From 4db4e5f899d94c81632b1d9c4c3f60e3d42f5225 Mon Sep 17 00:00:00 2001
From: mbergmann <maximilian.bergmann@student.uni-tuebingen.de>
Date: Tue, 22 Oct 2024 15:43:27 +0200
Subject: [PATCH] updated functions for easier power spectrum computation
---
code/useful_functions.py | 45 +++++++++++++++++++++++++++++++---------
1 file changed, 35 insertions(+), 10 deletions(-)
diff --git a/code/useful_functions.py b/code/useful_functions.py
index eb750e8..f94e59e 100644
--- a/code/useful_functions.py
+++ b/code/useful_functions.py
@@ -113,18 +113,14 @@ def firing_rate(binary_spikes, dt = 0.000025, box_width = 0.01):
rate = np.convolve(binary_spikes, box, mode = 'same')
return rate
-def power_spectrum(spike_times, duration, dt):
+def power_spectrum(stimulus):
'''
- Computes a power spectrum based on the spike times
+ Computes a power spectrum based from a stimulus
Parameters
----------
- spike_times : np.array
- The spike times.
- duration : float
- The trial duration:
- dt : float
- The temporal resolution.
+ stimulus : Stimulus object or rlxnix.base.repro module
+ The stimulus from which the data is needed.
Returns
-------
@@ -134,8 +130,9 @@ def power_spectrum(spike_times, duration, dt):
Power of the frequencies calculated.
'''
+ spikes, duration, dt = spike_times(stimulus)
# binarizes spikes
- binary = binary_spikes(spike_times, duration, dt)
+ binary = binary_spikes(spikes, duration, dt)
# computes firing rates
rate = firing_rate(binary, dt = dt)
# creates power spectrum
@@ -225,4 +222,32 @@ def sam_data(sam):
sam_eodf = np.mean(eodfs)
sam_nyquist = np.mean(ny_freqs)
sam_stim = np.mean(stim_freqs)
- return sam_amp, sam_am,sam_df, sam_eodf, sam_nyquist, sam_stim
\ No newline at end of file
+ return sam_amp, sam_am,sam_df, sam_eodf, sam_nyquist, sam_stim
+
+def spike_times(stim):
+ """
+ Reads out the spike times and other necessary parameters
+
+ Parameters
+ ----------
+ stim : Stimulus object or rlxnix.base.repro module
+ The stimulus from which the spike times should be calculated.
+
+ Returns
+ -------
+ spike_times : np.array
+ The spike times of the stimulus.
+ stim_dur : float
+ The duration of the stimulus.
+ dt : float
+ Time interval between two data points.
+
+ """
+ # reads out the spike times
+ spike_times, _ = stim.trace_data('Spikes-1')
+ # reads out the duration
+ stim_dur = stim.duration
+ # get the stimulus interval
+ ti = stim.trace_info("V-1")
+ dt = ti.sampling_interval
+ return spike_times, stim_dur, dt
\ No newline at end of file