feat: logging 0 - add logger configuration and update logging in step 1

src/icesat2waves/analysis_db/B01_SL_load_single_file.py

@@ -7,6 +7,7 @@
 import copy
 from pathlib import Path
 import warnings
+import logging
 
 import xarray as xr
 from sliderule import icesat2
@@ -40,6 +41,8 @@
     makeapp,
 )
 
+_logger = logging.getLogger(__name__)
+
 
 def make_B01_dict(table_data, split_by_beam=True, to_hdf5=False):
     """
@@ -91,7 +94,6 @@ def run_B01_SL_load_single_file(
     ID_flag: bool = True,
     plot_flag: bool = True,
     output_dir: str = typer.Option(..., callback=validate_output_dir),
-    verbose: bool = False,
 ):
     """
     Open an ICEsat2 tbeam_stats.pyrack, apply filters and corrections, and output smoothed photon heights on a regular grid in an .nc file.
@@ -109,174 +111,174 @@ def run_B01_SL_load_single_file(
     matplotlib.use("Agg")  # prevent plot windows from opening
 
     # Select region and retrieve batch of tracks
-    with suppress_stdout(verbose):
-        track_name, batch_key, ID_flag = io.init_from_input(
-            [
-                None,
-                track_name,
-                batch_key,
-                ID_flag,
-            ]  # init_from_input expects sys.argv with 4 elements
-        )  # loads standard experiment
 
-        hemis = batch_key.split("_")[0]
+    track_name, batch_key, ID_flag = io.init_from_input(
+        [
+            None,
+            track_name,
+            batch_key,
+            ID_flag,
+        ]  # init_from_input expects sys.argv with 4 elements
+    )  # loads standard experiment
+
+    hemis = batch_key.split("_")[0]
+
+    workdir, plotsdir = update_paths_mconfig(output_dir, mconfig)
+
+    save_path = Path(workdir, batch_key, "B01_regrid")
+    save_path.mkdir(parents=True, exist_ok=True)
+
+    save_path_json = Path(workdir, batch_key, "A01b_ID")
+    save_path_json.mkdir(parents=True, exist_ok=True)
+
+    ATL03_track_name = f"ATL03_{track_name}.h5"
+
+    # Configure SL Session
+    icesat2.init("slideruleearth.io")
+
+    # plot the ground tracks in geographic location
+    # Generate ATL06-type segments using the ATL03-native photon classification
+    # Use the ocean classification for photons with a confidence parameter to 2 or higher (low confidence or better)
+
+    # YAPC alternative
+    params_yapc = {
+        "srt": 1,
+        "len": 20,
+        "ats": 3,
+        "res": 10,
+        "dist_in_seg": False,  # if False units of len and res are in meters
+        "track": 0,
+        "pass_invalid": False,
+        "cnf": 2,
+        "cnt": 20,
+        "sigma_r_max": 4,  # maximum standard deviation of photon in extend
+        "maxi": 10,
+        "yapc": dict(
+            knn=0, win_h=6, win_x=11, min_ph=4, score=100
+        ),  # use the YAPC photon classifier; these are the recommended parameters, but the results might be more specific with a smaller win_h value, or a higher score cutoff
+        #   "yapc": dict(knn=0, win_h=3, win_x=11, min_ph=4, score=50),  # use the YAPC photon classifier; these are the recommended parameters, but the results might be more specific with a smaller win_h value, or a higher score cutoff
+        "atl03_geo_fields": ["dem_h"],
+    }
 
-        workdir, plotsdir = update_paths_mconfig(output_dir, mconfig)
+    maximum_height = 30  # (meters) maximum height past dem_h correction
+    _logger.info("Fetching ATL03 data from sliderule")
+    gdf = icesat2.atl06p(params_yapc, resources=[ATL03_track_name])
+    _logger.info("Finished fetching ATL03 data from sliderule")
+    gdf = sct.correct_and_remove_height(gdf, maximum_height)
 
-        save_path = Path(workdir, batch_key, "B01_regrid")
-        save_path.mkdir(parents=True, exist_ok=True)
+    cdict = dict()
+    for s, b in zip(
+        gdf["spot"].unique(), ["gt1l", "gt1r", "gt2l", "gt2r", "gt3l", "gt3r"]
+    ):
+        cdict[s] = color_schemes.rels[b]
 
-        save_path_json = Path(workdir, batch_key, "A01b_ID")
-        save_path_json.mkdir(parents=True, exist_ok=True)
+    font_for_pres()
+    F_atl06 = M.FigureAxisXY(6.5, 5, view_scale=0.6)
+    F_atl06.fig.suptitle(track_name)
 
-        ATL03_track_name = "ATL03_" + track_name + ".h5"
+    beam_stats.plot_ATL06_track_data(gdf, cdict)
 
-        # Configure SL Session
-        icesat2.init("slideruleearth.io")
+    # main routine for defining the x coordinate and sacing table data
 
