.. _gallery:
=======
Gallery
=======
**Click on any image to see full size image and source code**
.. raw:: html
.. plot:: tutorial/code_snippets/reading_seismograms.py
:target: tutorial/code_snippets/reading_seismograms.html
:alt: Reading Seismograms
.. plot:: tutorial/code_snippets/waveform_plotting_tutorial_1.py
:target: tutorial/code_snippets/waveform_plotting_tutorial.html
:alt: Basic Plotting
.. plot:: tutorial/code_snippets/waveform_plotting_tutorial_2.py
:target: tutorial/code_snippets/waveform_plotting_tutorial.html#customized-plots
:alt: Customized Plots
.. plot:: tutorial/code_snippets/waveform_plotting_tutorial_3.py
:target: tutorial/code_snippets/waveform_plotting_tutorial.html#plotting-multiple-channels
:alt: Plotting multiple Channels
.. plot:: tutorial/code_snippets/waveform_plotting_tutorial_4.py
:target: tutorial/code_snippets/waveform_plotting_tutorial.html#creating-a-one-day-plot
:alt: Creating a One-Day Plot
.. plot:: tutorial/code_snippets/waveform_plotting_tutorial_6.py
:target: tutorial/code_snippets/waveform_plotting_tutorial.html#plotting-a-record-section
:alt: Plotting a Record Section
.. plot:: tutorial/code_snippets/filtering_seismograms.py
:target: tutorial/code_snippets/filtering_seismograms.html
:alt: Filtering Seismograms
.. plot:: tutorial/code_snippets/downsampling_seismograms.py
:target: tutorial/code_snippets/downsampling_seismograms.html
:alt: Downsampling Seismograms
.. plot:: tutorial/code_snippets/seismogram_envelopes.py
:target: tutorial/code_snippets/seismogram_envelopes.html
:alt: Seismogram Envelopes
.. plot:: tutorial/code_snippets/seismometer_correction_simulation_1.py
:target: tutorial/code_snippets/seismometer_correction_simulation.html
:alt: Seismometer Correction/Simulation
.. plot:: tutorial/code_snippets/seismometer_correction_simulation_5.py
:target: tutorial/code_snippets/seismometer_correction_simulation.html
:alt: Seismometer Correction/Simulation
.. plot:: tutorial/code_snippets/plotting_spectrograms.py
:target: tutorial/code_snippets/plotting_spectrograms.html
:alt: Plotting Spectrograms
.. plot:: tutorial/code_snippets/trigger_tutorial_classic_sta_lta.py
:target: tutorial/code_snippets/trigger_tutorial.html#trigger-examples
:alt: Classic Sta Lta
.. plot:: tutorial/code_snippets/trigger_tutorial_z_detect.py
:target: tutorial/code_snippets/trigger_tutorial.html#trigger-examples
:alt: Z-Detect
.. plot:: tutorial/code_snippets/trigger_tutorial_recursive_sta_lta.py
:target: tutorial/code_snippets/trigger_tutorial.html#trigger-examples
:alt: Recursive Sta Lta
.. plot:: tutorial/code_snippets/frequency_response.py
:target: tutorial/code_snippets/frequency_response.html
:alt: Poles and Zeros, Frequency Response
.. plot:: tutorial/code_snippets/beachball_plot.py
:target: tutorial/code_snippets/beachball_plot.html
:alt: Beachball Plot
.. plot:: tutorial/code_snippets/cartopy_plot_with_beachballs.py
:target: tutorial/code_snippets/cartopy_plot_with_beachballs.html
:alt: cartopy Plot with Beachballs
.. plot:: tutorial/code_snippets/cartopy_plot_with_beachballs2.py
:target: tutorial/code_snippets/cartopy_plot_with_beachballs.html
:alt: Second cartopy Plot with Beachballs
.. plot:: tutorial/code_snippets/cartopy_with_beachball_read_events.py
:target: tutorial/code_snippets/cartopy_plot_with_beachballs.html
:alt: cartopy Plot with Beachball read_events
.. plot:: tutorial/code_snippets/merging_seismograms.py
:target: tutorial/code_snippets/merging_seismograms.html
:alt: Merging Seismograms
.. plot:: tutorial/code_snippets/beamforming_fk_analysis_1.py
:target: tutorial/code_snippets/beamforming_fk_analysis.html
:alt: Beamforming - FK Analysis
.. plot:: tutorial/code_snippets/beamforming_fk_analysis_2.py
:target: tutorial/code_snippets/beamforming_fk_analysis.html
:alt: Beamforming - FK Analysis
.. plot:: tutorial/code_snippets/hierarchical_clustering.py
:target: tutorial/code_snippets/hierarchical_clustering.html
