Expand Up @@ -131,30 +131,6 @@ def wrapper(*args, **kwargs): _year_length = 365.242198781 _month_length = _year_length / 12
# -------------------------------------------------------------------- # _seterr = How floating-point errors in the results of arithmetic # operations are handled. These defaults are those of # numpy 1.10.1. # -------------------------------------------------------------------- _seterr = { "divide": "warn", "invalid": "warn", "over": "warn", "under": "ignore", }
# -------------------------------------------------------------------- # _seterr_raise_to_ignore = As _seterr but with any values of 'raise' # changed to 'ignore'. # -------------------------------------------------------------------- _seterr_raise_to_ignore = _seterr.copy()

for key, value in _seterr.items(): if value == "raise": _seterr_raise_to_ignore[key] = "ignore" # --- End: for
_empty_set = set()
_units_None = Units() Expand Down Expand Up @@ -5747,182 +5723,6 @@ def mask(self):
return mask_data_obj
@staticmethod def seterr(all=None, divide=None, over=None, under=None, invalid=None): """Set how floating-point errors in the results of arithmetic operations are handled.
The options for handling floating-point errors are:
============ ======================================================== Treatment Action ============ ======================================================== ``'ignore'`` Take no action. Allows invalid values to occur in the result data array.
``'warn'`` Print a `RuntimeWarning` (via the Python `warnings` module). Allows invalid values to occur in the result data array.
``'raise'`` Raise a `FloatingPointError` exception. ============ ========================================================
The different types of floating-point errors are:
================= ================================= ================= Error Description Default treatment ================= ================================= ================= Division by zero Infinite result obtained from ``'warn'`` finite numbers.
Overflow Result too large to be expressed. ``'warn'``
Invalid operation Result is not an expressible ``'warn'`` number, typically indicates that a NaN was produced.
Underflow Result so close to zero that some ``'ignore'`` precision was lost. ================= ================================= =================
Note that operations on integer scalar types (such as int16) are handled like floating point, and are affected by these settings.
If called without any arguments then the current behaviour is returned.
.. seealso:: `cf.Data.mask_fpe`, `mask_invalid`
:Parameters:
all: `str`, optional Set the treatment for all types of floating-point errors at once. The default is not to change the current behaviour.
divide: `str`, optional Set the treatment for division by zero. The default is not to change the current behaviour.
over: `str`, optional Set the treatment for floating-point overflow. The default is not to change the current behaviour.
under: `str`, optional Set the treatment for floating-point underflow. The default is not to change the current behaviour.
invalid: `str`, optional Set the treatment for invalid floating-point operation. The default is not to change the current behaviour.
:Returns:
`dict` The behaviour prior to the change, or the current behaviour if no new values are specified.
**Examples**
Set treatment for all types of floating-point errors to ``'raise'`` and then reset to the previous behaviours:
>>> cf.Data.seterr() {'divide': 'warn', 'invalid': 'warn', 'over': 'warn', 'under': 'ignore'} >>> old = cf.Data.seterr('raise') >>> cf.Data.seterr(**old) {'divide': 'raise', 'invalid': 'raise', 'over': 'raise', 'under': 'raise'} >>> cf.Data.seterr() {'divide': 'warn', 'invalid': 'warn', 'over': 'warn', 'under': 'ignore'}
Set the treatment of division by zero to ``'ignore'`` and overflow to ``'warn'`` without changing the treatment of underflow and invalid operation:
>>> cf.Data.seterr(divide='ignore', over='warn') {'divide': 'warn', 'invalid': 'warn', 'over': 'warn', 'under': 'ignore'} >>> cf.Data.seterr() {'divide': 'ignore', 'invalid': 'warn', 'over': 'ignore', 'under': 'ignore'}
Some examples with data arrays:
>>> d = cf.Data([0., 1]) >>> e = cf.Data([1., 2])
>>> old = cf.Data.seterr('ignore') >>> e/d <CF Data: [inf, 2.0] > >>> e**12345 <CF Data: [1.0, inf] >
>>> cf.Data.seterr(divide='warn') {'divide': 'ignore', 'invalid': 'ignore', 'over': 'ignore', 'under': 'ignore'} >>> e/d RuntimeWarning: divide by zero encountered in divide <CF Data: [inf, 2.0] > >>> e**12345 <CF Data: [1.0, inf] >
>>> old = cf.Data.mask_fpe(False) >>> cf.Data.seterr(over='raise') {'divide': 'warn', 'invalid': 'ignore', 'over': 'ignore', 'under': 'ignore'} >>> e/d RuntimeWarning: divide by zero encountered in divide <CF Data: [inf, 2.0] > >>> e**12345 FloatingPointError: overflow encountered in power
>>> cf.Data.mask_fpe(True) False >>> cf.Data.seterr(divide='ignore') {'divide': 'warn', 'invalid': 'ignore', 'over': 'raise', 'under': 'ignore'} >>> e/d <CF Data: [inf, 2.0] > >>> e**12345 <CF Data: [1.0, --] >
""" old = _seterr.copy()
if all: _seterr.update( {"divide": all, "invalid": all, "under": all, "over": all} ) if all == "raise": _seterr_raise_to_ignore.update( { "divide": "ignore", "invalid": "ignore", "under": "ignore", "over": "ignore", } )
else: if divide: _seterr["divide"] = divide if divide == "raise": _seterr_raise_to_ignore["divide"] = "ignore"
if over: _seterr["over"] = over if over == "raise": _seterr_raise_to_ignore["over"] = "ignore"
if under: _seterr["under"] = under if under == "raise": _seterr_raise_to_ignore["under"] = "ignore"
if invalid: _seterr["invalid"] = invalid if invalid == "raise": _seterr_raise_to_ignore["invalid"] = "ignore" # --- End: if
return old
# `arctan2`, AT2 seealso @daskified(_DASKIFIED_VERBOSE) @_inplace_enabled(default=False) Expand Down