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Wiki source code of FDSN Guide

Version 3.1 by robert on 2025/03/24 10:35
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1 {{box cssClass="floatinginfobox" title="**Contents**"}}
2 {{toc/}}
3 {{/box}}
4
5 = [[How to Install ObsPy>>url:https://github.com/obspy/obspy/wiki#installation]] =
6
7 = [[Seed-Vault>>https://github.com/AuScope/seed-vault]] =
8
9 = Connecting to an FDSN Server =
10
11 == How to connect to AusPass with & without authenticated access ==
12
13
14 {{code language="python"}}
15 import obspy
16 from obspy.clients.fdsn import Client
17
18 # Initialize FDSN client for AusPass
19
20 # For open access data, no username or password is required.
21 client = Client('AUSPASS')
22
23 # To access restricted data, supply your username and password
24 # Replace 'Z1' and '12345' with your actual credentials
25 client = Client('AUSPASS', user='Z1', password='12345')
26 {{/code}}
27
28 = Station Metadata =
29
30 Information such as site locations, sensor and data logger types, response information, etc are in the station metadata. This can be accessed directly(link) or via the obspy get_stations (link) tool.
31
32
33 == How to download event, station, instrument response ==
34
35
36 {{code language="python"}}
37 import obspy
38 from obspy.clients.fdsn import Client
39
40 # Use AusPass client for station, waveform, and earthquake information
41 client = Client("AUSPASS")
42
43
44 # Download station information for AUMTC station in S1 network at the response level
45 inv = client.get_stations(network="S1", station="AUMTC", location="*",
46 channel="*", level="response")
47
48 # Inventory metadata is stored in a Inventory > Network > Station > Channel hierarchy
49
50 print(inv) #inventory level
51
52 print(inv[0]) # network level (the first network in the inventory)
53
54 print(inv[0][0]) # station level (the first station of the first network in the inventory)
55
56 print(inv[0][0][0]) # channel level (the first channel of the first station of the first network in the inventoy)
57
58 # you can also select items directly
59
60 print(inv.select(station='AUMTC',channel='HHZ')[0][0][0])
61
62 # instrument response is attached to a channel object
63
64 response = inv.select(station='AUMTC',channel='HHZ')[0][0][0].response
65 {{/code}}
66
67
68
69
70 = Waveform Data =
71
72 Waveform data (e.g. the actual seismic data) can be accessed directly (link) or via obspy's get_waveforms (link) tool. It can also be accessed via various tools such as seed-vault, pyweed, etc (add links).
73
74 == Downloading and Storing data ==
75
76 === How to download waveform data ===
77
78 {{code language="python"}}
79 from obspy import UTCDateTime
80 from obspy.clients.fdsn import Client
81
82 # Initialize the FDSN client (you can also specify other data centers)
83 client = Client("AUSPASS")
84
85 # Event information
86 network = "S1"
87 station = "AUGRF"
88 starttime = UTCDateTime("2021-09-21T23:15:53") # The time of the earthquake
89 endtime = starttime + 360 # One hour of data after the earthquake
90
91 # Download the MiniSEED data
92 st = client.get_waveforms(network=network, station=station, location="*", channel="BHZ",
93 starttime=starttime, endtime=endtime)
94 # Save the stream to a MiniSEED file
95 st.write("Woodspoint_2021.mseed", format="MSEED")
96 print("Downloaded and saved the MiniSEED file.")
