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_()
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)