# Copyright (c) 2015,2017 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.
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.
"""
from __future__ import division
import functools
import logging
import warnings
import numpy as np
import pint
import pint.unit
log = logging.getLogger(__name__)
UndefinedUnitError = pint.UndefinedUnitError
DimensionalityError = pint.DimensionalityError
units = pint.UnitRegistry(autoconvert_offset_to_baseunit=True)
# For pint 0.6, this is the best way to define a dimensionless unit. See pint #185
units.define(pint.unit.UnitDefinition('percent', '%', (),
pint.converters.ScaleConverter(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
try:
units._units['meter']._aliases = ('metre', 'gpm')
units._units['gpm'] = units._units['meter']
except AttributeError:
log.warning('Failed to add gpm alias to meters.')
# 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 united arrays.
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 united arrays 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.')
# 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] = df[column].values * units(column_units[column])
else:
res[column] = df[column].values
return res
[docs]def concatenate(arrs, axis=0):
r"""Concatenate multiple values into a new unitized object.
This is essentially a unit-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 diff(x, **kwargs):
"""Calculate the n-th discrete difference along given axis.
Wraps :func:`numpy.diff` to handle units.
Parameters
----------
x : array-like
Input data
n : int, optional
The number of times values are differenced.
axis : int, optional
The axis along which the difference is taken, default is the last axis.
Returns
-------
diff : ndarray
The n-th differences. The shape of the output is the same as `a`
except along `axis` where the dimension is smaller by `n`. The
type of the output is the same as that of the input.
See Also
--------
numpy.diff
"""
ret = np.diff(x, **kwargs)
if hasattr(x, 'units'):
# Can't just use units because of how things like temperature work
it = x.flat
true_units = (next(it) - next(it)).units
ret = ret * true_units
return ret
[docs]def atleast_1d(*arrs):
r"""Convert inputs to arrays with at least one dimension.
Scalars are converted to 1-dimensional arrays, whilst other
higher-dimensional inputs are preserved. This is a thin wrapper
around `numpy.atleast_1d` to preserve units.
Parameters
----------
arrs : arbitrary positional arguments
Input arrays to be converted if necessary
Returns
-------
`pint.Quantity`
A single quantity or a list of quantities, matching the number of inputs.
"""
mags = [a.magnitude if hasattr(a, 'magnitude') else a for a in arrs]
orig_units = [a.units if hasattr(a, 'units') else None for a in arrs]
ret = np.atleast_1d(*mags)
if len(mags) == 1:
if orig_units[0] is not None:
return units.Quantity(ret, orig_units[0])
else:
return ret
return [units.Quantity(m, u) if u is not None else m for m, u in zip(ret, orig_units)]
[docs]def atleast_2d(*arrs):
r"""Convert inputs to arrays with at least two dimensions.
Scalars and 1-dimensional arrays are converted to 2-dimensional arrays,
whilst other higher-dimensional inputs are preserved. This is a thin wrapper
around `numpy.atleast_2d` to preserve units.
Parameters
----------
arrs : arbitrary positional arguments
Input arrays to be converted if necessary
Returns
-------
`pint.Quantity`
A single quantity or a list of quantities, matching the number of inputs.
"""
mags = [a.magnitude if hasattr(a, 'magnitude') else a for a in arrs]
orig_units = [a.units if hasattr(a, 'units') else None for a in arrs]
ret = np.atleast_2d(*mags)
if len(mags) == 1:
if orig_units[0] is not None:
return units.Quantity(ret, orig_units[0])
else:
return ret
return [units.Quantity(m, u) if u is not None else m for m, u in zip(ret, orig_units)]
[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 ``units`` argument, or if this is ``None``, the units on ``data``
are used.
Parameters
----------
data : array_like
The source data. If ``units`` is `None`, this should be a `pint.Quantity` with
the desired units.
data_units : str or `pint.Unit`
The units for the resulting `pint.Quantity`
**kwargs : Arbitrary keyword arguments passed to `numpy.ma.masked_array`
Returns
-------
`pint.Quantity`
"""
if data_units is None:
data_units = data.units
return units.Quantity(np.ma.masked_array(data, **kwargs), data_units)
def _check_argument_units(args, 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
# See if the value passed in is appropriate
try:
if val.dimensionality != parsed:
yield arg, val.units, need
# No dimensionality
except AttributeError:
# If this argument is dimensionless, don't worry
if parsed != '':
yield arg, 'none', need
[docs]def check_units(*units_by_pos, **units_by_name):
"""Create a decorator to check units of function arguments."""
try:
from inspect import signature
def dec(func):
# Match the signature of the function to the arguments given to the decorator
sig = signature(func)
bound_units = sig.bind_partial(*units_by_pos, **units_by_name)
# 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()}
@functools.wraps(func)
def wrapper(*args, **kwargs):
# 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, dims))
# If there are any bad units, emit a proper error message making it clear
# what went wrong.
if bad:
msg = '`{0}` given arguments with incorrect units: {1}.'.format(
func.__name__,
', '.join('`{}` requires "{}" but given "{}"'.format(arg, req, given)
for arg, given, req in bad))
if 'none' in msg:
msg += ('\nAny variable `x` can be assigned a unit as follows:\n'
' from metpy.units import units\n'
' x = x * units.meter / units.second')
raise ValueError(msg)
return func(*args, **kwargs)
return wrapper
# signature() only available on Python >= 3.3, so for 2.7 we just do nothing.
except ImportError:
def dec(func):
return func
return dec
try:
# Try to enable pint's built-in support
units.setup_matplotlib()
except (AttributeError, RuntimeError, ImportError): # Pint's not available, try our own
import matplotlib.units as munits
# Inheriting from object fixes the fact that matplotlib 1.4 doesn't
# TODO: Remove object when we drop support for matplotlib 1.4
class PintAxisInfo(munits.AxisInfo, object):
"""Support default axis and tick labeling and default limits."""
def __init__(self, units):
"""Set the default label to the pretty-print of the unit."""
super(PintAxisInfo, self).__init__(label='{:P}'.format(units))
# TODO: Remove object when we drop support for matplotlib 1.4
class PintConverter(munits.ConversionInterface, object):
"""Implement support for pint within matplotlib's unit conversion framework."""
def __init__(self, registry):
"""Initialize converter for pint units."""
super(PintConverter, self).__init__()
self._reg = registry
def convert(self, value, unit, axis):
"""Convert :`Quantity` instances for matplotlib to use."""
if isinstance(value, (tuple, list)):
return [self._convert_value(v, unit, axis) for v in value]
else:
return self._convert_value(value, unit, axis)
def _convert_value(self, value, unit, axis):
"""Handle converting using attached unit or falling back to axis units."""
if hasattr(value, 'units'):
return value.to(unit).magnitude
else:
return self._reg.Quantity(value, axis.get_units()).to(unit).magnitude
@staticmethod
def axisinfo(unit, axis):
"""Return axis information for this particular unit."""
return PintAxisInfo(unit)
@staticmethod
def default_units(x, axis):
"""Get the default unit to use for the given combination of unit and axis."""
if isinstance(x, (tuple, list)):
return getattr(x[0], 'units', 'dimensionless')
else:
return getattr(x, 'units', 'dimensionless')
# Register the class
munits.registry[units.Quantity] = PintConverter(units)
del munits
del pint