Plotting the logo and the favicon

This example will go over the creation of the logo from the data in the example directory.

Warning

For some readon the logo is not rendered correctly in the gallery. To see the logo as generated by this script, please run it locally. Sorry aboot dat.

Loading all modules

import numpy as np
import obspy
import obsplotlib.plot as opl
import matplotlib.pyplot as plt

Loading data

event = obspy.read_events("DATA/CMTSOLUTION")[0]
raw = obspy.read("DATA/observed/traces/II.BFO.*.sac")
inv = obspy.read_inventory("DATA/observed/station.xml")

Before plotting anything let’s get some information about the event and the station and process the data

# Get event latitude and longitude for geometry evaluation
event_time = event.preferred_origin().time
event_latitude = event.preferred_origin().latitude
event_longitude = event.preferred_origin().longitude
event_depth = event.preferred_origin().depth  # in meters
event_name = 'C' + event.preferred_origin().resource_id.id.split('/')[-2]

Attach the event station geometry to the traces, important for rotation to RTZ

opl.attach_geometry(raw, event_latitude=event_latitude,
                    event_longitude=event_longitude, inv=inv)

Processing data

Here we’re just taking the data from the tutorial and are playing with the taper.

bandpass = [10, 50]
obs = opl.process(raw, inv=inv, remove_response=True, bandpass=bandpass,
                  starttime=event_time+800, npts=750, sampling_rate_in_hz=5
                  )

# Select a trace
network_str, station_str, component_str = "II", "BFO", "Z"
tr = obs.select(network=network_str, station=station_str,
                component=component_str)[0]

Finally we perform some fixes to really isolate the wavelet

# Tapering multiple time to attenuate boundaries
for i in range(10):
    tr.taper(type='cosine', max_percentage=0.4)

# Adding zero padding
tr.data = np.hstack((np.zeros(150), tr.data[:-75]))

# Offset the trace to be at the height of the 'T'
tr.data += 0.0000015

Plot Logo

We want the logo to be visible on both dark and light backgrounds. As it turns out, soft orange and soft blue are ideal colors for that

orange = np.array([232, 152, 59])/255
blue = np.array([65, 140, 216])/255

plt.figure(figsize=(2.0, 0.5))
ax = opl.trace(tr, plot_labels=False, lw=1.4, origin_time=event_time,
               solid_joinstyle='round', solid_capstyle='round', colors=[orange,],
               zorder=10)

# Remove bottom axis
ax.spines['bottom'].set_visible(False)

# Remove ticks
ax.tick_params(axis='x', labelbottom=False, bottom=False)

# Remove legend
ax.get_legend().set_visible(False)

# Remove xlabel
plt.xlabel('')

# Add label for
opl.plot_label(ax, 'Obsplotlib', location=13,
               dist=-0.41, box=False, fontsize='x-large', color=blue)
plt.subplots_adjust(left=0.35, top=0.95, bottom=0.05, right=1.0)
plt.show(block=False)

# To store as SVG
plt.savefig('logo.svg', transparent=True)

Plot Favicon

We want the logo to be visible on both dark and light backgrounds. As it turns out, soft orange and soft blue are ideal colors for that

orange = np.array([232, 152, 59])/255
blue = np.array([65, 140, 216])/255

plt.figure(figsize=(1.0, 1.0))


ax = opl.trace(tr, plot_labels=False, lw=4.0, origin_time=event_time,
               solid_joinstyle='round', solid_capstyle='round', colors=[orange,],
               zorder=10)
ax = opl.trace(tr, plot_labels=False, lw=4.0, origin_time=event_time-2,
               solid_joinstyle='round', solid_capstyle='round', colors=[blue,],
               zorder=10)

# Remove bottom axis
ax.spines['bottom'].set_visible(False)

# Remove ticks
ax.tick_params(axis='x', labelbottom=False, bottom=False)

# Remove legend
ax.get_legend().set_visible(False)

# Remove xlabel
plt.xlabel('')
plt.xlim(867, 905)
plt.subplots_adjust(left=0.0, top=1.0, bottom=0.0, right=1.0)
plt.show(block=False)

# To store as SVG
# plt.savefig('favicon.ico', format='PNG', transparent=True, dpi=32)