def load_all_csvs(directory='data/long-term-lake-monitoring'):
"""Takes a directory and loads all CSVs in the directory into memory
as an array of objects. The objects from the 'data' dir look like:
{
'Symbol': '',
'Stratum': 'E',
'VisitDate': '7/8/93',
'Depth': 'COM',
'Lab': 'VT',
'StationID': '16',
'Station': 'Shelburne Bay',
'Result': '11.5',
'Time': '1640',
'Test': 'Chloride',
'FieldID': '9341134'
}
"""
all_data = []
for filename in glob.glob('%s/*.csv' % safe_path(directory)):
with open(filename, 'rU') as fin:
f = csv.DictReader(fin)
data = [l for l in f]
all_data += data
return all_data
def normal_gif_to_lake_brite(normal_gif, duration):
"""Take a normal, animated GIF and allow it to display on lake brite"""
def iter_frames(gif):
"""Frame generator"""
im = Image.open(gif)
try:
i = 0
while 1:
im.seek(i)
imframe = im.copy()
if i == 0:
palette = imframe.getpalette()
else:
imframe.putpalette(palette)
yield imframe
i += 1
except EOFError:
pass
frames = []
for i, frame in enumerate(iter_frames(normal_gif)):
result = Image.new("RGB", (50, 150))
for i in range(0, 10):
img = frame.copy()
img.thumbnail((400, 400), Image.ANTIALIAS)
x = 0
y = i * 15
w, h = img.size
result.paste(img, (x, y, x + w, y + h))
frames.append(result)
return generate_gif(frames, safe_path("gif/video"), duration)
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 find_current_boundary():
"""Finds all non-white pixels in the low-res image of lake champlain
for use in an image clipper"""
im = Image.open('%s' % safe_path('champlain-low-res.png'))
lake_coords = []
arr = np.array(im)
for x, row in enumerate(arr):
for z, item in enumerate(row):
if not np.array_equal(item, np.array([255, 255, 255, 255])):
lake_coords.append([x, z])
return lake_coords
