Changes for page FDSN Guide

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43	43
44	44	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).
45	45
46		-== How to download waveform data ==
47	47
48		-{{code language="python"}}
49		-from obspy import UTCDateTime
50		-from obspy.clients.fdsn import Client
51		-
52		-# Initialize the FDSN client (you can also specify other data centers)
53		-client = Client("AUSPASS")
54		-
55		-# Event information
56		-network = "S1"
57		-station = "AUGRF"
58		-starttime = UTCDateTime("2021-09-21T23:15:53") # The time of the earthquake
59		-endtime = starttime + 360 # One hour of data after the earthquake
60		-
61		-# Download the MiniSEED data
62		-st = client.get_waveforms(network=network, station=station, location="*", channel="BHZ",
63		- starttime=starttime, endtime=endtime)
64		-# Save the stream to a MiniSEED file
65		-st.write("Woodspoint_2021.mseed", format="MSEED")
66		-print("Downloaded and saved the MiniSEED file.")
67		-{{/code}}
68		-
69		-== How to remove instrument response ==
70		-
71		-{{code language="python"}}
72		-from obspy import read
73		-from obspy.core.util import AttribDict
74		-
75		-# Load the MiniSEED file
76		-st = read("Woodspoint_2021.mseed")
77		-
78		-# Download the instrument response
79		-inv = client.get_stations(network=network, station=station, location="*",
80		- channel="*", starttime=starttime, endtime=endtime,
81		- level="response")
82		-
83		-# Remove the instrument response
84		-output = 'VEL' # Output unit ('VEL' = velocity (default), 'DISP' = displacement, 'ACC' = acceleration)
85		-
86		-for tr in st:
87		- tr.remove_response(inventory=inv, output=output, plot=True)
88		-
89		-# Save the corrected MiniSEED file
90		-st.write("Woodspoint_2021_corrected.mseed", format="MSEED")
91		-{{/code}}
92		-
93		-== How to apply a bandpass filter ==
94		-
95		-{{code language="python"}}
96		-from obspy import read
97		-
98		-# Load the MiniSEED file
99		-st = read("Woodspoint_2021.mseed")
100		-
101		-# Define the frequency band
102		-freq_min = 0.1 # Minimum frequency in Hz
103		-freq_max = 1.0 # Maximum frequency in Hz
104		-
105		-# Apply the bandpass filter
106		-for tr in st:
107		- tr.filter(type='bandpass', freqmin=freq_min, freqmax=freq_max)
108		-
109		-# Save the filtered MiniSEED file
110		-st.write("Woodspoint_2021_filtered.mseed", format="MSEED")
111		-{{/code}}
112		-
113		-== How to slice a waveform ==
114		-
115		-{{code language="python"}}
116		-from obspy import read, UTCDateTime, Stream # Importing Stream here
117		-
118		-# Load the filtered MiniSEED file
119		-st = read("Woodspoint_2021_filtered.mseed")
120		-
121		-# Define the time window for slicing
122		-slice_start = UTCDateTime("2021-09-21T23:20:00")
123		-slice_end = slice_start +10
124		-
125		-# Slice the waveform for each Trace in the Stream
126		-sliced_st = Stream() # Now Stream is defined
127		-for tr in st:
128		- sliced_tr = tr.slice(starttime=slice_start, endtime=slice_end)
129		- sliced_st.append(sliced_tr)
130		-
131		-# Save the sliced MiniSEED file
132		-sliced_st.write("Woodspoint_2021_filtered_sliced.mseed", format="MSEED")
133		-{{/code}}
134		-
135		-== How to save a waveform ==
136		-
137		-{{code language="python"}}
138		-# Save the sliced file as MiniSEED
139		-sliced_st.write("Woodspoint_2021_filtered_sliced.mseed", format="MSEED")
140		-
141		-# Or, save the sliced SAC file
142		-sliced_st.write("Woodspoint_2021_filtered_sliced.sac", format="SAC")
143		-{{/code}}
144		-
145		-== How to convert miniseed to sac ==
146		-
147		-{{code language="python"}}
148		-from obspy import read
149		-
150		-# Read the MiniSEED file
151		-st = read("Woodspoint_2021.mseed")
152		-
153		-# Take the first Trace from the Stream
154		-tr = st[0]
155		-
156		-# Save that Trace as a SAC file
157		-tr.write("Woodspoint_2021.sac", format="SAC")
158		-{{/code}}
159		-
160		-
161	161	= Earthquake Data =
162	162
163	163
	50	+
164	164	== How to download an Earthquake Catalog ==
165	165
166	166	{{code language="python"}}