-        # plot the ground tracks in geographic location
-        # Generate ATL06-type segments using the ATL03-native photon classification
-        # Use the ocean classification for photons with a confidence parameter to 2 or higher (low confidence or better)
-
-        # YAPC alternative
-        params_yapc = {
-            "srt": 1,
-            "len": 20,
-            "ats": 3,
-            "res": 10,
-            "dist_in_seg": False,  # if False units of len and res are in meters
-            "track": 0,
-            "pass_invalid": False,
-            "cnf": 2,
-            "cnt": 20,
-            "sigma_r_max": 4,  # maximum standard deviation of photon in extend
-            "maxi": 10,
-            "yapc": dict(
-                knn=0, win_h=6, win_x=11, min_ph=4, score=100
-            ),  # use the YAPC photon classifier; these are the recommended parameters, but the results might be more specific with a smaller win_h value, or a higher score cutoff
-            #   "yapc": dict(knn=0, win_h=3, win_x=11, min_ph=4, score=50),  # use the YAPC photon classifier; these are the recommended parameters, but the results might be more specific with a smaller win_h value, or a higher score cutoff
-            "atl03_geo_fields": ["dem_h"],
-        }
-
-        maximum_height = 30  # (meters) maximum height past dem_h correction
-        print("STARTS")
-        print("Fetching ATL03 data from sliderule")
-        gdf = icesat2.atl06p(params_yapc, resources=[ATL03_track_name])
-        print("ENDS")
-        gdf = sct.correct_and_remove_height(gdf, maximum_height)
-
-        cdict = dict()
-        for s, b in zip(
-            gdf["spot"].unique(), ["gt1l", "gt1r", "gt2l", "gt2r", "gt3l", "gt3r"]
-        ):
-            cdict[s] = color_schemes.rels[b]
+    # define reference point and then define 'x'
+    table_data = copy.copy(gdf)
 
-        font_for_pres()
-        F_atl06 = M.FigureAxisXY(6.5, 5, view_scale=0.6)
-        F_atl06.fig.suptitle(track_name)
+    # the reference point is defined as the most equatorward point of the polygon.
+    # It's distance from the equator is  subtracted from the distance of each photon.
+    table_data = sct.define_x_coordinate_from_data(table_data)
+    table_time = table_data["time"]
+    table_data.drop(columns=["time"], inplace=True)
+
+    # renames columns and splits beams
+    Ti = make_B01_dict(table_data, split_by_beam=True, to_hdf5=True)
+
+    with warnings.catch_warnings():
+        warnings.simplefilter(
+            "ignore", category=SettingWithCopyWarning
+        )  # TODO: remove when warnings are handled
+        for kk in Ti.keys():
+            Ti[kk]["dist"] = Ti[kk]["x"].copy()
+            Ti[kk]["heights_c_weighted_mean"] = Ti[kk]["h_mean"].copy()
+            Ti[kk]["heights_c_std"] = Ti[kk]["h_sigma"].copy()
+
+    segment = track_name.split("_")[1][-2:]
+    ID_name = sct.create_ID_name(gdf.iloc[0], segment=segment)
+    echoparam("ID_name", ID_name)
+    io.write_track_to_HDF5(Ti, ID_name + "_B01_binned", save_path)  # regridding heights
 
-        beam_stats.plot_ATL06_track_data(gdf, cdict)
+    #  plot the ground tracks in geographic location
 
-        # main routine for defining the x coordinate and sacing table data
+    all_beams = mconfig["beams"]["all_beams"]
+    high_beams = mconfig["beams"]["high_beams"]
+    low_beams = mconfig["beams"]["low_beams"]
 
-        # define reference point and then define 'x'
-        table_data = copy.copy(gdf)
+    D = beam_stats.derive_beam_statistics(Ti, all_beams, Lmeter=12.5e3, dx=10)
 
-        # the reference point is defined as the most equatorward point of the polygon.
-        # It's distance from the equator is  subtracted from the distance of each photon.
-        table_data = sct.define_x_coordinate_from_data(table_data)
-        table_time = table_data["time"]
-        table_data.drop(columns=["time"], inplace=True)
+    # save figure from above:
+    plot_path = Path(plotsdir, hemis, batch_key, ID_name)
+    plot_path.mkdir(parents=True, exist_ok=True)
 
-        # renames columns and splits beams
-        Ti = make_B01_dict(table_data, split_by_beam=True, to_hdf5=True)
+    F_atl06.save_light(path=plot_path, name="B01b_ATL06_corrected.png")
+    plt.close()
 
-        with warnings.catch_warnings():
-            warnings.simplefilter(
-                "ignore", category=SettingWithCopyWarning
-            )  # TODO: remove when warnings are handled
-            for kk in Ti.keys():
-                Ti[kk]["dist"] = Ti[kk]["x"].copy()
-                Ti[kk]["heights_c_weighted_mean"] = Ti[kk]["h_mean"].copy()
-                Ti[kk]["heights_c_std"] = Ti[kk]["h_sigma"].copy()
+    if plot_flag:
+        font_for_pres()
+        F = M.FigureAxisXY(8, 4.3, view_scale=0.6)
+        beam_stats.plot_beam_statistics(
+            D,
+            high_beams,
+            low_beams,
+            color_schemes.rels,
+            track_name=track_name
+            + "|  ascending ="
+            + str(sct.ascending_test_distance(gdf)),
+        )
+
+        F.save_light(path=plot_path, name="B01b_beam_statistics.png")
+        plt.close()
 
