    axisName,
    values,
    samples=None,
    glyphs=None,
    designLimits=None,
    pins=None,
    sanitize=False,
    plot=False,
):
    """Process a single axis."""

    axisLimits = None
    for axis in font["fvar"].axes:
        if axis.axisTag == axisTag:
            axisLimits = axis
            break
    if axisLimits is None:
        return ""
    axisLimits = (axisLimits.minValue, axisLimits.defaultValue, axisLimits.maxValue)

    log.info("Planning %s axis.", axisName)

    if "avar" in font:
        existingMapping = font["avar"].segments[axisTag]
        font["avar"].segments[axisTag] = {}
    else:
        existingMapping = None

    if values is not None and isinstance(values, str):
        values = [float(w) for w in values.split()]

    if designLimits is not None and isinstance(designLimits, str):
        designLimits = [float(d) for d in options.designLimits.split(":")]
        assert (
            len(designLimits) == 3
            and designLimits[0] <= designLimits[1] <= designLimits[2]
        )
    else:
        designLimits = None

    if pins is not None and isinstance(pins, str):
        newPins = {}
        for pin in pins.split():
            before, after = pin.split(":")
            newPins[float(before)] = float(after)
        pins = newPins
        del newPins

    mapping, mappingNormalized = planFunc(
        font.getGlyphSet,
        axisLimits,
        values,
        samples=samples,
        glyphs=glyphs,
        designLimits=designLimits,
        pins=pins,
        sanitize=sanitize,
    )

    if plot:
        from matplotlib import pyplot

        pyplot.plot(
            sorted(mappingNormalized),
            [mappingNormalized[k] for k in sorted(mappingNormalized)],
        )
        pyplot.show()

    if existingMapping is not None:
        log.info("Existing %s mapping:\n%s", axisName, pformat(existingMapping))

    if mapping:
        if "avar" not in font:
            addEmptyAvar(font)
        font["avar"].segments[axisTag] = mappingNormalized
    else:
        if "avar" in font:
            font["avar"].segments[axisTag] = {}

    designspaceSnippet = makeDesignspaceSnippet(
        axisTag,
        axisName,
        axisLimits,
        mapping,
    )
    return designspaceSnippet


def main(args=None):
    """Plan the standard axis mappings for a variable font"""

    if args is None:
        import sys

        args = sys.argv[1:]

    from fontTools import configLogger
    from fontTools.ttLib import TTFont
    import argparse

    parser = argparse.ArgumentParser(
        "fonttools varLib.avarPlanner",
        description="Plan `avar` table for variable font",
    )
    parser.add_argument("font", metavar="varfont.ttf", help="Variable-font file.")
    parser.add_argument(
        "-o",
        "--output-file",
        type=str,
        help="Output font file name.",
    )
    parser.add_argument(
        "--weights", type=str, help="Space-separate list of weights to generate."
    )
    parser.add_argument(
        "--widths", type=str, help="Space-separate list of widths to generate."
    )
    parser.add_argument(
        "--slants", type=str, help="Space-separate list of slants to generate."
    )
    parser.add_argument(
        "--sizes", type=str, help="Space-separate list of optical-sizes to generate."
    )
    parser.add_argument("--samples", type=int, help="Number of samples.")
    parser.add_argument(
        "-s", "--sanitize", action="store_true", help="Sanitize axis limits"
    )
    parser.add_argument(
        "-g",
        "--glyphs",
        type=str,
        help="Space-separate list of glyphs to use for sampling.",
    )
    parser.add_argument(
        "--weight-design-limits",
        type=str,
        help="min:default:max in design units for the `wght` axis.",
    )
    parser.add_argument(
        "--width-design-limits",
        type=str,
        help="min:default:max in design units for the `wdth` axis.",
    )
    parser.add_argument(
        "--slant-design-limits",
        type=str,
        help="min:default:max in design units for the `slnt` axis.",
    )
    parser.add_argument(
        "--optical-size-design-limits",
        type=str,
        help="min:default:max in design units for the `opsz` axis.",
    )
    parser.add_argument(
        "--weight-pins",
        type=str,
        help="Space-separate list of before:after pins for the `wght` axis.",
    )
    parser.add_argument(
        "--width-pins",
        type=str,
        help="Space-separate list of before:after pins for the `wdth` axis.",
    )
    parser.add_argument(
        "--slant-pins",
        type=str,
        help="Space-separate list of before:after pins for the `slnt` axis.",
    )
    parser.add_argument(
        "--optical-size-pins",
        type=str,
        help="Space-separate list of before:after pins for the `opsz` axis.",
    )
    parser.add_argument(
        "-p", "--plot", action="store_true", help="Plot the resulting mapping."
    )

    logging_group = parser.add_mutually_exclusive_group(required=False)
    logging_group.add_argument(
        "-v", "--verbose", action="store_true", help="Run more verbosely."
    )
    logging_group.add_argument(
        "-q", "--quiet", action="store_true", help="Turn verbosity off."
    )

    options = parser.parse_args(args)

    configLogger(
        level=("DEBUG" if options.verbose else "WARNING" if options.quiet else "INFO")
    )

    font = TTFont(options.font)
    if not "fvar" in font:
        log.error("Not a variable font.")
        return 1

    if options.glyphs is not None:
        glyphs = options.glyphs.split()
        if ":" in options.glyphs:
            glyphs = {}
            for g in options.glyphs.split():
                if ":" in g:
                    glyph, frequency = g.split(":")
                    glyphs[glyph] = float(frequency)
                else:
                    glyphs[g] = 1.0
    else:
        glyphs = None

    designspaceSnippets = []

    designspaceSnippets.append(
        processAxis(
            font,
            planWeightAxis,
            "wght",
            "Weight",
            values=options.weights,
            samples=options.samples,
            glyphs=glyphs,
            designLimits=options.weight_design_limits,
            pins=options.weight_pins,
            sanitize=options.sanitize,
            plot=options.plot,
        )
    )
    designspaceSnippets.append(
        processAxis(
            font,
            planWidthAxis,
            "wdth",
            "Width",
            values=options.widths,
            samples=options.samples,
            glyphs=glyphs,
            designLimits=options.width_design_limits,
            pins=options.width_pins,
            sanitize=options.sanitize,
            plot=options.plot,
        )
    )
    designspaceSnippets.append(
        processAxis(
            font,
            planSlantAxis,
            "slnt",
            "Slant",
            values=options.slants,
            samples=options.samples,
            glyphs=glyphs,
            designLimits=options.slant_design_limits,
            pins=options.slant_pins,
            sanitize=options.sanitize,
            plot=options.plot,
        )
    )
    designspaceSnippets.append(
        processAxis(
            font,
            planOpticalSizeAxis,
            "opsz",
            "OpticalSize",
            values=options.sizes,
            samples=options.samples,
            glyphs=glyphs,
            designLimits=options.optical_size_design_limits,
            pins=options.optical_size_pins,
            sanitize=options.sanitize,
            plot=options.plot,
        )
    )

    log.info("Designspace snippet:")
    for snippet in designspaceSnippets:
        if snippet:
            print(snippet)

    if options.output_file is None:
        outfile = makeOutputFileName(options.font, overWrite=True, suffix=".avar")
    else:
        outfile = options.output_file
    if outfile:
        log.info("Saving %s", outfile)
        font.save(outfile)


if __name__ == "__main__":
    import sys

    sys.exit(main())