numpy.seterrcall#
- numpy.seterrcall(func)[source]#
- 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:
- funccallable 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:
- hcallable, log instance or None
- The old error handler. 
 
 - See also - 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) <function err_handler at 0x...> >>> 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) <numpy.core.numeric.Log object at 0x...> >>> np.seterr(**save_err) {'divide': 'log', 'over': 'log', 'under': 'log', 'invalid': 'log'}