update phasenet plus

scripts/args.py

@@ -19,6 +19,9 @@ def parse_args():
     parser.add_argument("--num_nodes", type=int, default=1, help="number of nodes")
     parser.add_argument("--node_rank", type=int, default=0, help="node rank")
 
+    ## Model
+    parser.add_argument("--model", type=str, default="phasenet", help="model")
+
     ## ADLOC
     parser.add_argument("--iter", type=int, default=0, help="iteration")
 

scripts/merge_phasenet_picks.py

@@ -18,31 +18,31 @@
 from glob import glob
 
 
-def scan_csv(year, root_path, fs=None, bucket=None, protocol="file"):
+def scan_csv(year, root_path, region, model, fs=None, bucket=None, protocol="file"):
     # %%
     csv_list = []
     if protocol != "file":
-        jdays = fs.ls(f"{bucket}/{region}/{folder}/{year}")
+        jdays = fs.ls(f"{bucket}/{region}/{model}/picks/{year}")
     else:
-        jdays = os.listdir(f"{root_path}/{region}/phasenet/picks/{year}/")
+        jdays = os.listdir(f"{root_path}/{region}/{model}/picks/{year}/")
 
     for jday in jdays:
         if protocol != "file":
             csvs = fs.glob(f"{jday}/??/*.csv")
         else:
-            csvs = glob(f"{root_path}/{region}/phasenet/picks/{year}/{jday}/??/*.csv")
+            csvs = glob(f"{root_path}/{region}/{model}/picks/{year}/{jday}/??/*.csv")
 
         csv_list.extend([[year, jday, csv] for csv in csvs])
 
     csvs = pd.DataFrame(csv_list, columns=["year", "jday", "csv"])
-    csv_file = f"{root_path}/{region}/phasenet/csv_list_{year}.csv"
+    csv_file = f"{root_path}/{region}/{model}/csv_list_{year}.csv"
     csvs.to_csv(csv_file, index=False)
 
     return csv_file
 
 
 # %%
-def read_csv(rows, region, year, jday, root_path, fs=None, bucket=None):
+def read_csv(rows, region, model, year, jday, root_path, fs=None, bucket=None):
 
     picks = []
     for i, row in rows.iterrows():
@@ -58,15 +58,15 @@ def read_csv(rows, region, year, jday, root_path, fs=None, bucket=None):
 
     if len(picks) > 0:
         picks = pd.concat(picks, ignore_index=True)
-        if not os.path.exists(f"{root_path}/{region}/phasenet/{year}"):
-            os.makedirs(f"{root_path}/{region}/phasenet/{year}", exist_ok=True)
-        picks.to_csv(f"{root_path}/{region}/phasenet/{year}/{year}.{jday}.csv", index=False)
+        if not os.path.exists(f"{root_path}/{region}/{model}/{year}"):
+            os.makedirs(f"{root_path}/{region}/{model}/{year}", exist_ok=True)
+        picks.to_csv(f"{root_path}/{region}/{model}/{year}/{year}.{jday}.csv", index=False)
         # fs.put(
         #     f"{root_path}/{region}/phasenet/{year}/{jday}/{year}.{jday}.csv",
         #     f"{bucket}/{region}/phasenet_merged/{year}/{year}.{jday}.csv",
         # )
     else:
-        with open(f"{root_path}/{region}/phasenet/{year}/{year}.{jday}.csv", "w") as f:
+        with open(f"{root_path}/{region}/{model}/{year}/{year}.{jday}.csv", "w") as f:
             f.write("")
 
 
@@ -76,9 +76,9 @@ def read_csv(rows, region, year, jday, root_path, fs=None, bucket=None):
     args = parse_args()
     root_path = args.root_path
     region = args.region
+    model = args.model
 
-    data_path = f"{region}/phasenet/picks"
-    result_path = f"{region}/phasenet"
+    result_path = f"{region}/{model}"
 
     # %%
     # protocol = "gs"
@@ -88,32 +88,33 @@ def read_csv(rows, region, year, jday, root_path, fs=None, bucket=None):
     # fs = fsspec.filesystem(protocol, token=token)
 
