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fix bug of cut_templates #44

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ab70aba
fix bug of cut_templates
Aug 6, 2025
d57e869
update merge daily waveform templates
Aug 14, 2025
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43 changes: 37 additions & 6 deletions examples/california/cut_templates_cc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,12 @@ def fillin_missing_picks(picks, events, stations, config):
pivoted = picks.pivot(index=["event_index", "station_id"], columns="phase_type", values="traveltime")
pivoted.columns.name = None
pivoted = pivoted.reset_index()

# in case no P picks or S picks
if "P" not in pivoted.columns:
pivoted["P"] = np.nan
if "S" not in pivoted.columns:
pivoted["S"] = np.nan

pivoted["P_pred"] = np.where(pivoted["P"].isna(), pivoted["S"] / vp_vs_ratio, pivoted["P"])
pivoted["S_pred"] = np.where(pivoted["S"].isna(), pivoted["P"] * vp_vs_ratio, pivoted["S"])
Expand Down Expand Up @@ -407,12 +413,33 @@ def cut_templates(jdays, root_path, region, config, bucket, protocol, token):
config["zlim_km"] = (zmin, zmax)

# %% Eikonal for 1D velocity model
zz = [0.0, 5.5, 16.0, 32.0]
vp = [5.5, 5.5, 6.7, 7.8]
# zz = [0.0, 5.5, 16.0, 32.0]
# vp = [5.5, 5.5, 6.7, 7.8]
# zz = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 30]
# vp = [4.74, 5.01, 5.35, 5.71, 6.07, 6.17, 6.27, 6.34, 6.39, 7.8]
vp_vs_ratio = 1.73
vs = [v / vp_vs_ratio for v in vp]
# vs = [v / vp_vs_ratio for v in vp]
# Mendocino velocity in Clara's paper, the depth is the top of the layer corresponding to the velocity
zz = [0.0000, 0.6000, 1.2000, 1.8000, 2.4000,
3.0000, 3.6000, 4.2000, 4.8000, 5.4000,
6.0000, 8.0000, 10.000, 12.000, 14.000,
16.000, 18.000, 20.000, 22.000, 24.000,
26.000, 28.000, 30.000, 32.000, 34.000,
36.000, 38.000, 40.000, 60.000]

vp = [3.5000, 3.7214, 3.9429, 4.1643,
4.3857, 4.6071, 4.8286, 5.0500, 5.1124,
5.1747, 5.2371, 5.4449, 5.6528, 5.8607,
6.0685, 6.2764, 6.4843, 6.6921, 6.9000,
7.9000, 7.9000, 7.9000, 7.9000, 7.9000,
7.9000, 7.9000, 7.9000, 7.9000, 7.9000]

vs = [2.0208, 2.1486, 2.2765, 2.4043,
2.5322, 2.6600, 2.7879, 2.9157, 2.9517,
2.9877, 3.0237, 3.1437, 3.2637, 3.3838,
3.5038, 3.6238, 3.7438, 3.8638, 3.9838,
4.5612, 4.5612, 4.5612, 4.5612, 4.5612,
4.5612, 4.5612, 4.5612, 4.5612, 4.5612]
h = 0.3

if os.path.exists(f"{root_path}/{region}/obspy/velocity.csv"):
Expand Down Expand Up @@ -476,15 +503,19 @@ def cut_templates(jdays, root_path, region, config, bucket, protocol, token):
# events = pd.read_csv("adloc_events.csv", parse_dates=["time"])
if protocol == "file":
events = pd.read_csv(
f"{root_path}/{data_path}/{year:04d}/adloc_events_{jday:03d}.csv", parse_dates=["time"]
f"{root_path}/{data_path}/{year:04d}/adloc_events_{jday:03d}.csv", parse_dates=["time"],
# f"{root_path}/{data_path}/{year:04d}/ransac_events_{jday:03d}.csv",
parse_dates=["time"],
# parse_dates=["time"],
)
else:
with fs.open(f"{bucket}/{data_path}/{year:04d}/adloc_events_{jday:03d}.csv", "r") as fp:
# with fs.open(f"{bucket}/{data_path}/{year:04d}/ransac_events_{jday:03d}.csv", "r") as fp:
events = pd.read_csv(fp, parse_dates=["time"])


