def format_eff_robust(df, x_axis, y_axis_fit, transform):
df_line = df[df.use_for_line_fit == True]
x_acc_line_trans = transform_acc(df_line[x_axis], transform)
y_acc_line_trans = transform_acc(df_line[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis], transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust'] = df[y_axis_fit] - lin_fit_ys
return df
def format_eff_robust(df, x_axis, y_axis, x_axis_fit, y_axis_fit, transform):
df_line = df[df.use_for_line_fit == True]
if (df_line[y_axis_fit] == 0).any():
pivot = df_line[df_line[y_axis_fit] == 0][x_axis_fit][0]
df_line1 = df_line[df_line[x_axis_fit] < pivot]
x_acc_line_trans = transform_acc(df_line1[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line1[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust_y'] = df[y_axis_fit] - lin_fit_ys
df_line2 = df_line[df_line[x_axis_fit] > pivot]
x_acc_line_trans = transform_acc(df_line2[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line2[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df.loc[df[x_axis_fit] > pivot,
'eff_robust_y'] = (df[y_axis_fit] -
lin_fit_ys)[df[x_axis_fit] > pivot]
else:
x_acc_line_trans = transform_acc(df_line[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust_y'] = df[y_axis_fit] - lin_fit_ys
x_acc_line_trans = transform_acc(df_line[x_axis], transform)
y_acc_line_trans = transform_acc(df_line[y_axis], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis], transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust_x'] = df[y_axis] - lin_fit_ys
return df
def calc_eff_robust_corr(df, transform, x_axis, y_axis, x_axis_fit,
y_axis_fit):
df = df.copy()
df_line = df[df.use_for_line_fit == True]
if (df_line[y_axis_fit] == 0).any():
pivot = df_line[df_line[y_axis_fit] == 0][x_axis_fit][0]
df_line1 = df_line[df_line[x_axis_fit] < pivot]
x_acc_line_trans = transform_acc(df_line1[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line1[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust_y'] = df[y_axis_fit] - lin_fit_ys
df_line2 = df_line[df_line[x_axis_fit] > pivot]
x_acc_line_trans = transform_acc(df_line2[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line2[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df.loc[df[x_axis_fit] > pivot,
'eff_robust_y'] = (df[y_axis_fit] -
lin_fit_ys)[df[x_axis_fit] > pivot]
else:
x_acc_line_trans = transform_acc(df_line[x_axis_fit], transform)
y_acc_line_trans = transform_acc(df_line[y_axis_fit], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df[x_axis_fit],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df['eff_robust_y'] = df[y_axis_fit] - lin_fit_ys
df2 = df[[x_axis, y_axis, 'use_for_line_fit']].dropna()
df_line2 = df2[df2.use_for_line_fit == True]
x_acc_line_trans = transform_acc(df_line2[x_axis], transform)
y_acc_line_trans = transform_acc(df_line2[y_axis], transform)
lin_fit = scipy.stats.linregress(x_acc_line_trans, y_acc_line_trans)
intercept, slope = lin_fit[1], lin_fit[0]
lin_fit_ys_trans = transform_acc(df2[x_axis],
transform) * slope + intercept
lin_fit_ys = inv_transform_acc(lin_fit_ys_trans, transform)
df.loc[df2.index, 'eff_robust_x'] = df2[y_axis] - lin_fit_ys
df = df[df.show_in_plot][['eff_robust_x', 'eff_robust_y']].dropna()
return scipy.stats.pearsonr(df['eff_robust_x'], df['eff_robust_y'])[0]