def rt2dt(array, units_in, units_out=None, dummy1=None):
'''Convert reference times to date-time objects
The returned array is always independent.
:Parameters:
array: numpy array-like
units_in: `Units`
units_out: *optional*
Ignored.
dummy1:
Ignored.
:Returns:
`numpy.ndarray`
An array of `cf.Datetime` objects with the same shape as
*array*.
'''
mask = None
if numpy_ma_isMA(array):
# num2date has issues if the mask is nomask
mask = array.mask
if mask is numpy_ma_nomask or not numpy_ma_is_masked(array):
array = array.view(numpy_ndarray)
units = units_in.units
calendar = getattr(units_in, 'calendar', 'standard')
array = cftime.num2date(array, units, calendar,
only_use_cftime_datetimes=True)
# array = units_in._utime.num2date(array)
if mask is not None:
array = numpy_ma_masked_where(mask, array)
ndim = numpy_ndim(array)
if mask is None:
# There is no missing data
return numpy_array(array, dtype=object)
# return numpy_vectorize(
# partial(dt2Dt, calendar=units_in._calendar),
# otypes=[object])(array)
else:
# There is missing data
if not ndim:
return numpy_ma_masked_all((), dtype=object)
else:
# array = numpy_array(array)
# array = numpy_vectorize(
# partial(dt2Dt, calendar=units_in._calendar),
# otypes=[object])(array)
return numpy_ma_masked_where(mask, array)
def pmax(x, y):
"""The element-wise maximum of two arrays.
:Parameters:
x: array-like
May be updated in place and should not be used again.
y: array-like
Will not be updated in place.
:Returns:
`numpy.ndarray`
"""
if numpy_ma_isMA(x):
if numpy_ma_isMA(y):
# x and y are both masked
z = numpy_maximum(x, y)
z = numpy_ma_where(x.mask & ~y.mask, y, z)
x = numpy_ma_where(y.mask & ~x.mask, x, z)
if x.mask is numpy_ma_nomask: # not numpy_any(x.mask):
x = numpy_array(x)
else:
# Only x is masked
z = numpy_maximum(x, y)
x = numpy_ma_where(x.mask, y, z)
if x.mask is numpy_ma_nomask: # not numpy_any(x.mask):
x = numpy_array(x)
elif numpy_ma_isMA(y):
# Only y is masked
z = numpy_maximum(x, y)
x = numpy_ma_where(y.mask, x, z)
if x.mask is numpy_ma_nomask: # not numpy_any(x.mask):
x = numpy_array(x)
else:
# x and y are both unmasked
if not numpy_ndim(x):
# Make sure that we have a numpy array (as opposed to,
# e.g. a numpy.float64)
x = numpy_asanyarray(x)
numpy_maximum(x, y, out=x)
return x
def pmin(x, y):
'''TODO
:Parameters:
x: `numpy.ndarray`
May be updated in place and should not be used again.
y: `numpy.ndarray`
Will not be updated in place.
:Returns:
out: `numpy.ndarray`
'''
if numpy_ma_isMA(x):
if numpy_ma_isMA(y):
# x and y are both masked
z = numpy_minimum(x, y)
z = numpy_ma_where(x.mask & ~y.mask, y, z)
x = numpy_ma_where(y.mask & ~x.mask, x, z)
if x.mask is numpy_ma_nomask:
x = numpy_array(x)
else:
# Only x is masked
z = numpy_minimum(x, y)
x = numpy_ma_where(x.mask, y, z)
if x.mask is numpy_ma_nomask:
x = numpy_array(x)
elif numpy_ma_isMA(y):
# Only y is masked
z = numpy_minimum(x, y)
x = numpy_ma_where(y.mask, x, z)
if x.mask is numpy_ma_nomask:
x = numpy_array(x)
else:
# x and y are both unmasked
if not numpy_ndim(x):
# Make sure that we have a numpy array (as opposed to,
# e.g. a numpy.float64)
x = numpy_asanyarray(x)
numpy_minimum(x, y, out=x)
return x
def psum(x, y):
"""Add two arrays element-wise.
If either or both of the arrays are masked then the output array is
masked only where both input arrays are masked.
:Parameters:
x: numpy array-like
*Might be updated in place*.
y: numpy array-like
Will not be updated in place.
:Returns:
`numpy.ndarray`
**Examples:**
>>> c = psum(a, b)
"""
if numpy_ma_isMA(x):
if numpy_ma_isMA(y):
# x and y are both masked
x_mask = x.mask
x = x.filled(0)
x += y.filled(0)
x = numpy_ma_array(x, mask=x_mask & y.mask, copy=False)
else:
# Only x is masked
x = x.filled(0)
x += y
elif numpy_ma_isMA(y):
# Only y is masked
x += y.filled(0)
else:
# x and y are both unmasked
x += y
return x
def double_precision(a):
"""Convert the input array to double precision.
:Parameters:
a: `numpy.ndarray`
:Returns:
`numpy.ndarray`
"""
char = a.dtype.char
if char == "f":
newtype = float
elif char == "i":
newtype = int
else:
return a
if numpy_ma_isMA(a):
return a.astype(newtype)
else:
return a.astype(newtype, copy=False)