From c8f3daefdc545629d5c9b17b8b178f68314b8247 Mon Sep 17 00:00:00 2001
From: Leolab SDR PC <johannes.schabbauer@tuwien.ac.at>
Date: Mon, 9 Sep 2024 18:04:33 +0200
Subject: [PATCH] Adwin Analog inputs: added getting traces without writing to
hdf5 file (much faster, esp. if we need them just once for plotting)
---
ADwinProII/ADwin_utils.py | 16 ++++++++++++----
1 file changed, 12 insertions(+), 4 deletions(-)
diff --git a/ADwinProII/ADwin_utils.py b/ADwinProII/ADwin_utils.py
index 6825e3e..fa1d2f4 100644
--- a/ADwinProII/ADwin_utils.py
+++ b/ADwinProII/ADwin_utils.py
@@ -103,7 +103,7 @@ def get_channel_from_BLACS_name(BLACS_name):
return int(channel)
-def get_ain_traces(h5file, raw_data_name="ADwinAnalogIn_DATA", convert_data=True, device_name="ADwin"):
+def get_ain_traces(h5file, raw_data_name="ADwinAnalogIn_DATA", convert_data=True, device_name="ADwin", write_hdf5 = True):
"""
Split raw (sorted!) data from ADwin analog inputs into aquisitions
of channels and store the traces for each channel in the h5 file.
@@ -118,8 +118,11 @@ def get_ain_traces(h5file, raw_data_name="ADwinAnalogIn_DATA", convert_data=True
Set is the input voltage is stored as row value, or converted to volts.
device_name : str, optional
Name of the ADwin device.
+ write_hdf5 : bool, optional
+ Decides if the single traces are written to the hdf5 file or returned.
"""
- with h5py.File(h5file, 'r+') as f:
+ return_dict = {}
+ with h5py.File(h5file, 'r'+write_hdf5*'+') as f: # open with(out) write permission depending on argument
group = f["data/traces"]
if raw_data_name not in group:
print(f"No raw acquisition data with name '{raw_data_name}' found!")
@@ -154,8 +157,13 @@ def get_ain_traces(h5file, raw_data_name="ADwinAnalogIn_DATA", convert_data=True
else:
times = np.arange(acquisition_times["start_time"][i],acquisition_times["stop_time"][i]) / clock_rate
# print(times.size,acquisition.size)
- data = np.rec.fromarrays([times, acquisition], dtype=dtype)
- group.create_dataset(label, compression = config.compression, data = data)
+ if write_hdf5:
+ data = np.rec.fromarrays([times, acquisition], dtype=dtype)
+ group.create_dataset(label, compression = config.compression, data = data)
+ else:
+ return_dict[label] = times, acquisition
+ if not write_hdf5:
+ return return_dict
--
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