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Update visualize for main changes #179

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Merged
merged 2 commits into from
Oct 24, 2022
Merged

Update visualize for main changes #179

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bbcd465
Update visualize for main changes
dcherian Oct 24, 2022
40b7c28
Update tests/__init__.py
dcherian Oct 24, 2022
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27 changes: 15 additions & 12 deletions flox/visualize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
import numpy as np
import pandas as pd

from .core import find_group_cohorts
from .core import _unique, find_group_cohorts


def draw_mesh(
Expand Down Expand Up @@ -131,14 +131,14 @@ def factorize_cohorts(by, cohorts):
return factorized


def visualize_cohorts_2d(by, array, method="cohorts"):
def visualize_cohorts_2d(by, array):
assert by.ndim == 2
print("finding cohorts...")
before_merged = find_group_cohorts(
by, [array.chunks[ax] for ax in range(-by.ndim, 0)], merge=False, method=method
by, [array.chunks[ax] for ax in range(-by.ndim, 0)], merge=False
).values()
merged = find_group_cohorts(
by, [array.chunks[ax] for ax in range(-by.ndim, 0)], merge=True, method=method
by, [array.chunks[ax] for ax in range(-by.ndim, 0)], merge=True
).values()
print("finished cohorts...")

Expand All @@ -149,16 +149,12 @@ def visualize_cohorts_2d(by, array, method="cohorts"):
ax = ax.ravel()
ax[1].set_visible(False)
ax = ax[[0, 2, 3]]
flat = by.ravel()
ngroups = len(np.unique(flat[~np.isnan(flat)]))

ngroups = len(_unique(by))
h0 = ax[0].imshow(by, cmap=get_colormap(ngroups))
h1 = ax[1].imshow(
factorize_cohorts(by, before_merged),
vmin=0,
cmap=get_colormap(len(before_merged)),
)
h2 = ax[2].imshow(factorize_cohorts(by, merged), vmin=0, cmap=get_colormap(len(merged)))
h1 = _visualize_cohorts(by, before_merged, ax=ax[1])
h2 = _visualize_cohorts(by, merged, ax=ax[2])

for axx in ax:
axx.grid(True, which="both")
axx.set_xticks(xticks)
Expand All @@ -170,3 +166,10 @@ def visualize_cohorts_2d(by, array, method="cohorts"):
ax[1].set_title(f"{len(before_merged)} cohorts")
ax[2].set_title(f"{len(merged)} merged cohorts")
f.set_size_inches((6, 6))


def _visualize_cohorts(by, cohorts, ax=None):
if ax is None:
_, ax = plt.subplots(1, 1)

ax.imshow(factorize_cohorts(by, cohorts), vmin=0, cmap=get_colormap(len(cohorts)))