added newline separators to all codebookadd directives

neurokit2/ecg/ecg_eventrelated.py

@@ -37,18 +37,23 @@ def ecg_eventrelated(epochs, silent=False):
             ECG_Rate_SD|The standard deviation of the heart rate after stimulus onset.
             ECG_Rate_Max_Time|The time at which maximum heart rate occurs.
             ECG_Rate_Min_Time|The time at which minimum heart rate occurs.
-            ECG_Phase_Atrial|Indication of whether the onset of the event concurs with respiratory systole (1) or diastole (0).
-            ECG_Phase_Ventricular|Indication of whether the onset of the event concurs with respiratory systole (1) or diastole (0).
-            ECG_Phase_Atrial_Completion|Indication of the stage of the current cardiac (atrial) phase (0 to 1) at the onset of the event.
-            ECG_Phase_Ventricular_Completion|Indication of the stage of the current cardiac (ventricular) phase (0 to 1) at the onset of the event.
+            ECG_Phase_Atrial|Indication of whether the onset of the event concurs with \
+                respiratory systole (1) or diastole (0).
+            ECG_Phase_Ventricular|Indication of whether the onset of the event concurs with \
+                respiratory systole (1) or diastole (0).
+            ECG_Phase_Atrial_Completion|Indication of the stage of the current cardiac (atrial) \
+                phase (0 to 1) at the onset of the event.
+            ECG_Phase_Ventricular_Completion|Indication of the stage of the current cardiac \
+                (ventricular) phase (0 to 1) at the onset of the event.
 
         We also include the following *experimental* features related to the parameters of a
         quadratic model:
 
         .. codebookadd::
             ECG_Rate_Trend_Linear|The parameter corresponding to the linear trend.
             ECG_Rate_Trend_Quadratic|The parameter corresponding to the curvature.
-            ECG_Rate_Trend_R2|The quality of the quadratic model. If too low, the parameters might not be reliable or meaningful.
+            ECG_Rate_Trend_R2|The quality of the quadratic model. If too low, the parameters \
+                might not be reliable or meaningful.
 
     See Also
     --------

neurokit2/ecg/ecg_process.py

@@ -56,8 +56,10 @@ def ecg_process(ecg_signal, sampling_rate=1000, method="neurokit"):
             ECG_T_Onsets|The T-onsets marked as "1" in a list of zeros.
             ECG_T_Offsets|The T-offsets marked as "1" in a list of zeros.
             ECG_Phase_Atrial|Cardiac phase, marked by "1" for systole and "0" for diastole.
-            ECG_Phase_Completion_Atrial|Cardiac phase (atrial) completion, expressed in percentage (from 0 to 1), representing the stage of the current cardiac phase.
-            ECG_Phase_Completion_Ventricular|Cardiac phase (ventricular) completion, expressed in percentage (from 0 to 1), representing the stage of the current cardiac phase.
+            ECG_Phase_Completion_Atrial|Cardiac phase (atrial) completion, expressed in \
+                percentage (from 0 to 1), representing the stage of the current cardiac phase.
+            ECG_Phase_Completion_Ventricular|Cardiac phase (ventricular) completion, expressed \
+                in percentage (from 0 to 1), representing the stage of the current cardiac phase.
 
     rpeaks : dict
         A dictionary containing the samples at which the R-peaks occur, accessible with the key

neurokit2/eda/eda_eventrelated.py

@@ -31,12 +31,17 @@ def eda_eventrelated(epochs, silent=False):
         the following:
 
         .. codebookadd::
-            EDA_SCR|indication of whether Skin Conductance Response (SCR) occurs following the event (1 if an SCR onset is present and 0 if absent) and if so, its corresponding peak amplitude, time of peak, rise and recovery time. If there is no occurrence of SCR, nans are displayed for the below features.
+            EDA_SCR|indication of whether Skin Conductance Response (SCR) occurs following the \
+                event (1 if an SCR onset is present and 0 if absent) and if so, its corresponding \
+                peak amplitude, time of peak, rise and recovery time. If there is no occurrence \
+                of SCR, nans are displayed for the below features.
             EDA_Peak_Amplitude|The maximum amplitude of the phasic component of the signal.
             SCR_Peak_Amplitude|The peak amplitude of the first SCR in each epoch.
             SCR_Peak_Amplitude_Time|The timepoint of each first SCR peak amplitude.
-            SCR_RiseTime|The risetime of each first SCR i.e., the time it takes for SCR to reach peak amplitude from onset.
-            SCR_RecoveryTime|The half-recovery time of each first SCR i.e., the time it takes for SCR to decrease to half amplitude.
+            SCR_RiseTime|The risetime of each first SCR i.e., the time it takes for SCR to \
+                reach peak amplitude from onset.
+            SCR_RecoveryTime|The half-recovery time of each first SCR i.e., the time it takes \
+                for SCR to decrease to half amplitude.
 