:alt: Hierarchical Clustering
.. plot:: tutorial/code_snippets/probabilistic_power_spectral_density.py
:target: tutorial/code_snippets/probabilistic_power_spectral_density.html
:alt: Visualizing Probabilistic Power Spectral Densities
.. plot:: tutorial/code_snippets/probabilistic_power_spectral_density3.py
:target: tutorial/code_snippets/probabilistic_power_spectral_density.html
:alt: Visualizing Probabilistic Power Spectral Densities
.. plot:: tutorial/code_snippets/probabilistic_power_spectral_density4.py
:target: tutorial/code_snippets/probabilistic_power_spectral_density.html
:alt: Visualizing Probabilistic Power Spectral Densities
.. plot:: tutorial/code_snippets/probabilistic_power_spectral_density5.py
:target: tutorial/code_snippets/probabilistic_power_spectral_density.html
:alt: Visualizing Probabilistic Power Spectral Densities
.. plot:: tutorial/code_snippets/array_response_function.py
:target: tutorial/code_snippets/array_response_function.html
:alt: Array Response Function
.. plot:: tutorial/code_snippets/continuous_wavelet_transform_obspy.py
:target: tutorial/code_snippets/continuous_wavelet_transform.html
:alt: Continuous Wavelet Transform (ObsPy)
.. plot:: tutorial/code_snippets/continuous_wavelet_transform_mlpy.py
:target: tutorial/code_snippets/continuous_wavelet_transform.html
:alt: Continuous Wavelet Transform (MLPY)
.. plot:: tutorial/code_snippets/time_frequency_misfit_ex1.py
:target: tutorial/code_snippets/time_frequency_misfit.html#plot-the-time-frequency-representation
:alt: Plot the Time Frequency Representation
.. plot:: tutorial/code_snippets/time_frequency_misfit_ex2.py
:target: tutorial/code_snippets/time_frequency_misfit.html#plot-the-time-frequency-misfits
:alt: Time Frequency Misfit
.. plot:: tutorial/code_snippets/plot_travel_times.py
:target: tutorial/code_snippets/travel_time.html#travel-time-plot
:alt: Travel Time Plot
.. plot:: tutorial/code_snippets/travel_time_cartesian_raypath.py
:target: tutorial/code_snippets/travel_time.html#cartesian-ray-paths
:alt: Cartesian Ray Paths
.. plot:: tutorial/code_snippets/travel_time_spherical_raypath.py
:target: tutorial/code_snippets/travel_time.html#spherical-ray-paths
:alt: Spherical Ray Paths
.. plot:: tutorial/code_snippets/plot_ray_paths.py
:target: tutorial/code_snippets/travel_time.html#ray-path-plot
:alt: Ray Path Plot
.. plot:: tutorial/code_snippets/travel_time_body_waves.py
:target: tutorial/code_snippets/travel_time.html#travel-time-body-waves
:alt: Body Wave Ray Paths
.. plot:: tutorial/code_snippets/xcorr_pick_correction.py
:target: tutorial/code_snippets/xcorr_pick_correction.html
:alt: Cross-Correlation Pick Correction
.. plot::
:target: tutorial/code_snippets/xcorr_detector.html
:alt: Cross-Correlation Detector
from obspy import read, Trace, UTCDateTime as UTC
from obspy.signal.cross_correlation import correlation_detector
stream = read('https://examples.obspy.org/NKC_PLN_ROHR.HHZ.2018.130.mseed')
stream.filter('highpass', freq=1, zerophase=True)
otimes = [UTC('2018-05-10 14:24:50'), UTC('2018-05-10 19:42:08')]
templates = []
for otime in otimes:
template = stream.select(station='NKC').slice(otime + 2, otime + 7)
template += stream.select(station='ROHR').slice(otime + 2, otime + 7)
template += stream.select(station='PLN').slice(otime + 6, otime + 12)
templates.append(template)
height = 0.5 # similarity threshold
distance = 10 # distance between detections in seconds
template_names = ['1st template', '2nd template']
detections, sims = correlation_detector(stream, templates, height, distance, plot=stream, template_names=template_names)
.. plot::
:target: packages/autogen/obspy.core.inventory.inventory.Inventory.plot.html
:alt: cartopy preview plot of Inventory class
from obspy import read_inventory
inv = read_inventory()
inv.plot(projection="local", color_per_network={'GR': 'blue', 'BW': 'green'})
.. plot::
:target: packages/autogen/obspy.core.inventory.network.Network.plot.html