97 {{/code}}
98
99 === How to download a LOT of waveform data ===
100
101 {{code language="python"}}
102 from obspy import UTCDateTime
103 from obspy.clients.fdsn import Client
104 import datetime
105
106 # Initialize client and set parameters
107 client = Client("IRIS")
108 start_date = UTCDateTime("2023-07-01")
109 end_date = UTCDateTime("2023-07-02")
110 network = "S1"
111 station = "AUMTS"
112 channel = "BHZ"
113
114 # Loop to download data one day at a time
115 while start_date <= end_date:
116 next_date = start_date + datetime.timedelta(days=1)
117 try:
118 st = client.get_waveforms(network, station, "*", channel, start_date, next_date)
119 st.write(f"{start_date.date}.mseed", format="MSEED")
120 except:
121 print(f"Failed for {start_date} to {next_date}")
122 start_date = next_date
123 {{/code}}
124
125 === How to store and archive waveform data in SeisComP Data Structure (SDS) ===
126
127 {{code language="python"}}
128 import os
129 from obspy import UTCDateTime, read
130 from obspy.clients.fdsn import Client
131
132 # Initialize the client
133 client = Client("AUSPASS") # Replace with the correct client endpoint if different
134
135 # Define event time and time window
136 event_time = UTCDateTime("2021-09-21T23:15:53")
137 starttime = event_time - 600 # 10 minutes before the event
138 endtime = event_time + 1800 # 30 minutes after the event
139
140 # Download the waveform data
141 st = client.get_waveforms(network="S1", station="AUMTS", location="*", channel="*", starttime=starttime, endtime=endtime)
142
143 # Create SDS structure: ROOT/YEAR/NET/STA/CHAN.TYPE/NET.STA.LOC.CHAN.YEAR.DAY
144 sds_root = "." # Replace with your desired directory
145
146 for tr in st:
147 net = tr.stats.network
148 sta = tr.stats.station
149 loc = tr.stats.location
150 chan = tr.stats.channel
151 year = str(tr.stats.starttime.year)
152 jday = str(tr.stats.starttime.julday).zfill(3)
153
154 sds_path = os.path.join(sds_root, year, net, sta, f"{chan}.D", f"{net}.{sta}.{loc}.{chan}.{year}.{jday}")
155
156 # Create directories if they don't exist
157 os.makedirs(os.path.dirname(sds_path), exist_ok=True)
158
159 # Save the trace as a MiniSEED file
160 tr.write(sds_path, format="MSEED")
161 {{/code}}
162
163 ==
164 Common Data Operations ==
165
166 === How to remove instrument response ===
167
168 {{code language="python"}}
169 from obspy import read
170 from obspy.core.util import AttribDict
171
172 # Load the MiniSEED file
173 st = read("Woodspoint_2021.mseed")
174
175 # Download the instrument response
176 inv = client.get_stations(network=network, station=station, location="*",
177 channel="*", starttime=starttime, endtime=endtime,
178 level="response")
179
180 # Remove the instrument response
181 output = 'VEL' # Output unit ('VEL' = velocity (default), 'DISP' = displacement, 'ACC' = acceleration)
182
183 for tr in st:
184 tr.remove_response(inventory=inv, output=output, plot=True)
185
186 # Save the corrected MiniSEED file
187 st.write("Woodspoint_2021_corrected.mseed", format="MSEED")
188 {{/code}}
189
190 === How to apply a bandpass filter ===
191
192 {{code language="python"}}
193 from obspy import read
194
195 # Load the MiniSEED file
196 st = read("Woodspoint_2021.mseed")
197
198 # Define the frequency band
199 freq_min = 0.1 # Minimum frequency in Hz
200 freq_max = 1.0 # Maximum frequency in Hz
201
202 # Apply the bandpass filter
203 for tr in st:
204 tr.filter(type='bandpass', freqmin=freq_min, freqmax=freq_max)
205
206 # Save the filtered MiniSEED file
207 st.write("Woodspoint_2021_filtered.mseed", format="MSEED")
208 {{/code}}
209
210 === How to slice a waveform ===
211
212 {{code language="python"}}
213 from obspy import read, UTCDateTime, Stream # Importing Stream here
214
215 # Load the filtered MiniSEED file
216 st = read("Woodspoint_2021_filtered.mseed")
217
218 # Define the time window for slicing
219 slice_start = UTCDateTime("2021-09-21T23:20:00")
220 slice_end = slice_start +10
221