# avoid empty events dataframe
if len(events) == 0:
print(f"No events for {year:04d}-{jday:03d}")
continue
# # ############### DEBUG ###############
# events = events[
# (events["latitude"] >= minlat)
Expand Down
37 changes: 31 additions & 6 deletions examples/california/cut_templates_merge.py
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Original file line number Diff line number Diff line change
Expand Up @@ -247,12 +247,31 @@ def process_day(year_jday):

events_["latitude"] = events_["latitude"].astype(float)
events_["longitude"] = events_["longitude"].astype(float)
events_ = events_[
(events_["latitude"] > config["minlatitude"])
& (events_["latitude"] < config["maxlatitude"])
& (events_["longitude"] > config["minlongitude"])
& (events_["longitude"] < config["maxlongitude"])
]

# the following filter cannot effectively remove the horizontal boundary events
# events_ = events_[
# (events_["latitude"] > config["minlatitude"])
# & (events_["latitude"] < config["maxlatitude"])
# & (events_["longitude"] > config["minlongitude"])
# & (events_["longitude"] < config["maxlongitude"])
# ]

# remove horizontal boundary events
# filtering by x_km and y_km is better than by latitude and longitude
lon0 = (config["minlongitude"] + config["maxlongitude"]) / 2
lat0 = (config["minlatitude"] + config["maxlatitude"]) / 2
proj = Proj(f"+proj=aeqd +lon_0={lon0} +lat_0={lat0} +units=km")
events_[["x_km", "y_km"]] = events_.apply(
lambda x: pd.Series(proj(longitude=x.longitude, latitude=x.latitude)), axis=1
)
xmin, ymin = proj(config["minlongitude"], config["minlatitude"])
xmax, ymax = proj(config["maxlongitude"], config["maxlatitude"])
zmin, zmax = config["mindepth"], config["maxdepth"]
idx = (events_["y_km"] > ymin)
idx &= (events_["y_km"] < ymax)
idx &= (events_["x_km"] > xmin)
idx &= (events_["x_km"] < xmax)
events_ = events_[idx]

picks_["year"] = year
picks_["jday"] = jday
Expand Down Expand Up @@ -318,6 +337,9 @@ def process_day(year_jday):
+ picks["idx_eve"].astype(str).str.zfill(6)
)
events["idx_eve"] = np.arange(len(events))
# keep the original event index and new idx_eve
# important for tracking the events
events[["event_index", "idx_eve"]].to_csv(f"{root_path}/{result_path}/events_index_pair.csv", index=False)
events["event_index"] = np.arange(len(events))
print(f"events: {len(events):,} ")
print(events.iloc[:5])
Expand Down Expand Up @@ -438,6 +460,9 @@ def process_day(year_jday):
fs.put(f"{root_path}/{result_path}/config.json", f"{bucket}/{folder}/config.json")
print(f"{root_path}/{result_path}/pairs.txt -> {bucket}/{folder}/pairs.txt")
fs.put(f"{root_path}/{result_path}/pairs.txt", f"{bucket}/{folder}/pairs.txt")
# upload the event index pair file
print(f"{root_path}/{result_path}/events_index_pair.csv -> {bucket}/{folder}/events_index_pair.csv")
fs.put(f"{root_path}/{result_path}/events_index_pair.csv", f"{bucket}/{folder}/events_index_pair.csv")
# print(f"{root_path}/{result_path}/template.dat -> {bucket}/{folder}/template.dat")
# fs.put(f"{root_path}/{result_path}/template.dat", f"{bucket}/{folder}/template.dat")
# print(f"{root_path}/{result_path}/traveltime.dat -> {bucket}/{folder}/traveltime.dat")
Expand Down