run_one_dsp to build_dsp

Author: ggmarshall

src/legenddataflowscripts/par/geds/dsp/eopt.py

@@ -10,13 +10,13 @@
 import pygama.pargen.energy_optimisation as om  # noqa: F401
 import sklearn.gaussian_process.kernels as ker
 from dbetto.catalog import Props
+from dspeed import build_dsp
 from dspeed.units import unit_registry as ureg
 from lgdo import lh5
 from pygama.math.distributions import hpge_peak
 from pygama.pargen.dsp_optimize import (
     BayesianOptimizer,
     run_bayesian_optimisation,
-    run_one_dsp,
 )
 
 from ....utils import build_log
@@ -127,7 +127,7 @@ def par_geds_dsp_eopt() -> None:
 
         dsp_config["outputs"] = ["tp_99", "tp_0_est", "dt_eff"]
 
-        init_data = run_one_dsp(tb_data, dsp_config, db_dict=db_dict, verbosity=0)
+        init_data = build_dsp(raw_in=tb_data, dsp_config=dsp_config, database=db_dict)
         full_dt = (init_data["tp_99"].nda - init_data["tp_0_est"].nda)[idx_list[-1]]
         flat_val = np.ceil(1.1 * np.nanpercentile(full_dt, 99) / 100) / 10
 
@@ -193,7 +193,7 @@ def par_geds_dsp_eopt() -> None:
             msg = f"Initialising values {i + 1} : {db_dict}"
             log.info(msg)
 
-            tb_out = run_one_dsp(tb_data, dsp_config, db_dict=db_dict, verbosity=0)
+            tb_out = build_dsp(raw_in=tb_data, dsp_config=dsp_config, database=db_dict)
 
             res = fom(tb_out, kwarg_dict[0])
             results_cusp.append(res)

src/legenddataflowscripts/par/geds/dsp/evtsel.py

@@ -12,9 +12,9 @@
 import pygama.math.histogram as pgh
 import pygama.pargen.energy_cal as pgc
 from dbetto.catalog import Props
+from dspeed import build_dsp
 from lgdo import lh5
 from pygama.pargen.data_cleaning import generate_cuts, get_keys
-from pygama.pargen.dsp_optimize import run_one_dsp
 
 from ....utils import build_log, get_pulser_mask
 
@@ -247,7 +247,7 @@ def par_geds_dsp_evtsel() -> None:
         ]
 
         log.debug("Processing data")
-        tb_data = run_one_dsp(input_data, dsp_config, db_dict=db_dict)
+        tb_data = build_dsp(raw_in=input_data, dsp_config=dsp_config, database=db_dict)
 
         if cut_parameters is not None:
             cut_dict = generate_cuts(tb_data, cut_parameters)
@@ -297,8 +297,10 @@ def par_geds_dsp_evtsel() -> None:
                         peak_dict["obj_buf_start"] += n_rows_read_i
                     if peak_dict["n_rows_read"] >= 10000 or file == raw_files[-1]:
                         if "e_lower_lim" not in peak_dict:
-                            tb_out = run_one_dsp(
-                                peak_dict["obj_buf"], dsp_config, db_dict=db_dict
+                            tb_out = build_dsp(
+                                raw_in=peak_dict["obj_buf"],
+                                dsp_config=dsp_config,
+                                database=db_dict,
                             )
                             energy = tb_out[energy_parameter].nda
 
@@ -396,8 +398,10 @@ def par_geds_dsp_evtsel() -> None:
                             peak_dict["obj_buf"] is not None
                             and len(peak_dict["obj_buf"]) > 0
                         ):
-                            tb_out = run_one_dsp(
-                                peak_dict["obj_buf"], dsp_config, db_dict=db_dict
+                            tb_out = build_dsp(
+                                raw_in=peak_dict["obj_buf"],
+                                dsp_config=dsp_config,
+                                database=db_dict,
                             )
                             out_tbl, n_wfs = get_out_data(
                                 peak_dict["obj_buf"],

src/legenddataflowscripts/par/geds/dsp/nopt.py

@@ -8,9 +8,9 @@
 import numpy as np
 import pygama.pargen.noise_optimization as pno
 from dbetto.catalog import Props
+from dspeed import build_dsp
 from lgdo import lh5
 from pygama.pargen.data_cleaning import generate_cuts, get_cut_indexes
-from pygama.pargen.dsp_optimize import run_one_dsp
 
 from ....utils import build_log
 
@@ -73,7 +73,7 @@ def par_geds_dsp_nopt() -> None:
 
         msg = f"Select baselines {len(tb_data)}"
         log.info(msg)
-        dsp_data = run_one_dsp(tb_data, dsp_config)
+        dsp_data = build_dsp(raw_in=tb_data, dsp_config=dsp_config)
         cut_dict = generate_cuts(dsp_data, cut_dict=opt_dict.pop("cut_pars"))
         cut_idxs = get_cut_indexes(dsp_data, cut_dict)
         tb_data = lh5.read(

src/legenddataflowscripts/par/geds/dsp/pz.py

@@ -7,9 +7,9 @@
 
 import numpy as np
 from dbetto.catalog import Props
+from dspeed import build_dsp
 from lgdo import lh5
 from pygama.pargen.data_cleaning import get_cut_indexes
-from pygama.pargen.dsp_optimize import run_one_dsp
 from pygama.pargen.pz_correct import PZCorrect
 
 from ....utils import (
@@ -134,7 +134,7 @@ def par_geds_dsp_pz() -> None:
         if "frac" in dsp_config["outputs"]:
             dsp_config_optimise_removed["outputs"].remove("frac")
 
-        tb_out = run_one_dsp(tb_data, dsp_config_optimise_removed)
+        tb_out = build_dsp(raw_in=tb_data, dsp_config=dsp_config_optimise_removed)
         log.debug("Processed Data")
         cut_parameters = kwarg_dict.get("cut_parameters", None)
         if cut_parameters is not None: