def test_quick():
x, y, z = ipyvolume.examples.xyz()
p3.volshow(x*y*z)
ipyvolume.quickvolshow(x*y*z, lighting=True)
ipyvolume.quickvolshow(x*y*z, lighting=True, level=1, opacity=1, level_width=1)
x, y, z, u, v, w = np.random.random((6, 100))
ipyvolume.quickscatter(x, y, z)
ipyvolume.quickquiver(x, y, z, u, v, w)
def init_kelp_vis(self):
self.kelp_header = ipw.HTML("<b>Kelp</b>")
with self.log_area:
self.kelp_controls, self.kelp_figure = ipv.quickvolshow(
np.zeros([3, 3, 3])
).children
self.kelp_figure.xlabel = 'x'
self.kelp_figure.xlim = [
self.kelp.grid.x.minval,
self.kelp.grid.x.maxval
]
# z-axis is flipped
self.kelp_figure.ylabel = 'z'
self.kelp_figure.ylim = [
self.kelp.grid.z.maxval,
self.kelp.grid.z.minval
]
self.kelp_figure.zlabel = 'y'
self.kelp_figure.zlim = [
self.kelp.grid.y.minval,
self.kelp.grid.y.maxval
]
self.calculate_kelp_button = ipw.Button(
description="Calculate Kelp"
)
self.load_kelp_button = ipw.Button(
description="Load Kelp"
)
def init_elements(self):
self.log_widget = ipw.Output()
self.controller, self.fig = ipv.quickvolshow(np.zeros([3,3,3])).children
self.theta_slider = ipw.IntSlider(
min=0,
max=self.ntheta-1,
description='theta',
#continuous_update=False
)
self.phi_slider = ipw.IntSlider(
min=0,
max=self.nphi-1,
description='phi',
#continuous_update=False
)
self.reset_button = ipw.Button(description='Reset Radiance')
self.update_button = ipw.Button(description='Update Plots')
self.heatmap = HeatMapWidget(
#x=self.light.grid.theta.vals,
#y=self.light.grid.phi.vals,
x=np.arange(self.light.grid.theta.num),
y=np.arange(self.light.grid.phi.num),
labels=dict(
x='theta',
y='phi'
)
)
self.stats = ipw.HTML()
def init_light_vis(self):
self.light_header = ipw.HTML("<b>Irradiance</b>")
with self.log_area:
self.light_controls, self.light_figure = ipv.quickvolshow(
np.zeros([3, 3, 3])
).children
self.light_figure.xlabel = 'x'
self.light_figure.xlim = [
self.light.grid.x.minval,
self.light.grid.x.maxval
]
# z-axis is flipped
self.light_figure.ylabel = 'z'
self.light_figure.ylim = [
self.light.grid.z.maxval,
self.light.grid.z.minval
]
self.light_figure.zlabel = 'y'
self.light_figure.zlim = [
self.light.grid.y.minval,
self.light.grid.y.maxval
]
self.calculate_light_button = ipw.Button(
description='Calculate Light'
)
self.load_light_button = ipw.Button(
description="Load Light"
)
def show_ipv(data: np.ndarray):
"""
Show a 3d visualization of 3d numpy array
:param data: The numpy array to show
:return: The ipyvolume figure
"""
import ipyvolume as ipv
return ipv.quickvolshow(data)
def volshow(volume):
"""
Use jupyter notebook to visualize 3d volumes.
:param volume: 3d numpy array
:return:
"""
import scipy.ndimage
sampled = scipy.ndimage.zoom(volume, 0.3, order=2)
fig = ipv.quickvolshow(sampled, level=[0.24, 0.29], opacity=[0.09, 0.14])
ipv.pylab.style.use(axis_off)
return fig
def my_volshow_1channel(volume,
view=(0, 0, 0),
rotation=(0, 0, 0, 'XYZ'),
perspective=None,
**kwargs):
"""Customized volume show function, with specified camera position and angle.
Args:
volume: volume data
view: camera position
rotation: camera angle
"""
ipv.quickvolshow(volume, **kwargs)
ipv.show()
# wait for plot to be generated (JavaScript)
time.sleep(0.6)
# set camera position and angle
set_perspective(view=view, rotation=rotation, perspective=perspective)
def ball(rmax=3, rmin=0, shape=128, limits=[-4, 4], display=True, **kwargs):
__, __, __, r, theta, phi = xyz(shape=shape, limits=limits, spherical=True)
data = r * 0
data[(r < rmax) & (r >= rmin)] = 0.5
if "data_min" not in kwargs:
kwargs["data_min"] = 0
if "data_max" not in kwargs:
kwargs["data_max"] = 1
if display:
return ipyvolume.quickvolshow(data=data.T, **kwargs)
else:
return data.T
def volume(filename=None,
data=None,
colormap="viridis",
nbins=256,
save=None,
**kwargs):
"""
Make a 3D volume rendering using ipyvolume
"""
try:
import ipyvolume as ipv
except ImportError:
print("Volume rendering makes use of the ipyvolume package which was "
"not found on this system. Install using pip install ipyvolume.")
