def _run_benchmark(
resources_dir: Path,
extensions: List[str],
non_aics_reader: List[Callable],
iterations: int = 3,
):
# Collect files matching the extensions provided
files = []
for ext in extensions:
files += list(resources_dir.glob(ext))
files += list(Path("/Users/jamies/Data").glob(ext))
# Run reads for each file and store details in results
aics_czi_reader = lambda file: (aics.CziFile(file).read_image(S=0))
results = []
for file in files:
print(file)
yx_planes = np.prod(
aics.CziFile(file).size[:-2]) #info_read.size("STCZ"))
for reader in [aics_czi_reader, non_aics_reader]:
reader_path = f"{reader.__module__}.{reader.__name__}"
for i in tqdm(range(iterations),
desc=f"{reader_path}: {file.name}"):
reader(str(file)) # warmup run
start = time.perf_counter()
reader(str(file))
results.append({
"file_name":
file.name,
"file_size_gb":
file.stat().st_size / 10e8,
"reader":
("other" if "czifile" in reader_path else "aics"),
"yx_planes":
int(yx_planes),
"read_duration":
time.perf_counter() - start,
})
return results
def extract_aicspylibczi(self,max_projection=True):
'''
Use aicspylibczi to extract images from czi file. Assumes time and series dimensions = 1.
Params
max_projection : bool : Make minimal projection of z_stack
'''
if VERBOSE: print("Reading file: " + self.raw_path + "\t and extracting to folder: " + self.extracted_folder)
czi = aicspylibczi.CziFile(pathlib.Path(self.raw_path))
dims = czi.dims_shape()[0]
channels = list(range(dims['C'][1]))
z_indexes = list(range(dims['Z'][1]))
for c in channels:
img_projection = None
for z in z_indexes:
img = czi.read_mosaic(C=c,Z=z,scale_factor=1)
img = np.squeeze(img)
if not max_projection:
out_path = out_path.join(self.extracted_folder,self.file_id + "_INFO_0_0_"+str(z)+"_"+str(c)+self.file_ending)
if VERBOSE: print("\tChannel: "+str(c)+"/"+str(max(channels))+"\tZ_index: "+str(z)+"/"+str(max(z))+"\tWriting: "+out_path)
if not cv2.imwrite(out_path,img):
raise ValueError("Could not save image to: "+out_path)
else:
if img_projection is None:
img_projection = img
else:
img_projection = np.maximum(img_projection,img)
if max_projection:
out_path = os.path.join(self.extracted_folder,self.file_id + "_INFO_0_0_0_"+str(c)+self.file_ending)
if VERBOSE: print("\tChannel: "+str(c)+"/"+str(max(channels))+"\tWriting: "+out_path)
if not cv2.imwrite(out_path,img_projection):
raise ValueError("Could not save image to: "+out_path)
self.meta_xml_to_file(czi,os.path.join(self.extracted_folder,"meta_data.txt"),os.path.join(self.extracted_folder,"meta_data_all.txt"))
img_paths = []
for path in os.listdir(self.extracted_folder):
if path.endswith(".tiff"):
img_paths.append(os.path.join(self.extracted_folder,path))
with open(self.extracted_images_info_file,'w') as f:
for path in img_paths:
f.write(path+"\n")
def writeMozaicImages(filePath="",
channel_nr=None,
z_stack_nr=None,
czi_image=None,
output_dir=""):
# Checking if args were filledi n correctly
if not filePath and czi_image is None:
print(
"No filepath or czi image was supplied, so the function cannot perform anything."
)
return
if filePath and czi_image is not None:
print("Filepath and czi image cannot both be supplied as arguments.")
return
if filePath:
czi = aicspylibczi.CziFile(filePath)
if not czi.is_mosaic():
print("Given file is not a mosaic file.")
return
if z_stack_nr is not None and channel_nr is not None:
mosaic_data = czi.read_mosaic(C=channel_nr,
Z=z_stack_nr,
scale_factor=1)
else:
if not czi_image.is_mosaic():
print("Given file is not a mosaic file.")
return
if z_stack_nr is not None and channel_nr is not None:
channel_index = channel_nr - 1
z_stack_index = z_stack_nr - 1
mosaic_data = czi_image.read_mosaic(C=channel_index,
Z=z_stack_index,
scale_factor=1)
mosaic_data = mosaic_data[0, 0, :, :].astype(np.uint16)
img = Image.fromarray(mosaic_data)
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
output_filename = os.path.join(
output_dir, f"channel{channel_nr}_z-stack{z_stack_nr}.tif")
img.save(output_filename)
print(
f"Extracted channel {channel_nr}: z-stack {z_stack_nr} from original image to {output_filename}."
