1jx6 d Z ddlZddlZddlZddlmZ ddlmZm Z m
Z
m Z m Z m
Z
mZmZmZmZmZmZ ddlmZ g dZe e
e e e
ed Zd
e D Z ed dd Z ed d
Z ed d Z ed d Z ed d Z ed d Z G d d Z e Z ed G d dej! Z"d Z# e# ej$ dd Z% ed ej& d Z'dS ) z}
Functions for changing global ufunc configuration
This provides helpers which wrap `umath.geterrobj` and `umath.seterrobj`
N )
set_module ) UFUNC_BUFSIZE_DEFAULT
ERR_IGNOREERR_WARN ERR_RAISEERR_CALL ERR_PRINTERR_LOG ERR_DEFAULTSHIFT_DIVIDEBYZEROSHIFT_OVERFLOWSHIFT_UNDERFLOW
SHIFT_INVALID)umath)seterrgeterr
setbufsize
getbufsize
seterrcall
geterrcallerrstate_no_nep50_warning)ignorewarnraisecallprintlogc i | ]\ }}|| S r" ).0keyvalues O/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/core/_ufunc_config.py
r' s >>>zsEs>>> numpyc t j }t }|
| p|d }|
| p|d }|
| p|d }|
| p|d }t | t z t | t
z z t | t z z t | t z z }||d< t j | |S )a
Set how floating-point errors are handled.
Note that operations on integer scalar types (such as `int16`) are
handled like floating point, and are affected by these settings.
Parameters
----------
all : {'ignore', 'warn', 'raise', 'call', 'print', 'log'}, optional
Set treatment for all types of floating-point errors at once:
- ignore: Take no action when the exception occurs.
- warn: Print a `RuntimeWarning` (via the Python `warnings` module).
- raise: Raise a `FloatingPointError`.
- call: Call a function specified using the `seterrcall` function.
- print: Print a warning directly to ``stdout``.
- log: Record error in a Log object specified by `seterrcall`.
The default is not to change the current behavior.
divide : {'ignore', 'warn', 'raise', 'call', 'print', 'log'}, optional
Treatment for division by zero.
over : {'ignore', 'warn', 'raise', 'call', 'print', 'log'}, optional
Treatment for floating-point overflow.
under : {'ignore', 'warn', 'raise', 'call', 'print', 'log'}, optional
Treatment for floating-point underflow.
invalid : {'ignore', 'warn', 'raise', 'call', 'print', 'log'}, optional
Treatment for invalid floating-point operation.
Returns
-------
old_settings : dict
Dictionary containing the old settings.
See also
--------
seterrcall : Set a callback function for the 'call' mode.
geterr, geterrcall, errstate
Notes
-----
The floating-point exceptions are defined in the IEEE 754 standard [1]_:
- Division by zero: infinite result obtained from finite numbers.
- Overflow: result too large to be expressed.
- Underflow: result so close to zero that some precision
was lost.
- Invalid operation: result is not an expressible number, typically
indicates that a NaN was produced.
.. [1] https://en.wikipedia.org/wiki/IEEE_754
Examples
--------
>>> old_settings = np.seterr(all='ignore') #seterr to known value
>>> np.seterr(over='raise')
{'divide': 'ignore', 'over': 'ignore', 'under': 'ignore', 'invalid': 'ignore'}
>>> np.seterr(**old_settings) # reset to default
{'divide': 'ignore', 'over': 'raise', 'under': 'ignore', 'invalid': 'ignore'}
>>> np.int16(32000) * np.int16(3)
30464
>>> old_settings = np.seterr(all='warn', over='raise')
>>> np.int16(32000) * np.int16(3)
Traceback (most recent call last):
File "", line 1, in
FloatingPointError: overflow encountered in scalar multiply
>>> old_settings = np.seterr(all='print')
>>> np.geterr()
{'divide': 'print', 'over': 'print', 'under': 'print', 'invalid': 'print'}
>>> np.int16(32000) * np.int16(3)
30464
Ndivideoverunderinvalidr ) r geterrobjr _errdictr r r r seterrobj)allr+ r, r- r. pyvalsold maskvalues r& r r ! s Z _
F
((C
~%H
|!c&k }#s7|'Y 6"&884.N245/_46 7#}46I
F1I OF Jr( c ( t j d } d}i }| t z |z }t | |d< | t z |z }t | |d< | t
z |z }t | |d< | t z |z }t | |d< |S )a
Get the current way of handling floating-point errors.
