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fit_function_to_data_points function

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Luis Aleixo 2021-09-01 16:00:20 +02:00
parent 5cdf955d58
commit d79469ffba
1 changed files with 84 additions and 8 deletions
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92
cara/plot_output.py
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@ -5,14 +5,90 @@ import csv
viral_loads = np.linspace(2, 12, 600)
#er_means = exposure_model_from_vl_talking(viral_loads)
er_means = exposure_model_from_vl_talking_new_points(viral_loads)
#er_means = exposure_model_from_vl_talking_new_points(viral_loads)
#er_means = exposure_model_from_vl_breathing(viral_loads)
#er_means = exposure_model_from_vl_talking_cn(viral_loads)
with open('data.csv', 'w', newline='') as csvfile:
fieldnames = ['viral load', 'emission rate']
thewriter = csv.DictWriter(csvfile, fieldnames=fieldnames)
thewriter.writeheader()
for i, vl in enumerate(viral_loads):
thewriter.writerow(
{'viral load': 10**vl, 'emission rate': er_means[i]})
# with open('data.csv', 'w', newline='') as csvfile:
# fieldnames = ['viral load', 'emission rate']
# thewriter = csv.DictWriter(csvfile, fieldnames=fieldnames)
# thewriter.writeheader()
# for i, vl in enumerate(viral_loads):
# thewriter.writerow(
# {'viral load': 10**vl, 'emission rate': er_means[i]})
def fit_function_to_data_points():
rna_copies = np.array([4.01624,
4.38393,
4.65486,
4.99213,
5.35982,
5.66392,
5.90444,
6.11178,
6.30254,
6.47947,
6.67023,
6.83057,
6.97433,
7.13467,
7.24802,
7.4056,
7.59912,
7.80646,
7.9834,
8.11057,
8.23774,
8.41467,
8.55843,
8.74918,
8.97311,
9.23022,
9.43756,
9.74166,
10.06235,
10.34987,
10.59038,
10.76455,
10.92489])
r_inf = np.array([0.004036804,
0.003189439,
0.003189439,
0.007288068,
0.013790595,
0.022835218,
0.03258901,
0.043190166,
0.05392952,
0.066083573,
0.080077827,
0.093079245,
0.108626396,
0.121773284,
0.135622068,
0.149616322,
0.171666,
0.192864676,
0.212510456,
0.228057606,
0.238658763,
0.254205913,
0.268905699,
0.284452849,
0.3,
0.315547151,
0.326995672,
0.338444194,
0.346641452,
0.353143979,
0.356391606,
0.357242608,
0.357242608])
result = np.polyfit(rna_copies, r_inf, 1)
print(result)
fit_function_to_data_points()