Random

normal(*args, **kwargs)	Overloaded function.
uniform(*args, **kwargs)	Overloaded function.

lue.framework.normal(*args, **kwargs)

Overloaded function.

1. normal(arg0: lue.lue_py.framework.PartitionedArray_uint8_2, arg1: object, arg2: object, arg3: object) -> object

2. normal(arg0: lue.lue_py.framework.PartitionedArray_uint32_2, arg1: object, arg2: object, arg3: object) -> object

3. normal(arg0: lue.lue_py.framework.PartitionedArray_uint64_2, arg1: object, arg2: object, arg3: object) -> object

4. normal(arg0: lue.lue_py.framework.PartitionedArray_int32_2, arg1: object, arg2: object, arg3: object) -> object

5. normal(arg0: lue.lue_py.framework.PartitionedArray_int64_2, arg1: object, arg2: object, arg3: object) -> object

6. normal(arg0: lue.lue_py.framework.PartitionedArray_float32_2, arg1: object, arg2: object, arg3: object) -> object

7. normal(arg0: lue.lue_py.framework.PartitionedArray_float64_2, arg1: object, arg2: object, arg3: object) -> object

8. normal(array_shape: tuple, dtype: object, mean: object, stddev: object, *, partition_shape: Optional[tuple] = None) -> object

   Create new array, filled with normally distributed random values

   param tuple array_shape:

   Shape of the array

   param numpy.dtype dtype:

   Type of the array elements

   param mean:

   Mean of normal distribution

   param stddev:

   Standard deviation of normal distribution

   param tuple partition_shape:

   Shape of the array partitions. When not passed in, a default shape will be used which might not result in the best performance and scalability.

   rtype:

   PartitionedArray specialization

   The type of the array returned depends on the rank of the array and the type of the array elements.

lue.framework.uniform(*args, **kwargs)

Overloaded function.

1. uniform(arg0: lue.lue_py.framework.PartitionedArray_uint8_2, arg1: object, arg2: object, arg3: object) -> object

2. uniform(arg0: lue.lue_py.framework.PartitionedArray_uint32_2, arg1: object, arg2: object, arg3: object) -> object

3. uniform(arg0: lue.lue_py.framework.PartitionedArray_uint64_2, arg1: object, arg2: object, arg3: object) -> object

4. uniform(arg0: lue.lue_py.framework.PartitionedArray_int32_2, arg1: object, arg2: object, arg3: object) -> object

5. uniform(arg0: lue.lue_py.framework.PartitionedArray_int64_2, arg1: object, arg2: object, arg3: object) -> object

6. uniform(arg0: lue.lue_py.framework.PartitionedArray_float32_2, arg1: object, arg2: object, arg3: object) -> object

7. uniform(arg0: lue.lue_py.framework.PartitionedArray_float64_2, arg1: object, arg2: object, arg3: object) -> object

8. uniform(array_shape: tuple, dtype: object, min_value: object, max_value: object, *, partition_shape: Optional[tuple] = None) -> object

   Create new array, filled with uniformly distributed random values

   param tuple array_shape:

   Shape of the array

   param numpy.dtype dtype:

   Type of the array elements

   param min_value:

   Minimum potentially generated value

   param max_value:

   Maximum potentially generated value

   param tuple partition_shape:

   Shape of the array partitions. When not passed in, a default shape will be used which might not result in the best performance and scalability.

   rtype:

   PartitionedArray specialization

   The type of the array returned depends on the rank of the array and the type of the array elements.