Commit 199d6504 authored by Félix Hartmann's avatar Félix Hartmann
Browse files

[bugfix] Remove all underscores ('_') used as dummy variables.

parent 71c43192
......@@ -683,8 +683,8 @@ def _export_to_csv():
for i in range(len(base_tiges)):
hdfid = hdf_tiges_id[i]
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone,\
_ = load_postprocessed_data(hdf5file, hdfid)
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone, \
dummy = load_postprocessed_data(hdf5file, hdfid)
tige_R = tiges_data.diam[i]/2.0
tige_name = tiges_names[i]
......@@ -756,7 +756,7 @@ def _export_xytemps_to_csv():
hdfid = hdf_tiges_id[i]
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone,\
_ = load_postprocessed_data(hdf5file, hdfid)
dummy = load_postprocessed_data(hdf5file, hdfid)
tige_R = tiges_data.diam[i]/2.0
tige_name = tiges_names[i]
......@@ -810,8 +810,8 @@ def _export_mean_to_csv():
for i in range(len(base_tiges)):
hdfid = hdf_tiges_id[i]
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone,\
_ = load_postprocessed_data(hdf5file, hdfid)
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone, \
dummy = load_postprocessed_data(hdf5file, hdfid)
tige_R = tiges_data.diam[i]/2.0
tige_name = tiges_names[i]
......@@ -868,8 +868,8 @@ def _export_meandata_for_each_tiges():
for i in range(len(base_tiges)):
hdfid = hdf_tiges_id[i]
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone,\
_ = load_postprocessed_data(hdf5file, hdfid)
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone, \
dummy = load_postprocessed_data(hdf5file, hdfid)
tige_R = tiges_data.diam[i]/2.0
tige_name = tiges_names[i]
......@@ -2535,7 +2535,8 @@ def show_beta_tilde():
i2 = flatnonzero(times >= t2)[0]
fit_zone = slice(i1, i2)
fit_tip_angles, res, _, _, _ = ma.polyfit(times[fit_zone], tip_angles[fit_zone],
# 'd' is for 'dummy'
fit_tip_angles, res, d, d, d = ma.polyfit(times[fit_zone], tip_angles[fit_zone],
1, full=True)
dAdt, intercept = fit_tip_angles[0], fit_tip_angles[1]
plfit_angles.set_data(times[fit_zone], dAdt * times[fit_zone] + intercept)
......@@ -2854,7 +2855,8 @@ def show_gamma_tilde():
# - http://mathworld.wolfram.com/LeastSquaresFittingExponential.html
# - https://stackoverflow.com/questions/3433486/how-to-do-exponential-and-logarithmic-curve-fitting-in-python-i-found-only-poly
weights = ma.sqrt(A_dev_range)
fit_log_A_dev, res, _, _, _ = ma.polyfit(time_range, log_A_dev_range, 1,
# 'd' is for 'dummy'
fit_log_A_dev, res, d, d, d = ma.polyfit(time_range, log_A_dev_range, 1,
w=weights, full=True)
weighted_mean = mean(weights * log_A_dev_range)
......@@ -3251,8 +3253,8 @@ def plot_moyenne():
for i in range(len(base_tiges)):
hdfid = hdf_tiges_id[i]
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone,\
_ = load_postprocessed_data(hdf5file, hdfid)
tige_x, tige_y, tige_s, tige_taille, tige_angle, tige_tip_angle, tige_zone, \
dummy = load_postprocessed_data(hdf5file, hdfid)
tige_R = tiges_data.diam[i]/2.0
tige_name = tiges_names[i]
......@@ -4739,7 +4741,8 @@ class Interekt:
# Retrieve tige ids from the h5 file
hdf_tiges_id = h5store.get_tiges_indices(hdf5file)
hdfid = hdf_tiges_id[tige]
smoothed_x, smoothed_y, s, _, angles, _, _, _ = \
# 'd' is for 'dummy'
smoothed_x, smoothed_y, s, d, angles, d, d, d = \
load_postprocessed_data(hdf5file, hdfid)
s, angles = s[image], angles[image]
# Remove non-valid values
......
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