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Iris Yoon irishryoon

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irishryoon / build_graph.py
Created Oct 8, 2021
Code for building artist graph in BFS way.
View build_graph.py
def continue_building_graph(G, queue, visited, ID_artists, max_count, sp):
"""Builds a weighted graph G using BFS.
Given a (possibly empty) graph G and a (possibly empty) queue,
(1) create nodes for new artists,
(2) create edges for new collaborations,
(3) update the 'albums' attribute of an edge to keep track of all albums accounted for.
In the very last step, find the weight of each edge as the number of albums
in the 'albums' attribute.
Furthermore, update the dictionary of artist ID and names.
View covid19.ipynb
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@irishryoon
irishryoon / fit_SIR_model.py
Last active Mar 26, 2020
an example SIR model fitting
View fit_SIR_model.py
from symfit import Parameter, variables, Fit, D, ODEModel
import numpy as np
# define number of susceptible population
n_susceptible = 195000
# Some data
data_I = np.array([1, 2, 11, 23, 36, 75, 104, 137, 166, 209, 313, 400, 496, 693, 914, 1635, 2391, 5213, 8054, 11293, 15157, 19938, 24336, 29010])
data_R = np.array([0, 0, 0, 0, 0, 1, 2, 5, 7, 11, 15, 21, 29, 39, 53, 71, 104, 152, 256, 417, 643, 946, 1345, 1831])
data_S = [n_susceptible - x - data_R[idx] for idx, x in enumerate(data_I)]