Cython implementation multiply and from_attributes

.circleci/config.yml

@@ -21,18 +21,17 @@ jobs:
                 command: |
                     python3 -m venv venv
                     source venv/bin/activate
-                    pip install -U pip
                     pip install -r requirements-dev.txt
-                    pip install .[dev]
+                    pip install -e .[dev]
             - save_cache:
                 key: py310-{{ checksum "requirements-dev.txt"}}
                 paths:
                     - venv
             - run:
-                name: "Run pylint"
+                name: "Run pytest"
                 command: |
                     source venv/bin/activate
-                    pylint --rcfile=.pylintrc -E numpoly
+                    pytest --doctest-modules numpoly/ test/
             - run:
                 name: "Run pydocstyle"
                 command: |
@@ -72,7 +71,7 @@ jobs:
                 command: |
                     source venv/bin/activate
                     pip install twine build
-                    python -m build
+                    python -m build -s
                     twine upload -u __token__ -p $PYPI_PASSWORD --non-interactive dist/*
 
 workflows:

MANIFEST.in

@@ -1,3 +1,5 @@
 include README.rst
 include LICENSE.txt
 global-exclude *.pyc
+recursive-include numpoly/cfunctions *.pyx
+recursive-include numpoly/cfunctions *.pxd

docs/reference/constructor.rst

@@ -40,9 +40,5 @@ Save/Load
 .. autosummary::
    :toctree: ../api
 
-   load
    loadtxt
-   save
    savetxt
-   savez
-   savez_compressed

numpoly/__init__.py

@@ -32,6 +32,7 @@
 from .sympy_ import to_sympy
 
 from .array_function import *
+from .cfunctions import *
 from .poly_function import *
 from .utils import (
     bindex,

numpoly/align.py

@@ -29,7 +29,7 @@ def align_polynomials(*polys: PolyLike) -> Tuple[ndpoly, ...]:
         >>> q0
         polynomial(q0)
         >>> q0.coefficients
-        [1]
+        [np.int64(1)]
         >>> q0.indeterminants
         polynomial([q0])
         >>> q0, _ = numpoly.align_polynomials(q0, q0q1)

numpoly/array_function/__init__.py

@@ -46,7 +46,6 @@
 from .hsplit import hsplit
 from .less import less
 from .less_equal import less_equal
-from .load import load
 from .inner import inner
 from .isclose import isclose
 from .isfinite import isfinite
@@ -74,10 +73,7 @@
 from .result_type import result_type
 from .rint import rint
 from .roots import roots
-from .save import save
 from .savetxt import savetxt
-from .savez import savez
-from .savez_compressed import savez_compressed
 from .split import split
 from .square import square
 from .stack import stack

numpoly/array_function/all.py

@@ -48,11 +48,11 @@ def all(
     Example:
         >>> q0 = numpoly.variable()
         >>> numpoly.all(q0)
-        True
+        np.True_
         >>> numpoly.all(0*q0)
-        False
+        np.False_
         >>> numpoly.all([1, q0, 0])
-        False
+        np.False_
         >>> numpoly.all([[True*q0, False], [True, True]], axis=0)
         array([ True, False])
 

numpoly/array_function/any.py

@@ -50,11 +50,11 @@ def any(
     Example:
         >>> q0 = numpoly.variable()
         >>> numpoly.any(q0)
-        True
+        np.True_
         >>> numpoly.any(0*q0)
-        False
+        np.False_
         >>> numpoly.any([1, q0, 0])
-        True
+        np.True_
         >>> numpoly.any([[True*q0, False], [True, True]], axis=0)
         array([ True,  True])
 

numpoly/array_function/argmax.py

@@ -44,11 +44,11 @@ def argmax(
     Example:
         >>> q0, q1 = numpoly.variable(2)
         >>> numpoly.argmax([13, 7])
-        0
+        np.int64(0)
         >>> numpoly.argmax([1, q0, q0**2, q1])
-        2
+        np.int64(2)
         >>> numpoly.argmax([1, q0, q1])
-        2
+        np.int64(2)
         >>> numpoly.argmax([[3*q0**2, q0**2],
         ...                 [2*q0**2, 4*q0**2]], axis=0)
         array([0, 1])

numpoly/array_function/argmin.py

@@ -44,11 +44,11 @@ def argmin(
     Example:
         >>> q0, q1 = numpoly.variable(2)
         >>> numpoly.argmin([13, 7])
-        1
+        np.int64(1)
         >>> numpoly.argmin([1, q0, q0**2, q1])
-        0
+        np.int64(0)
         >>> numpoly.argmin([q0*q1, q0, q1])
-        1
+        np.int64(1)
         >>> numpoly.argmin([[3*q0**2, q0**2], [2*q0**2, 4*q0**2]], axis=0)
         array([1, 0])
 

