around(x, decimals=0)
This docstring was copied from numpy.around.
Some inconsistencies with the Dask version may exist.
For values exactly halfway between rounded decimal values, NumPy rounds to the nearest even value. Thus 1.5 and 2.5 round to 2.0, -0.5 and 0.5 round to 0.0, etc.
np.around
uses a fast but sometimes inexact algorithm to round floating-point datatypes. For positive :None:None:`decimals` it is equivalent to np.true_divide(np.rint(a * 10**decimals), 10**decimals)
, which has error due to the inexact representation of decimal fractions in the IEEE floating point standard and errors introduced when scaling by powers of ten. For instance, note the extra "1" in the following:
>>> np.round(56294995342131.5, 3) # doctest: +SKIP 56294995342131.51
If your goal is to print such values with a fixed number of decimals, it is preferable to use numpy's float printing routines to limit the number of printed decimals:
>>> np.format_float_positional(56294995342131.5, precision=3) # doctest: +SKIP '56294995342131.5'
The float printing routines use an accurate but much more computationally demanding algorithm to compute the number of digits after the decimal point.
Alternatively, Python's builtin round
function uses a more accurate but slower algorithm for 64-bit floating point values:
>>> round(56294995342131.5, 3) # doctest: +SKIP 56294995342131.5 >>> np.round(16.055, 2), round(16.055, 2) # equals 16.0549999999999997 # doctest: +SKIP (16.06, 16.05)
Input data.
Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point.
Alternative output array in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary. See ufuncs-output-type
for more details.
An array of the same type as a, containing the rounded values. Unless :None:None:`out` was specified, a new array is created. A reference to the result is returned.
The real and imaginary parts of complex numbers are rounded separately. The result of rounding a float is a float.
Evenly round to the given number of decimals.
ndarray.round
equivalent method
>>> np.around([0.37, 1.64]) # doctest: +SKIP array([0., 2.])This example is valid syntax, but we were not able to check execution
>>> np.around([0.37, 1.64], decimals=1) # doctest: +SKIP array([0.4, 1.6])This example is valid syntax, but we were not able to check execution
>>> np.around([.5, 1.5, 2.5, 3.5, 4.5]) # rounds to nearest even value # doctest: +SKIP array([0., 2., 2., 4., 4.])This example is valid syntax, but we were not able to check execution
>>> np.around([1,2,3,11], decimals=1) # ndarray of ints is returned # doctest: +SKIP array([ 1, 2, 3, 11])This example is valid syntax, but we were not able to check execution
>>> np.around([1,2,3,11], decimals=-1) # doctest: +SKIP array([ 0, 0, 0, 10])See :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.routines.round
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