From e582fb567db584254c1dd56b7e15510fda8c7a67 Mon Sep 17 00:00:00 2001
From: maaijke <mevius@astron.nl>
Date: Wed, 7 May 2025 15:17:38 +0200
Subject: [PATCH] automaticly find correct beam for IDOLS lik data
---
scintillation/averaging.py | 39 +++++++++++++++++++-------------------
1 file changed, 20 insertions(+), 19 deletions(-)
diff --git a/scintillation/averaging.py b/scintillation/averaging.py
index 247396d..d2c7836 100644
--- a/scintillation/averaging.py
+++ b/scintillation/averaging.py
@@ -165,7 +165,7 @@ def copy_attrs_to_dict(h5_leaf, dict_container: Optional[Dict] = None,
def parse_datetime_str(datetime_str):
- return Time(datetime_str.split(' ')[0], format='isot', scale='utc').to_datetime()
+ return Time(datetime_str.split(' ')[0], format='isot', scale='utc').to_datetime().replace(tzinfo=timezone.utc)
def extract_root_metadata(dataset):
@@ -527,8 +527,8 @@ def make_plot(data_array, time_axis, frequency_axis, station_name, plot_full_pat
label="Dynspec"):
fig = plt.figure(figsize=(6, 4), dpi=120)
ax = plt.gca()
- start_time = datetime.fromtimestamp(time_axis[0]).strftime("%Y/%m/%d %H:%M:%S")
- datetime_axis = [datetime.fromtimestamp(time_s) for time_s in time_axis]
+ start_time = datetime.utcfromtimestamp(time_axis[0]).strftime("%Y/%m/%d %H:%M:%S")
+ datetime_axis = [datetime.utcfromtimestamp(time_s) for time_s in time_axis]
times = mdates.date2num(datetime_axis)
title = '{label} {station_name} - {start_time}'.format(label=label,
@@ -565,8 +565,8 @@ def make_S4plot(data_array, time_axis, frequency_axis, station_name, plot_full_p
label="S4"):
fig = plt.figure(figsize=(6, 4), dpi=120)
ax = plt.gca()
- start_time = datetime.fromtimestamp(time_axis[0]).strftime("%Y/%m/%d %H:%M:%S")
- datetime_axis = [datetime.fromtimestamp(time_s) for time_s in time_axis]
+ start_time = datetime.utcfromtimestamp(time_axis[0]).strftime("%Y/%m/%d %H:%M:%S")
+ datetime_axis = [datetime.utcfromtimestamp(time_s) for time_s in time_axis]
times = mdates.date2num(datetime_axis)
title = '{label} {station_name} - {start_time}'.format(label=label,
@@ -601,7 +601,7 @@ def make_S4plot(data_array, time_axis, frequency_axis, station_name, plot_full_p
def make_cross_corr_plots(plot_full_path, cross_corr, uvpp, time,vel):
fig = plt.figure(figsize=(6, 4), dpi=120)
ax = plt.gca()
- #start_time = datetime.fromtimestamp(time).strftime("%Y/%m/%d %H:%M:%S")
+ #start_time = datetime.utcfromtimestamp(time).strftime("%Y/%m/%d %H:%M:%S")
start_time = time.strftime("%Y/%m/%d %H:%M:%S")
label = "Cross correlation (at delay 0)"
@@ -627,7 +627,7 @@ def make_cross_corr_plots(plot_full_path, cross_corr, uvpp, time,vel):
def make_delay_plots(plot_full_path, delays, uvpp, time,vel):
fig = plt.figure(figsize=(6, 4), dpi=120)
ax = plt.gca()
- #start_time = datetime.fromtimestamp(time).strftime("%Y/%m/%d %H:%M:%S")
+ #start_time = datetime.utcfromtimestamp(time).strftime("%Y/%m/%d %H:%M:%S")
start_time = time.strftime("%Y/%m/%d %H:%M:%S")
label = "Delay"
@@ -679,11 +679,11 @@ def create_averaged_dataset(sample_info, data_array, flags=None, bandpass=None):
def round_up_datetime(datet, interval):
- return datetime.fromtimestamp(numpy.ceil(datet.timestamp() / interval) * interval)
+ return datetime.utcfromtimestamp(numpy.ceil(datet.timestamp() / interval) * interval).replace(tzinfo=timezone.utc)
def round_down_datetime(datet, interval):
