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