def make_proj(img_list):
"""Function to make a dict of max projections from a list of paths
to images. Each channel will make one max projection"""
channels = []
print('Making max projections')
ptime = time.time()
sorted_images = defaultdict(list)
max_imgs = {}
for path in img_list:
img = File(path)
channel = img.get_name('C\d\d')
sorted_images[channel].append(img.read_image())
max_imgs[channel] = np.maximum.reduce(sorted_images[channel])
print('Max proj:' + str(time.time()-ptime) + ' secs')
return max_imgs
def get_imgs(path, imdir, job_order, f_job=None, img_save=None, csv_save=None):
"""Function to handle the acquired images, do renaming,
max projections etc."""
if f_job is None:
f_job = 2
if img_save is None:
img_save = True
if csv_save is None:
csv_save = True
img_paths = Directory(path).get_all_files('*' + job_order + '*.tif')
new_paths = []
metadata_d = {}
for img_path in img_paths:
img = File(img_path)
img_array = img.read_image()
well = img.get_name('U\d\d--V\d\d')
job_order = img.get_name('E\d\d')
job_ord_int = int(re.sub("\D", "", job_order))
field = img.get_name('X\d\d--Y\d\d')
z_slice = img.get_name('Z\d\d')
channel = img.get_name('C\d\d')
if job_ord_int == f_job:
new_name = os.path.normpath(os.path.join(path, (well + '--' +
job_order + '--' +
field + '--' +
z_slice + '--' +
channel +
'.ome.tif'
)
)
)
elif job_ord_int == f_job + 1 and channel == 'C00':
new_name = os.path.normpath(os.path.join(path, (well + '--' +
job_order + '--' +
field + '--' +
z_slice +
'--C01.ome.tif'
)
)
)
channel = 'C01'
elif job_ord_int == f_job + 1 and channel == 'C01':
new_name = os.path.normpath(os.path.join(path, (well + '--' +
job_order + '--' +
field + '--' +
z_slice +
'--C02.ome.tif'
)
)
)
channel = 'C02'
elif job_ord_int == f_job + 2:
new_name = os.path.normpath(os.path.join(path, (well + '--' +
job_order + '--' +
field + '--' +
z_slice +
'--C03.ome.tif'
)
)
)
channel = 'C03'
else:
new_name = img_path
if not (len(img_array) == 16 or len(img_array) == 256):
new_paths.append(new_name)
metadata_d[well + '--' + field + '--' + channel] = img.meta_data()
os.rename(img_path, new_name)
max_projs = make_proj(new_paths)
new_dir = os.path.normpath(os.path.join(imdir, 'maxprojs'))
if not os.path.exists(new_dir):
os.makedirs(new_dir)
if img_save:
print('Saving images')
if csv_save:
print('Calculating histograms')
for channel, proj in max_projs.iteritems():
if img_save:
ptime = time.time()
p = os.path.normpath(os.path.join(new_dir, 'image--' + well + '--' +
field + '--' + channel + '.ome.tif'))
metadata = metadata_d[well + '--' + field + '--' + channel]
File(p).save_image(proj, metadata)
print('Save image:' + str(time.time()-ptime) + ' secs')
if csv_save:
ptime = time.time()
if proj.dtype.name == 'uint8':
max_int = 255
if proj.dtype.name == 'uint16':
max_int = 65535
histo = histogram(proj, 0, max_int, 256)
rows = defaultdict(list)
for b, count in enumerate(histo):
rows[b].append(count)
p = os.path.normpath(os.path.join(new_dir, well + '--' + channel +
'.ome.csv'))
write_csv(p, rows, ['bin', 'count'])
print('Save csv:' + str(time.time()-ptime) + ' secs')
return
