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updated metadata extraction in useful functions

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mbergmann 2024-10-23 11:32:24 +02:00
parent 702cbd08bb
commit 3b493fa079
1 changed files with 11 additions and 3 deletions
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14
code/useful_functions.py
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@ -110,6 +110,8 @@ def extract_stim_data(stimulus):
Current EODf. Current EODf.
stim_freq : float stim_freq : float
The total stimulus frequency (EODF+df). The total stimulus frequency (EODF+df).
stim_dur : float
The stimulus duration.
amp_mod : float amp_mod : float
The current amplitude modulation. The current amplitude modulation.
ny_freq : float ny_freq : float
@ -122,9 +124,10 @@ def extract_stim_data(stimulus):
df = stimulus.metadata[stimulus.name]['DeltaF'][0][0] df = stimulus.metadata[stimulus.name]['DeltaF'][0][0]
eodf = round(stimulus.metadata[stimulus.name]['EODf'][0][0]) eodf = round(stimulus.metadata[stimulus.name]['EODf'][0][0])
stim_freq = round(stimulus.metadata[stimulus.name]['Frequency'][0][0]) stim_freq = round(stimulus.metadata[stimulus.name]['Frequency'][0][0])
stim_dur = stimulus.duration
# calculates the amplitude modulation # calculates the amplitude modulation
amp_mod, ny_freq = AM(eodf, stim_freq) amp_mod, ny_freq = AM(eodf, stim_freq)
return amplitude, df, eodf, stim_freq, amp_mod, ny_freq return amplitude, df, eodf, stim_freq,stim_dur, amp_mod, ny_freq
def find_exceeding_points(frequency, power, points, delta, threshold): def find_exceeding_points(frequency, power, points, delta, threshold):
""" """
@ -286,6 +289,8 @@ def sam_data(sam):
Returns Returns
------- -------
avg_dur : float
Average stimulus duarion.
sam_amp : float sam_amp : float
amplitude in percent, relative to the fish amplitude. amplitude in percent, relative to the fish amplitude.
sam_am : float sam_am : float
@ -307,19 +312,21 @@ def sam_data(sam):
stim_freqs = [] stim_freqs = []
amp_mods = [] amp_mods = []
ny_freqs = [] ny_freqs = []
durations = []
# get the stimuli # get the stimuli
stimuli = sam.stimuli stimuli = sam.stimuli
# loop over the stimuli # loop over the stimuli
for stim in stimuli: for stim in stimuli:
amplitude, df, eodf, stim_freq, amp_mod, ny_freq = extract_stim_data(stim) amplitude, df, eodf, stim_freq,stim_dur, amp_mod, ny_freq = extract_stim_data(stim)
amplitudes.append(amplitude) amplitudes.append(amplitude)
dfs.append(df) dfs.append(df)
eodfs.append(eodf) eodfs.append(eodf)
stim_freqs.append(stim_freq) stim_freqs.append(stim_freq)
amp_mods.append(amp_mod) amp_mods.append(amp_mod)
ny_freqs.append(ny_freq) ny_freqs.append(ny_freq)
durations.append(stim_dur)
# get the means # get the means
sam_amp = np.mean(amplitudes) sam_amp = np.mean(amplitudes)
@ -328,7 +335,8 @@ def sam_data(sam):
sam_eodf = np.mean(eodfs) sam_eodf = np.mean(eodfs)
sam_nyquist = np.mean(ny_freqs) sam_nyquist = np.mean(ny_freqs)
sam_stim = np.mean(stim_freqs) sam_stim = np.mean(stim_freqs)
return sam_amp, sam_am, sam_df, sam_eodf, sam_nyquist, sam_stim avg_dur = np.mean(durations)
return avg_dur, sam_amp, sam_am, sam_df, sam_eodf, sam_nyquist, sam_stim
def spike_times(stim): def spike_times(stim):
""" """