Returns
-------
res : dict
A dictionary with keys "divide", "over", "under", and "invalid",
whose values are from the strings "ignore", "print", "log", "warn",
"raise", and "call". The keys represent possible floating-point
exceptions, and the values define how these exceptions are handled.
See Also
--------
geterrcall, seterr, seterrcall
Notes
-----
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> np.geterr()
{'divide': 'warn', 'over': 'warn', 'under': 'ignore', 'invalid': 'warn'}
>>> np.arange(3.) / np.arange(3.)
array([nan, 1., 1.])
>>> oldsettings = np.seterr(all='warn', over='raise')
>>> np.geterr()
{'divide': 'warn', 'over': 'raise', 'under': 'warn', 'invalid': 'warn'}
>>> np.arange(3.) / np.arange(3.)
array([nan, 1., 1.])
r r+ r, r- r. )r r/ r _errdict_revr r r )r5 maskresvals r& r r s H !!!$I D
C * *d
2C %CM &$
.C s#CK '4
/C $CL
%
-C!#&C N Jr( c | dk rt d| z | dk rt d| z | dz dk rt d| z t j }t }| |d< t j | |S )z{
Set the size of the buffer used in ufuncs.
Parameters
----------
size : int
Size of buffer.
g cAz Buffer size, %s, is too big. z Buffer size, %s, is too small. r z)Buffer size, %s, is not a multiple of 16.)
ValueErrorr r/ r r1 )sizer3 r4 s r& r r s d{{7$>??? axx9D@AAA byA~~DtKLLL
_
F
,,CF1I OF Jr( c 4 t j d S )z
Return the size of the buffer used in ufuncs.
Returns
-------
getbufsize : int
Size of ufunc buffer in bytes.
r r r/ r" r( r& r r s ? Q r( c B | bt | t j j sCt | d r$t | j t j j st
d t j }t }| |d< t j
| |S )a
Set the floating-point error callback function or log object.
There are two ways to capture floating-point error messages. The first
is to set the error-handler to 'call', using `seterr`. Then, set
the function to call using this function.
The second is to set the error-handler to 'log', using `seterr`.
Floating-point errors then trigger a call to the 'write' method of
the provided object.
Parameters
----------
func : callable f(err, flag) or object with write method
Function to call upon floating-point errors ('call'-mode) or
object whose 'write' method is used to log such message ('log'-mode).
The call function takes two arguments. The first is a string describing
the type of error (such as "divide by zero", "overflow", "underflow",
or "invalid value"), and the second is the status flag. The flag is a
byte, whose four least-significant bits indicate the type of error, one
of "divide", "over", "under", "invalid"::
[0 0 0 0 divide over under invalid]
In other words, ``flags = divide + 2*over + 4*under + 8*invalid``.
If an object is provided, its write method should take one argument,
a string.
Returns
-------
h : callable, log instance or None
The old error handler.
See Also
--------
seterr, geterr, geterrcall
Examples
--------
Callback upon error:
>>> def err_handler(type, flag):
... print("Floating point error (%s), with flag %s" % (type, flag))
...
>>> saved_handler = np.seterrcall(err_handler)
>>> save_err = np.seterr(all='call')
>>> np.array([1, 2, 3]) / 0.0
Floating point error (divide by zero), with flag 1
array([inf, inf, inf])
>>> np.seterrcall(saved_handler)
>>> np.seterr(**save_err)
{'divide': 'call', 'over': 'call', 'under': 'call', 'invalid': 'call'}
Log error message:
>>> class Log:
... def write(self, msg):
... print("LOG: %s" % msg)
...
>>> log = Log()
>>> saved_handler = np.seterrcall(log)
>>> save_err = np.seterr(all='log')
>>> np.array([1, 2, 3]) / 0.0
LOG: Warning: divide by zero encountered in divide
array([inf, inf, inf])
>>> np.seterrcall(saved_handler)
>>> np.seterr(**save_err)
{'divide': 'log', 'over': 'log', 'under': 'log', 'invalid': 'log'}
Nwritez%Only callable can be used as callbackr )
isinstance collectionsabcCallablehasattrrD r? r r/ r r1 )funcr3 r4 s r& r r s d
4 1I J Jg&& F tz;?+CDD F DEE E
_
F
,,CF1I OF Jr( c 4 t j d S )a
Return the current callback function used on floating-point errors.
