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