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Make unary matrix prettier #201

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Sep 18, 2024
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Make unary matrix prettier #201

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46 changes: 22 additions & 24 deletions py/visualize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,8 +25,9 @@ def make_numpy_matrix(obs, entities, relations):
for ob in obs:
val = ob.value
ent_index = entities.index(ob.items[0])
rel_index = relations.index(ob.relation)
m[ent_index][rel_index] = val
if ob.relation in relations:
rel_index = relations.index(ob.relation)
m[ent_index][rel_index] = val
return m


Expand All @@ -35,14 +36,13 @@ def normalize_matrix(m):
return (m - np.min(m)) / np.ptp(m)


def unary_matrix(cluster, obs, all_relations, clusters):
def unary_matrix(cluster, obs, clusters):
"""Plot a matrix visualization for the cluster of unary relations."""
fig = plt.figure()
ax = plt.gca()
fontsize = 12

ax.xaxis.tick_top()
ax.set_xticks(np.arange(len(all_relations)))
ax.set_xticklabels(all_relations, rotation=90)
relations = sorted(cluster.relations)
num_columns = len(relations)
longest_relation_length = max(len(r) for r in relations)

all_entities = []
domain = ""
Expand All @@ -53,27 +53,26 @@ def unary_matrix(cluster, obs, all_relations, clusters):
print("Error in unary_matrix: Found multiple domains in clusters")
sys.exit(1)

all_entities.extend(dc.entities)
all_entities.extend(sorted(dc.entities))

num_rows = len(all_entities)
longest_entity_length = max(len(e) for e in all_entities)

ax.set_yticks(np.arange(len(all_entities)))
ax.set_yticklabels(all_entities)
width = (num_columns + longest_entity_length) * fontsize / 72.0 + 0.2 # Fontsize is in points, 1 pt = 1/72in
height = (num_rows + longest_relation_length) * fontsize / 72.0 + 0.2
fig, ax = plt.subplots(figsize=(width,height))

ax.xaxis.tick_top()
ax.set_xticks(np.arange(num_columns), labels=relations,
rotation=90, fontsize=fontsize)
ax.set_yticks(np.arange(num_rows), labels=all_entities, fontsize=fontsize)

# Matrix of data
m = make_numpy_matrix(obs, all_entities, all_relations)
m = make_numpy_matrix(obs, all_entities, relations)
cmap = copy.copy(plt.get_cmap('Greys'))
cmap.set_bad(color='gray')
ax.imshow(normalize_matrix(m))

# Red lines between columns (relations)
d = 0
for c in clusters:
if cluster.cluster_id == c.cluster_id:
ax.axvline(d - 0.5, color='r', linewidth=2)
d += len(clusters[i].relations)
if cluster.cluster_id == c.cluster_id:
ax.axvline(d - 0.5, color='r', linewidth=2)
break

# Red lines between rows (entities)
n = 0
for dc in cluster.domain_clusters:
Expand All @@ -87,11 +86,10 @@ def unary_matrix(cluster, obs, all_relations, clusters):

def plot_unary_matrices(clusters, obs, output):
"""Write a matrix visualization for each cluster in clusters."""
all_relations = sum([c.relations for c in clusters], [])
with open(output, 'w') as f:
f.write("<html><body>\n\n")
for cluster in clusters:
f.write("<h1>IRM #" + cluster.cluster_id + "\n")
fig = unary_matrix(cluster, obs, all_relations, clusters)
fig = unary_matrix(cluster, obs, clusters)
f.write(figure_to_html(fig) + "\n\n")
f.write("</body></html>\n")