def locate_valleys(self, scale=0.3, smooth=1, interpolate_past=200):
xs = self.xs
ys = self.ys
if len(xs) > interpolate_past:
xs, ys = self.interpolate(xs, ys, interpolate_past)
if smooth:
ys = smooth_leveled(xs, ys, smooth)
maxima_indices, minima_indices = self._extreme_indices(ys)
candidates = []
for i in range(len(maxima_indices)):
max_i = maxima_indices[i]
for j in range(i + 1, len(maxima_indices)):
max_j = maxima_indices[j]
for k in range(len(minima_indices)):
min_k = minima_indices[k]
y_i = ys[max_i]
y_j = ys[max_j]
y_k = ys[min_k]
if max_i < min_k < max_j and (y_i - y_k) > (y_i * scale) and (
y_j - y_k) > (y_j * scale):
point = ValleyPoint(y_i, y_k, y_j, xs[max_i], xs[min_k], xs[max_j])
candidates.append(point)
if candidates:
candidates = sorted(candidates, key=lambda x: x.total_distance, reverse=True)
best_point = candidates[0]
self.partition_sites.append(best_point)
return candidates
def locate_valleys(self, scale=0.3, smooth=1, interpolate_past=200):
xs = self.xs
ys = self.ys
if len(xs) > interpolate_past:
xs, ys = self.interpolate(xs, ys, interpolate_past)
if smooth:
ys = smooth_leveled(xs, ys, smooth)
maxima_indices, minima_indices = self._extreme_indices(ys)
candidates = []
for i in range(len(maxima_indices)):
max_i = maxima_indices[i]
for j in range(i + 1, len(maxima_indices)):
max_j = maxima_indices[j]
for k in range(len(minima_indices)):
min_k = minima_indices[k]
y_i = ys[max_i]
y_j = ys[max_j]
y_k = ys[min_k]
if max_i < min_k < max_j and (y_i - y_k) > (y_i * scale) and (
y_j - y_k) > (y_j * scale):
point = ValleyPoint(y_i, y_k, y_j, xs[max_i], xs[min_k], xs[max_j])
candidates.append(point)
if candidates:
candidates = sorted(candidates, key=lambda x: x.total_distance, reverse=True)
best_point = candidates[0]
self.partition_sites.append(best_point)
return candidates
def is_flat(feature, fraction=0.5, smooth=1):
xs, ys = feature.as_arrays()
ys = smooth_leveled(xs, ys, smooth)
apex = ys.max()
return apex * fraction < ys[0] and apex * fraction < ys[-1]
def is_flat(feature, fraction=0.5, smooth=1):
xs, ys = feature.as_arrays()
ys = smooth_leveled(xs, ys, smooth)
apex = ys.max()
return apex * fraction < ys[0] and apex * fraction < ys[-1]