normal

hana_ml.algorithms.pal.random.normal(conn_context, mean=0, sigma=None, variance=None, num_random=100, seed=None, thread_ratio=None)

Draw samples from a normal distribution.

Parameters:
conn_contextConnectionContext

Database connection object.

meanfloat, optional

Mean value.

Defaults to 0.

sigmafloat, optional

Standard deviation. It cannot be used together with variance.

Defaults to 1.

variancefloat, optional

Variance. It cannot be used together with sigma.

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

Controls the proportion of available threads to use.

The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates up to all available threads.

Values between 0 and 1 will use that percentage of available threads.

Values outside the range [0, 1] tell PAL to heuristically determine the number of threads to use.

Defaults to 0.

Returns:
DataFrame

Dataframe containing the generated random samples, structured as follows:

  • ID, type INTEGER, ID column.

  • GENERATED_NUMBER, type DOUBLE, sample value.

Examples

Draw samples from a normal distribution.

>>> res = normal(conn_context=cc, mean=0, sigma=1, num_random=10)
>>> res.collect()
   ID  GENERATED_NUMBER
0   0          0.321078
1   1         -1.327626
2   2          0.798867
3   3         -0.116128
4   4         -0.213519
5   5          0.008566
6   6          0.251733
7   7          0.404510
8   8         -0.534899
9   9         -0.420968