where x and y are the center points
where x-proj and y-proj are the vector projections at each center
"""
from napari import ViewerApp
from napari.util import app_context
from skimage import data
import numpy as np
with app_context():
# create the viewer and window
viewer = ViewerApp()
layer = viewer.add_image(data.camera(), name='photographer')
layer.colormap = 'gray'
# sample vector coord-like data
n = 1000
pos = np.zeros((n, 4), dtype=np.float32)
phi_space = np.linspace(0, 4 * np.pi, n)
radius_space = np.linspace(0, 100, n)
# assign x-y position
pos[:, 0] = radius_space * np.cos(phi_space) + 350
pos[:, 1] = radius_space * np.sin(phi_space) + 256
# assign x-y projection
pos[:, 2] = 2 * radius_space * np.cos(phi_space)
pos[:, 3] = 2 * radius_space * np.sin(phi_space)
"""
from napari import ViewerApp
from napari.util import app_context
import numpy as np
with app_context():
# create the viewer and window
viewer = ViewerApp()
n = 100
m = 200
image = 0.2*np.random.random((n, m)) + 0.5
layer = viewer.add_image(image, clim_range=[0, 1], name='background')
layer.colormap = 'gray'
# sample vector image-like data
# n x m grid of slanted lines
# random data on the open interval (-1, 1)
pos = np.zeros(shape=(n, m, 2), dtype=np.float32)
rand1 = 2*(np.random.random_sample(n * m)-0.5)
rand2 = 2*(np.random.random_sample(n * m)-0.5)
# assign projections for each vector
pos[:, :, 0] = rand1.reshape((n, m))
pos[:, :, 1] = rand2.reshape((n, m))
# add the vectors
vect = viewer.add_vectors(pos, width=0.2, length=2.5)
Display one markers layer ontop of one image layer using the add_markers and
add_image APIs
"""
import numpy as np
from skimage import data
from skimage.color import rgb2gray
from napari import ViewerApp
from napari.util import app_context
with app_context():
# create the viewer and window
viewer = ViewerApp()
# add the image
viewer.add_image(rgb2gray(data.astronaut()))
# add the markers
markers = np.array([[100, 100], [200, 200], [333, 111]])
size = np.array([10, 20, 20])
viewer.add_markers(markers, size=size)
# unselect the image layer
viewer.layers[0].selected = False
# adjust some of the marker layer properties
layer = viewer.layers[1]
# change the layer name
layer.name = 'spots'
# change the layer visibility
"""
Display one 4-D image layer using the add_image API
"""
import numpy as np
from skimage import data
from napari import ViewerApp
from napari.util import app_context
with app_context():
viewer = ViewerApp()
blobs = data.binary_blobs(length=128, blob_size_fraction=0.05,
n_dim=2, volume_fraction=.25).astype(float)
viewer.add_image(blobs, name='blobs')
def accept_image(viewer):
msg = 'this is a good image'
viewer.status = msg
print(msg)
next(viewer)
def reject_image(viewer):
msg = 'this is a bad image'
viewer.status = msg
print(msg)
next(viewer)
def next(viewer):
blobs = data.binary_blobs(length=128, blob_size_fraction=0.05,
your shapes.
"""
import numpy as np
from skimage import data
from skimage.color import rgb2gray
from napari import ViewerApp
from napari.util import app_context
from vispy.color import Colormap
with app_context():
# create the viewer and window
viewer = ViewerApp()
# add the image
layer = viewer.add_image(data.camera(), name='photographer')
layer.colormap = 'gray'
# create a list of polygons
polygons = [
np.array([[11, 13], [111, 113], [22, 246]]),
np.array([[505, 60], [402, 71], [383, 42], [251, 95], [212, 59],
[131, 137], [126, 187], [191, 204], [171, 248], [211, 260],
[273, 243], [264, 225], [430, 173], [512, 160]]),
np.array([[310, 382], [229, 381], [209, 401], [221, 411], [258, 411],
[300, 412], [306, 435], [268, 434], [265, 454], [298, 461],
[307, 461], [307, 507], [349, 510], [352, 369], [330, 366],
[330, 366]])
]
# add polygons