Add any, all, cbrt, linalg.solve

docs/numpy.ipynb

@@ -284,7 +284,7 @@
     "\n",
     "The following [ufuncs](http://docs.scipy.org/doc/numpy/reference/ufuncs.html) can be applied to a Quantity object:\n",
     "\n",
-    "- **Math operations**: `add`, `subtract`, `multiply`, `divide`, `logaddexp`, `logaddexp2`, `true_divide`, `floor_divide`, `negative`, `remainder`, `mod`, `fmod`, `absolute`, `rint`, `sign`, `conj`, `exp`, `exp2`, `log`, `log2`, `log10`, `expm1`, `log1p`, `sqrt`, `square`, `reciprocal`\n",
+    "- **Math operations**: `add`, `subtract`, `multiply`, `divide`, `logaddexp`, `logaddexp2`, `true_divide`, `floor_divide`, `negative`, `remainder`, `mod`, `fmod`, `absolute`, `rint`, `sign`, `conj`, `exp`, `exp2`, `log`, `log2`, `log10`, `expm1`, `log1p`, `sqrt`, `square`, `cbrt`, `reciprocal`\n",
     "- **Trigonometric functions**: `sin`, `cos`, `tan`, `arcsin`, `arccos`, `arctan`, `arctan2`, `hypot`, `sinh`, `cosh`, `tanh`, `arcsinh`, `arccosh`, `arctanh`\n",
     "- **Comparison functions**: `greater`, `greater_equal`, `less`, `less_equal`, `not_equal`, `equal`\n",
     "- **Floating functions**: `isreal`, `iscomplex`, `isfinite`, `isinf`, `isnan`, `signbit`, `copysign`, `nextafter`, `modf`, `ldexp`, `frexp`, `fmod`, `floor`, `ceil`, `trunc`\n",
@@ -301,7 +301,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['alen', 'amax', 'amin', 'append', 'argmax', 'argmin', 'argsort', 'around', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'average', 'block', 'broadcast_to', 'clip', 'column_stack', 'compress', 'concatenate', 'copy', 'copyto', 'count_nonzero', 'cross', 'cumprod', 'cumproduct', 'cumsum', 'diagonal', 'diff', 'dot', 'dstack', 'ediff1d', 'einsum', 'empty_like', 'expand_dims', 'fix', 'flip', 'full_like', 'gradient', 'hstack', 'insert', 'interp', 'isclose', 'iscomplex', 'isin', 'isreal', 'linspace', 'mean', 'median', 'meshgrid', 'moveaxis', 'nan_to_num', 'nanargmax', 'nanargmin', 'nancumprod', 'nancumsum', 'nanmax', 'nanmean', 'nanmedian', 'nanmin', 'nanpercentile', 'nanstd', 'nansum', 'nanvar', 'ndim', 'nonzero', 'ones_like', 'pad', 'percentile', 'ptp', 'ravel', 'resize', 'result_type', 'rollaxis', 'rot90', 'round_', 'searchsorted', 'shape', 'size', 'sort', 'squeeze', 'stack', 'std', 'sum', 'swapaxes', 'tile', 'transpose', 'trapz', 'trim_zeros', 'unwrap', 'var', 'vstack', 'where', 'zeros_like']\n"
+      "['alen', 'all', 'amax', 'amin', 'any', 'append', 'argmax', 'argmin', 'argsort', 'around', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'average', 'block', 'broadcast_to', 'clip', 'column_stack', 'compress', 'concatenate', 'copy', 'copyto', 'count_nonzero', 'cross', 'cumprod', 'cumproduct', 'cumsum', 'diagonal', 'diff', 'dot', 'dstack', 'ediff1d', 'einsum', 'empty_like', 'expand_dims', 'fix', 'flip', 'full_like', 'gradient', 'hstack', 'insert', 'interp', 'isclose', 'iscomplex', 'isin', 'isreal', 'linalg.solve', 'linspace', 'mean', 'median', 'meshgrid', 'moveaxis', 'nan_to_num', 'nanargmax', 'nanargmin', 'nancumprod', 'nancumsum', 'nanmax', 'nanmean', 'nanmedian', 'nanmin', 'nanpercentile', 'nanstd', 'nansum', 'nanvar', 'ndim', 'nonzero', 'ones_like', 'pad', 'percentile', 'ptp', 'ravel', 'resize', 'result_type', 'rollaxis', 'rot90', 'round_', 'searchsorted', 'shape', 'size', 'sort', 'squeeze', 'stack', 'std', 'sum', 'swapaxes', 'tile', 'transpose', 'trapz', 'trim_zeros', 'unwrap', 'var', 'vstack', 'where', 'zeros_like']\n"
      ]
     }
    ],

pint/numpy_func.py

@@ -194,6 +194,8 @@ def get_op_output_unit(unit_op, first_input_units, all_args=None, size=None):
         result_unit = first_input_units ** 2
     elif unit_op == "sqrt":
         result_unit = first_input_units ** 0.5
+    elif unit_op == "cbrt":
+        result_unit = first_input_units ** (1 / 3)
     elif unit_op == "reciprocal":
         result_unit = first_input_units ** -1
     elif unit_op == "size":
@@ -255,7 +257,11 @@ def implement_func(func_type, func_str, input_units=None, output_unit=None):
     if np is None:
         return
 
