NetworkData

../../_images/logo.png

NetworkData#

class fracability.Statistics.NetworkData(obj=None, use_survival=True, complete_only=True)#

Class used to represent fracture or fracture network data. It acts as a wrapper for the scipy CensoredData class

Parameters:

  • obj – fracture/fracture network object

  • use_survival – Use survival analysis to get the distribution. If false the whole dataset is used considering all fractures complete

  • complete_only – When not using survival, use only the complete length values

property b5: ndarray#

Calculate the sample 5th percentile of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample 5th percentile

property b95: ndarray#

Calculate the sample 95th percentile of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample 95th percentile

property censored_lengths: ndarray#

This property returns or sets the list of censored length data of the fracture network

Getter:

Return the list of censored data

Setter:

Set the list of censored data

Returns:

property censoring_percentage: float#

Percentage of censoring of ALl the input data (i.e. it ignores the complete_only flag) :return: Float. Censoring %

property data#

Property that returns or sets the CensoredData class of the fracture network :return:

property ecdf: ndarray#

Property that returns the empirical CDF of the input data (it ignores the complete_only flag but ) using Kaplan-Meier. :return: Numpy array of the calculated CDF values using KM

property esf: ndarray#

Property that returns the empirical SF of the ALL the input data (i.e. it ignores the complete_only flag) using Kaplan-Meier. :return: Numpy array of the calculated SF values using KM

property function_list: list#

Property that returns the list of available probability functions (pdf, cdf etc) :return:

property lengths: ndarray#

This property returns or sets the complete list of length data (censored and uncesored) for the fracture network

Getter:

Return the complete list of lengths

Setter:

Set the complete list of lengths

property mean: ndarray#

Calculate the sample mean of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample mean

property median: ndarray#

Calculate the sample median of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample median

property mode: tuple#

Calculate the sample mode of ALL the input data (i.e. it ignores the complete_only flag). :return: Tuple of the most frequent value(s)

property non_censored_lengths: ndarray#

This property returns or sets the list of non-censored length data of the fracture network

Getter:

Return the list of non-censored data

Setter:

Set the list of non-censored data

property std: ndarray#

Calculate the sample standard deviation of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample standard deviation

property total_n_fractures: int#

Total number of fractures of ALl the input data (i.e. it ignores the complete_only flag) :return: Int. Number of fractures

property var: ndarray#

Calculate the sample variance of ALL the input data (i.e. it ignores the complete_only flag). :return: Numpy array of the sample variance

Contents