Visualization & Figure Creation (ipynb)

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
sns.set_theme(style="whitegrid")

df = pd.read_csv('./lapalma.csv')
df['Time'] = df['UTC time']
df.head()

df.describe()

df['Depth'] = 'Crustal (<20km)'
df.loc[df['Depth(km)'] >= 20, 'Depth'] = 'Mantle (>20km)'

cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)

g = sns.relplot(
    data=df,
    x="Longitude", y="Latitude",
    size="Magnitude", hue="Magnitude",
    col='Depth',
    palette=cmap,
    height=7,
    sizes=(1,150),
).set_titles("Reservoir: {col_name}")
_=g.despine(left=True, bottom=True)

g = sns.jointplot(x="Magnitude", y="Depth(km)", data=df,
                  kind='scatter', hue="Depth",
                  color="m", height=10)
g.plot_joint(sns.kdeplot, color="r", zorder=1, levels=15)
g.fig.axes[0].invert_yaxis();

df['timestamp'] = pd.to_numeric(pd.to_datetime(df['Date'] + ' ' + df['Time']))
df['Datetime'] = (df['Date'] + ' ' + df['Time']).apply(pd.to_datetime, format='%Y-%m-%d %H:%M:%S')
df.tail()

def get_numeric_datetime(dt: str):
    return pd.to_numeric(pd.to_datetime([dt]))[0]

sns.relplot(
    data=df[df['Date'] < '2022-01-01'],
    x="timestamp", y="Depth(km)",
    hue="Magnitude", size="Magnitude", 
    kind="scatter",palette=sns.color_palette("ch:s=.25,rot=-.25", as_cmap=True),
    height=8, aspect=2
)
plt.gca().invert_yaxis()
xticks = plt.gca().get_xticks()
new_xticks = [get_numeric_datetime('2021-09-11 03:18:42'),
    get_numeric_datetime('2021-09-19 14:13:00')]
new_xticks = np.append(new_xticks, xticks[2:-1])
# new_xticks = np.append(new_xticks, [get_numeric_datetime('2021-11-9 16:00:00')])

plt.gca().set_xticks(new_xticks)
xtick_labels = [pd.to_datetime(tm).strftime('%Y-%m-%d\n %H:%M:%S') for tm in new_xticks]
plt.gca().set_xticklabels(xtick_labels, rotation=50)



plt.title('Recorded seismicity since start of the La Palma volcanic crisis on 11 Sept 2021', fontdict=dict(fontsize=20))
plt.xlabel('Timeline', fontsize=16)
plt.ylabel('Event Depth (km)', fontsize=16);


plt.axvline(x=new_xticks[1], ymin=0, color='r')
plt.annotate('ERUPTION', (0.102, 0.13), rotation=90, xycoords='axes fraction', fontweight='bold', fontsize=16, color='r')
plt.annotate("Pre-Eruptive\nEarthquake Swarm", (0.0, 0.835), xycoords='axes fraction', horizontalalignment="center", bbox=dict(boxstyle="rarrow,pad=0.3", fc="lightblue", ec="b", lw=2))
plt.annotate("Crustal Reservoir\nFrequent Events", (0.15, 0.56), rotation=15, xycoords='axes fraction', horizontalalignment="center", bbox=dict(boxstyle="rarrow,pad=0.3", fc="lightblue", ec="b", lw=2))
plt.annotate("Mantle Reservoir\nHigh Magnitude Events", (0.22, 0.1), rotation=15, xycoords='axes fraction', horizontalalignment="center", bbox=dict(boxstyle="rarrow,pad=0.3", fc="lightblue", ec="b", lw=2));