numpoly/array_function/isfinite.py

@@ -50,15 +50,15 @@ def isfinite(
 
     Example:
         >>> numpoly.isfinite(1)
-        True
+        np.True_
         >>> numpoly.isfinite(0)
-        True
+        np.True_
         >>> numpoly.isfinite(numpy.nan*numpoly.variable())
-        False
+        np.False_
         >>> numpoly.isfinite(numpy.inf)
-        False
-        >>> numpoly.isfinite(numpy.NINF)
-        False
+        np.False_
+        >>> numpoly.isfinite(-numpy.inf)
+        np.False_
         >>> numpoly.isfinite([numpy.log(-1.), 1., numpy.log(0)])
         array([False,  True, False])
 

numpoly/array_function/logical_and.py

@@ -49,7 +49,7 @@ def logical_and(
     Example:
         >>> q0, q1 = numpoly.variable(2)
         >>> numpoly.logical_and(q0, 0)
-        False
+        np.False_
         >>> numpoly.logical_and([q0, False], [q0, q1])
         array([ True, False])
         >>> const = numpy.arange(5)

numpoly/array_function/logical_or.py

@@ -48,7 +48,7 @@ def logical_or(
 
     Example:
         >>> numpoly.logical_or(True, False)
-        True
+        np.True_
         >>> numpoly.logical_or([True, False], [False, False])
         array([ True, False])
         >>> x = numpy.arange(5)

numpoly/array_function/multiply.py

@@ -1,4 +1,5 @@
 """Multiply arguments element-wise."""
+
 from __future__ import annotations
 from typing import Any, Optional
 
@@ -56,6 +57,7 @@ def multiply(
 
     """
     x1, x2 = numpoly.align_indeterminants(x1, x2)
+
     dtype = numpy.result_type(x1, x2)
     shape = numpy.broadcast_shapes(x1.shape, x2.shape)
 
@@ -76,21 +78,33 @@ def multiply(
         else out
     )
 
-    seen = set()
-    for expon1, coeff1 in zip(x1.exponents, x1.coefficients):
-        for expon2, coeff2 in zip(x2.exponents, x2.coefficients):
-            key = (expon1 + expon2 + x1.KEY_OFFSET).ravel()
-            key = key.view(f"U{len(expon1)}").item()
-            if key in seen:
-                out_.values[key] += numpy.multiply(
-                    coeff1, coeff2, where=where, **kwargs
-                )
-            else:
-                numpy.multiply(
-                    coeff1, coeff2, out=out_.values[key], where=where, **kwargs
-                )
-            seen.add(key)
+    #    seen = set()
+    #    for expon1, coeff1 in zip(x1.exponents, x1.coefficients):
+    #        for expon2, coeff2 in zip(x2.exponents, x2.coefficients):
+    #            key = (expon1 + expon2 + x1.KEY_OFFSET).ravel()
+    #            key = key.view(f"U{len(expon1)}").item()
+    #            if key in seen:
+    #                out_.values[key] += numpy.multiply(
+    #                    coeff1, coeff2, where=where, **kwargs
+    #                )
+    #            else:
+    #                numpy.multiply(
+    #                    coeff1, coeff2, out=out_.values[key], where=where, **kwargs
+    #                )
+    #            seen.add(key)
+    #
+    #    if out is None:
+    #        out_ = numpoly.clean_attributes(out_)
 
+    numpoly.cmultiply(
+        x1.exponents,
+        x2.exponents,
+        x1.coefficients,
+        x2.coefficients,
+        x1.KEY_OFFSET,
+        out_.values.ravel(),
+    )
     if out is None:
         out_ = numpoly.clean_attributes(out_)
+
     return out_

numpoly/array_function/reshape.py

@@ -20,16 +20,18 @@
 @implements(numpy.reshape)
 def reshape(
     a: PolyLike,
-    newshape: Union[int, Sequence[int]],
+    /,
+    shape: Union[int, Sequence[int]] = None,
     order: Order = "C",
+    newshape: Union[int, Sequence[int]] = None,
 ) -> ndpoly:
     """
     Give a new shape to an array without changing its data.
 
     Args:
         a:
             Array to be reshaped.
-        newshape:
+        shape:
             The new shape should be compatible with the original shape. If an
             integer, then the result will be a 1-D array of that length. One
             shape dimension can be -1. In this case, the value is inferred from
@@ -63,5 +65,5 @@ def reshape(
 
     """
     poly = numpoly.aspolynomial(a)
-    array = numpy.reshape(poly.values, newshape=newshape, order=order)
+    array = numpy.reshape(poly.values, shape=shape, newshape=newshape, order=order)
     return numpoly.aspolynomial(array, names=poly.indeterminants)