def main():
parser = argparse.ArgumentParser(description="make images out of brain imaging data")
parser.add_argument("--input", dest="image", help="full path to jpg image", type=str, default=None, required=True)
parser.add_argument("--db", dest="db", help="path to folder for png images for database", type=str, default=None)
parser.add_argument("--sample", dest="sample", help="sample every SAMPLEth pixel", type=int, default=10)
parser.add_argument(
"--N",
dest="N",
help="Number of top N brains to sample from when seleting image. Larger N means more variation in brains and color.",
type=float,
default=20,
)
parser.add_argument("--update", dest="update", help="regenerate png database", default=False, action="store_true")
parser.add_argument("--background-color", dest="bgcolor", help="background color", type=str, default="black")
parser.add_argument(
"--color-lookup",
dest="lookup",
help="color lookup (white, black) which currently determined background color.",
type=str,
default="white",
)
parser.add_argument("--output-folder", dest="output", help="output folder for html file", type=str, default=None)
try:
args = parser.parse_args()
except:
parser.print_help()
sys.exit(0)
# Regenerate database of png images
if args.update == True:
if args.db is not None:
get_data(args.folder)
else:
print "Please specify location for png images for database with --db argument"
else:
if args.image == None:
print "Please specify input jpg image with --input argument."
# Check background color
if args.lookup not in ["black", "white"]:
print "Unrecognized lookup table! Setting to white."
args.lookup = "white"
generate(
template=args.image,
output_folder=args.output,
color_lookup=args.lookup,
bgcolor=args.bgcolor,
top=args.N,
sample=args.sample,
)
def main():
parser = argparse.ArgumentParser(
description="make images out of brain imaging data")
parser.add_argument("--input",
dest='image',
help="full path to jpg image",
type=str,
default=None,
required=True)
parser.add_argument("--db",
dest='db',
help="path to folder for png images for database",
type=str,
default=None)
parser.add_argument("--sample",
dest='sample',
help="sample every SAMPLEth pixel",
type=int,
default=10)
parser.add_argument(
"--N",
dest='N',
help=
"Number of top N brains to sample from when seleting image. Larger N means more variation in brains and color.",
type=float,
default=20)
parser.add_argument('--update',
dest='update',
help="regenerate png database",
default=False,
action='store_true')
parser.add_argument("--background-color",
dest='bgcolor',
help="background color",
type=str,
default="black")
parser.add_argument(
"--color-lookup",
dest='lookup',
help=
"color lookup (white, black) which currently determined background color.",
type=str,
default="white")
parser.add_argument("--output-folder",
dest='output',
help="output folder for html file",
type=str,
default=None)
try:
args = parser.parse_args()
except:
parser.print_help()
sys.exit(0)
# Regenerate database of png images
if args.update == True:
if args.db is not None:
get_data(args.folder)
else:
print "Please specify location for png images for database with --db argument"
else:
if args.image == None:
print "Please specify input jpg image with --input argument."
# Check background color
if args.lookup not in ["black", "white"]:
print "Unrecognized lookup table! Setting to white."
args.lookup = "white"
generate(template=args.image,
output_folder=args.output,
color_lookup=args.lookup,
bgcolor=args.bgcolor,
top=args.N,
sample=args.sample)
from brainart.mosaic import generate
import shutil
import os
import re
# If you use the command line tool, a mosaic will be generated using
# the database of online images. This script will show how that
# database was generated, and how you can make your own set
download_folder = "/home/vanessa/Documents/Work/NEUROVAULT/mosaic"
png_folder = "%s/png" % (download_folder)
if not os.path.exists(png_folder):
os.mkdir(png_folder)
# Download NeuroVault collections, non thresholded, MNI, with DOI, group maps
brainmaps = get_data(download_folder)
# For each of the below, images with black backgrounds and white bgs are produced
# brains with multiple colors from matplotlib color maps
png_colormaps = make_colormap_brains(brainmaps, png_folder)
# Single brains (using 500+ hex colors) - this function returns the table
lookup_table_hex = make_hexcolor_brains(brainmaps, png_folder)
# Split into black and white
lookups = dict()
exp = re.compile("white")
white_index = [x for x in lookup_table_hex.index.tolist() if exp.search(x)]
black_index = [x for x in lookup_table_hex.index.tolist() if not exp.search(x)]
lookups["white"] = lookup_table_hex.loc[white_index]
from brainart.mosaic import generate
import shutil
import os
import re
# If you use the command line tool, a mosaic will be generated using
# the database of online images. This script will show how that
# database was generated, and how you can make your own set
download_folder = "/home/vanessa/Documents/Work/NEUROVAULT/mosaic"
png_folder = "%s/png" % (download_folder)
if not os.path.exists(png_folder):
os.mkdir(png_folder)
# Download NeuroVault collections, non thresholded, MNI, with DOI, group maps
brainmaps = get_data(download_folder)
# For each of the below, images with black backgrounds and white bgs are produced
# brains with multiple colors from matplotlib color maps
png_colormaps = make_colormap_brains(brainmaps, png_folder)
# Single brains (using 500+ hex colors) - this function returns the table
lookup_table_hex = make_hexcolor_brains(brainmaps, png_folder)
# Split into black and white
lookups = dict()
exp = re.compile("white")
white_index = [x for x in lookup_table_hex.index.tolist() if exp.search(x)]
black_index = [x for x in lookup_table_hex.index.tolist() if not exp.search(x)]
lookups["white"] = lookup_table_hex.loc[white_index]
