def genValMap(self) -> None:
"""
Generate `valmap` by inverting `nummap`.
"""
if self.nummap is None:
self.valmap = None
else:
self.valmap = {hashable_val(val): num for num, val in self.nummap.items()}
def mapVal(self) -> None:
"""
Map the output value to a number or array of numbers.
"""
if self.valmap is None:
self.num = np.array(self.val)
elif self.isscalar:
self.num = np.array(self.valmap[hashable_val(self.val)])
else:
num = np.array(self.val, dtype='object')
if len(self.shape) == 1:
for i in range(self.shape[0]):
num[i] = self.valmap[hashable_val(self.val[i])]
else:
for i in range(self.shape[0]):
for j in range(self.shape[1]):
num[i][j] = self.valmap[hashable_val(self.val[i][j])]
self.num = np.array(num, dtype='float')
def genNumMap(self) -> None:
"""
Invert the valmap to get a nummap.
"""
if self.valmap is None:
self.nummap = None
else:
self.nummap = {
hashable_val(np.array(num)): val
for val, num in self.valmap.items()
}
def extractValMap(self) -> None:
"""
Parse the output value and extract a valmap.
"""
vals_flattened = flatten([self.val])
if all((isinstance(x, bool) or isinstance(x, np.bool_))
for x in vals_flattened):
self.valmap = {True: 1, False: 0}
elif any(not is_num(x) for x in vals_flattened):
sorted_vals = sorted(set(hashable_val(x) for x in vals_flattened))
self.valmap = {val: idx for idx, val in enumerate(sorted_vals)}
def genValMap(self) -> None:
"""
Generate the valmap based on the nummap.
"""
if self.nummap is None:
self.valmap = None
else:
self.valmap = {
hashable_val(val): num
for num, val in self.nummap.items()
}