from path import path # Used in examples
import runtrackpy

movdir = path('bigtracks-demo-movie').abspath()
print movdir
movdir.makedirs_p()
frames_extension = 'PNG'
frames_pattern = '*.' + frames_extension

import runtrackpy.test
import scipy.misc
for framenumber in range(20):
    x, y, img = runtrackpy.test.fake_image(framenumber)
    scipy.misc.imsave(movdir / 'example_%.4i.%s' % (framenumber, frames_extension), img)

print runtrackpy.track.__doc__

imgfiles = movdir.glob(frames_pattern)
im = imread(imgfiles[0])
def crop():
    pass
    # If you wish, set a restricted view here, so you can zoom in on details.
    #xlim(0, 240)
    #ylim(0, 240)
imshow(im)
gray()
colorbar()
crop()

gcf().set_size_inches(10, 10)
params = dict(bright=1, featsize=5, bphigh=2, threshold=0.5, maxdisp=3 * sqrt(8))

features = runtrackpy.track.identify_frame(im, params)

imshow(im)
plot(features.x, features.y, 'r+', markersize=10)
axis('image')
crop()

hist((features.x % 1, features.y % 1));

outputfile = movdir / 'bigtracks.h5'
if outputfile.exists():
    outputfile.remove()

runtrackpy.track.track2disk(imgfiles, outputfile, 
    params, 
    #selectframes=range(1, 3), # To speed things up, we could do just 2 frames
    progress=True)

import pantracks
bt = pantracks.BigTracks(movdir / 'bigtracks.h5')

bt.maxframe()

bt.get_all()

ftr = bt.get_frame(1)
print ftr.frame.values[0] # Which frame was this, again?
ftr.head()

ftr = bt[1]
print ftr.frame.values[0]

for fnum in bt.framerange():
    ftr = bt.get_frame(fnum)
    print fnum, len(ftr)

ftr = bt.query('(x < xmax) & (y < ymax)', {'xmax': 100, 'ymax': 100})
ftr.x.max(), ftr.y.max(), ftr.frame.unique()

import pandas
with bt:
    ftr = pandas.DataFrame(bt.table.readWhere('(particle >= 2) & (particle <= 5)'))
ftr.particle.min(), ftr.particle.max(), ftr.frame.unique()

%%timeit
for fnum in range(10):
    ftr = bt.get_frame(1)

%%timeit
with bt:
    for i in range(10):
        ftr = bt.get_frame(1)

btq = pantracks.bigtracks.compute_quality(bt, frame_interval=1)
btq.head()

pantracks.bigtracks.plot_quality(btq)