scipy.stats.CensoredData.left_censored#

classmethod CensoredData.left_censored(x, censored)[source]#

Create a CensoredData instance of left-censored data.

Parameters:

xarray_like: x is the array of observed data or measurements. x must be a one-dimensional sequence of finite numbers.
censoredarray_like of bool: censored must be a one-dimensional sequence of boolean values. If censored[k] is True, the corresponding value in x is left-censored. That is, the value x[k] is the upper bound of the true (but unknown) value.

Returns:

dataCensoredData: An instance of CensoredData that represents the collection of uncensored and left-censored values.

Examples

>>> from scipy.stats import CensoredData

Two uncensored values (0.12 and 0.033) and two left-censored values (both 1e-3).

>>> data = CensoredData.left_censored([0.12, 0.033, 1e-3, 1e-3],
...                                   [False, False, True, True])
>>> data
CensoredData(uncensored=array([0.12 , 0.033]),
left=array([0.001, 0.001]), right=array([], dtype=float64),
interval=array([], shape=(0, 2), dtype=float64))
>>> print(data)
CensoredData(4 values: 2 not censored, 2 left-censored)