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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(location)
if loc in self.values.keys():
return self.values[loc]
values = list(self.values.values())
loc = dict(self._normalized_location(loc))
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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