if data is None:
data = load(filename, ids=True, tofs=True, **kwargs)
t = np.linspace(0.0, 7.2e4, nbins + 1)
z, xe, ye = np.histogram2d(
data.ids,
data.tofs / 1.0e3,
bins=[np.arange(-0.5, data.nx * data.ny + 0.5), t])
z = np.transpose(z.reshape(data.ny, data.nx, nbins), axes=[2, 1, 0])
ipv.quickvolshow(z,
extent=[[data.x[0, 0] * 100.0, data.x[0, -1] * 100.0],
[data.y[0, 0] * 100.0, data.y[-1, 0] * 100.0],
[t[0], t[-1]]])
ipv.pylab.xlabel("x [cm]")
ipv.pylab.ylabel("y [cm]")
ipv.pylab.zlabel("Tof [us]")
if save is not None:
ipv.pylab.save(save)
else:
ipv.show()
return
def show_volume(self, renderer: str = 'itkwidgets', **kwargs) -> None:
"""Show volume using `itkwidgets` or `ipyvolume`.
Extra keyword arguments (`kwargs`) are passed to
`itkwidgets.view` or `ipyvolume.quickvolshow`.
"""
if renderer in ('ipyvolume', 'ipv'):
import ipyvolume as ipv
return ipv.quickvolshow(self.image, **kwargs)
elif renderer in ('itkwidgets', 'itk', 'itkw'):
import itkwidgets as itkw
return itkw.view(self.image)
else:
raise ValueError(f'No such renderer: {renderer!r}')
def show3d(self, channel=0, controls=False, **kwargs):
with warnings.catch_warnings():
warnings.filterwarnings('ignore')
v = self.v[channel] if len(self.v.shape) > 3 else self.v
ipv.quickvolshow(v, controls=controls, **kwargs)
ipv.show()
def display(self):
return ipv.quickvolshow(self.volume)
# -*- coding: utf-8 -*-
from logging import getLogger
import ipyvolume as ipv
from niwidgets import NiftiWidget
import numpy as np
logger = getLogger(__name__)
if __name__ == '__main__':
ddd = np.random.random((100, 100, 100))
ipv.quickvolshow(ddd)
my_widget = NiftiWidget(fname)
my_widget.nifti_plotter()
pass
from astropy.io import fits
# +
hdu1 = fits.open('../Ratios-for-Alba/ratio-6583-6563.fits')[0]
hdu2 = fits.open('../Ratios-for-Alba/ratio-5007-4861.fits')[0]
hdu3 = fits.open('../Ratios-for-Alba/ratio-9069-6731.fits')[0]
x = hdu1.data.ravel()
y = hdu2.data.ravel()
z = hdu3.data.ravel()
xyzrange = [0.0, 0.7], [0.0, 5.0], [0, 25]
H, edges = np.histogramdd(np.stack((x, y, z)).T, bins=[150, 150, 150], range=xyzrange)
# + {"scrolled": false}
ipv.quickvolshow(H.T, lighting=True, level=[0.08, 0.2, 0.50], opacity=[0.04, 0.05, 0.10], level_width=0.05)
# +
hdu1 = fits.open('../Ratios-for-Alba/ratio-6583-6563.fits')[0]
hdu2 = fits.open('../Ratios-for-Alba/ratio-5007-4861.fits')[0]
hdu3 = fits.open('../Ratios-for-Alba/ratio-7330-6583.fits')[0]
x = hdu1.data.ravel()
y = hdu2.data.ravel()
z = hdu3.data.ravel()
xyzrange = [0.0, 0.7], [0.0, 5.0], [0, 0.2]
H, edges = np.histogramdd(np.stack((x, y, z)).T, bins=[150, 150, 150], range=xyzrange)
# -
ipv.quickvolshow(H.T, lighting=True, level=[0.08, 0.2, 0.50], opacity=[0.04, 0.05, 0.10], level_width=0.05)
def volume_plot(self):
"Transform so that the new y is the old -z for IPyVolume."
return ipv.quickvolshow(np.swapaxes(self.irradiance[:, :, ::-1], 1, 2))
def plot_galaxy_components(components, draw=True, show=True, shape=128, unit="pc", width=700, height=800, style='light', **kwargs):
"""
This function ....
