from pyssem.model import Model
import json
import cProfile

!pip show pyssem

Name: pyssem
Version: 0.1.dev143
Summary: A detailed description of your project.
Home-page: 
Author: 
Author-email: Indigo Brownhall <indigo.brownhall.20@ucl.ac.uk>
License: MIT License
        
        Copyright (c) 2024 ARCLab
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Location: c:\users\it\anaconda3\envs\fspsim\lib\site-packages
Requires: numpy, pandas, scipy, setuptools, sympy, tqdm
Required-by: 

with open('example-sim-simple.json') as f:
  simulation_data = json.load(f)

scenario_props = simulation_data['scenario_properties']
# Create an instance of the pySSEM_model with the simulation parameters
model = Model(
      start_date=scenario_props["start_date"].split("T")[0],  # Assuming the date is in ISO format
      simulation_duration=scenario_props["simulation_duration"],
      steps=scenario_props["steps"],
      min_altitude=scenario_props["min_altitude"],
      max_altitude=scenario_props["max_altitude"],
      n_shells=scenario_props["n_shells"],
      launch_function=scenario_props["launch_function"],
      integrator=scenario_props["integrator"],
      density_model=scenario_props["density_model"],
      LC=scenario_props["LC"],
      v_imp=scenario_props["v_imp"],
      launchfile = 'x0_launch_repeatlaunch_2018to2022_megaconstellationLaunches_Constellations.csv'
  )

species = simulation_data["species"]

species_list = model.configure_species(species)

results = model.run_model()

resetting species
Splitting species Su into 2 species with masses [260, 473].
Splitting species N into 4 species with masses [0.00141372, 0.567, 260, 473].
Added 2 active species, 4 debris species, and 0 rocket body species to the simulation.
Pairing the following active species to debris classes for PMD modeling...
['Su_260kg', 'Su_473kg']
Matched species Su_260kg to debris species N_260kg.
Matched species Su_473kg to debris species N_473kg.
    Name: N_0.00141372kg
    pmd_linked_species: []
    Name: N_0.567kg
    pmd_linked_species: []
    Name: N_260kg
    pmd_linked_species: ['Su_260kg']
    Name: N_473kg
    pmd_linked_species: ['Su_473kg']

Creating collision pairs:  24%|██▍       | 5/21 [00:07<00:26,  1.64s/it]

import matplotlib.pyplot as plt
import numpy as np

n_species = 15
shells_per_species = 40

# Set up the figure and axes
fig, axes = plt.subplots(3, 5, figsize=(20, 12))  # Adjust the size as needed

# Loop over each species
for species_index in range(n_species):
    ax = axes.flatten()[species_index]  # Get the current axis
    species_data = results.output.y[species_index*shells_per_species:(species_index+1)*shells_per_species]

    # Plot each shell for this species
    for shell_index in range(shells_per_species):
        ax.plot(results.output.t, species_data[shell_index], label=f'Shell {shell_index+1}')

    # Calculate and plot the sum of all shells for this species
    total = np.sum(species_data, axis=0)
    #ax.plot(output.t, total, label='Total', linestyle='--', color='black')

    # Setting titles and labels
    ax.set_title(f'{results.species_names[species_index]}')
    ax.set_xlabel('Time')
    ax.set_ylabel('Value')

    # You may need to adjust or disable the legend if it's too crowded
    # ax.legend()

plt.suptitle('Species 1 All Shells')  # Set a super title for the entire figure
plt.tight_layout(rect=[0, 0.03, 1, 0.95])  # Adjust layout to make room for the super title
plt.show()