def build_items():
x = np.linspace(-10, 10, 200)
y = np.sin(np.sin(np.sin(x)))
filename = osp.join(osp.dirname(__file__), "brain.png")
items = [
make.curve(x, y, color="b"),
make.image(filename=filename),
make.trimage(filename=filename),
make.maskedimage(filename=filename, colormap='gray',
show_mask=True, xdata=[0, 40], ydata=[0, 50]),
make.label("Relative position <b>outside</b>",
(x[0], y[0]), (-10, -10), "BR"),
make.label("Relative position <i>inside</i>",
(x[0], y[0]), (10, 10), "TL"),
make.label("Absolute position", "R", (0, 0), "R"),
make.legend("TR"),
make.rectangle(-3, -0.8, -0.5, -1., "rc1"),
make.segment(-3, -0.8, -0.5, -1., "se1"),
make.ellipse(-10, 0.0, 0, 0, "el1"),
make.annotated_rectangle(0.5, 0.8, 3, 1., "rc1", "tutu"),
make.annotated_segment(-1, -1, 1, 1., "rc1", "tutu"),
Axes( (0, 0), (1, 0), (0, 1) ),
PolygonShape(np.array([[150., 330.],
[270., 520.],
[470., 480.],
[520., 360.],
[460., 200.],
[250., 240.]])),
]
return items
def imshow(data, interpolation=None, mask=None):
"""
Display the image in *data* to current axes
interpolation: 'nearest', 'linear' (default), 'antialiasing'
Example:
import numpy as np
x = np.linspace(-5, 5, 1000)
img = np.fromfunction(lambda x, y:
np.sin((x/200.)*(y/200.)**2), (1000, 1000))
gray()
imshow(img)
show()
"""
axe = gca()
import numpy as np
if isinstance(data, np.ma.MaskedArray) and mask is None:
mask = data.mask
data = data.data
if mask is None:
img = make.image(data)
else:
img = make.maskedimage(data, mask, show_mask=True)
if interpolation is not None:
interp_dict = {'nearest': INTERP_NEAREST,
'linear': INTERP_LINEAR,
'antialiasing': INTERP_AA}
assert interpolation in interp_dict, "invalid interpolation option"
img.set_interpolation(interp_dict[interpolation], size=5)
axe.add_image(img)
axe.yreverse = True
_show_if_interactive()
return [img]
def build_items():
x = np.linspace(-10, 10, 200)
y = np.sin(np.sin(np.sin(x)))
filename = osp.join(osp.dirname(__file__), "brain.png")
items = [
make.curve(x, y, color="b"),
make.image(filename=filename),
make.trimage(filename=filename),
make.maskedimage(filename=filename,
colormap='gray',
show_mask=True,
xdata=[0, 40],
ydata=[0, 50]),
make.label("Relative position <b>outside</b>", (x[0], y[0]),
(-10, -10), "BR"),
make.label("Relative position <i>inside</i>", (x[0], y[0]), (10, 10),
"TL"),
make.label("Absolute position", "R", (0, 0), "R"),
make.legend("TR"),
make.rectangle(-3, -0.8, -0.5, -1., "rc1"),
make.segment(-3, -0.8, -0.5, -1., "se1"),
make.ellipse(-10, 0.0, 0, 0, "el1"),
make.annotated_rectangle(0.5, 0.8, 3, 1., "rc1", "tutu"),
make.annotated_segment(-1, -1, 1, 1., "rc1", "tutu"),
Axes((0, 0), (1, 0), (0, 1)),
PolygonShape(
np.array([[150., 330.], [270., 520.], [470., 480.], [520., 360.],
[460., 200.], [250., 240.]])),
]
return items
def imshow(data, interpolation=None, mask=None):
"""
Display the image in *data* to current axes
interpolation: 'nearest', 'linear' (default), 'antialiasing'
Example::
import numpy as np
x = np.linspace(-5, 5, 1000)
img = np.fromfunction(lambda x, y: np.sin((x/200.)*(y/200.)**2), (1000, 1000))
gray()
imshow(img)
show()
"""
axe = gca()
import numpy as np
