files moved

'''

this script is processing the data from the hierarchical interface results

the values for nx, ny were obtained as the L value as given in all_curves.ipynb 

'''

import csv

import collections

import numpy as np

def sort_lil(lil : list[list]) -> list[list]:

    for sublist in lil:

        sublist.sort()

    lil.sort()

    return lil

def read_edge_list(edge_list_path : str) -> list[list]:

    edge_list = []

    with open(edge_list_path, "r") as file:

        for row in file:

            edge_str = row.split(" ")

            edge = [int(node) for node in edge_str]

            edge_list.append(edge)

    return edge_list

def get_posititons(node : int, nx : int, ny : int) -> list[int,int,int] :

    return get_xposition(node, nx), get_yposition(node, nx, ny), get_zposition(node, nx, ny)

def get_xposition(node : int, nx : int) -> int:

    return (node%nx)

def get_yposition(node : int, nx : int, ny : int) -> int:

    return ((node//nx)%ny)

def get_zposition(node : int, nx : int, ny : int) -> int:

    return (node// (nx*ny))

def get_node_property_dictionary(edge_list : list[list], nx : int, ny : int) -> dict:

    node_list = []

    for edge in edge_list:

        node_list.extend(edge)

    node_list = set(node_list)

    node_property_dict = {}

    for node in node_list:

        x,y,z = get_posititons(node, nx, ny) 

        node_property_dict[node] = {"xposition" : x, "yposition" : y, "zposition" : z}

    return node_property_dict

if __name__ == "__main__":

    edge_list = read_edge_list("data/edgelist_0_seed1000_0")

    sorted_edge_list = sort_lil(edge_list)

    print(np.sqrt(sorted_edge_list[0][1]))

    nx = 128

    ny = nx

    node_property_dict = get_node_property_dictionary(edge_list, nx, ny)

import matplotlib.pyplot as plt

import csv

with open("data/iv_seed1002_0") as file:

    reader = csv.reader(file, delimiter= ' ')

    data = [ row for row in reader]

x = [float(row[0]) for row in data[::500]]

y = [float(row[1]) for row in data[::500]]

fig, ax = plt.subplots()

plt.plot(x,y, ".")

plt.show()

print("cut-off prevention")