Source code for metpy.units

# Copyright (c) 2015,2017,2019 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
r"""Module to provide unit support.

This makes use of the :mod:`pint` library and sets up the default settings
for good temperature support.

See Also: :doc:`Working with Units </tutorials/unit_tutorial>`.

units : :class:`pint.UnitRegistry`
    The unit registry used throughout the package. Any use of units in MetPy should
    import this registry and use it to grab units.

import functools
from inspect import Parameter, signature
import logging
import re
import warnings

import numpy as np
import pint

log = logging.getLogger(__name__)

UndefinedUnitError = pint.UndefinedUnitError
DimensionalityError = pint.DimensionalityError

_base_unit_of_dimensionality = {
    '[pressure]': 'Pa',
    '[temperature]': 'K',
    '[dimensionless]': '',
    '[length]': 'm',
    '[speed]': 'm s**-1'

# Create registry, with preprocessors for UDUNITS-style powers (m2 s-2) and percent signs
units = pint.UnitRegistry(
        lambda string: string.replace('%', 'percent')

# Capture v0.10 NEP 18 warning on first creation
with warnings.catch_warnings():

# Add a percent unit
units.define('percent = 0.01 = %')

# Define commonly encountered units not defined by pint
units.define('degrees_north = degree = degrees_N = degreesN = degree_north = degree_N '
             '= degreeN')
units.define('degrees_east = degree = degrees_E = degreesE = degree_east = degree_E = degreeE')

# Alias geopotential meters (gpm) to just meters
units.define('@alias meter = gpm')

# Silence UnitStrippedWarning
if hasattr(pint, 'UnitStrippedWarning'):
    warnings.simplefilter('ignore', category=pint.UnitStrippedWarning)

