114 lines
		
	
	
		
			4.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			114 lines
		
	
	
		
			4.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from fontTools.varLib.models import VariationModel, normalizeValue, piecewiseLinearMap
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| 
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| 
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| def Location(loc):
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|     return tuple(sorted(loc.items()))
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| 
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| 
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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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| 
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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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| 
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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(["%s=%i" % (ax, loc) for ax, loc in location])
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|             items.append("%s:%i" % (loc, value))
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|         return "(" + (" ".join(items)) + ")"
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| 
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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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| 
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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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| 
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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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| 
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|         return Location(normalized_location)
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| 
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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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| 
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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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| 
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|         self.values[Location(location)] = value
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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