Interactive Timelines (ipynb)

import pandas as pd
import altair as alt
alt.data_transformers.enable('default', max_rows=None)
import numpy as np

df = pd.read_csv('./lapalma.csv')

df['Datetime'] = (df['Date'] + ' ' + df['UTC time']).apply(pd.to_datetime, format='%Y-%m-%d %H:%M:%S')
df.head()

df.describe()

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

brush = alt.selection_interval(encodings=['x'])

bars = alt.Chart(df, width=700, height=150).mark_bar().encode(
    x=alt.X('Date:T', axis=alt.Axis(labelAngle=-45)),
    y=alt.Y('count():Q', title='Number of Events', axis=alt.Axis(labelAngle=-45)),
    color=alt.condition(brush, 'Depth:N', alt.value('lightgray'))
).properties(
    title='Earthquake event magnitude since 11 Sep 2021'
).add_selection(
    brush
)


detail_scatter = alt.Chart(df, width=700, height=350).mark_circle(opacity=0.3, strokeOpacity=1.0).encode(
    x=alt.X('Datetime:T', axis=alt.Axis(labelAngle=-45)),
    y=alt.Y('Depth(km):Q', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[45, 0])),
    color=alt.condition(brush, 'Depth:N', alt.value('lightgray'), scale=alt.Scale(scheme='category10')),
    size=alt.Size('Magnitude:Q', scale=alt.Scale(type='log', domain=[1.5,6], range=[2,200]))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).transform_filter(brush)


detail_scatter & bars

brush = alt.selection_interval(encodings=['x'])

bars = alt.Chart(df, width=700, height=150).mark_bar().encode(
    x=alt.X('Date:T', axis=alt.Axis(labelAngle=-45)),
    y=alt.Y('count():Q', title='Number of Events', axis=alt.Axis(labelAngle=-45)),
    color=alt.condition(brush, 'Depth:N', alt.value('lightgray'))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).add_selection(
    brush
)


detail_scatter = alt.Chart(df, width=700, height=500).mark_circle(opacity=0.3, strokeOpacity=1.0).encode(
    x=alt.X('Magnitude:Q', title='magnitude', axis=alt.Axis(labelAngle=-45), scale=alt.Scale(domain=[1.5, 6])),
    y=alt.Y('Depth(km):Q', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[45, 0])),
    color=alt.condition(brush, 'Depth:N', alt.value('lightgray')),
    size=alt.Size('Magnitude:Q', scale=alt.Scale(type='log', domain=[1.5,6], range=[2,200]))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).transform_filter(brush)


detail_scatter & bars

brush = alt.selection_interval(encodings=['x'])

total_width = 1200
scatter_height = 500

bars = alt.Chart(df, width=total_width, height=150).mark_bar().encode(
    x=alt.X('Date:T', axis=alt.Axis(labelAngle=-45)),
    y=alt.Y('count():Q', title='Number of Events', axis=alt.Axis(labelAngle=-45)),
    color=alt.condition(brush, 'Depth:N', alt.value('lightgray'))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).add_selection(
    brush
)


detail_scatter_long = alt.Chart(df, width=total_width/2, height=scatter_height).mark_circle(opacity=0.3, strokeOpacity=1.0).encode(
    x=alt.X('Longitude:Q', title='Longitude', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[-18, -17.7])),
    y=alt.Y('Depth(km):Q', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[45, 0])),
    size=alt.Size('Magnitude:Q', scale=alt.Scale(type='log', domain=[1.5,6], range=[2,200]))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).transform_filter(brush)

detail_scatter_lat = alt.Chart(df, width=total_width/2, height=scatter_height).mark_circle(opacity=0.3, strokeOpacity=1.0).encode(
    x=alt.X('Latitude:Q', title='Latitude', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[28.4, 28.7])),
    y=alt.Y('Depth(km):Q', axis=alt.Axis(labelAngle=-45),scale=alt.Scale(domain=[45, 0])),
    color=alt.Color('Magnitude:Q'),
    size=alt.Size('Magnitude:Q', scale=alt.Scale(type='log', domain=[1.5,5], range=[2,200]))
).properties(
    title='Number of Earthquakes per day since 11 Sep 2021'
).transform_filter(brush)


( detail_scatter_long | detail_scatter_lat ) & bars

import math
import matplotlib.pyplot as plt

angle_to_north = -25*(math.pi/180)
s = np.array([math.sin(angle_to_north), math.cos(angle_to_north)])

def project(sn, x):
    return sn * (np.dot(x, sn) / np.dot(sn, sn))
    

lat = np.linspace(-5, 5, 11)
lng = np.linspace(-5, 5, 11)
# full coorindate arrays
llng, llat = np.meshgrid(lng, lat, indexing='xy')

plt.scatter(llng, llat)
    
points = np.stack((llng.flatten(),llat.flatten()), axis=1)
ppts = [project(s,points[n,:]) for n in range(0,points.shape[0]) ]

llng, llat = np.stack(ppts, axis=1)

plt.scatter(llng, llat, color='r')

# remote geojson data object
url_geojson = 'https://raw.githubusercontent.com/mattijn/datasets/master/two_polygons.geo.json'
data_geojson_remote = alt.Data(url=url_geojson, format=alt.DataFormat(property='features',type='json'))

# chart object
alt.Chart(data_geojson_remote).mark_geoshape(
).encode(
    color="properties.name:N"
).project(
    type='identity', reflectY=True
)