Version 1.3.0.
Addition of an extra layer of outlier detection before normalization for the values before stimulation:
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Values that are lower than the the lower quartile minus 1.5 * Interquartile range of the median skeleton length before stimulation are discarded
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Values that are higher than the the upper quartile plus 1.5 * Interquartile range of the median skeleton length before stimulation are discarded
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This avoids that average values before stimulation are not equal to 1.0 due to strong outliers that affect normalization
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Fixed a bug where Normalization and Data Analysis functions are only possible, when raw_angle files are present. Now possible without.