     # %%
-    years = os.listdir(f"{root_path}/{region}/phasenet/picks")
+    # years = os.listdir(f"{root_path}/{region}/{model}/picks_{model}")
+    years = glob(f"{root_path}/{region}/{model}/picks_{model}/????/")
+    years = [year.rstrip("/").split("/")[-1] for year in years]
+    print(f"Years: {years}")
 
     for year in years:
 
-        csv_list = scan_csv(year, root_path)
+        csv_list = scan_csv(year, root_path, region, model)
 
         # %%
         csv_list = pd.read_csv(csv_list, dtype=str)
 
         # for jday, csvs in csv_list.groupby("jday"):
-        #     read_csv(csvs, region, year, jday, root_path)
+        #     read_csv(csvs, region, model, year, jday, root_path)
         #     raise
 
-        # ncpu = os.cpu_count()
-        ncpu = 64
+        ncpu = min(64, mp.cpu_count())
         print(f"Number of processors: {ncpu}")
         csv_by_jday = csv_list.groupby("jday")
         pbar = tqdm(total=len(csv_by_jday), desc=f"Loading csv files (year {year})")
 
-        # with mp.Pool(ncpu) as pool:
         ctx = mp.get_context("spawn")
         with ctx.Pool(ncpu) as pool:
             jobs = []
             for jday, csvs in csv_by_jday:
                 job = pool.apply_async(
-                    read_csv, (csvs, region, year, jday, root_path), callback=lambda _: pbar.update()
+                    read_csv, (csvs, region, model, year, jday, root_path), callback=lambda _: pbar.update()
                 )
                 jobs.append(job)
             pool.close()
@@ -126,11 +127,11 @@ def read_csv(rows, region, year, jday, root_path, fs=None, bucket=None):
         pbar.close()
 
     # %%
-    csvs = glob(f"{root_path}/{region}/phasenet/????/????.???.csv")
+    csvs = glob(f"{root_path}/{region}/{model}/????/????.???.csv")
     picks = []
     for csv in tqdm(csvs, desc="Merge csv files"):
         picks.append(pd.read_csv(csv, dtype=str))
     picks = pd.concat(picks, ignore_index=True)
-    picks.to_csv(f"{root_path}/{region}/phasenet/phasenet_picks.csv", index=False)
+    picks.to_csv(f"{root_path}/{region}/{model}/{model}_picks.csv", index=False)
 