When the error handling for a floating-point error (one of "divide",
"over", "under", or "invalid") is set to 'call' or 'log', the function
that is called or the log instance that is written to is returned by
`geterrcall`. This function or log instance has been set with
`seterrcall`.
Returns
-------
errobj : callable, log instance or None
The current error handler. If no handler was set through `seterrcall`,
``None`` is returned.
See Also
--------
seterrcall, seterr, geterr
Notes
-----
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> np.geterrcall() # we did not yet set a handler, returns None
>>> oldsettings = np.seterr(all='call')
>>> def err_handler(type, flag):
... print("Floating point error (%s), with flag %s" % (type, flag))
>>> oldhandler = np.seterrcall(err_handler)
>>> np.array([1, 2, 3]) / 0.0
Floating point error (divide by zero), with flag 1
array([inf, inf, inf])
>>> cur_handler = np.geterrcall()
>>> cur_handler is err_handler
True
r rB r" r( r& r r : s V ? Q r( c e Zd ZdS ) _unspecifiedN)__name__
__module__ __qualname__r" r( r& rM rM h s Dr( rM c * e Zd ZdZeddZd Zd ZdS )r a/
errstate(**kwargs)
Context manager for floating-point error handling.
Using an instance of `errstate` as a context manager allows statements in
that context to execute with a known error handling behavior. Upon entering
the context the error handling is set with `seterr` and `seterrcall`, and
upon exiting it is reset to what it was before.
.. versionchanged:: 1.17.0
`errstate` is also usable as a function decorator, saving
a level of indentation if an entire function is wrapped.
See :py:class:`contextlib.ContextDecorator` for more information.
Parameters
----------
kwargs : {divide, over, under, invalid}
Keyword arguments. The valid keywords are the possible floating-point
exceptions. Each keyword should have a string value that defines the
treatment for the particular error. Possible values are
{'ignore', 'warn', 'raise', 'call', 'print', 'log'}.
See Also
--------
seterr, geterr, seterrcall, geterrcall
Notes
-----
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> olderr = np.seterr(all='ignore') # Set error handling to known state.
>>> np.arange(3) / 0.
array([nan, inf, inf])
>>> with np.errstate(divide='warn'):
... np.arange(3) / 0.
array([nan, inf, inf])
>>> np.sqrt(-1)
nan
>>> with np.errstate(invalid='raise'):
... np.sqrt(-1)
Traceback (most recent call last):
File "", line 2, in
FloatingPointError: invalid value encountered in sqrt
Outside the context the error handling behavior has not changed:
>>> np.geterr()
{'divide': 'ignore', 'over': 'ignore', 'under': 'ignore', 'invalid': 'ignore'}
)r c " || _ || _ d S N)r kwargs)selfr rT s r& __init__zerrstate.__init__ s r( c t di | j | _ | j t urt | j | _ d S d S Nr" )r rT oldstater _Unspecifiedr oldcall)rU s r& __enter__zerrstate.__enter__ sC ----
9L ( (%di00DLLL ) (r( c p t di | j | j t urt | j d S d S rX )r rY r rZ r r[ )rU exc_infos r& __exit__zerrstate.__exit__ sC 9L ( ( t| $ $ $ $ $ ) (r( N)rN rO rP __doc__rZ rV r\ r_ r" r( r& r r o s[ 7 7r , 1 1 1
% % % % %r( r c L t t d g} t j | d S rS )r r
r r1 )defvals r& _setdefrc s$ #[$
7F OFr( r F)defaultc # K t d } dV t | dS # t | w xY w)z
Context manager to disable NEP 50 warnings. This context manager is
only relevant if the NEP 50 warnings are enabled globally (which is not
thread/context safe).
This warning context manager itself is fully safe, however.
TN)NO_NEP50_WARNINGsetreset)tokens r& r r s^
& &E&
u%%%%% u%%%%s > A)NNNNN)(r` collections.abcrF
contextlib contextvars_utilsr r r r r r r
r r r
r r r r __all__r0 itemsr8 r r r r r r rM rZ ContextDecoratorr rc
ContextVarrf contextmanagerr r" r( r& rt s
! ?>X^^-=-=>>> G_ _ _ _D G. . .b G 0 G
GY Y Yx G* * * Z |~~ GF% F% F% F% F%z* F% F% F%R *;)*=uMMM G & & & & &r(