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another bug
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@j-i-l
j-i-l committed Feb 20, 2020
1 parent fe21fa6 commit 473493b
Showing 1 changed file with 91 additions and 90 deletions.
181 changes: 91 additions & 90 deletions pyalluv/plotting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,97 +325,98 @@ def distribute_clusters(self, x_pos):
attribute.
"""
nbr_clusters = len(self.clusters[x_pos])
# sort clusters according to height
_clusters = sorted(self.clusters[x_pos], key=lambda x: x.height)
# sort so to put biggest height in the middle
self.clusters[x_pos] = _clusters[::-2][::-1] + \
_clusters[nbr_clusters % 2::2][::-1]
# set positioning
self._distribute_column(x_pos, self.cluster_w_spacing)
# now sort again considering the fluxes.
old_mid_heights = [
cluster.mid_height for cluster in self.clusters[x_pos]
]
# do the redistribution 4 times
_redistribute = False
for _ in range(self._redistribute_vertically):
for cluster in self.clusters[x_pos]:
weights = []
positions = []
for in_flux in cluster.in_fluxes:
if in_flux.source_cluster is not None:
weights.append(in_flux.flux_width)
positions.append(in_flux.source_cluster.mid_height)
if sum(weights) > 0.0:
_redistribute = True
cluster.set_mid_height(
sum(
[weights[i] * positions[i]
for i in range(len(weights))]
) / sum(weights)
)
if _redistribute:
sort_key = [
bisect_left(
old_mid_heights, self.clusters[x_pos][i].mid_height
) for i in range(nbr_clusters)
]
cs, _sort_key = zip(
*sorted(
zip(
list(range(nbr_clusters)),
sort_key,
),
key=lambda x: x[1]
)
)
self.clusters[x_pos] = [self.clusters[x_pos][_k] for _k in cs]
# redistribute them
self._distribute_column(x_pos, self.cluster_w_spacing)
old_mid_heights = [
if nbr_clusters:
# sort clusters according to height
_clusters = sorted(self.clusters[x_pos], key=lambda x: x.height)
# sort so to put biggest height in the middle
self.clusters[x_pos] = _clusters[::-2][::-1] + \
_clusters[nbr_clusters % 2::2][::-1]
# set positioning
self._distribute_column(x_pos, self.cluster_w_spacing)
# now sort again considering the fluxes.
old_mid_heights = [
cluster.mid_height for cluster in self.clusters[x_pos]
]
else:
break
# perform pairwise swapping for backwards fluxes
for _ in range(int(0.5 * nbr_clusters)):
for i in range(1, nbr_clusters):
n1, n2 = self.clusters[x_pos][i-1], self.clusters[x_pos][i]
if self._swap_clusters(n1, n2, 'backwards'):
n2.set_y_pos(n1.y_pos)
n1.set_y_pos(
n2.y_pos + n2.height + self.cluster_w_spacing
)
self.clusters[x_pos][i-1], self.clusters[x_pos][i] = n2, n1
for _ in range(int(0.5 * nbr_clusters)):
for i in range(1, nbr_clusters):
n1 = self.clusters[x_pos][nbr_clusters-i-1]
n2 = self.clusters[x_pos][nbr_clusters-i]
if self._swap_clusters(n1, n2, 'backwards'):
n2.set_y_pos(n1.y_pos)
n1.set_y_pos(
n2.y_pos + n2.height + self.cluster_w_spacing
)
self.clusters[x_pos][nbr_clusters-i-1] = n2
self.clusters[x_pos][nbr_clusters-i] = n1

_min_y = min(
self.clusters[x_pos], key=lambda x: x.y_pos
).y_pos - 2 * self.cluster_w_spacing
_max_y_cluster = max(
self.clusters[x_pos],
key=lambda x: x.y_pos + x.height
)
_max_y = _max_y_cluster.y_pos + \
_max_y_cluster.height + 2 * self.cluster_w_spacing
self.y_min = min(
self.y_min,
_min_y
) if self.y_min is not None else _min_y
self.y_max = max(
self.y_max,
_max_y
) if self.y_max is not None else _max_y
]
# do the redistribution 4 times
_redistribute = False
for _ in range(self._redistribute_vertically):
for cluster in self.clusters[x_pos]:
weights = []
positions = []
for in_flux in cluster.in_fluxes:
if in_flux.source_cluster is not None:
weights.append(in_flux.flux_width)
positions.append(in_flux.source_cluster.mid_height)
if sum(weights) > 0.0:
_redistribute = True
cluster.set_mid_height(
sum(
[weights[i] * positions[i]
for i in range(len(weights))]
) / sum(weights)
)
if _redistribute:
sort_key = [
bisect_left(
old_mid_heights, self.clusters[x_pos][i].mid_height
) for i in range(nbr_clusters)
]
cs, _sort_key = zip(
*sorted(
zip(
list(range(nbr_clusters)),
sort_key,
),
key=lambda x: x[1]
)
)
self.clusters[x_pos] = [self.clusters[x_pos][_k] for _k in cs]
# redistribute them
self._distribute_column(x_pos, self.cluster_w_spacing)
old_mid_heights = [
cluster.mid_height for cluster in self.clusters[x_pos]
]
else:
break
# perform pairwise swapping for backwards fluxes
for _ in range(int(0.5 * nbr_clusters)):
for i in range(1, nbr_clusters):
n1, n2 = self.clusters[x_pos][i-1], self.clusters[x_pos][i]
if self._swap_clusters(n1, n2, 'backwards'):
n2.set_y_pos(n1.y_pos)
n1.set_y_pos(
n2.y_pos + n2.height + self.cluster_w_spacing
)
self.clusters[x_pos][i-1], self.clusters[x_pos][i] = n2, n1
for _ in range(int(0.5 * nbr_clusters)):
for i in range(1, nbr_clusters):
n1 = self.clusters[x_pos][nbr_clusters-i-1]
n2 = self.clusters[x_pos][nbr_clusters-i]
if self._swap_clusters(n1, n2, 'backwards'):
n2.set_y_pos(n1.y_pos)
n1.set_y_pos(
n2.y_pos + n2.height + self.cluster_w_spacing
)
self.clusters[x_pos][nbr_clusters-i-1] = n2
self.clusters[x_pos][nbr_clusters-i] = n1

_min_y = min(
self.clusters[x_pos], key=lambda x: x.y_pos
).y_pos - 2 * self.cluster_w_spacing
_max_y_cluster = max(
self.clusters[x_pos],
key=lambda x: x.y_pos + x.height
)
_max_y = _max_y_cluster.y_pos + \
_max_y_cluster.height + 2 * self.cluster_w_spacing
self.y_min = min(
self.y_min,
_min_y
) if self.y_min is not None else _min_y
self.y_max = max(
self.y_max,
_max_y
) if self.y_max is not None else _max_y

def set_dates_xaxis(self, ax, resolution='months'):
r"""
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