Input Data and Graphs

We first began by formatting and graphing the results of ETAS by proffessor John Rundle to serve as a baseline for our model and to compare our results with. We also wrote instructions on how to run ETAS and uploaded it to the repository

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Import Libraries

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import seaborn as sns

csv_file = 'Formatted_ETAS_Output.csv'
df = pd.read_csv(csv_file)

Data Table

df.head()

	Date	Time	Year	X	Y	Magnitude	Z
0	12/31/59	0:03:09.00	1960.002196	-119.0502	33.9790	6.50	8.2474
1	1/2/60	0:08:49.00	1960.006125	-115.6222	33.0793	4.25	7.9322
2	1/2/60	0:10:31.00	1960.007305	-115.6323	33.1220	3.03	8.4015
3	1/2/60	0:10:32.00	1960.007320	-115.5851	33.0745	3.03	7.9678
4	1/2/60	0:11:07.00	1960.007720	-115.6256	33.0290	3.08	7.9737

Scatter Plot

plt.figure(figsize=(10, 6))
sns.set_context("notebook", rc={"font.size": 14, "axes.labelsize": 16, "axes.titlesize": 18})
sns.scatterplot(data=df, x='Year', y='Magnitude', color = '#1f77b4', edgecolor='none', s=100, alpha=0.7)

plt.xlabel('Year')
plt.ylabel('Magnitude')
plt.title('Earthquake Magnitude over Time')

plt.grid(color='gray', linestyle='--', linewidth=0.5)
sns.despine()
plt.gca().patch.set_facecolor('none')
plt.gca().set_frame_on(True)
plt.xticks(rotation=45)

plt.grid(True)
plt.show()

Histogram

plt.figure(figsize=(10, 6))
sns.set_context("notebook", rc={"font.size": 14, "axes.labelsize": 16, "axes.titlesize": 18})
sns.histplot(data=df, x='Magnitude', bins=10, kde=False, color='#17becf', alpha=0.7, edgecolor='black')

plt.title('Magnitude Histogram')
plt.xlabel('Magnitude')
plt.ylabel('Frequency')

plt.grid(color='gray', linestyle='--', linewidth=0.5)
sns.despine()
plt.gca().patch.set_facecolor('none')
plt.gca().set_frame_on(True)

plt.grid(axis='x')
plt.show()

Scatter Plot

plt.figure(figsize=(10, 6))
scatter_plot = sns.scatterplot(data=df, x='X', y='Y', hue='Magnitude', palette='viridis', size='Magnitude', sizes=(10, 200))

plt.title('Earthquake Coordinates')
plt.xlabel('X')
plt.ylabel('Y')

plt.grid(color='gray', linestyle='--', linewidth=0.5)
sns.despine()
plt.gca().patch.set_facecolor('none')
plt.gca().set_frame_on(True)

sm = cm.ScalarMappable(cmap='viridis')
sm.set_array(df['Magnitude'])
cbar = plt.colorbar(scatter_plot.collections[0], aspect=40, ticks=range(int(df['Magnitude'].min()), int(df['Magnitude'].max())+1))
cbar.set_label('Magnitude')

plt.grid(True)
plt.show()