     See Also
     --------

neurokit2/eda/eda_process.py

@@ -47,10 +47,12 @@ def eda_process(
             EDA_Phasic|The phasic component of the signal, or the Phasic Skin Conductance Response (SCR).
             SCR_Onsets|The samples at which the onsets of the peaks occur, marked as "1" in a list of zeros.
             SCR_Peaks|The samples at which the peaks occur, marked as "1" in a list of zeros.
-            SCR_Height|The SCR amplitude of the signal including the Tonic component. Note that cumulative effects of close-occurring SCRs might lead to an underestimation of the amplitude.
+            SCR_Height|The SCR amplitude of the signal including the Tonic component. Note that cumulative \
+                effects of close-occurring SCRs might lead to an underestimation of the amplitude.
             SCR_Amplitude|The SCR amplitude of the signal excluding the Tonic component.
             SCR_RiseTime|The SCR amplitude of the signal excluding the Tonic component.
-            SCR_Recovery|The samples at which SCR peaks recover (decline) to half amplitude, marked  as "1" in a list of zeros.
+            SCR_Recovery|The samples at which SCR peaks recover (decline) to half amplitude, marked  as "1" \
+                in a list of zeros.
 
     info : dict
         A dictionary containing the information of each SCR peak (see :func:`eda_findpeaks`),

neurokit2/eda/eda_sympathetic.py

@@ -48,8 +48,10 @@ def eda_sympathetic(
         by total power).
 
         .. codebookadd::
-            EDA_Sympathetic|Derived from Posada-Quintero et al. (2016), who argue that dynamics of the sympathetic component of EDA signal is represented in the frequency band of 0.045-0.25Hz.
-            EDA_SympatheticN|normalized version of "EDA_Sympathetic" obtained by dividing EDA_Sympathetic by total power
+            EDA_Sympathetic|Derived from Posada-Quintero et al. (2016), who argue that dynamics of \
+                the sympathetic component of EDA signal is represented in the frequency band of 0.045-0.25Hz.
+            EDA_SympatheticN|normalized version of "EDA_Sympathetic" obtained by dividing \
+                EDA_Sympathetic by total power
 
     Examples
     --------

neurokit2/emg/emg_process.py

@@ -39,7 +39,8 @@ def emg_process(emg_signal, sampling_rate=1000, report=None, **kwargs):
             EMG_Raw|The raw EMG signal.
             EMG_Clean|The cleaned EMG signal.
             EMG_Amplitude|The signal amplitude, or the activation of the signal.
-            EMG_Activity|The activity of the signal for which amplitude exceeds the threshold specified,marked as "1" in a list of zeros.
+            EMG_Activity|The activity of the signal for which amplitude exceeds the threshold \
+                specified,marked as "1" in a list of zeros.
             EMG_Onsets|The onsets of the amplitude, marked as "1" in a list of zeros.
             EMG_Offsets|The offsets of the amplitude, marked as "1" in a list of zeros.
 

neurokit2/hrv/hrv_frequency.py

@@ -104,15 +104,20 @@ def hrv_frequency(
         DataFrame consisting of the computed HRV frequency metrics, which includes:
 
         .. codebookadd::
-            HRV_ULF|The spectral power of ultra low frequencies (by default, .0 to .0033 Hz). Very long signals are required for this to index to be extracted, otherwise, will return NaN.
+            HRV_ULF|The spectral power of ultra low frequencies (by default, .0 to .0033 Hz). \
+                Very long signals are required for this to index to be extracted, otherwise, \
+                will return NaN.
             HRV_VLF|The spectral power of very low frequencies (by default, .0033 to .04 Hz).
             HRV_LF|The spectral power of low frequencies (by default, .04 to .15 Hz).
             HRV_HF|The spectral power of high frequencies (by default, .15 to .4 Hz).
             HRV_VHF|The spectral power of very high frequencies (by default, .4 to .5 Hz).
             HRV_TP|The total spectral power.
-            HRV_LFHF|The ratio obtained by dividing the low frequency power by the high frequency power.
-            HRV_LFn|The normalized low frequency, obtained by dividing the low frequency power by the total power.
-            HRV_HFn|The normalized high frequency, obtained by dividing the low frequency power by the total power.
+            HRV_LFHF|The ratio obtained by dividing the low frequency power by the high frequency \
+                power.
+            HRV_LFn|The normalized low frequency, obtained by dividing the low frequency power by \
+                the total power.
+            HRV_HFn|The normalized high frequency, obtained by dividing the low frequency power by \
+                the total power.
             HRV_LnHF|The log transformed HF.
 
