From 577f47cdf6560bcaae8ef04f42f1b0aaafb13ce3 Mon Sep 17 00:00:00 2001
From: Nikos Karastathis <n.karastathis@kit.edu>
Date: Sat, 14 Oct 2023 11:42:09 +0200
Subject: [PATCH] Radio produces a nice dataframe with all showers and all
antennas for each radio process
---
python/corsika/io/outputs/radio_process.py | 37 ++++++++++++----------
1 file changed, 20 insertions(+), 17 deletions(-)
diff --git a/python/corsika/io/outputs/radio_process.py b/python/corsika/io/outputs/radio_process.py
index 0913eaa1f..9edc6baae 100644
--- a/python/corsika/io/outputs/radio_process.py
+++ b/python/corsika/io/outputs/radio_process.py
@@ -10,10 +10,8 @@
import logging
import os.path as op
from typing import Any
-
import pyarrow.parquet as pq
import pandas as pd
-import numpy as np
from .output import Output
@@ -60,11 +58,13 @@ class RadioProcess(Output):
The path to the directory containing this output.
"""
-
data = pq.read_table(op.join(path, "antennas.parquet"))
nshowers = data.to_pandas()['shower'].iloc[-1] + 1
antennas = list(self.config["antennas"].keys())
- nr_antennas = len(antennas)
+
+ # check that we got some events
+ if nshowers == 0:
+ logging.warn(f"Radio Process {self.config['name']} contains 0 showers.")
# if there are no antennas,
if len(antennas) == 0:
@@ -72,19 +72,22 @@ class RadioProcess(Output):
ant_nr = 0
dictionary = {}
- # loop over each of the antennas
- for name in antennas:
- dictionary[ant_nr] = name
- sampling_period = self.config["antennas"][name]["number of bins"]
- antenna_data = data[ant_nr*sampling_period:(ant_nr+1)*sampling_period].to_pandas()
- shower = antenna_data["shower"]#.to_numpy()
- times = antenna_data["Time"]#.to_numpy()
- Ex = antenna_data["Ex"]#.to_numpy()
- Ey = antenna_data["Ey"]#.to_numpy()
- Ez = antenna_data["Ez"]#.to_numpy()
- dataset = pd.DataFrame({'shower': shower, 'time': times, 'Ex': Ex, 'Ey': Ey, 'Ez': Ez})
-
- ant_nr = ant_nr+ 1
+ dataset = {}
+ # loop over all showers
+ for i in range(nshowers):
+ # loop over each of the antennas
+ for name in antennas:
+ dictionary[ant_nr] = name
+ sampling_period = self.config["antennas"][name]["number of bins"]
+ antenna_data = data[ant_nr*sampling_period:(ant_nr+1)*sampling_period].to_pandas()
+ times = antenna_data["Time"]
+ Ex = antenna_data["Ex"]
+ Ey = antenna_data["Ey"]
+ Ez = antenna_data["Ez"]
+ dictionary[name] = pd.DataFrame({'time': times, 'Ex': Ex, 'Ey': Ey, 'Ez': Ez})
+ ant_nr = ant_nr+ 1
+
+ dataset[str(i)] = dictionary
return dataset
--
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