Extend numpy support to v1.20

Add support for M1 processors

Author: MattiSG

CHANGELOG.md

@@ -1,5 +1,12 @@
 # Changelog
 
+### 35.3.7 [#990](https://github.com/openfisca/openfisca-core/pull/990)
+
+#### Technical changes
+
+- Update dependencies.
+  - Extend NumPy compatibility to v1.20 to support M1 processors.
+
 ### 35.3.6 [#984](https://github.com/openfisca/openfisca-core/pull/984)
 
 #### Technical changes

openfisca_core/indexed_enums/enum.py

@@ -7,40 +7,47 @@
 
 from openfisca_core.indexed_enums import config, EnumArray
 
+if typing.TYPE_CHECKING:
+    IndexedEnumArray = numpy.object_
+
 
 class Enum(enum.Enum):
     """
-    Enum based on `enum34 <https://pypi.python.org/pypi/enum34/>`_, whose items have an
-    index.
+    Enum based on `enum34 <https://pypi.python.org/pypi/enum34/>`_, whose items
+    have an index.
     """
 
     # Tweak enums to add an index attribute to each enum item
     def __init__(self, name: str) -> None:
-        # When the enum item is initialized, self._member_names_ contains the names of
-        # the previously initialized items, so its length is the index of this item.
+        # When the enum item is initialized, self._member_names_ contains the
+        # names of the previously initialized items, so its length is the index
+        # of this item.
         self.index = len(self._member_names_)
 
     # Bypass the slow Enum.__eq__
     __eq__ = object.__eq__
 
-    # In Python 3, __hash__ must be defined if __eq__ is defined to stay hashable.
+    # In Python 3, __hash__ must be defined if __eq__ is defined to stay
+    # hashable.
     __hash__ = object.__hash__
 
     @classmethod
     def encode(
             cls,
             array: typing.Union[
                 EnumArray,
-                numpy.ndarray[int],
-                numpy.ndarray[str],
-                numpy.ndarray[Enum],
+                numpy.int_,
+                numpy.float_,
+                IndexedEnumArray,
                 ],
             ) -> EnumArray:
         """
-        Encode a string numpy array, an enum item numpy array, or an int numpy array
-        into an :any:`EnumArray`. See :any:`EnumArray.decode` for decoding.
+        Encode a string numpy array, an enum item numpy array, or an int numpy
+        array into an :any:`EnumArray`. See :any:`EnumArray.decode` for
+        decoding.
 
-        :param ndarray array: Array of string identifiers, or of enum items, to encode.
+        :param ndarray array: Array of string identifiers, or of enum items, to
+                              encode.
 
         :returns: An :any:`EnumArray` encoding the input array values.
         :rtype: :any:`EnumArray`
@@ -59,24 +66,31 @@ def encode(
         >>> encoded_array[0]
         2  # Encoded value
         """
-        if type(array) is EnumArray:
+        if isinstance(array, EnumArray):
             return array
 
-        if array.dtype.kind in {'U', 'S'}:  # String array
+        # String array
+        if isinstance(array, numpy.ndarray) and \
+                array.dtype.kind in {'U', 'S'}:
             array = numpy.select(
                 [array == item.name for item in cls],
                 [item.index for item in cls],
                 ).astype(config.ENUM_ARRAY_DTYPE)
 
-        elif array.dtype.kind == 'O':  # Enum items arrays
+        # Enum items arrays
+        elif isinstance(array, numpy.ndarray) and \
+                array.dtype.kind == 'O':
             # Ensure we are comparing the comparable. The problem this fixes:
             # On entering this method "cls" will generally come from
-            # variable.possible_values, while the array values may come from directly
-            # importing a module containing an Enum class. However, variables (and
-            # hence their possible_values) are loaded by a call to load_module, which
-            # gives them a different identity from the ones imported in the usual way.
-            # So, instead of relying on the "cls" passed in, we use only its name to
-            # check that the values in the array, if non-empty, are of the right type.
+            # variable.possible_values, while the array values may come from
+            # directly importing a module containing an Enum class. However,
+            # variables (and hence their possible_values) are loaded by a call
+            # to load_module, which gives them a different identity from the
+            # ones imported in the usual way.
+            #
+            # So, instead of relying on the "cls" passed in, we use only its
+            # name to check that the values in the array, if non-empty, are of
+            # the right type.
             if len(array) > 0 and cls.__name__ is array[0].__class__.__name__:
                 cls = array[0].__class__
 

openfisca_core/indexed_enums/enum_array.py

@@ -7,6 +7,8 @@
 if typing.TYPE_CHECKING:
     from openfisca_core.indexed_enums import Enum
 
