Initialize an inventory

This example shows four ways to initialise an inventory object using the Spatiocoexistence package. The first method involves defining the number of different species and dimensions. Secondly, by loading a file. Thirdly, by defining a structured NumPy array. Fourth, by copying the first inventory.

Necessary imports

from spatiocoexistence import Inventory
import numpy as np
from spatiocoexistence.data import inventory_file

1. Create a new random inventory from scratch. Individuals are placed according to the density of BCI randomly in the defined area. Also plot the inventory map afterwards.

inv1 = Inventory.from_random(n_species=5, dim_x=100, dim_y=100)
print(
    f"Random inventory: {inv1.data.shape[0]} individuals, fields: {inv1.data.dtype.names}"
)
inv1.plot_map()

Random inventory: 646 individuals, fields: ('x', 'y', 'dbh', 'species', 'status', 'CI_CS', 'CI_HS', 'CI_CS_d', 'CI_HS_d', 'CI_C', 'CI_H', 'CI_C_d', 'CI_H_d')

2. Load an inventory from a file. Exchange ‘inventory_file’ with the path to your file. Also plot the inventory map afterwards.

inv2 = Inventory.from_data(inventory_file)
print(
    f"Loaded inventory: {inv2.data.shape[0]} individuals, fields: {inv2.data.dtype.names}"
)
inv2.plot_map(scale=5, filter=2)

Loaded inventory: 20531 individuals, fields: ('x', 'y', 'dbh', 'species', 'status', 'CI_CS', 'CI_HS', 'CI_CS_d', 'CI_HS_d', 'CI_C', 'CI_H', 'CI_C_d', 'CI_H_d')

3. Initialize from a structured numpy array (must match expected dtype)

dtype = inv1.data.dtype
n_individuals = 2000
arr = np.zeros(n_individuals, dtype=dtype)
arr["x"] = np.linspace(0, 10, n_individuals)
arr["y"] = np.linspace(0, 10, n_individuals)
arr["dbh"] = np.random.uniform(1, 10, n_individuals)
arr["species"] = np.arange(n_individuals)
arr["status"] = np.ones(n_individuals)
inv3 = Inventory.from_data(arr)
print(
    f"Inventory from array: {inv3.data.shape[0]} individuals, fields: {inv3.data.dtype.names}"
)

Inventory from array: 2000 individuals, fields: ('x', 'y', 'dbh', 'species', 'status', 'CI_CS', 'CI_HS', 'CI_CS_d', 'CI_HS_d', 'CI_C', 'CI_H', 'CI_C_d', 'CI_H_d')

4. Copy from another Inventory object

inv4 = Inventory.from_data(inv1)
print(
    f"Copied inventory: {inv4.data.shape[0]} individuals, fields: {inv4.data.dtype.names}"
)

Copied inventory: 646 individuals, fields: ('x', 'y', 'dbh', 'species', 'status', 'CI_CS', 'CI_HS', 'CI_CS_d', 'CI_HS_d', 'CI_C', 'CI_H', 'CI_C_d', 'CI_H_d')