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Code Duplication    Length = 27-27 lines in 3 locations

app/core.py 1 location

@@ 393-419 (lines=27) @@
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    return half_wave_potential
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def peak_heights(DataFrame_x, DataFrame_y):
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    """Outputs heights of minimum peak and maximum
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         peak from cyclic voltammetry data.
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       Parameters
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       ----------
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       DataFrame_x : should be in the form of a pandas DataFrame column.
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         For example, df['potentials'] could be input as the column of x
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         data.
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        DataFrame_y : should be in the form of a pandas DataFrame column.
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          For example, df['currents'] could be input as the column of y
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          data.
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        Returns
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        -------
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        Results: height of maximum peak, height of minimum peak
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          in that order in the form of a list."""
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    current_max = peak_values(DataFrame_x, DataFrame_y)[1]
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    current_min = peak_values(DataFrame_x, DataFrame_y)[3]
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    x1, x2 = split(DataFrame_x)
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    y1, y2 = split(DataFrame_y)
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    line_at_min = linear_background(x1, y1)[peak_detection_fxn(DataFrame_y)[1]]
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    line_at_max = linear_background(x2, y2)[peak_detection_fxn(DataFrame_y)[0]]
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    height_of_max = current_max - line_at_max
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    height_of_min = abs(current_min - line_at_min)
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    return [height_of_max, height_of_min]
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def peak_ratio(DataFrame_x, DataFrame_y):

voltcycle/core.py 1 location

@@ 349-375 (lines=27) @@
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    return half_wave_potential
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def peak_heights(DataFrame_x, DataFrame_y):
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    """Outputs heights of minimum peak and maximum
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         peak from cyclic voltammetry data.
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       Parameters
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       ----------
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       DataFrame_x : should be in the form of a pandas DataFrame column.
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         For example, df['potentials'] could be input as the column of x
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         data.
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        DataFrame_y : should be in the form of a pandas DataFrame column.
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          For example, df['currents'] could be input as the column of y
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          data.
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        Returns
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        -------
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        Results: height of maximum peak, height of minimum peak
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          in that order in the form of a list."""
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    current_max = peak_values(DataFrame_x, DataFrame_y)[1]
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    current_min = peak_values(DataFrame_x, DataFrame_y)[3]
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    x1, x2 = split(DataFrame_x)
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    y1, y2 = split(DataFrame_y)
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    line_at_min = linear_background(x1, y1)[peak_detection_fxn(DataFrame_y)[1]]
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    line_at_max = linear_background(x2, y2)[peak_detection_fxn(DataFrame_y)[0]]
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    height_of_max = current_max - line_at_max
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    height_of_min = abs(current_min - line_at_min)
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    return [height_of_max, height_of_min]
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def peak_ratio(DataFrame_x, DataFrame_y):

voltcycle/submodule/calculations.py 1 location

@@ 81-107 (lines=27) @@
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    return half_wave_potential
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def peak_heights(DataFrame_x, DataFrame_y):
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    """Outputs heights of minimum peak and maximum
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         peak from cyclic voltammetry data.
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       Parameters
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       ----------
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       DataFrame_x : should be in the form of a pandas DataFrame column.
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         For example, df['potentials'] could be input as the column of x
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         data.
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        DataFrame_y : should be in the form of a pandas DataFrame column.
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          For example, df['currents'] could be input as the column of y
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          data.
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        Returns
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        -------
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        Results: height of maximum peak, height of minimum peak
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          in that order in the form of a list."""
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    current_max = peak_values(DataFrame_x, DataFrame_y)[1]
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    current_min = peak_values(DataFrame_x, DataFrame_y)[3]
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    x1, x2 = split(DataFrame_x)
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    y1, y2 = split(DataFrame_y)
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    line_at_min = linear_background(x1, y1)[peak_detection(DataFrame_y)[1]]
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    line_at_max = linear_background(x2, y2)[peak_detection(DataFrame_y)[0]]
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    height_of_max = current_max - line_at_max
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    height_of_min = abs(current_min - line_at_min)
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    return [height_of_max, height_of_min]
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def peak_ratio(DataFrame_x, DataFrame_y):