+    IndexedEnumArray = numpy.object_
+
 
 class EnumArray(numpy.ndarray):
     """
@@ -20,23 +22,23 @@ class EnumArray(numpy.ndarray):
     # https://docs.scipy.org/doc/numpy-1.13.0/user/basics.subclassing.html#slightly-more-realistic-example-attribute-added-to-existing-array.
     def __new__(
             cls,
-            input_array: numpy.ndarray[int],
+            input_array: numpy.int_,
             possible_values: typing.Optional[typing.Type[Enum]] = None,
             ) -> EnumArray:
         obj = numpy.asarray(input_array).view(cls)
         obj.possible_values = possible_values
         return obj
 
     # See previous comment
-    def __array_finalize__(self, obj: typing.Optional[numpy.ndarray[int]]) -> None:
+    def __array_finalize__(self, obj: typing.Optional[numpy.int_]) -> None:
         if obj is None:
             return
 
         self.possible_values = getattr(obj, "possible_values", None)
 
     def __eq__(self, other: typing.Any) -> bool:
-        # When comparing to an item of self.possible_values, use the item index to
-        # speed up the comparison.
+        # When comparing to an item of self.possible_values, use the item index
+        # to speed up the comparison.
         if other.__class__.__name__ is self.possible_values.__name__:
             # Use view(ndarray) so that the result is a classic ndarray, not an
             # EnumArray.
@@ -49,8 +51,8 @@ def __ne__(self, other: typing.Any) -> bool:
 
     def _forbidden_operation(self, other: typing.Any) -> typing.NoReturn:
         raise TypeError(
-            "Forbidden operation. The only operations allowed on EnumArrays are "
-            "'==' and '!='.",
+            "Forbidden operation. The only operations allowed on EnumArrays "
+            "are '==' and '!='.",
             )
 
     __add__ = _forbidden_operation
@@ -62,7 +64,7 @@ def _forbidden_operation(self, other: typing.Any) -> typing.NoReturn:
     __and__ = _forbidden_operation
     __or__ = _forbidden_operation
 
-    def decode(self) -> numpy.ndarray[Enum]:
+    def decode(self) -> IndexedEnumArray:
         """
         Return the array of enum items corresponding to self.
 
@@ -72,14 +74,16 @@ def decode(self) -> numpy.ndarray[Enum]:
         >>> enum_array[0]
         >>> 2  # Encoded value
         >>> enum_array.decode()[0]
-        <HousingOccupancyStatus.free_lodger: 'Free lodger'>  # Decoded value : enum item
+        <HousingOccupancyStatus.free_lodger: 'Free lodger'>
+
+        Decoded value: enum item
         """
         return numpy.select(
             [self == item.index for item in self.possible_values],
             list(self.possible_values),
             )
 
-    def decode_to_str(self) -> numpy.ndarray[str]:
+    def decode_to_str(self) -> numpy.str_:
         """
         Return the array of string identifiers corresponding to self.
 

openfisca_core/taxscales/abstract_rate_tax_scale.py

@@ -3,28 +3,36 @@
 import typing
 import warnings
 
-import numpy
-
 from openfisca_core.taxscales import RateTaxScaleLike
 
+if typing.TYPE_CHECKING:
+    import numpy
+
+    NumericalArray = typing.Union[numpy.int_, numpy.float_]
+
 
 class AbstractRateTaxScale(RateTaxScaleLike):
     """
-    Base class for various types of rate-based tax scales: marginal rate, linear
-    average rate...
+    Base class for various types of rate-based tax scales: marginal rate,
+    linear average rate...
     """
 
-    def __init__(self, name: typing.Optional[str] = None, option = None, unit = None) -> None:
+    def __init__(
+            self, name: typing.Optional[str] = None,
+            option: typing.Any = None,
+            unit: typing.Any = None,
+            ) -> None:
         message = [
-            "The 'AbstractRateTaxScale' class has been deprecated since version",
-            "34.7.0, and will be removed in the future.",
+            "The 'AbstractRateTaxScale' class has been deprecated since",
+            "version 34.7.0, and will be removed in the future.",
             ]
+
         warnings.warn(" ".join(message), DeprecationWarning)
-        super(AbstractRateTaxScale, self).__init__(name, option, unit)
+        super().__init__(name, option, unit)
 
     def calc(
             self,
-            tax_base: typing.Union[numpy.ndarray[int], numpy.ndarray[float]],
+            tax_base: NumericalArray,
             right: bool,
             ) -> typing.NoReturn:
         raise NotImplementedError(

openfisca_core/taxscales/abstract_tax_scale.py

@@ -3,24 +3,34 @@
 import typing
 import warnings
 
-import numpy
-
 from openfisca_core.taxscales import TaxScaleLike
 
+if typing.TYPE_CHECKING:
+    import numpy
+
+    NumericalArray = typing.Union[numpy.int_, numpy.float_]
+
 
 class AbstractTaxScale(TaxScaleLike):
     """
-    Base class for various types of tax scales: amount-based tax scales, rate-based
-    tax scales...
+    Base class for various types of tax scales: amount-based tax scales,
+    rate-based tax scales...
     """
 