)
elif channel_nr is not None:
# Here we want maxIP of a certain channel
channel_index = channel_nr - 1 # Indexing in czi api is 0 based, but user will be thinking in 1 based indexing.
z_stack_min, z_stack_max = czi_image.dims_shape()[0][
'Z'] #unpack the necessary
image_list = []
for i in range(z_stack_min, z_stack_max):
mosaic_data = czi_image.read_mosaic(C=channel_index,
Z=i,
scale_factor=1)
mosaic_data = mosaic_data[0, 0, :, :].astype(np.uint16)
image_list.append(mosaic_data)
maxIP = maxIPstack(image_list)
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
output_filename = os.path.join(output_dir,
f"channel_{channel_nr}_maxIP.tif")
io.imsave(output_filename, maxIP, check_contrast=False)
print(
f"Wrote z-stack-maxIP of channel {channel_nr} to {output_filename}"
)
image_list = []
for i in range(z_stack_min, z_stack_max):
mosaic_data = czi_image.read_mosaic(C=channel_index,
Z=i,
scale_factor=1)
mosaic_data = mosaic_data[0, 0, :, :].astype(np.uint16)
image_list.append(mosaic_data)
maxIP = maxIPstack(image_list)
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
output_filename = os.path.join(output_dir,
f"channel_{channel_nr}_maxIP.tif")
io.imsave(output_filename, maxIP, check_contrast=False)
print(
f"Wrote z-stack-maxIP of channel {channel_nr} to {output_filename}"
)
for index, round_img in enumerate(mosaic_file_list):
czi = aicspylibczi.CziFile(round_img)
c_stack_min, c_stack_max = czi.dims_shape()[0]['C']
for i in range(c_stack_min + 1, c_stack_max +
1): # I want them named starting at 1, not at 0
writeMozaicImages(
czi_image=czi,
channel_nr=i,
output_dir=
f"/media/tool/gabriele_data/161230_161220_3_1/maxIP-seperate-channels/Round{index+1}/"
)
def get_czi_planetable(czifile):
# get the czi object using pylibczi
czi = aicspylibczi.CziFile(czifile)
# get the czi metadata
md, add = imf.get_metadata(czifile)
# initialize the plane table
df_czi = define_czi_planetable()
# define subblock counter
sbcount = -1
# create progressbar
# total = md['SizeS'] * md['SizeM'] * md['SizeT'] * md['SizeZ'] * md['SizeC']
# pbar = tqdm(total=total)
# pbar = progressbar.ProgressBar(max_value=total)
# in case the CZI has the M-Dimension
if md['czi_isMosaic']:
for s, m, t, z, c in product(range(md['SizeS']),
range(md['SizeM']),
range(md['SizeT']),
range(md['SizeZ']),
range(md['SizeC'])):
sbcount += 1
# print(s, m, t, z, c)
info = czi.read_subblock_rect(S=s, M=m, T=t, Z=z, C=c)
# read information from subblock
sb = czi.read_subblock_metadata(unified_xml=True,
B=0,
S=s,
M=m,
T=t,
Z=z,
C=c)
try:
time = sb.xpath('//AcquisitionTime')[0].text
timestamp = dt.parse(time).timestamp()
except IndexError as e:
timestamp = 0.0
try:
xpos = np.double(sb.xpath('//StageXPosition')[0].text)
except IndexError as e:
xpos = 0.0
try:
ypos = np.double(sb.xpath('//StageYPosition')[0].text)
except IndexError as e:
ypos = 0.0
try:
zpos = np.double(sb.xpath('//FocusPosition')[0].text)
except IndexError as e:
zpos = 0.0
df_czi = df_czi.append({'Subblock': sbcount,
'Scene': s,
'Tile': m,
'T': t,
'Z': z,
'C': c,
'X[micron]': xpos,
'Y[micron]': ypos,
'Z[micron]': zpos,
'Time[s]': timestamp,
'xstart': info[0],
'ystart': info[1],
'xwidth': info[2],
'ywidth': info[3]},
ignore_index=True)
if not md['czi_isMosaic']:
"""
for s, t, z, c in it.product(range(md['SizeS']),
range(md['SizeT']),
range(md['SizeZ']),
range(md['SizeC'])):
"""
for s, t, z, c in product(range(md['SizeS']),
