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			119 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			Python
		
	
			
		
		
	
	
			119 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			Python
		
	
from fontTools.varLib.models import VariationModel, normalizeValue, piecewiseLinearMap
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def Location(loc):
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    return tuple(sorted(loc.items()))
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class VariableScalar:
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    """A scalar with different values at different points in the designspace."""
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    def __init__(self, location_value={}):
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        self.values = {}
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        self.axes = {}
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        for location, value in location_value.items():
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            self.add_value(location, value)
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    def __repr__(self):
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        items = []
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        for location, value in self.values.items():
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            loc = ",".join(
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                [
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                    f"{ax}={int(coord) if float(coord).is_integer() else coord}"
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                    for ax, coord in location
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                ]
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            )
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            items.append("%s:%i" % (loc, value))
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        return "(" + (" ".join(items)) + ")"
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    @property
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    def does_vary(self):
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        values = list(self.values.values())
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        return any(v != values[0] for v in values[1:])
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    @property
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    def axes_dict(self):
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        if not self.axes:
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            raise ValueError(
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                ".axes must be defined on variable scalar before interpolating"
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            )
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        return {ax.axisTag: ax for ax in self.axes}
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    def _normalized_location(self, location):
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        location = self.fix_location(location)
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        normalized_location = {}
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        for axtag in location.keys():
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            if axtag not in self.axes_dict:
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                raise ValueError("Unknown axis %s in %s" % (axtag, location))
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            axis = self.axes_dict[axtag]
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            normalized_location[axtag] = normalizeValue(
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                location[axtag], (axis.minValue, axis.defaultValue, axis.maxValue)
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            )
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        return Location(normalized_location)
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    def fix_location(self, location):
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        location = dict(location)
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        for tag, axis in self.axes_dict.items():
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            if tag not in location:
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                location[tag] = axis.defaultValue
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        return location
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    def add_value(self, location, value):
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        if self.axes:
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            location = self.fix_location(location)
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        self.values[Location(location)] = value
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    def fix_all_locations(self):
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        self.values = {
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            Location(self.fix_location(l)): v for l, v in self.values.items()
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        }
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    @property
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    def default(self):
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        self.fix_all_locations()
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        key = Location({ax.axisTag: ax.defaultValue for ax in self.axes})
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        if key not in self.values:
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            raise ValueError("Default value could not be found")
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            # I *guess* we could interpolate one, but I don't know how.
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        return self.values[key]
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    def value_at_location(self, location, model_cache=None, avar=None):
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        loc = Location(location)
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        if loc in self.values.keys():
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            return self.values[loc]
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        values = list(self.values.values())
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        loc = dict(self._normalized_location(loc))
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        return self.model(model_cache, avar).interpolateFromMasters(loc, values)
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    def model(self, model_cache=None, avar=None):
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        if model_cache is not None:
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            key = tuple(self.values.keys())
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            if key in model_cache:
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                return model_cache[key]
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        locations = [dict(self._normalized_location(k)) for k in self.values.keys()]
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        if avar is not None:
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            mapping = avar.segments
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            locations = [
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                {
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                    k: piecewiseLinearMap(v, mapping[k]) if k in mapping else v
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                    for k, v in location.items()
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                }
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                for location in locations
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            ]
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        m = VariationModel(locations)
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        if model_cache is not None:
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            model_cache[key] = m
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        return m
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    def get_deltas_and_supports(self, model_cache=None, avar=None):
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        values = list(self.values.values())
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        return self.model(model_cache, avar).getDeltasAndSupports(values)
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    def add_to_variation_store(self, store_builder, model_cache=None, avar=None):
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        deltas, supports = self.get_deltas_and_supports(model_cache, avar)
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        store_builder.setSupports(supports)
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        index = store_builder.storeDeltas(deltas)
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        return int(self.default), index
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