fivpy.srs

Module to perform forest inventories using Simple Random Sampling

Module Contents

Classes

RandomSampling

Class to create a forest inventory object
class fivpy.srs.RandomSampling(dataframe, unit_area, sampling_area, significance=95, sampling_error=20, deg_free=None)[source]

Class to create a forest inventory object which uses Simple Random Sampling to estimate total wood volume

_add_vol(self)[source]
get_vol(self, beta_0=7.4e-05, beta_1=1.707348, beta_2=1.16873)[source]

Add a column with volume info to the dataframe

Parameters

  • beta_0 (float, optional) – first parameter. Defaults to 0.000074.

  • beta_1 (float, optional) – second parameter. Defaults to 1.707348.

  • beta_2 (float, optional) – third parameter. Defaults to 1.16873.

Returns

A DataFrame containing volume info.

Return type

dataframe (pd.DataFrame)

Examples

>>> instance.get_vol()
### To change the equation used to calculate volume
>>> instance.get_vol(beta_0=0.000025, beta_1=1.4568, beta_2=1.2563)
_get_deg_free(self)[source]
get_sample_size(self)[source]

Returns the estimated required sample size to perform the definitive inventory

Returns

the required sample size

Return type

sample size (int)

Examples

>>> instance.get_sample_size()
srs_inventory(self)[source]

Performs the Simple Random Sampling inventory

Raises

  • ValueError – If the required sample size is greater than the number

  • of units sampled, it is not possible to perform the inventory. –

Returns

A DataFrame containing the inventory results.

Return type

dataframe (pd.DataFrame)

Examples

>>> instance.srs_inventory()