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.
Changed in version 1.17.0: errstate
is also usable as a function decorator, saving a level of indentation if an entire function is wrapped.
Changed in version 2.0: errstate
is now fully thread and asyncio safe, but may not be entered more than once. It is not safe to decorate async functions using errstate
.
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’}.
Notes
For complete documentation of the types of floating-point exceptions and treatment options, see seterr
.
Examples
>>> import numpy as np >>> olderr = np.seterr(all='ignore') # Set error handling to known state.
>>> np.arange(3) / 0. array([nan, inf, inf]) >>> with np.errstate(divide='ignore'): ... np.arange(3) / 0. array([nan, inf, inf])
>>> np.sqrt(-1) np.float64(nan) >>> with np.errstate(invalid='raise'): ... np.sqrt(-1) Traceback (most recent call last): File "<stdin>", line 2, in <module> 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'} >>> olderr = np.seterr(**olderr) # restore original state
Methods
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