-        segment = track_name.split("_")[1][-2:]
-        ID_name = sct.create_ID_name(gdf.iloc[0], segment=segment)
-        echoparam("ID_name", ID_name)
-        io.write_track_to_HDF5(Ti, ID_name + "_B01_binned", save_path)  # regridding heights
+        # plot the ground tracks in geographic location
+        gdf[::100].plot(markersize=0.1, figsize=(4, 6))
+        plt.title(
+            track_name + "\nascending =" + str(sct.ascending_test_distance(gdf)),
+            loc="left",
+        )
+        M.save_anyfig(plt.gcf(), path=plot_path, name="B01_track.png")
+        plt.close()
 
-        #  plot the ground tracks in geographic location
+    _logger.info("write A01b .json")
+    DD = {"case_ID": ID_name, "tracks": {}}
 
-        all_beams = mconfig["beams"]["all_beams"]
-        high_beams = mconfig["beams"]["high_beams"]
-        low_beams = mconfig["beams"]["low_beams"]
+    DD["tracks"]["ATL03"] = f"ATL10-{track_name}"
 
-        D = beam_stats.derive_beam_statistics(Ti, all_beams, Lmeter=12.5e3, dx=10)
+    start_pos = abs(table_data.lats).argmin()
+    end_pos = abs(table_data.lats).argmax()
 
-        # save figure from above:
-        plot_path = Path(plotsdir, hemis, batch_key, ID_name)
-        plot_path.mkdir(parents=True, exist_ok=True)
+    # add other pars:
+    DD["pars"] = {
+        "poleward": sct.ascending_test(gdf),
+        "region": "0",
+        "start": {
+            "longitude": table_data.lons[start_pos],
+            "latitude": table_data.lats[start_pos],
+            "seg_dist_x": float(table_data.x[start_pos]),
+            "delta_time": datetime.datetime.timestamp(table_time[start_pos]),
+        },
+        "end": {
+            "longitude": table_data.lons[end_pos],
+            "latitude": table_data.lats[end_pos],
+            "seg_dist_x": float(table_data.x[end_pos]),
+            "delta_time": datetime.datetime.timestamp(table_time[end_pos]),
+        },
+    }
 
-        F_atl06.save_light(path=plot_path, name="B01b_ATL06_corrected.png")
-        plt.close()
+    MT.json_save2(name="A01b_ID_" + ID_name, path=save_path_json, data=DD)
 
-        if plot_flag:
-            font_for_pres()
-            F = M.FigureAxisXY(8, 4.3, view_scale=0.6)
-            beam_stats.plot_beam_statistics(
-                D,
-                high_beams,
-                low_beams,
-                color_schemes.rels,
-                track_name=track_name
-                + "|  ascending ="
-                + str(sct.ascending_test_distance(gdf)),
-            )
-
-            F.save_light(path=plot_path, name="B01b_beam_statistics.png")
-            plt.close()
-
-            # plot the ground tracks in geographic location
-            gdf[::100].plot(markersize=0.1, figsize=(4, 6))
-            plt.title(
-                track_name + "\nascending =" + str(sct.ascending_test_distance(gdf)),
-                loc="left",
-            )
-            M.save_anyfig(plt.gcf(), path=plot_path, name="B01_track.png")
-            plt.close()
-
-        echo("write A01b .json")
-        DD = {"case_ID": ID_name, "tracks": {}}
-
-        DD["tracks"]["ATL03"] = "ATL10-" + track_name
-
-        start_pos = abs(table_data.lats).argmin()
-        end_pos = abs(table_data.lats).argmax()
-
-        # add other pars:
-        DD["pars"] = {
-            "poleward": sct.ascending_test(gdf),
-            "region": "0",
-            "start": {
-                "longitude": table_data.lons[start_pos],
-                "latitude": table_data.lats[start_pos],
-                "seg_dist_x": float(table_data.x[start_pos]),
-                "delta_time": datetime.datetime.timestamp(table_time[start_pos]),
-            },
-            "end": {
-                "longitude": table_data.lons[end_pos],
-                "latitude": table_data.lats[end_pos],
-                "seg_dist_x": float(table_data.x[end_pos]),
-                "delta_time": datetime.datetime.timestamp(table_time[end_pos]),
-            },
-        }
-
-        MT.json_save2(name="A01b_ID_" + ID_name, path=save_path_json, data=DD)
-
-        echo("done")
+    _logger.info("done")
 
 
 load_file_app = makeapp(run_B01_SL_load_single_file, name="load-file")
 
 if __name__ == "__main__":
+    logging.basicConfig(level=logging.WARNING)
     load_file_app()