-    def __init__(self, name: typing.Optional[str] = None, option = None, unit = None) -> None:
+    def __init__(
+            self,
+            name: typing.Optional[str] = None,
+            option: typing.Any = None,
+            unit: numpy.int_ = None,
+            ) -> None:
+
         message = [
-            "The 'AbstractTaxScale' class has been deprecated since version 34.7.0,",
-            "and will be removed in the future.",
+            "The 'AbstractTaxScale' class has been deprecated since",
+            "version 34.7.0, and will be removed in the future.",
             ]
+
         warnings.warn(" ".join(message), DeprecationWarning)
-        super(AbstractTaxScale, self).__init__(name, option, unit)
+        super().__init__(name, option, unit)
 
     def __repr__(self) -> typing.NoReturn:
         raise NotImplementedError(
@@ -30,7 +40,7 @@ def __repr__(self) -> typing.NoReturn:
 
     def calc(
             self,
-            tax_base: typing.Union[numpy.ndarray[int], numpy.ndarray[float]],
+            tax_base: NumericalArray,
             right: bool,
             ) -> typing.NoReturn:
         raise NotImplementedError(

openfisca_core/taxscales/amount_tax_scale_like.py

@@ -9,22 +9,28 @@
 
 class AmountTaxScaleLike(TaxScaleLike, abc.ABC):
     """
-    Base class for various types of amount-based tax scales: single amount, marginal
-    amount...
+    Base class for various types of amount-based tax scales: single amount,
+    marginal amount...
     """
 
     amounts: typing.List
 
-    def __init__(self, name: typing.Optional[str] = None, option = None, unit = None) -> None:
-        super(AmountTaxScaleLike, self).__init__(name, option, unit)
+    def __init__(
+            self,
+            name: typing.Optional[str] = None,
+            option: typing.Any = None,
+            unit: typing.Any = None,
+            ) -> None:
+        super().__init__(name, option, unit)
         self.amounts = []
 
     def __repr__(self) -> str:
         return tools.indent(
             os.linesep.join(
                 [
                     f"- threshold: {threshold}{os.linesep}  amount: {amount}"
-                    for (threshold, amount) in zip(self.thresholds, self.amounts)
+                    for (threshold, amount)
+                    in zip(self.thresholds, self.amounts)
                     ]
                 )
             )
@@ -37,6 +43,7 @@ def add_bracket(
         if threshold in self.thresholds:
             i = self.thresholds.index(threshold)
             self.amounts[i] += amount
+
         else:
             i = bisect.bisect_left(self.thresholds, threshold)
             self.thresholds.insert(i, threshold)
@@ -45,5 +52,6 @@ def add_bracket(
     def to_dict(self) -> dict:
         return {
             str(threshold): self.amounts[index]
-            for index, threshold in enumerate(self.thresholds)
+            for index, threshold
+            in enumerate(self.thresholds)
             }

openfisca_core/taxscales/helpers.py

@@ -10,11 +10,13 @@
 if typing.TYPE_CHECKING:
     from openfisca_core.parameters import ParameterNodeAtInstant
 
+    TaxScales = typing.Optional[taxscales.MarginalRateTaxScale]
+
 
 def combine_tax_scales(
         node: ParameterNodeAtInstant,
-        combined_tax_scales: typing.Optional[taxscales.MarginalRateTaxScale] = None,
-        ) -> typing.Optional[taxscales.MarginalRateTaxScale]:
+        combined_tax_scales: TaxScales = None,
+        ) -> TaxScales:
     """
     Combine all the MarginalRateTaxScales in the node into a single
     MarginalRateTaxScale.

openfisca_core/taxscales/linear_average_rate_tax_scale.py

@@ -10,14 +10,17 @@
 
 log = logging.getLogger(__name__)
 
+if typing.TYPE_CHECKING:
+    NumericalArray = typing.Union[numpy.int_, numpy.float_]
+
 
 class LinearAverageRateTaxScale(RateTaxScaleLike):
 
     def calc(
             self,
-            tax_base: typing.Union[numpy.ndarray[int], numpy.ndarray[float]],
+            tax_base: NumericalArray,
             right: bool = False,
-            ) -> numpy.ndarray[float]:
+            ) -> numpy.float_:
         if len(self.rates) == 1:
             return tax_base * self.rates[0]