code/test.py

@@ -129,61 +129,6 @@ def remove_poor(files):
             good_files.append(files[i])
     return good_files
 
-def sam_data(sam):
-    '''
-    Gets metadata for each SAM
-
-    Parameters
-    ----------
-    sam : ReproRun object
-        The sam the metdata should be extracted from.
-
-    Returns
-    -------
-    sam_amp : float
-        amplitude in percent, relative to the fish amplitude.
-    sam_am : float
-        Amplitude modulation frequency.
-    sam_df : float
-        Difference from the stimulus to the current fish eodf.
-    sam_eodf : float
-        The current EODf.
-    sam_nyquist : float
-        The Nyquist frequency of the EODf.
-    sam_stim : float
-        The stimulus frequency.
-
-    '''
-    # create lists for the values we want
-    amplitudes = []
-    dfs = []
-    eodfs = []
-    stim_freqs = []
-    amp_mods = []
-    ny_freqs = []
-    
-    # get the stimuli
-    stimuli = sam.stimuli
-    
-    # loop over the stimuli
-    for stim in stimuli:
-        amplitude, df, eodf, stim_freq, amp_mod, ny_freq = extract_stim_data(stim)
-        amplitudes.append(amplitude)
-        dfs.append(df)
-        eodfs.append(eodf)
-        stim_freqs.append(stim_freq)
-        amp_mods.append(amp_mod)
-        ny_freqs.append(ny_freq)
-      
-    # get the means
-    sam_amp = np.mean(amplitudes)
-    sam_am = np.mean(amp_mods)
-    sam_df = np.mean(dfs)
-    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
-    
 #find example data
 datafolder = "../../data"
 

code/useful_functions.py

@@ -171,58 +171,3 @@ def remove_poor(files):
             # if its good or fair add it to the good files
             good_files.append(files[i])
     return good_files
-
-def sam_data(sam):
-    '''
-    Gets metadata for each SAM
-
-    Parameters
-    ----------
-    sam : ReproRun object
-        The sam the metdata should be extracted from.
-
-    Returns
-    -------
-    sam_amp : float
-        amplitude in percent, relative to the fish amplitude.
-    sam_am : float
-        Amplitude modulation frequency.
-    sam_df : float
-        Difference from the stimulus to the current fish eodf.
-    sam_eodf : float
-        The current EODf.
-    sam_nyquist : float
-        The Nyquist frequency of the EODf.
-    sam_stim : float
-        The stimulus frequency.
-
-    '''
-    # create lists for the values we want
-    amplitudes = []
-    dfs = []
-    eodfs = []
-    stim_freqs = []
-    amp_mods = []
-    ny_freqs = []
-    
-    # get the stimuli
-    stimuli = sam.stimuli
-    
-    # loop over the stimuli
-    for stim in stimuli:
-        amplitude, df, eodf, stim_freq, amp_mod, ny_freq = extract_stim_data(stim)
-        amplitudes.append(amplitude)
-        dfs.append(df)
-        eodfs.append(eodf)
-        stim_freqs.append(stim_freq)
-        amp_mods.append(amp_mod)
-        ny_freqs.append(ny_freq)
-      
-    # get the means
-    sam_amp = np.mean(amplitudes)
-    sam_am = np.mean(amp_mods)
-    sam_df = np.mean(dfs)
-    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