# Source code for mars.tensor.arithmetic.nan_to_num

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2020 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from ... import opcodes as OperandDef
from ..utils import infer_dtype
from ..core import Tensor
from .core import TensorUnaryOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode='unary')
class TensorNanToNum(TensorUnaryOp):
_op_type_ = OperandDef.NAN_TO_NUM
_func_name = 'nan_to_num'
[docs]@infer_dtype(np.nan_to_num)
def nan_to_num(x, copy=True, **kwargs):
"""
Replace nan with zero and inf with large finite numbers.
If `x` is inexact, NaN is replaced by zero, and infinity and -infinity
replaced by the respectively largest and most negative finite floating
point values representable by ``x.dtype``.
For complex dtypes, the above is applied to each of the real and
imaginary components of `x` separately.
If `x` is not inexact, then no replacements are made.
Parameters
----------
x : array_like
Input data.
copy : bool, optional
Whether to create a copy of `x` (True) or to replace values
in-place (False). The in-place operation only occurs if
casting to an array does not require a copy.
Default is True.
Returns
-------
out : Tensor
`x`, with the non-finite values replaced. If `copy` is False, this may
be `x` itself.
See Also
--------
isinf : Shows which elements are positive or negative infinity.
isneginf : Shows which elements are negative infinity.
isposinf : Shows which elements are positive infinity.
isnan : Shows which elements are Not a Number (NaN).
isfinite : Shows which elements are finite (not NaN, not infinity)
Notes
-----
Mars uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754). This means that Not a Number is not equivalent to infinity.
Examples
--------
>>> import mars.tensor as mt
>>> x = mt.array([mt.inf, -mt.inf, mt.nan, -128, 128])
>>> mt.nan_to_num(x).execute()
array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000,
-1.28000000e+002, 1.28000000e+002])
>>> y = mt.array([complex(mt.inf, mt.nan), mt.nan, complex(mt.nan, mt.inf)])
>>> mt.nan_to_num(y).execute()
array([ 1.79769313e+308 +0.00000000e+000j,
0.00000000e+000 +0.00000000e+000j,
0.00000000e+000 +1.79769313e+308j])
"""
op = TensorNanToNum(**kwargs)
ret = op(x)
if copy:
return ret
# set back, make sure x is a Tensor
if not isinstance(x, Tensor):
raise ValueError(f'`x` must be a Tensor, got {type(x)} instead')
x.data = ret.data
return x
```