# 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>`.
Attributes
----------
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(
autoconvert_offset_to_baseunit=True,
preprocessors=[
functools.partial(
re.sub,
r'(?<=[A-Za-z\)])(?![A-Za-z\)])(?<![0-9\-][eE])(?<![0-9\-])(?=[0-9\-])',
'**'
),
lambda string: string.replace('%', 'percent')
]
)
# Capture v0.10 NEP 18 warning on first creation
with warnings.catch_warnings():
warnings.simplefilter('ignore')
units.Quantity([])
# 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 = a.to(dest).magnitude
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 = np.ma.concatenate(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:`numpy.ma.MaskedArray` with units attached.
This is a thin wrapper around :func:`numpy.ma.masked_array` 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 `numpy.ma.masked_array`, optional
Returns
-------
`pint.Quantity`
"""
if data_units is None:
data_units = data.units
return units.Quantity(np.ma.masked_array(data, **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, np.ma.core.MaskedArray) 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: '
'https://unidata.github.io/MetPy/latest/tutorials/unit_tutorial.html')
# 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 = q.to(this_output_control[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 = q.to(output_control[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