def generate_lake_brite_gif(metric, palette='winter_r', duration=0.125,
clip_to_lake=True, tween_frames=1, empty_frames=0):
"""Generate 3D Lake GIF for consumption by LakeBrite"""
print "Generating 3D Lake GIFs of %s" % metric
a = generate_lake_array(metric, clip_to_lake, tween_frames)
max_value = get_max_of_data(a)
min_value = get_min_of_data(a)
print "Rotating matrix"
rotated = []
for index, frame in enumerate(a):
rotated.append(zip(*frame))
print "Increasing dimensions"
slices = [increase_dimensions(frame, max_value, min_value) for
frame in rotated]
print "Stackining frames"
frames = [stack_frames(frame) for frame in slices]
print "Normalizing values"
normalized = [normalize_values(frame, max_value, min_value)
for frame in frames]
# TODO: this should live outside of `generate_lake_brite_gif()`
# it lives here because I use `palette` from the arguments
# and can't figure out how to bind it to `color_map` otherwise
def color_map(x, palette=palette):
"""To be consumed by np.vectorize to transform nan values to black
and provide the color map"""
if np.isnan(x):
return [0, 0, 0]
elif x < 0:
return list(cm.get_cmap(palette)(0, bytes=True)[:3])
else:
return list(cm.get_cmap(palette)(x, bytes=True)[:3])
print "Mapping values to colors"
a = map_value_to_color(normalized, color_map)
print "Adding empty frames"
with_empties = add_empty_frames(a, empty_frames)
print "Converting to numpy array"
arrays = [np.fliplr(np.asarray(with_empties[i], 'uint8'))
for i, f in enumerate(with_empties)]
print "Generating GIFs"
path_to_gif = safe_path('gif/lake-animation')
generate_gif(arrays, path_to_gif, duration)
return '%s.gif' % path_to_gif
def make_temp_gif():
"""A single GIF of the entire temperature dataset"""
data = csv_to_matrix()
max_temp = get_max_of_data(data)
min_temp = get_min_of_data(data)
three_d_data = increase_dimensions(data, max_temp, min_temp)
colored_data = assign_colors(three_d_data, max_temp, min_temp)
arrays = [np.asarray(colored_data[i], 'uint8')
for i, f in enumerate(colored_data)]
generate_gif(arrays, 'temp')
def make_lake_brite_gif():
"""A single GIF, "10 slices" tall that contains the USHCN temperature
visualization for consumption by Lake Brite"""
print "Making USHCN GIF"
data = csv_to_matrix()
max_temp = get_max_of_data(data)
min_temp = get_min_of_data(data)
three_d_data = increase_dimensions(data, max_temp, min_temp)
colored_data = assign_colors(three_d_data, max_temp, min_temp)
add_empties = add_empty_slices(colored_data)
frames = make_frames(add_empties)
arrays = np.asarray(frames, 'uint8')
generate_gif(arrays, 'ushcn/temperature')
def make_three_d_gifs():
"""Turn temperature dataset into 3d GIFs for LakeBrite"""
data = csv_to_matrix()
max_temp = get_max_of_data(data)
min_temp = get_min_of_data(data)
three_d_data = increase_dimensions(data, max_temp, min_temp)
colored_data = assign_colors(three_d_data, max_temp, min_temp)
length = len(colored_data)
arrays = []
for index, frame in enumerate(colored_data):
if index < length - 10:
single_frame = colored_data[index:index + 10]
frame = stack_frames(single_frame)
arrays.append(np.asarray(frame))
generate_gif(arrays, 'temperature/lake')
