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if x <= 1e-4:
return '0{}'.format(duration_label_unit)
elif x < 1:
return '<1{}'.format(duration_label_unit)
else:
return '{:d}{}'.format(int(x), duration_label_unit)
cluster_images = _get_cluster_images(clusters, False, n=10, c=10)
plot_heatmap_with_images(
raw_heatmap, channels, cluster_images,
'Images of {} and Their Corresponding Screen Time As Distributed within a Channel'.format(name) if show_titles else '',
heatmap_label_fn=heatmap_raw_label_fn,
save_path=save_paths[0] if save_paths else None
)
plot_heatmap_with_images(
raw_heatmap / raw_heatmap.sum(axis=0)[np.newaxis, :],
channels, cluster_images,
'Images of {} and Screen Time Distributed Within a Channel (Column Normalized)'.format(name) if show_titles else '',
save_path=save_paths[2] if save_paths else None
)
plot_heatmap_with_images(
raw_heatmap / raw_heatmap.sum(axis=1)[:, np.newaxis],
channels, cluster_images,
'Images of {} and Screen Time As Distributed Across Channels (Row Normalized)'.format(name) if show_titles else '',
save_path=save_paths[1] if save_paths else None
)
raw_bar_chart = defaultdict(lambda: {}) # {CNN: [{Anderson Cooper: 360 mins}, ...], MSNBC:[{...},...,{...}]}
cnndict = defaultdict(lambda: 0)
msnbcdict = defaultdict(lambda: 0)
foxdict = defaultdict(lambda: 0)
elif duration_label_unit == 'h':
x /= 3600
elif duration_label_unit == 's':
pass
else:
raise Exception('Unknown unit: {}'.format(duration_label_unit))
if x <= 1e-4:
return '0{}'.format(duration_label_unit)
elif x < 1:
return '<1{}'.format(duration_label_unit)
else:
return '{:d}{}'.format(int(x), duration_label_unit)
cluster_images = _get_cluster_images(clusters, False, n=10, c=10)
plot_heatmap_with_images(
raw_heatmap, channels, cluster_images,
'Images of {} and Their Corresponding Screen Time As Distributed within a Channel'.format(name) if show_titles else '',
heatmap_label_fn=heatmap_raw_label_fn,
save_path=save_paths[0] if save_paths else None
)
plot_heatmap_with_images(
raw_heatmap / raw_heatmap.sum(axis=0)[np.newaxis, :],
channels, cluster_images,
'Images of {} and Screen Time Distributed Within a Channel (Column Normalized)'.format(name) if show_titles else '',
save_path=save_paths[2] if save_paths else None
)
plot_heatmap_with_images(
raw_heatmap / raw_heatmap.sum(axis=1)[:, np.newaxis],
channels, cluster_images,
'Images of {} and Screen Time As Distributed Across Channels (Row Normalized)'.format(name) if show_titles else '',
save_path=save_paths[1] if save_paths else None