     See Also

neurokit2/hrv/hrv_nonlinear.py

@@ -147,27 +147,52 @@ def hrv_nonlinear(peaks, sampling_rate=1000, show=False, **kwargs):
         DataFrame consisting of the computed non-linear HRV metrics, which includes:
 
         .. codebookadd::
-            HRV_SD1|Standard deviation perpendicular to the line of identity. It is an index of short-term RR interval fluctuations, i.e., beat-to-beat variability. It is equivalent (although on another scale) to RMSSD, and therefore it is redundant to report correlation with both.
+            HRV_SD1|Standard deviation perpendicular to the line of identity. It is an index of \
+                short-term RR interval fluctuations, i.e., beat-to-beat variability. It is \
+                equivalent (although on another scale) to RMSSD, and therefore it is redundant to \
+                report correlation with both.
             HRV_SD2|Standard deviation along the identity line. Index of long-term HRV changes.
-            HRV_SD1SD2|Ratio of SD1 to SD2. Describes the ratio of short term to long term variations in HRV.
-            HRV_S|Area of ellipse described by *SD1* and *SD2* (``pi * SD1 * SD2``). It is proportional to *SD1SD2*.
-            HRV_CSI|The Cardiac Sympathetic Index (Toichi, 1997) is a measure of cardiac sympathetic function independent of vagal activity, calculated by dividing the longitudinal variability of the Poincaré plot (``4*SD2``) by its transverse variability (``4*SD1``).
-            HRV_CVI|The Cardiac Vagal Index (Toichi, 1997) is an index of cardiac parasympathetic function (vagal activity unaffected by sympathetic activity), and is equal equal to the logarithm of the product of longitudinal (``4*SD2``) and transverse variability (``4*SD1``).
-            HRV_CSI_Modified|The modified CSI (Jeppesen, 2014) obtained by dividing the square of the longitudinal variability by its transverse variability.
-            HRV_GI|Guzik's Index, defined as the distance of points above line of identity (LI) to LI divided by the distance of all points in Poincaré plot to LI except those that are located on LI.
-            HRV_SI|Slope Index, defined as the phase angle of points above LI divided by the phase angle of all points in Poincaré plot except those that are located on LI.
-            HRV_AI|Area Index, defined as the cumulative area of the sectors corresponding to the points that are located above LI divided by the cumulative area of sectors corresponding to all points in the Poincaré plot except those that are located on LI.
-            HRV_PI|Porta's Index, defined as the number of points below LI divided by the total number of points in Poincaré plot except those that are located on LI.
-            HRV_SD1a|Short-term variance of contributions of decelerations (prolongations of RR intervals), (Piskorski, 2011).
-            HRV_SD1d|Short-term variance of contributions of accelerations (shortenings of RR intervals), (Piskorski, 2011).
-            HRV_C1a|The contributions of heart rate accelerations to short-term HRV, (Piskorski,  2011).
-            HRV_C1d|The contributions of heart rate decelerations to short-term HRV, (Piskorski,  2011).
-            HRV_SD2a|Long-term variance of contributions of accelerations (shortenings of RR intervals), (Piskorski, 2011).
-            HRV_SD2d|Long-term variance of contributions of decelerations (prolongations of RR intervals),  (Piskorski, 2011).
+            HRV_SD1SD2|Ratio of SD1 to SD2. Describes the ratio of short term to long term \
+                variations in HRV.
+            HRV_S|Area of ellipse described by *SD1* and *SD2* (``pi * SD1 * SD2``). It is \
+                proportional to *SD1SD2*.
+            HRV_CSI|The Cardiac Sympathetic Index (Toichi, 1997) is a measure of cardiac \
+                sympathetic function independent of vagal activity, calculated by dividing the \
+                longitudinal variability of the Poincaré plot (``4*SD2``) by its transverse \
+                variability (``4*SD1``).
+            HRV_CVI|The Cardiac Vagal Index (Toichi, 1997) is an index of cardiac parasympathetic \
+                function (vagal activity unaffected by sympathetic activity), and is equal equal \
+                to the logarithm of the product of longitudinal (``4*SD2``) and transverse \
+                variability (``4*SD1``).
+            HRV_CSI_Modified|The modified CSI (Jeppesen, 2014) obtained by dividing the square of \
+                the longitudinal variability by its transverse variability.
+            HRV_GI|Guzik's Index, defined as the distance of points above line of identity (LI) to \
+                LI divided by the distance of all points in Poincaré plot to LI except those that \
+                are located on LI.
+            HRV_SI|Slope Index, defined as the phase angle of points above LI divided by the phase \
+                angle of all points in Poincaré plot except those that are located on LI.
+            HRV_AI|Area Index, defined as the cumulative area of the sectors corresponding to the \
+                points that are located above LI divided by the cumulative area of sectors \
+                corresponding to all points in the Poincaré plot except those that are located \
+                on LI.
+            HRV_PI|Porta's Index, defined as the number of points below LI divided by the total \
+                number of points in Poincaré plot except those that are located on LI.
+            HRV_SD1a|Short-term variance of contributions of decelerations (prolongations of RR \
+                intervals), (Piskorski, 2011).
+            HRV_SD1d|Short-term variance of contributions of accelerations (shortenings of RR \
+                intervals), (Piskorski, 2011).
+            HRV_C1a|The contributions of heart rate accelerations to short-term HRV, (Piskorski, 2011).
+            HRV_C1d|The contributions of heart rate decelerations to short-term HRV, (Piskorski, 2011).
+            HRV_SD2a|Long-term variance of contributions of accelerations (shortenings of RR \
+                intervals), (Piskorski, 2011).
+            HRV_SD2d|Long-term variance of contributions of decelerations (prolongations of RR \
+                intervals),  (Piskorski, 2011).
             HRV_C2a|The contributions of heart rate accelerations to long-term HRV, (Piskorski, 2011).
             HRV_C2d|The contributions of heart rate decelerations to long-term HRV, (Piskorski, 2011).
-            HRV_SDNNa|Total variance of contributions of accelerations (shortenings of RR intervals), (Piskorski, 2011).
-            HRV_SDNNd|Total variance of contributions of decelerations (prolongations of RR intervals), (Piskorski, 2011).
+            HRV_SDNNa|Total variance of contributions of accelerations (shortenings of RR \
+                intervals), (Piskorski, 2011).
+            HRV_SDNNd|Total variance of contributions of decelerations (prolongations of RR \
+                intervals), (Piskorski, 2011).
             HRV_Ca|The total contributions of heart rate accelerations to HRV.
             HRV_Cd|The total contributions of heart rate decelerations to HRV.
             HRV_PIP|Percentage of inflection points of the RR intervals series.

