uniform
- hana_ml.algorithms.pal.random.uniform(conn_context, low=0, high=1, num_random=100, seed=None, thread_ratio=None)
-
Draw samples from a uniform distribution.
- Parameters:
-
- conn_contextConnectionContext
-
Database connection object.
- lowfloat, optional
-
The lower bound.
Defaults to 0.
- highfloat, optional
-
The upper bound.
Defaults to 1.
- num_randomint, optional
-
Specifies the number of random data to be generated.
Defaults to 100.
- seedint, optional
-
Indicates the seed used to initialize the random number generator:
-
0: Uses the system time.
-
Not 0: Uses the specified seed.
Note
When multithreading is enabled, the random number sequences of different runs might be different even if the SEED value remains the same.
Defaults to 0.
-
- thread_ratiofloat, optional
-
Adjusts the percentage of available threads to use, from 0 to 1. A value of 0 indicates the use of a single thread, while 1 implies the use of all possible current threads. Values outside the range will be ignored and this function heuristically determines the number of threads to use.
Defaults to 0.
- Returns:
-
- DataFrame
-
Dataframe containing the generated random samples.
Examples
Draw samples from a uniform distribution.
>>> res = uniform(conn_context=cc, low=-1, high=1, num_random=10) >>> res.collect() ID GENERATED_NUMBER 0 0 0.032920 1 1 0.201923 2 2 0.823313 3 3 -0.495260 4 4 -0.138329 5 5 0.677732 6 6 0.685200 7 7 0.363627 8 8 0.024849 9 9 -0.441779