def graph_data_distribution(graph, color_function, colorscale, nbins=10):
node_averages = []
for node_id, member_ids in graph["nodes"].items():
member_colors = color_function[member_ids]
node_averages.append(np.mean(member_colors))
histogram = build_histogram(node_averages,
colorscale=colorscale,
nbins=nbins)
return histogram
def test_color_hist_matches_nodes(self):
""" The histogram colors dont seem to match the node colors, this should confirm the colors will match and we need to look at the javascript instead.
"""
color_values = np.array([0.55] * 10 + [0.0] * 10)
member_ids = [1, 2, 3, 4, 5, 6]
hist = build_histogram(color_values[member_ids])
c = round(_node_color_function(member_ids, color_values), 2)
single_bar = [bar for bar in hist if bar["perc"] == 100.0]
assert len(single_bar) == 1
assert _map_val2color(c, 0.0, 1.0) == single_bar[0]["color"]
def _tooltip_components(
member_ids,
X,
X_names,
lens,
lens_names,
color_function,
node_ID,
colorscale,
nbins=10,
):
projection_stats = km.visuals._format_projection_statistics(
member_ids, lens, lens_names)
cluster_stats = km.visuals._format_cluster_statistics(
member_ids, X, X_names)
member_histogram = build_histogram(color_function[member_ids],
colorscale=colorscale,
nbins=nbins)
return projection_stats, cluster_stats, member_histogram
def test_histogram(self):
data = np.random.random((100, 1))
hist = visuals.build_histogram(data)
assert isinstance(hist, list)
assert isinstance(hist[0], dict)
assert len(hist) == 10