neurokit2/ppg/ppg_eventrelated.py

@@ -41,7 +41,8 @@ def ppg_eventrelated(epochs, silent=False):
         .. codebookadd::
             PPG_Rate_Trend_Linear|The parameter corresponding to the linear trend.
             PPG_Rate_Trend_Quadratic|The parameter corresponding to the curvature.
-            PPG_Rate_Trend_R2|The quality of the quadratic model. If too low, the parameters might not be reliable or meaningful.
+            PPG_Rate_Trend_R2|The quality of the quadratic model. If too low, the parameters \
+                might not be reliable or meaningful.
 
     See Also
     --------

neurokit2/rsp/rsp_process.py

@@ -61,11 +61,13 @@ def rsp_process(
             RSP_Raw|The raw signal.
             RSP_Clean|The raw signal.
             RSP_Peaks|The respiratory peaks (exhalation onsets) marked as "1" in a list of zeros.
-            RSP_Troughs|The respiratory troughs (inhalation onsets) marked as "1" in a list of zeros.
+            RSP_Troughs|The respiratory troughs (inhalation onsets) marked as "1" in a list \
+                of zeros.
             RSP_Rate|The breathing rate interpolated between inhalation peaks.
             RSP_Amplitude|The breathing amplitude interpolated between inhalation peaks.
             RSP_Phase|The breathing phase, marked by "1" for inspiration and "0" for expiration.
-            RSP_Phase_Completion|The breathing phase completion, expressed in percentage (from 0 to 1), representing the stage of the current respiratory phase.
+            RSP_Phase_Completion|The breathing phase completion, expressed in percentage \
+                (from 0 to 1), representing the stage of the current respiratory phase.
             RSP_RVT|Respiratory volume per time (RVT).
 
     info : dict