X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/blobdiff_plain/4447c60265c5c5de3281ca135461d91ab5339f03..f20365c07e93ae71b95af314f869fcdcfb58100f:/visualization/tsne_vis.py diff --git a/visualization/tsne_vis.py b/visualization/tsne_vis.py index 1e2aeae..c39a740 100644 --- a/visualization/tsne_vis.py +++ b/visualization/tsne_vis.py @@ -1,37 +1,175 @@ import pyarrow import altair as alt alt.data_transformers.disable_max_rows() -alt.data_transformers.enable('data_server') +alt.data_transformers.enable('default') +from sklearn.neighbors import NearestNeighbors import pandas as pd from numpy import random +import fire import numpy as np -from sklearn.manifold import TSNE -pd.read_feather("tsne_subreddit_fit.feather") +def base_plot(plot_data): -slider = alt.binding_range(min=1,max=100,step=1,name='zoom: ') -selector = alt.selection_single(name='zoomselect',fields=['zoom'],bind='scales',init={'zoom':1}) +# base = base.encode(alt.Color(field='color',type='nominal',scale=alt.Scale(scheme='category10'))) -xrange = plot_data.x.max()-plot_data.x.min() -yrange = plot_data.y.max()-plot_data.y.min() + cluster_dropdown = alt.binding_select(options=[str(c) for c in sorted(set(plot_data.cluster))]) -chart = alt.Chart(plot_data).mark_text().encode( - alt.X('x',axis=alt.Axis(grid=False)), - alt.Y('y',axis=alt.Axis(grid=False)), - text='subreddit') + # subreddit_dropdown = alt.binding_select(options=sorted(plot_data.subreddit)) -#chart = chart.add_selection(selector) + cluster_click_select = alt.selection_single(on='click',fields=['cluster'], bind=cluster_dropdown, name=' ') + # cluster_select = alt.selection_single(fields=['cluster'], bind=cluster_dropdown, name='cluster') + # cluster_select_and = cluster_click_select & cluster_select + # + # subreddit_select = alt.selection_single(on='click',fields=['subreddit'],bind=subreddit_dropdown,name='subreddit_click') + + color = alt.condition(cluster_click_select , + alt.Color(field='color',type='nominal',scale=alt.Scale(scheme='category10')), + alt.value("lightgray")) + + + base = alt.Chart(plot_data).mark_text().encode( + alt.X('x',axis=alt.Axis(grid=False),scale=alt.Scale(domain=(-65,65))), + alt.Y('y',axis=alt.Axis(grid=False),scale=alt.Scale(domain=(-65,65))), + color=color, + text='subreddit') -chart = chart.configure_view( - continuousHeight=xrange/20, - continuousWidth=yrange/20 -) + base = base.add_selection(cluster_click_select) + -amount_shown = lambda zoom: {'width':xrange/zoom,'height':yrange/zoom} + return base -alt.data_transformers.enable('default') -chart = chart.properties(width=1000,height=1000) -chart = chart.interactive() -chart.save("test_tsne_whole.html") -chart = chart.properties(width=10000,height=10000) -chart.save("test_tsne_whole.svg") +def zoom_plot(plot_data): + chart = base_plot(plot_data) + + chart = chart.interactive() + chart = chart.properties(width=1275,height=800) + + return chart + +def viewport_plot(plot_data): + selector1 = alt.selection_interval(encodings=['x','y'],init={'x':(-65,65),'y':(-65,65)}) + selectorx2 = alt.selection_interval(encodings=['x'],init={'x':(30,40)}) + selectory2 = alt.selection_interval(encodings=['y'],init={'y':(-20,0)}) + + base = base_plot(plot_data) + + viewport = base.mark_point(fillOpacity=0.2,opacity=0.2).encode( + alt.X('x',axis=alt.Axis(grid=False)), + alt.Y('y',axis=alt.Axis(grid=False)), + ) + + viewport = viewport.properties(width=600,height=400) + + viewport1 = viewport.add_selection(selector1) + + viewport2 = viewport.encode( + alt.X('x',axis=alt.Axis(grid=False),scale=alt.Scale(domain=selector1)), + alt.Y('y',axis=alt.Axis(grid=False),scale=alt.Scale(domain=selector1)) + ) + + viewport2 = viewport2.add_selection(selectorx2) + viewport2 = viewport2.add_selection(selectory2) + + sr = base.encode(alt.X('x',axis=alt.Axis(grid=False),scale=alt.Scale(domain=selectorx2)), + alt.Y('y',axis=alt.Axis(grid=False),scale=alt.Scale(domain=selectory2)) + ) + + + sr = sr.properties(width=1275,height=600) + + + chart = (viewport1 | viewport2) & sr + + + return chart + +def assign_cluster_colors(tsne_data, clusters, n_colors, n_neighbors = 4): + tsne_data = tsne_data.merge(clusters,on='subreddit') + + centroids = tsne_data.groupby('cluster').agg({'x':np.mean,'y':np.mean}) + + color_ids = np.arange(n_colors) + + distances = np.empty(shape=(centroids.shape[0],centroids.shape[0])) + + groups = tsne_data.groupby('cluster') + + points = np.array(tsne_data.loc[:,['x','y']]) + centers = np.array(centroids.loc[:,['x','y']]) + + # point x centroid + point_center_distances = np.linalg.norm((points[:,None,:] - centers[None,:,:]),axis=-1) + + # distances is cluster x point + for gid, group in groups: + c_dists = point_center_distances[group.index.values,:].min(axis=0) + distances[group.cluster.values[0],] = c_dists + + # nbrs = NearestNeighbors(n_neighbors=n_neighbors).fit(centroids) + # distances, indices = nbrs.kneighbors() + + nearest = distances.argpartition(n_neighbors,0) + indices = nearest[:n_neighbors,:].T + # neighbor_distances = np.copy(distances) + # neighbor_distances.sort(0) + # neighbor_distances = neighbor_distances[0:n_neighbors,:] + + # nbrs = NearestNeighbors(n_neighbors=n_neighbors,metric='precomputed').fit(distances) + # distances, indices = nbrs.kneighbors() + + color_assignments = np.repeat(-1,len(centroids)) + + for i in range(len(centroids)): + knn = indices[i] + knn_colors = color_assignments[knn] + available_colors = color_ids[list(set(color_ids) - set(knn_colors))] + + if(len(available_colors) > 0): + color_assignments[i] = available_colors[0] + else: + raise Exception("Can't color this many neighbors with this many colors") + + + centroids = centroids.reset_index() + colors = centroids.loc[:,['cluster']] + colors['color'] = color_assignments + + tsne_data = tsne_data.merge(colors,on='cluster') + return(tsne_data) + +def build_visualization(tsne_data, clusters, output): + + # tsne_data = "/gscratch/comdata/output/reddit_tsne/subreddit_author_tf_similarities_10000.feather" + # clusters = "/gscratch/comdata/output/reddit_clustering/subreddit_author_tf_similarities_10000.feather" + + tsne_data = pd.read_feather(tsne_data) + clusters = pd.read_feather(clusters) + + tsne_data = assign_cluster_colors(tsne_data,clusters,10,8) + + # sr_per_cluster = tsne_data.groupby('cluster').subreddit.count().reset_index() + # sr_per_cluster = sr_per_cluster.rename(columns={'subreddit':'cluster_size'}) + + tsne_data = tsne_data.merge(sr_per_cluster,on='cluster') + + term_zoom_plot = zoom_plot(tsne_data) + + term_zoom_plot.save(output) + + term_viewport_plot = viewport_plot(tsne_data) + + term_viewport_plot.save(output.replace(".html","_viewport.html")) + +if __name__ == "__main__": + fire.Fire(build_visualization) + +# commenter_data = pd.read_feather("tsne_author_fit.feather") +# clusters = pd.read_feather('author_3000_clusters.feather') +# commenter_data = assign_cluster_colors(commenter_data,clusters,10,8) +# commenter_zoom_plot = zoom_plot(commenter_data) +# commenter_viewport_plot = viewport_plot(commenter_data) +# commenter_zoom_plot.save("subreddit_commenters_tsne_3000.html") +# commenter_viewport_plot.save("subreddit_commenters_tsne_3000_viewport.html") + +# chart = chart.properties(width=10000,height=10000) +# chart.save("test_tsne_whole.svg")