222 # Slice the waveform for each Trace in the Stream
223 sliced_st = Stream() # Now Stream is defined
224 for tr in st:
225 sliced_tr = tr.slice(starttime=slice_start, endtime=slice_end)
226 sliced_st.append(sliced_tr)
227
228 # Save the sliced MiniSEED file
229 sliced_st.write("Woodspoint_2021_filtered_sliced.mseed", format="MSEED")
230 {{/code}}
231
232 === How to save a waveform ===
233
234 {{code language="python"}}
235 # Save the sliced file as MiniSEED
236 sliced_st.write("Woodspoint_2021_filtered_sliced.mseed", format="MSEED")
237
238 # Or, save the sliced SAC file
239 sliced_st.write("Woodspoint_2021_filtered_sliced.sac", format="SAC")
240 {{/code}}
241
242 === How to convert miniSEED to SAC ===
243
244 {{code language="python"}}
245 from obspy import read
246
247 # Read the MiniSEED file
248 st = read("Woodspoint_2021.mseed")
249
250 # Take the first Trace from the Stream
251 tr = st[0]
252
253 # Save that Trace as a SAC file
254 tr.write("Woodspoint_2021.sac", format="SAC")
255 {{/code}}
256
257
258 = Earthquake Data =
259
260 Earthquake data can be accessed directly or via ObsPy's get_events code
261
262 == How to download an Earthquake Catalog ==
263
264 {{code language="python"}}
265 from obspy.clients.fdsn import Client
266 from obspy import UTCDateTime
267
268 # Initialize the AusPass FDSN client
269 client = Client("AUSPASS")
270
271 # Define the time range for the earthquake catalog
272 start_time = UTCDateTime("2021-08-01")
273 end_time = UTCDateTime("2022-01-01") # End of year
274
275 # Define the geographic region (latitude and longitude for Woodspoint, Victoria, Australia)
276 latitude = -37.47
277 longitude = 146.10
278 max_radius = 5 # in degrees
279
280 # Download the earthquake catalog
281 catalog = client.get_events(starttime=start_time, endtime=end_time,
282 minmagnitude=2, latitude=latitude, longitude=longitude,
283 maxradius=max_radius)
284
285 # Save the catalog to a file (e.g., QuakeML format)
286 catalog.write("Woodspoint_earthquakes.xml", format="QUAKEML")
287 {{/code}}
288
289 == How to plot (Global) Earthquakes ==
290
291 {{code language="python"}}
292 from obspy import UTCDateTime
293 from obspy.clients.fdsn import Client
294
295 # Initialize FDSN client to connect to the IRIS data center
296 client = Client("IRIS")
297
298 # Set the time range for fetching earthquake data
299 # Start time: January 1, 2023
300 # End time: Current time
301 starttime = UTCDateTime("2023-01-01")
302 endtime = UTCDateTime()
303
304 # Fetch earthquake events with a minimum magnitude of 7
305 catalog = client.get_events(starttime=starttime, endtime=endtime, minmagnitude=7)
306 #client.get_events(). This function returns a Catalog object that contains a list of Event objects.
307 #Each Event object, in turn, has an Origins attribute that contains the depth information
308
309 # Plot the fetched earthquake data using an orthographic projection
310 catalog.plot(projection="ortho", title="Global Earthquakes with Magnitude >= 7 since 2023")
311 #catalog.plot(), ObsPy automatically uses the depth information to color the events in the plot
312 {{/code}}
313
314 == How to plot (Local) Earthquakes ==
315
316 {{code language="python"}}
317 from obspy import UTCDateTime
318 from obspy.clients.fdsn import Client
319
320 # Initialize FDSN client
321 client = Client("AUSPASS")
322
323 # Define time range
324 starttime = UTCDateTime("2023-01-01")
325 endtime = UTCDateTime()
326
327 # Latitude and longitude bounds for Australia
328 minlatitude = -44.0
329 maxlatitude = -10.0
330 minlongitude = 113.0
331 maxlongitude = 154.0
332
333 # Fetch event data for Australia with a minimum magnitude
334 catalog = client.get_events(starttime=starttime, endtime=endtime, minmagnitude=4,
335 minlatitude=minlatitude, maxlatitude=maxlatitude,
336 minlongitude=minlongitude, maxlongitude=maxlongitude)
337
338 # Plot the earthquakes
339 catalog.plot(projection="local", title="Australia Earthquakes", resolution="i")
340 {{/code}}
341
342