def inverse_transform(value, left_scale, right_scale, scale=0):
if left_scale is None or right_scale is None:
raise Exception('Left or Right scales cannot be None.')
if scale not in [0, 1]:
raise Exception('Scale must be 0 or 1.')
invalid_err = np.geterr().get('invalid')
np.seterr(invalid='ignore')
if scale == 0:
range_ = np.absolute(right_scale - left_scale)
translated_value = value * range_
if (left_scale > right_scale):
ret_val = left_scale - translated_value
else:
ret_val = left_scale + translated_value
else:
ls = np.log10(left_scale)
rs = np.log10(right_scale)
range_ = rs - ls
translated_value = value * range_
translated_value = np.round(translated_value, 3)
translated_value = translated_value + ls
ret_val = np.power(10, translated_value)
np.seterr(invalid=invalid_err)
return ret_val
###############################################################################
###############################################################################
python类geterr()的实例源码
def test_default(self):
err = np.geterr()
self.assertEqual(err, dict(
divide='warn',
invalid='warn',
over='warn',
under='ignore',
))
def test_set(self):
with np.errstate():
err = np.seterr()
old = np.seterr(divide='print')
self.assertTrue(err == old)
new = np.seterr()
self.assertTrue(new['divide'] == 'print')
np.seterr(over='raise')
self.assertTrue(np.geterr()['over'] == 'raise')
self.assertTrue(new['divide'] == 'print')
np.seterr(**old)
self.assertTrue(np.geterr() == old)
def setUp(self):
# Base data definition.
self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
self.err_status = np.geterr()
np.seterr(divide='ignore', invalid='ignore')
def geterr():
"""
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()
{'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
'under': 'ignore'}
>>> np.arange(3.) / np.arange(3.)
array([ NaN, 1., 1.])
>>> oldsettings = np.seterr(all='warn', over='raise')
>>> np.geterr()
{'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
>>> np.arange(3.) / np.arange(3.)
__main__:1: RuntimeWarning: invalid value encountered in divide
array([ NaN, 1., 1.])
"""
maskvalue = umath.geterrobj()[1]
mask = 7
res = {}
val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
res['divide'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_OVERFLOW) & mask
res['over'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_UNDERFLOW) & mask
res['under'] = _errdict_rev[val]
val = (maskvalue >> SHIFT_INVALID) & mask
res['invalid'] = _errdict_rev[val]
return res
def geterrcall():
"""
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
"""
return umath.geterrobj()[2]