- return datetime.fromtimestamp(numpy.floor(datet.timestamp() / interval) * interval)
+ return datetime.utcfromtimestamp(numpy.floor(datet.timestamp() / interval) * interval).replace(tzinfo=timezone.utc)
def split_samples(dynspec_name,
@@ -710,11 +710,11 @@ def split_samples(dynspec_name,
time_delta = metadata['SAMPLING_TIME']
if 'DYNSPEC_START_UTC' in metadata:
- obs_start_time = parse_datetime_str(metadata['DYNSPEC_START_UTC'])
- obs_end_time = parse_datetime_str(metadata['DYNSPEC_STOP_UTC'])
+ obs_start_time = parse_datetime_str(metadata['DYNSPEC_START_UTC']).replace(tzinfo=timezone.utc)
+ obs_end_time = parse_datetime_str(metadata['DYNSPEC_STOP_UTC']).replace(tzinfo=timezone.utc)
else:
- obs_start_time = parse_datetime_str(metadata['OBSERVATION_START_UTC'])
- obs_end_time = parse_datetime_str(metadata['OBSERVATION_END_UTC'])
+ obs_start_time = parse_datetime_str(metadata['OBSERVATION_START_UTC']).replace(tzinfo=timezone.utc)
+ obs_end_time = parse_datetime_str(metadata['OBSERVATION_END_UTC']).replace(tzinfo=timezone.utc)
if 'AXIS_VALUE_WORLD' in metadata['SPECTRAL']:
frequency = metadata['SPECTRAL']['AXIS_VALUE_WORLD']
else:
@@ -732,9 +732,10 @@ def split_samples(dynspec_name,
data_array = dataset[dynspec_name]['DATA']
nofch = 1 #TODO check if this is always the case for DYNSPEC data
else:
- data_array = dataset[dynspec_name]['BEAM_000']['STOKES_0']
+ beam_name = [ibeam for ibeam in dataset[dynspec_name].keys() if "BEAM" in ibeam ][0]
+ data_array = dataset[dynspec_name][beam_name]['STOKES_0']
#take median over channels for raw data
- nofch = dataset[dynspec_name]['BEAM_000']['STOKES_0'].attrs['NOF_CHANNELS'][0]
+ nofch = dataset[dynspec_name][beam_name]['STOKES_0'].attrs['NOF_CHANNELS'][0]
averaging_window_in_samples = int(numpy.ceil(averaging_window / time_delta))
averaging_window_in_seconds = averaging_window_in_samples * time_delta
S4_60s_window_in_samples = int(60. / time_delta)
@@ -772,8 +773,8 @@ def split_samples(dynspec_name,
'average_window_samples': averaging_window_in_samples,
'average_window_seconds': averaging_window_in_seconds,
'sample_time_samples': output_time_samples,
- 'sample_start_datetime': datetime.fromtimestamp(time_obs[start_index]),
- 'sample_end_datetime': datetime.fromtimestamp(time_obs[end_index]),
+ 'sample_start_datetime': datetime.utcfromtimestamp(time_obs[start_index]).replace(tzinfo=timezone.utc),
+ 'sample_end_datetime': datetime.utcfromtimestamp(time_obs[end_index]).replace(tzinfo=timezone.utc),
'n_time_samples': len(indexs),
'sample_start_frequency': start_frequency,
'sample_end_frequency': end_frequency}
@@ -909,8 +910,8 @@ def get_velocities(metadata,
'average_window_samples': averaging_window_in_samples,
'average_window_seconds': averaging_window_in_seconds,
'sample_time_samples': output_time_samples,
- 'sample_start_datetime': datetime.fromtimestamp(time_obs[start_index]),
- 'sample_end_datetime': datetime.fromtimestamp(time_obs[end_index]),
+ 'sample_start_datetime': datetime.utcfromtimestamp(time_obs[start_index]).replace(tzinfo=timezone.utc),
+ 'sample_end_datetime': datetime.utcfromtimestamp(time_obs[end_index]).replace(tzinfo=timezone.utc),
'n_time_samples': len(indexs),
'sample_start_frequency': start_frequency,
'sample_end_frequency': end_frequency,
--
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