-    func = getattr(np, func_str)
+    # Handle functions in submodules
+    func_str_split = func_str.split(".")
+    func = getattr(np, func_str_split[0])
+    for func_str_piece in func_str_split[1:]:
+        func = getattr(func, func_str_piece)
 
     @implements(func_str, func_type)
     def implementation(*args, **kwargs):
@@ -295,6 +301,7 @@ def implementation(*args, **kwargs):
             "variance",
             "square",
             "sqrt",
+            "cbrt",
             "reciprocal",
             "size",
         ]:
@@ -408,6 +415,7 @@ def implementation(*args, **kwargs):
     "divide": "div",
     "floor_divide": "div",
     "sqrt": "sqrt",
+    "cbrt": "cbrt",
     "square": "square",
     "reciprocal": "reciprocal",
     "std": "sum",
@@ -665,6 +673,24 @@ def _recursive_convert(arg, unit):
     )
 
 
+@implements("any", "function")
+def _any(a, *args, **kwargs):
+    # Only valid when multiplicative unit/no offset
+    if a._is_multiplicative:
+        return np.any(a._magnitude, *args, **kwargs)
+    else:
+        raise ValueError("Boolean value of Quantity with offset unit is ambiguous.")
+
+
+@implements("all", "function")
+def _all(a, *args, **kwargs):
+    # Only valid when multiplicative unit/no offset
+    if a._is_multiplicative:
+        return np.all(a._magnitude, *args, **kwargs)
+    else:
+        raise ValueError("Boolean value of Quantity with offset unit is ambiguous.")
+
+
 # Implement simple matching-unit or stripped-unit functions based on signature
 
 
@@ -836,6 +862,8 @@ def implementation(a, *args, **kwargs):
     implement_func("function", func_str, input_units=None, output_unit="delta")
 for func_str in ["gradient"]:
     implement_func("function", func_str, input_units=None, output_unit="delta,div")
+for func_str in ["linalg.solve"]:
+    implement_func("function", func_str, input_units=None, output_unit="div")
 for func_str in ["var", "nanvar"]:
     implement_func("function", func_str, input_units=None, output_unit="variance")
 
@@ -846,11 +874,15 @@ def numpy_wrap(func_type, func, args, kwargs, types):
 
     if func_type == "function":
         handled = HANDLED_FUNCTIONS
+        # Need to handle functions in submodules
+        name = ".".join(func.__module__.split(".")[1:] + [func.__name__])
     elif func_type == "ufunc":
         handled = HANDLED_UFUNCS
+        # ufuncs do not have func.__module__
+        name = func.__name__
     else:
         raise ValueError("Invalid func_type {}".format(func_type))
 
-    if func.__name__ not in handled or any(is_upcast_type(t) for t in types):
+    if name not in handled or any(is_upcast_type(t) for t in types):
         return NotImplemented
-    return handled[func.__name__](*args, **kwargs)
+    return handled[name](*args, **kwargs)

pint/testsuite/test_numpy.py

@@ -374,6 +374,13 @@ def test_einsum(self):
             np.array([30, 80, 130, 180, 230]) * self.ureg.m ** 2,
         )
 
+    @helpers.requires_array_function_protocol()
+    def test_solve(self):
+        self.assertQuantityAlmostEqual(
+            np.linalg.solve(self.q, [[3], [7]] * self.ureg.s),
+            self.Q_([[1], [1]], "m / s"),
+        )
+
     # Arithmetic operations
     def test_addition_with_scalar(self):
         a = np.array([0, 1, 2])
@@ -414,6 +421,14 @@ def test_power(self):
         )
         self.assertNDArrayEqual(arr ** self.Q_(2), np.array([0, 1, 4]))
 
+    def test_sqrt(self):
+        q = self.Q_(100, "m**2")
+        self.assertQuantityEqual(np.sqrt(q), self.Q_(10, "m"))
+
+    def test_cbrt(self):
+        q = self.Q_(1000, "m**3")
+        self.assertQuantityEqual(np.cbrt(q), self.Q_(10, "m"))
+
     @unittest.expectedFailure
     @helpers.requires_numpy()
     def test_exponentiation_array_exp_2(self):
@@ -537,6 +552,18 @@ def test_nonzero_numpy_func(self):
         q = [1, 0, 5, 6, 0, 9] * self.ureg.m
         self.assertNDArrayEqual(np.nonzero(q)[0], [0, 2, 3, 5])
 
+    @helpers.requires_array_function_protocol()
+    def test_any_numpy_func(self):
+        q = [0, 1] * self.ureg.m
+        self.assertTrue(np.any(q))
+        self.assertRaises(ValueError, np.any, self.q_temperature)
+
+    @helpers.requires_array_function_protocol()
+    def test_all_numpy_func(self):
+        q = [0, 1] * self.ureg.m
+        self.assertFalse(np.all(q))
+        self.assertRaises(ValueError, np.all, self.q_temperature)
+
     @helpers.requires_array_function_protocol()
     def test_count_nonzero_numpy_func(self):
         q = [1, 0, 5, 6, 0, 9] * self.ureg.m