[docs]def pandas_dataframe_to_unit_arrays(df, column_units=None): """Attach units to data in pandas dataframes and return quantities. Parameters ---------- df : `pandas.DataFrame` Data in pandas dataframe. column_units : dict Dictionary of units to attach to columns of the dataframe. Overrides the units attribute if it is attached to the dataframe. Returns ------- Dictionary containing `Quantity` instances with keys corresponding to the dataframe column names. """ if not column_units: try: column_units = df.units except AttributeError: raise ValueError('No units attribute attached to pandas ' 'dataframe and col_units not given.') from None # Iterate through columns attaching units if we have them, if not, don't touch it res = {} for column in df: if column in column_units and column_units[column]: res[column] = units.Quantity(df[column].values, column_units[column]) else: res[column] = df[column].values return res
[docs]def concatenate(arrs, axis=0): r"""Concatenate multiple values into a new quantity. This is essentially a scalar-/masked array-aware version of `numpy.concatenate`. All items must be able to be converted to the same units. If an item has no units, it will be given those of the rest of the collection, without conversion. The first units found in the arguments is used as the final output units. Parameters ---------- arrs : Sequence of arrays The items to be joined together axis : integer, optional The array axis along which to join the arrays. Defaults to 0 (the first dimension) Returns ------- `pint.Quantity` New container with the value passed in and units corresponding to the first item. """ dest = 'dimensionless' for a in arrs: if hasattr(a, 'units'): dest = a.units break data = [] for a in arrs: if hasattr(a, 'to'): a = data.append(np.atleast_1d(a)) # Use masked array concatenate to ensure masks are preserved, but convert to an # array if there are no masked values. data =, axis=axis) if not np.any(data.mask): data = np.asarray(data) return units.Quantity(data, dest)
[docs]def masked_array(data, data_units=None, **kwargs): """Create a :class:`` with units attached. This is a thin wrapper around :func:`` that ensures that units are properly attached to the result (otherwise units are silently lost). Units are taken from the ``data_units`` argument, or if this is ``None``, the units on ``data`` are used. Parameters ---------- data : array_like The source data. If ``data_units`` is `None`, this should be a `pint.Quantity` with the desired units. data_units : str or `pint.Unit`, optional The units for the resulting `pint.Quantity` kwargs Arbitrary keyword arguments passed to ``, optional Returns ------- `pint.Quantity` """ if data_units is None: data_units = data.units return units.Quantity(, **kwargs), data_units)
def _mutate_arguments(bound_args, check_type, mutate_arg): """Handle adjusting bound arguments. Calls ``mutate_arg`` on every argument, including those passed as ``*args``, if they are of type ``check_type``. """ for arg_name, arg_val in bound_args.arguments.items(): if isinstance(arg_val, check_type): bound_args.arguments[arg_name] = mutate_arg(arg_val, arg_name) if isinstance(bound_args.arguments.get('args'), tuple): bound_args.arguments['args'] = tuple( mutate_arg(arg_val, '(unnamed)') if isinstance(arg_val, check_type) else arg_val for arg_val in bound_args.arguments['args']) def _check_argument_units(args, defaults, dimensionality): """Yield arguments with improper dimensionality.""" for arg, val in args.items(): # Get the needed dimensionality (for printing) as well as cached, parsed version # for this argument. try: need, parsed = dimensionality[arg] except KeyError: # Argument did not have units specified in decorator continue if arg in defaults and (defaults[arg] is not None or val is None): check = val == defaults[arg] if np.all(check): continue # See if the value passed in is appropriate try: if val.dimensionality != parsed: yield arg, val, val.units, need # No dimensionality except AttributeError: # If this argument is dimensionless, don't worry if parsed != '': yield arg, val, 'none', need def _get_changed_version(docstring): """Find the most recent version in which the docs say a function changed.""" matches = re.findall(r'.. versionchanged:: ([\d.]+)', docstring) return max(matches) if matches else None def _check_units_outer_helper(func, *args, **kwargs): """Get dims and defaults from function signature and specified dimensionalities.""" # Match the signature of the function to the arguments given to the decorator sig = signature(func) bound_units = sig.bind_partial(*args, **kwargs) # Convert our specified dimensionality (e.g. "[pressure]") to one used by # pint directly (e.g. "[mass] / [length] / [time]**2). This is for both efficiency # reasons and to ensure that problems with the decorator are caught at import, # rather than runtime. dims = {name: (orig, units.get_dimensionality(orig.replace('dimensionless', ''))) for name, orig in bound_units.arguments.items()} defaults = {name: sig.parameters[name].default for name in sig.parameters if sig.parameters[name].default is not Parameter.empty} return sig, dims, defaults def _check_units_inner_helper(func, sig, defaults, dims, *args, **kwargs): """Check bound arguments for unit correctness.""" # Match all passed in value to their proper arguments so we can check units bound_args = sig.bind(*args, **kwargs) bad = list(_check_argument_units(bound_args.arguments, defaults, dims)) # If there are any bad units, emit a proper error message making it clear # what went wrong. if bad: msg = f'`{func.__name__}` given arguments with incorrect units: ' msg += ', '.join( f'`{arg}` requires "{req}" but given "{given}"' for arg, _, given, req in bad ) if 'none' in msg: if any(isinstance(x, for _, x, _, _ in bad): msg += ('\nA masked array `m` can be assigned a unit as follows:\n' ' from metpy.units import units\n' ' m = units.Quantity(m, "m/s")') else: msg += ('\nA xarray DataArray or numpy array `x` can be assigned a unit as ' 'follows:\n' ' from metpy.units import units\n' ' x = x * units("m/s")') msg += ('\nFor more information see the Units Tutorial: ' '') # If function has changed, mention that fact if func.__doc__: changed_version = _get_changed_version(func.__doc__) if changed_version: msg = ( f'This function changed in {changed_version}--double check ' 'that the function is being called properly.\n' ) + msg raise ValueError(msg) # Return the bound arguments for reuse return bound_args
[docs]def check_units(*units_by_pos, **units_by_name): """Create a decorator to check units of function arguments.""" def dec(func): sig, dims, defaults = _check_units_outer_helper(func, *units_by_pos, **units_by_name) @functools.wraps(func) def wrapper(*args, **kwargs): _check_units_inner_helper(func, sig, defaults, dims, *args, **kwargs) return func(*args, **kwargs) return wrapper return dec
[docs]def process_units( input_dimensionalities, output_dimensionalities, output_to=None, ignore_inputs_for_output=None ): """Wrap a non-Quantity-using function in base units to fully handle units.""" def dec(func): sig, dims, defaults = _check_units_outer_helper(func, **input_dimensionalities) @functools.wraps(func) def wrapper(*args, **kwargs): bound_args = _check_units_inner_helper(func, sig, defaults, dims, *args, **kwargs) # Determine unit(s) with which to wrap output (first, since we mutate the bound # args) if isinstance(output_dimensionalities, tuple): multiple_output = True outputs = output_dimensionalities else: multiple_output = False outputs = (output_dimensionalities,) output_control = [] for i, output in enumerate(outputs): convert_to = ( output_to if not multiple_output or output_to is None else output_to[i] ) # Find matching input, if it exists if convert_to is None: for name, (this_dim, _) in dims.items(): if ( this_dim == output and ( ignore_inputs_for_output is None or name not in ignore_inputs_for_output ) ): try: convert_to = bound_args.arguments[name].units except AttributeError: # We don't have units, so given prior check, is dimensionless convert_to = '' break output_control.append((_base_unit_of_dimensionality[output], convert_to)) # Convert all inputs as specified, assuming dimensionality is fine based on above _mutate_arguments(bound_args, units.Quantity, lambda val, _: val.to_base_units().m) # Evaluate inner calculation result = func(*bound_args.args, **bound_args.kwargs) # Wrap output if multiple_output: wrapped_result = [] for this_result, this_output_control in zip(result, output_control): q = units.Quantity(this_result, this_output_control[0]) if this_output_control[1] is not None: q =[1]) wrapped_result.append(q) return tuple(wrapped_result) else: q = units.Quantity(result, output_control[0][0]) if output_control[0][1] is not None: q =[0][1]) return q # Attach the unwrapped func for internal use wrapper._nounit = func return wrapper return dec
# Enable pint's built-in matplotlib support units.setup_matplotlib() del pint