range(md['SizeT']),
range(md['SizeZ']),
range(md['SizeC'])):
sbcount += 1
info = czi.read_subblock_rect(S=s, T=t, Z=z, C=c)
# read information from subblocks
sb = czi.read_subblock_metadata(unified_xml=True, B=0, S=s, T=t, Z=z, C=c)
try:
time = sb.xpath('//AcquisitionTime')[0].text
timestamp = dt.parse(time).timestamp()
except IndexError as e:
timestamp = 0.0
try:
xpos = np.double(sb.xpath('//StageXPosition')[0].text)
except IndexError as e:
xpos = 0.0
try:
ypos = np.double(sb.xpath('//StageYPosition')[0].text)
except IndexError as e:
ypos = 0.0
try:
zpos = np.double(sb.xpath('//FocusPosition')[0].text)
except IndexError as e:
zpos = 0.0
df_czi = df_czi.append({'Subblock': sbcount,
'Scene': s,
'Tile': 0,
'T': t,
'Z': z,
'C': c,
'X[micron]': xpos,
'Y[micron]': ypos,
'Z[micron]': zpos,
'Time[s]': timestamp,
'xstart': info[0],
'ystart': info[1],
'xwidth': info[2],
'ywidth': info[3]},
ignore_index=True)
# normalize timestamps
df_czi = imf.norm_columns(df_czi, colname='Time[s]', mode='min')
# cast data types
df_czi = df_czi.astype({'Subblock': 'int32',
'Scene': 'int32',
'Tile': 'int32',
'T': 'int32',
'Z': 'int32',
'C': 'int16',
'xstart': 'int32',
'xstart': 'int32',
'ystart': 'int32',
'xwidth': 'int32',
'ywidth': 'int32'},
copy=False,
errors='ignore')
return df_czi
maxIP = np.maximum.reduce(parsed_list)
return maxIP
def writeMozaicImages(czi_image, channel_nr, output_prefix=""):
channel_index = channel_nr - 1 # Indexing in czi api is 0 based, but user will be thinking in 1 based indexing.
z_stack_min, z_stack_max = czi_image.dims_shape()[0][
'Z'] #unpack the necessary
image_list = []
for i in range(z_stack_min, z_stack_max):
mosaic_data = czi_image.read_mosaic(C=channel_index,
Z=i,
scale_factor=1)
mosaic_data = mosaic_data[0, 0, :, :].astype(np.uint16)
image_list.append(mosaic_data)
maxIP = maxIPstack(image_list)
output_filename = f"{ output_prefix }_c{channel_nr}.tif"
io.imsave(output_filename, maxIP)
filepath = sys.argv[1]
prefix = os.path.splitext(filepath)[0]
# if a third argument is inputted, it should be teh dir where the user want the files stored, otherwise the code will assume this is part of an entire workflow and just write to cwd.
czi = aicspylibczi.CziFile(filepath)
c_stack_min, c_stack_max = czi.dims_shape()[0]['C']
for i in range(c_stack_min + 1,
c_stack_max + 1): # I want them named starting at 1, not at 0
writeMozaicImages(czi_image=czi, channel_nr=i, output_prefix=prefix)
output = r"W:\Neurophysiology-Storage1\Wahl\Hendrik\PhD\Data\Tests\export_test\quicknii_output"
step = 3
prepare_stack_for_quicknii(path, output, step)
#%% Trying to open multiscene mosaic CZI files
def norm_by(x, min_, max_):
norms = np.percentile(x, [min_, max_])
i2 = np.clip((x - norms[0]) / (norms[1] - norms[0]), 0, 1)
return i2
path = r"W:\Neurophysiology-Storage1\Wahl\Hendrik\PhD\Data\Batch3\histology\Batch3_quant\images\M41_01.czi"
czi = aicspylibczi.CziFile(path)
mosaic_data = czi.read_mosaic(C=2, scale_factor=0.1)
normed_mosaic_data = norm_by(mosaic_data[0, :, :], 5, 98) * 255
plt.imshow(normed_mosaic_data)
czi.read_subblock_rect(S=1, M=100)
#%% Open OME TIFF
path = r"W:\Neurophysiology-Storage1\Wahl\Victor\M11_1.czi - Scene #0.ome.tif"
# path = r"Z:\data\h.heiser\slidescanner_transfer_20210209_0901\M41_01_DAPI_8bit.ome.tiff"
ome = tiff.imread(path)
plt.imshow(ome[0])
#%% Try to read .flat file from QuickNII to get atlas identifier data