How to use the neuroglancer.set_static_content_source function in neuroglancer

'--order',
        choices=['min', 'sum'],
        default='min',
        help='Method by which to combine synaptic partner counts from multiple segments.')
    ap.add_argument(
        '-a',
        '--bind-address',
        help='Bind address for Python web server.  Use 127.0.0.1 (the default) to restrict access '
        'to browers running on the local machine, use 0.0.0.0 to permit access from remote browsers.')
    ap.add_argument(
        '--static-content-url', help='Obtain the Neuroglancer client code from the specified URL.')
    args = ap.parse_args()
    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)

    demo = Demo(
        synapse_path=args.synapses,
        num_top_partners=args.num_partners,
        top_method=args.order,
    )
    print(demo.viewer)
    import time
    time.sleep(5000)
    while True:
        time.sleep(1000)

if __name__ == '__main__':
    ap = argparse.ArgumentParser()
    ap.add_argument(
        '-a',
        '--bind-address',
        help='Bind address for Python web server.  Use 127.0.0.1 (the default) to restrict access '
        'to browers running on the local machine, use 0.0.0.0 to permit access from remote browsers.')
    ap.add_argument(
        '--static-content-url', help='Obtain the Neuroglancer client code from the specified URL.')
    args = ap.parse_args()
    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)

    inf = InteractiveInference()
    print(inf.viewer)

    while True:
        time.sleep(1000)

ap_render.add_argument(
        '--prefetch-frames',
        type=int,
        default=10,
        help='Number of frames to prefetch when rendering.')
    ap_render.add_argument(
        '--cross-section-background-color',
        type=str,
        default='black',
        help='Background color for cross sections.')

    args = ap.parse_args()
    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)
    args.func(args)

],
            skeleton_shader='void main() { emitRGB(colormapJet(affinity)); }',
            selected_alpha=0,
            not_selected_alpha=0,
        ))

if __name__ == '__main__':
    ap = argparse.ArgumentParser()
    ap.add_argument('--static-content-url')
    ap.add_argument('-a', '--bind-address')
    args = ap.parse_args()
    neuroglancer.server.debug = True
    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)
    print(viewer)

import neuroglancer

ap = argparse.ArgumentParser()
ap.add_argument(
    '-a',
    '--bind-address',
    help='Bind address for Python web server.  Use 127.0.0.1 (the default) to restrict access '
    'to browers running on the local machine, use 0.0.0.0 to permit access from remote browsers.')
ap.add_argument(
    '--static-content-url', help='Obtain the Neuroglancer client code from the specified URL.')
args = ap.parse_args()
if args.bind_address:
    neuroglancer.set_server_bind_address(args.bind_address)
if args.static_content_url:
    neuroglancer.set_static_content_source(url=args.static_content_url)

viewer = neuroglancer.Viewer()

a = np.zeros((3, 100, 100, 100), dtype=np.uint8)
ix, iy, iz = np.meshgrid(* [np.linspace(0, 1, n) for n in a.shape[1:]], indexing='ij')
a[0, :, :, :] = np.abs(np.sin(4 * (ix + iy))) * 255
a[1, :, :, :] = np.abs(np.sin(4 * (iy + iz))) * 255
a[2, :, :, :] = np.abs(np.sin(4 * (ix + iz))) * 255

with viewer.txn() as s:
    s.layers['image'] = neuroglancer.ImageLayer(
        source='precomputed://gs://neuroglancer-public-data/flyem_fib-25/image',
    )
    s.layers['ground_truth'] = neuroglancer.SegmentationLayer(
        source='precomputed://gs://neuroglancer-public-data/flyem_fib-25/ground_truth',
    )

'-a',
        '--bind-address',
        help='Bind address for Python web server.  Use 127.0.0.1 (the default) to restrict access '
        'to browers running on the local machine, use 0.0.0.0 to permit access from remote browsers.'
    )
    ap.add_argument(
        '--static-content-url', help='Obtain the Neuroglancer client code from the specified URL.')

    ap.add_argument('--labels', nargs='+', help='Labels to use')
    ap.add_argument('--prefetch', type=int, default=10, help='Number of bodies to prefetch')

    args = ap.parse_args()
    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)

    bodies = []

    with open(args.bodies, 'r') as f:
        csv_reader = csv.DictReader(f)
        for row in csv_reader:
            bodies.append(
                Body(
                    segment_id=int(row['id']),
                    num_voxels=int(row['num_voxels']),
                    bbox_start=np.array(
                        [
                            int(row['bbox.start.x']),
                            int(row['bbox.start.y']),
                            int(row['bbox.start.z'])
                        ],

#!/usr/bin/env python2
"""Tool for extending via equivalences a set of segments."""

from __future__ import absolute_import, print_function

import argparse
import copy
import os
import webbrowser

import neuroglancer
from neuroglancer.json_utils import decode_json, encode_json

neuroglancer.set_static_content_source(url='http://localhost:8080')


def get_segmentation_layer(layers):
    for layer in layers:
        if isinstance(layer.layer, neuroglancer.SegmentationLayer):
            return layer


class Annotator(object):
    def __init__(self, filename):
        self.filename = filename
        self.point_annotation_layer_name = 'false-merges'
        self.states = []
        self.state_index = None
        viewer = self.viewer = neuroglancer.Viewer()
        self.other_state_segment_ids = dict()

import neuroglancer

ap = argparse.ArgumentParser()
ap.add_argument(
    '-a',
    '--bind-address',
    help='Bind address for Python web server.  Use 127.0.0.1 (the default) to restrict access '
    'to browers running on the local machine, use 0.0.0.0 to permit access from remote browsers.')
ap.add_argument(
    '--static-content-url', help='Obtain the Neuroglancer client code from the specified URL.')
args = ap.parse_args()
if args.bind_address:
    neuroglancer.set_server_bind_address(args.bind_address)
if args.static_content_url:
    neuroglancer.set_static_content_source(url=args.static_content_url)

a = np.zeros((3, 100, 100, 100), dtype=np.uint8)
ix, iy, iz = np.meshgrid(* [np.linspace(0, 1, n) for n in a.shape[1:]], indexing='ij')
a[0, :, :, :] = np.abs(np.sin(4 * (ix + iy))) * 255
a[1, :, :, :] = np.abs(np.sin(4 * (iy + iz))) * 255
a[2, :, :, :] = np.abs(np.sin(4 * (ix + iz))) * 255

b = np.cast[np.uint32](np.floor(np.sqrt((ix - 0.5)**2 + (iy - 0.5)**2 + (iz - 0.5)**2) * 10))
b = np.pad(b, 1, 'constant')

viewer = neuroglancer.Viewer()
dimensions = neuroglancer.CoordinateSpace(
    names=['x', 'y', 'z'],
    units='nm',
    scales=[10, 10, 10])
with viewer.txn() as s:

def run_interactive(args, graph):
    # Make splitter a global variable so that it is accessible from the
    # interactive `python -i` shell.
    global splitter

    if args.bind_address:
        neuroglancer.set_server_bind_address(args.bind_address)
    if args.static_content_url:
        neuroglancer.set_static_content_source(url=args.static_content_url)

    splitter = InteractiveSplitter(
        graph,
        agglo_id=args.agglo_id,
        image_url=args.image_url,
        segmentation_url=args.segmentation_url,
        state_path=args.state)
    print(splitter.viewer)