numpy.errstate¶
- class numpy.errstate(**kwargs)[source]¶
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.
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
Notes
The with statement was introduced in Python 2.5, and can only be used there by importing it: from __future__ import with_statement. In earlier Python versions the with statement is not available.
For complete documentation of the types of floating-point exceptions and treatment options, see seterr.
Examples
>>> from __future__ import with_statement # use 'with' in Python 2.5 >>> 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. ... __main__:2: RuntimeWarning: divide by zero encountered in divide array([ NaN, Inf, Inf])
>>> np.sqrt(-1) 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 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() {'over': 'warn', 'divide': 'warn', 'invalid': 'warn', 'under': 'ignore'}