 # %%

scripts/merge_phasenet_plus_picks.py

@@ -0,0 +1,134 @@
+# %%
+import json
+import multiprocessing as mp
+import os
+
+import fsspec
+import numpy as np
+import pandas as pd
+from tqdm import tqdm
+from args import parse_args
+from glob import glob
+
+
+def scan_csv(year, root_path, region, model, data="picks", fs=None, bucket=None, protocol="file"):
+    # %%
+    csv_list = []
+    if protocol != "file":
+        jdays = fs.ls(f"{bucket}/{region}/{model}/{data}_{model}/{year}")
+    else:
+        jdays = os.listdir(f"{root_path}/{region}/{model}/{data}_{model}/{year}/")
+
+    for jday in jdays:
+        if protocol != "file":
+            csvs = fs.glob(f"{jday}/??/*.csv")
+        else:
+            csvs = glob(f"{root_path}/{region}/{model}/{data}_{model}/{year}/{jday}/??/*.csv")
+
+        csv_list.extend([[year, jday, csv] for csv in csvs])
+
+    csvs = pd.DataFrame(csv_list, columns=["year", "jday", "csv"])
+    csv_file = f"{root_path}/{region}/{model}/{data}_list_{year}.csv"
+    csvs.to_csv(csv_file, index=False)
+
+    return csv_file
+
+
+# %%
+def read_csv(rows, region, model, data, year, jday, root_path, fs=None, bucket=None):
+
+    picks = []
+    for i, row in rows.iterrows():
+        # if fs.info(row["csv"])["size"] == 0:
+        #     continue
+        # with fs.open(row["csv"], "r") as f:
+        #     picks_ = pd.read_csv(f, dtype=str)
+        if os.path.getsize(row["csv"]) == 0:
+            continue
+        with open(row["csv"], "r") as f:
+            picks_ = pd.read_csv(f, dtype=str)
+        picks.append(picks_)
+
+    if len(picks) > 0:
+        picks = pd.concat(picks, ignore_index=True)
+        if not os.path.exists(f"{root_path}/{region}/{model}/{year}"):
+            os.makedirs(f"{root_path}/{region}/{model}/{year}", exist_ok=True)
+        picks.to_csv(f"{root_path}/{region}/{model}/{year}/{year}.{jday}.{data}.csv", index=False)
+        # fs.put(
+        #     f"{root_path}/{region}/phasenet/{year}/{jday}/{year}.{jday}.csv",
+        #     f"{bucket}/{region}/phasenet_merged/{year}/{year}.{jday}.csv",
+        # )
+    else:
+        with open(f"{root_path}/{region}/{model}/{year}/{year}.{jday}.{data}.csv", "w") as f:
+            f.write("")
+
+
+# %%
+if __name__ == "__main__":
+
+    args = parse_args()
+    root_path = args.root_path
+    region = args.region
+    # model = args.model
+    model = "phasenet_plus"
+
+    result_path = f"{region}/{model}"
+
+    # %%
+    # protocol = "gs"
+    # token_json = f"{os.environ['HOME']}/.config/gcloud/application_default_credentials.json"
+    # with open(token_json, "r") as fp:
+    #     token = json.load(fp)
+    # fs = fsspec.filesystem(protocol, token=token)
+
+    # %%
+    # years = os.listdir(f"{root_path}/{region}/{model}/picks_{model}")
+    years = glob(f"{root_path}/{region}/{model}/picks_{model}/????/")
+    years = [year.rstrip("/").split("/")[-1] for year in years]
+    print(f"Years: {years}")
+
+    for year in years:
+
+        for data in ["picks", "events"]:
+
+            csv_list = scan_csv(year, root_path, region, model, data)
+
+            # %%
+            csv_list = pd.read_csv(csv_list, dtype=str)
+
+            # for jday, csvs in csv_list.groupby("jday"):
+            #     read_csv(csvs, region, model, data, year, jday, root_path)
+            #     raise
+
+            ncpu = min(64, mp.cpu_count())
+            print(f"Number of processors: {ncpu}")
+            csv_by_jday = csv_list.groupby("jday")
+            pbar = tqdm(total=len(csv_by_jday), desc=f"Loading {data} csv files (year {year})")
+
+            ctx = mp.get_context("spawn")
+            with ctx.Pool(ncpu) as pool:
+                jobs = []
+                for jday, csvs in csv_by_jday:
+                    job = pool.apply_async(
+                        read_csv, (csvs, region, model, data, year, jday, root_path), callback=lambda _: pbar.update()
+                    )
+                    jobs.append(job)
+                pool.close()
+                pool.join()
+                for job in jobs:
+                    output = job.get()
+                    if output:
+                        print(output)
+
+            pbar.close()
+
+    # %%
+    for data in ["picks", "events"]:
+        csvs = glob(f"{root_path}/{region}/{model}/????/????.???.{data}.csv")
+        picks = []
+        for csv in tqdm(csvs, desc=f"Merge {data} csv files"):
+            picks.append(pd.read_csv(csv, dtype=str))
+        picks = pd.concat(picks, ignore_index=True)
+        picks.to_csv(f"{root_path}/{region}/{model}/{model}_{data}.csv", index=False)
+
+    # %%

scripts/run_adloc.py

@@ -46,6 +46,9 @@ def run_adloc(
     data_path = f"{root_path}/{region}/gamma"
     picks_file = os.path.join(data_path, f"gamma_picks.csv")
     events_file = os.path.join(data_path, f"gamma_events.csv")
+    # picks_file = f"{root_path}/{region}/phasenet_plus/phasenet_plus_picks_associated.csv"
+    # events_file = f"{root_path}/{region}/phasenet_plus/phasenet_plus_events_associated.csv"
+
     # stations_file = os.path.join(data_path, "stations.csv")
     stations_file = f"{root_path}/{region}/obspy/stations.json"
 
@@ -93,7 +96,7 @@ def run_adloc(
         events[["x_km", "y_km"]] = events.apply(
             lambda x: pd.Series(proj(longitude=x.longitude, latitude=x.latitude)), axis=1
         )
-        events["z_km"] = events["depth_km"]
+        events["z_km"] = events["depth_km"] if "depth_km" in events.columns else 10.0
 
     ## set up the config; you can also specify the region manually
     if ("xlim_km" not in config) or ("ylim_km" not in config) or ("zlim_km" not in config):