if isinstance(data, np.ma.MaskedArray) and mask is None:
mask = data.mask
data = data.data
if mask is None:
img = make.image(data)
else:
img = make.maskedimage(data, mask, show_mask=True)
if interpolation is not None:
interp_dict = {
'nearest': INTERP_NEAREST,
'linear': INTERP_LINEAR,
'antialiasing': INTERP_AA
}
assert interpolation in interp_dict, "invalid interpolation option"
img.set_interpolation(interp_dict[interpolation], size=5)
axe.add_image(img)
axe.yreverse = True
_show_if_interactive()
return [img]
def test():
"""Test"""
# -- Create QApplication
import guidata
_app = guidata.qapplication()
# --
win = OCSImageDialog(toolbar=True, wintitle="Oblique averaged cross section test")
win.resize(600, 600)
# from guiqwt.tests.image import compute_image
# data = np.array((compute_image(4000, grid=False)+1)*32e3, dtype=np.uint16)
# image = make.maskedimage(data, colormap="bone", show_mask=True)
filename = osp.join(osp.dirname(__file__), "brain_cylinder.png")
image = make.maskedimage(filename=filename, colormap="bone")
plot = win.get_plot()
plot.add_item(image)
win.exec_()
def test():
"""Test"""
# -- Create QApplication
import guidata
_app = guidata.qapplication()
# --
win = OCSImageDialog(toolbar=True,
wintitle="Oblique averaged cross section test")
win.resize(600, 600)
# from guiqwt.tests.image import compute_image
# data = np.array((compute_image(4000, grid=False)+1)*32e3, dtype=np.uint16)
# image = make.maskedimage(data, colormap="bone", show_mask=True)
filename = osp.join(osp.dirname(__file__), "brain_cylinder.png")
image = make.maskedimage(filename=filename, colormap="bone")
plot = win.get_plot()
plot.add_item(image)
win.exec_()
import os, os.path as osp, pickle
from guiqwt.plot import ImageDialog
from guiqwt.tools import ImageMaskTool
from guiqwt.builder import make
SHOW = True # Show test in GUI-based test launcher
FNAME = "image_masked.pickle"
if __name__ == "__main__":
import guidata
_app = guidata.qapplication()
win = ImageDialog(toolbar=True, wintitle="Masked image item test")
win.add_tool(ImageMaskTool)
if os.access(FNAME, os.R_OK):
print("Restoring mask...", end=" ")
iofile = open(FNAME, "rb")
image = pickle.load(iofile)
iofile.close()
print("OK")
else:
fname = osp.join(osp.abspath(osp.dirname(__file__)), "brain.png")
image = make.maskedimage(filename=fname, colormap="gray", show_mask=True, xdata=[0, 20], ydata=[0, 25])
win.get_plot().add_item(image)
win.show()
win.exec_()
iofile = open(FNAME, "wb")
pickle.dump(image, iofile)
SHOW = True # Show test in GUI-based test launcher
FNAME = "image_masked.pickle"
if __name__ == "__main__":
import guidata
_app = guidata.qapplication()
win = ImageDialog(toolbar=True, wintitle="Masked image item test")
win.add_tool(ImageMaskTool)
if os.access(FNAME, os.R_OK):
print("Restoring mask...", end=" ")
iofile = open(FNAME, "rb")
image = pickle.load(iofile)
iofile.close()
print("OK")
else:
fname = osp.join(osp.abspath(osp.dirname(__file__)), "brain.png")
image = make.maskedimage(
filename=fname,
colormap="gray",
show_mask=True,
xdata=[0, 20],
ydata=[0, 25],
)
win.get_plot().add_item(image)
win.show()
win.exec_()
iofile = open(FNAME, "wb")
pickle.dump(image, iofile)
