allow using a string for the layer

Can't use it in gdsii, but no reason to forbit it in masque...
lethe/HEAD
Jan Petykiewicz 4 years ago
parent 247b31a9d6
commit 8302286a7a

@ -151,7 +151,7 @@ def dose2dtype(patterns: List[Pattern],
For each shape in each pattern, set shape.layer to the tuple
(base_layer, datatype), where:
layer is chosen to be equal to the original shape.layer if it is an int,
or shape.layer[0] if it is a tuple
or shape.layer[0] if it is a tuple. `str` layers raise a PatterError.
datatype is chosen arbitrarily, based on calcualted dose for each shape.
Shapes with equal calcualted dose will have the same datatype.
A list of doses is retured, providing a mapping between datatype
@ -213,8 +213,10 @@ def dose2dtype(patterns: List[Pattern],
data_type = dose_vals_list.index(shape.dose * pat_dose)
if isinstance(shape.layer, int):
shape.layer = (shape.layer, data_type)
else:
elif isinstance(shape.layer, tuple):
shape.layer = (shape.layer[0], data_type)
else:
raise PatternError(f'Invalid layer for gdsii: {shape.layer}')
new_pats[(pat_id, pat_dose)] = pat
@ -377,12 +379,14 @@ def _mlayer2gds(mlayer: layer_t) -> Tuple[int, int]:
if isinstance(mlayer, int):
layer = mlayer
data_type = 0
else:
elif isinstance(mlayer, tuple):
layer = mlayer[0]
if len(mlayer) > 1:
data_type = mlayer[1]
else:
data_type = 0
else:
raise PatternError(f'Invalid layer for gdsii: {layer}. Note that gdsii layers cannot be strings.')
return layer, data_type

@ -55,7 +55,7 @@ class Label:
@property
def layer(self) -> layer_t:
"""
Layer number (int or tuple of ints)
Layer number or name (int, tuple of ints, or string)
"""
return self._layer

@ -174,7 +174,7 @@ class Shape(metaclass=ABCMeta):
@property
def layer(self) -> layer_t:
"""
Layer number (int or tuple of ints)
Layer number or name (int, tuple of ints, or string)
"""
return self._layer

@ -8,7 +8,7 @@ import numpy
# Type definitions
vector2 = Union[numpy.ndarray, Tuple[float, float], Sequence[float]]
layer_t = Union[int, Tuple[int, int]]
layer_t = Union[int, Tuple[int, int], str]
def is_scalar(var: Any) -> bool:

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