Source code for

# Copyright 2016 Autodesk Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
from moldesign import utils

from .quantity import *

[docs]def units_transfer(from_var, to_var, force=False): """ Give the "to_var" object the same units as "from_var" Args: from_var (MdtQuantity): use this quantities units to_var (MdtQuantity): apply units to this quantity force (bool): Transfer the units even if from_var and to_var have incompatible units Returns: MdtQuantity: to_var with from_var's units """ # If from_var is not a Quantity-like object, return a normal python scalar if not hasattr(from_var, '_units'): try: if to_var.dimensionless or force: return to_var._magnitude else: raise DimensionalityError(from_var, to_var) except AttributeError: return to_var # If to_var is a quantity-like object, just perform in-place conversion try: return except AttributeError: pass # If to_var has no units, return a Quantity object return to_var * from_var.units
[docs]def get_units(q): """ Return the base unit system of an quantity """ x = q while True: try: x = x.__iter__().next() except (AttributeError, TypeError): break try: y = 1.0 * x y._magnitude = 1.0 return y except AttributeError: return 1.0 * ureg.dimensionless
[docs]def array(qlist, baseunit=None): """ Facilitates creating an array with units - like numpy.array, but it also checks units for all components of the array Args: qlist (List[MdtQuantity]): List-like object of quantity objects baseunit (MdtUnit) unit to standardize with Returns: MdtQuantity: array with standardized units """ if hasattr(qlist, 'units') and hasattr(qlist, 'magnitude'): return MdtQuantity(qlist) if baseunit is None: baseunit = get_units(qlist) try: if baseunit == 1.0: return np.array(qlist) except DimensionalityError: pass try: newlist = [array(item, baseunit=baseunit).value_in(baseunit) for item in qlist] return baseunit * newlist except TypeError as exc: return
[docs]def broadcast_to(arr, *args, **kwargs): units = arr.units newarr = np.zeros(2) * units # TODO: replace with np.broadcast_to once numpy 1.10 is available in most package managers tmp = _from_np_broadcast_to(arr, *args, **kwargs) newarr._magnitude = tmp return newarr
# TODO: remove once numpy 1.10 is available in most package managers def _from_np_broadcast_to(array, shape, subok=False, readonly=True): """ Temporary copy of a new NumPy function in 1.10, which isn't available in pkg managers yet """ shape = tuple(shape) if np.iterable(shape) else (shape,) array = np.array(array, copy=False, subok=subok) if not shape and array.shape: raise ValueError('cannot broadcast a non-scalar to a scalar array') if any(size < 0 for size in shape): raise ValueError('all elements of broadcast shape must be non-' 'negative') needs_writeable = not readonly and array.flags.writeable extras = ['reduce_ok'] if needs_writeable else [] op_flag = 'readwrite' if needs_writeable else 'readonly' broadcast = np.nditer( (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras, op_flags=[op_flag], itershape=shape, order='C').itviews[0] result = _maybe_view_as_subclass(array, broadcast) if needs_writeable and not result.flags.writeable: result.flags.writeable = True return result # TODO: remove once numpy 1.10 is available in most package managers def _maybe_view_as_subclass(original_array, new_array): """ Temporary copy of a new NumPy function in 1.10, which isn't available in pkg managers yet """ if type(original_array) is not type(new_array): # if input was an ndarray subclass and subclasses were OK, # then view the result as that subclass. new_array = new_array.view(type=type(original_array)) # Since we have done something akin to a view from original_array, we # should let the subclass finalize (if it has it implemented, i.e., is # not None). if new_array.__array_finalize__: new_array.__array_finalize__(original_array) return new_array