:alt: cartopy preview plot of Network class
from obspy import read_inventory
net = read_inventory()[0]
net.plot(projection="ortho")
.. plot::
:target: packages/autogen/obspy.core.event.catalog.Catalog.plot.html
:alt: cartopy preview plot of Catalog class
from obspy import read_events
cat = read_events()
cat.plot()
.. plot::
:target: packages/autogen/obspy.core.inventory.inventory.Inventory.plot_response.html
:alt: Bode plot of Inventory class
from obspy import read_inventory
inv = read_inventory()
inv.plot_response(0.001, station="RJOB")
.. plot::
:target: packages/autogen/obspy.core.inventory.inventory.Inventory.plot_response.html
:alt: Bode plot of Inventory indicating different epochs
from obspy import read_inventory
inv = read_inventory()
inv = inv.select(station='RJOB', channel='EHZ')
inv.plot_response(0.001, label_epoch_dates=True)
.. plot::
:target: packages/autogen/obspy.core.inventory.response.Response.plot.html
:alt: Bode plot of Response class
from obspy import read_inventory
resp = read_inventory()[0][0][0].response
resp.plot(0.001, output="VEL")
.. plot::
:target: packages/autogen/obspy.signal.interpolation.plot_lanczos_windows.html
:alt: Plot the Lanczos windows.
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 12))
from obspy.signal.interpolation import plot_lanczos_windows
plot_lanczos_windows(a=20)
.. plot::
:target: packages/autogen/obspy.core.inventory.inventory.Inventory.plot.html
:alt: cartopy plot of station and event data together
from obspy import read_inventory, read_events
inv = read_inventory()
cat = read_events()
fig = inv.plot(show=False)
cat.plot(fig=fig)
.. plot::
:target: packages/autogen/obspy.signal.detrend.polynomial.html
:alt: Polynomial detrending
import obspy
from obspy.signal.detrend import polynomial
tr = obspy.read()[0].filter("highpass", freq=2)
tr.data += 6000 + 4 * tr.times() ** 2 - 0.1 * tr.times() ** 3 - \
0.00001 * tr.times() ** 5
polynomial(tr.data, order=3, plot=True)
.. plot::
:target: packages/autogen/obspy.core.event.event.Event.plot.html
:alt: Event plot
from obspy import read_events
event = read_events("/path/to/CMTSOLUTION")[0]
event.plot()
.. plot::
:target: packages/autogen/obspy.core.event.event.Event.plot.html
:alt: Event plot
from obspy import read_events
event = read_events("/path/to/CMTSOLUTION")[0]
event.plot(kind=[['global'], ['p_sphere', 'p_quiver']])
.. image:: /_static/sds_report.png
:target: packages/autogen/obspy.scripts.sds_html_report.html
:alt: SDS html report
:scale: 50%
Colormap comparison
===================
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import _colormap_plot_overview
_colormap_plot_overview()
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r
from obspy.imaging.cm import _colormap_plot_cwt
_colormap_plot_cwt([viridis, viridis_r, viridis_white, viridis_white_r])
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r
from obspy.imaging.cm import _colormap_plot_array_response
_colormap_plot_array_response([viridis, viridis_r, viridis_white, viridis_white_r])
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r
from obspy.imaging.cm import _colormap_plot_similarity
_colormap_plot_similarity([viridis, viridis_r, viridis_white, viridis_white_r])
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r
from obspy.imaging.cm import _colormap_plot_beamforming_time
_colormap_plot_beamforming_time([viridis, viridis_r, viridis_white, viridis_white_r])
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r
from obspy.imaging.cm import _colormap_plot_beamforming_polar
_colormap_plot_beamforming_polar([viridis, viridis_r, viridis_white, viridis_white_r])
.. plot::
:target: packages/autogen/obspy.imaging.cm.html
:alt: Colormap comparisons
from obspy.imaging.cm import viridis, viridis_r, viridis_white, viridis_white_r, pqlx
from obspy.imaging.cm import _colormap_plot_ppsd
_colormap_plot_ppsd([viridis, viridis_r, viridis_white, viridis_white_r, pqlx])
.. raw:: html