:param components:
:param draw:
:param show:
:param shape:
:param unit:
:param width:
:param height:
:param style:
:param kwargs:
:return:
"""
# Determine the limits
limits = determine_model_limits(components, unit, symmetric=True)
# Debugging
log.debug("Plot limits: " + str(limits))
# Create coordinate data
x, y, z, r, theta, phi = xyz(shape=shape, limits=limits, spherical=True)
data = r * 0
# Loop over the components
for name in components:
# Debugging
log.debug("Computing the density of the " + name + " component ...")
component = components[name]
density = component.density_function(normalize=True)(x, y, z)
data += density
# DRAW FIGURE
if draw:
# :param lighting: boolean, to use lighting or not, if set to false, lighting parameters will be overriden
# :param data_min: minimum value to consider for data, if None, computed using np.nanmin
# :param data_max: maximum value to consider for data, if None, computed using np.nanmax
# :param tf: transfer function (see ipyvolume.transfer_function, or use the argument below)
# :param stereo: stereo view for virtual reality (cardboard and similar VR head mount)
# :param width: width of rendering surface
# :param height: height of rendering surface
# :param ambient_coefficient: lighting parameter
# :param diffuse_coefficient: lighting parameter
# :param specular_coefficient: lighting parameter
# :param specular_exponent: lighting parameter
# :param downscale: downscale the rendering for better performance, for instance when set to 2, a 512x512 canvas will show a 256x256 rendering upscaled, but it will render twice as fast.
# :param level: level(s) for the where the opacity in the volume peaks, maximum sequence of length 3
# :param opacity: opacity(ies) for each level, scalar or sequence of max length 3
# :param level_width: width of the (gaussian) bumps where the opacity peaks, scalar or sequence of max length 3
# :param kwargs: extra argument passed to Volume and default transfer function
# DEFAULT:
# lighting=False, data_min=None, data_max=None, tf=None, stereo=False,
# width=400, height=500,
# ambient_coefficient=0.5, diffuse_coefficient=0.8,
# specular_coefficient=0.5, specular_exponent=5,
# downscale=1,
# level=[0.1, 0.5, 0.9], opacity=[0.01, 0.05, 0.1], level_width=0.1,
level = [0.2]
#opacity = [0.05, 0.0, 0.0]
opacity = [0.08, 0.0, 0.0]
level_width = 0.2
level_width = [level_width] * 3
kwargs = dict()
kwargs["width"] = width
kwargs["height"] = height
kwargs["stereo"] = False
kwargs["level"] = level
kwargs["opacity"] = opacity
kwargs["level_width"] = level_width
kwargs["downscale"] = 1
# Create transfer function arguments
tf_kwargs = {}
# Clip off lists
min_length = min(len(level), len(level_width), len(opacity))
level = list(level[:min_length])
opacity = list(opacity[:min_length])
level_width = list(level_width[:min_length])
# append with zeros
while len(level) < 3:
level.append(0)
while len(opacity) < 3:
opacity.append(0)
while len(level_width) < 3:
level_width.append(0)
for i in range(1,4):
tf_kwargs["level"+str(i)] = level[i-1]
tf_kwargs["opacity"+str(i)] = opacity[i-1]
tf_kwargs["width"+str(i)] = level_width[i-1]
tf = TransferFunctionWidgetJs3(**tf_kwargs)
# Set the transfer function
kwargs["tf"] = tf
# Set style
if style == "dark": kwargs["style"] = dark
elif style == "light": kwargs["style"] = light
elif style == "minimal": kwargs["style"] = minimal
else: raise ValueError("Invalid style: " + style)
# Create the volume plot
vol = ipyvolume.quickvolshow(data=data.T, **kwargs)
#vol = p3.volshow(data=data, **kwargs)
# SHOW?
if show:
#p3.volshow()
vol.show()
return vol
# ONLY RETURN THE DATA
else: return data
def plot_galaxy_components(components,
draw=True,
show=True,
shape=128,
unit="pc",
width=700,
height=800,
style='light',
**kwargs):
"""
This function ....
:param components:
:param draw:
:param show:
:param shape:
:param unit:
:param width:
:param height:
:param style:
:param kwargs:
:return:
"""
# Determine the limits
limits = determine_model_limits(components, unit, symmetric=True)
# Debugging
log.debug("Plot limits: " + str(limits))
# Create coordinate data
x, y, z, r, theta, phi = xyz(shape=shape, limits=limits, spherical=True)
data = r * 0
# Loop over the components
for name in components:
# Debugging
log.debug("Computing the density of the " + name + " component ...")
component = components[name]
density = component.density_function(normalize=True)(x, y, z)
data += density
# DRAW FIGURE
if draw:
# :param lighting: boolean, to use lighting or not, if set to false, lighting parameters will be overriden
# :param data_min: minimum value to consider for data, if None, computed using np.nanmin
# :param data_max: maximum value to consider for data, if None, computed using np.nanmax
# :param tf: transfer function (see ipyvolume.transfer_function, or use the argument below)
# :param stereo: stereo view for virtual reality (cardboard and similar VR head mount)
# :param width: width of rendering surface
# :param height: height of rendering surface
# :param ambient_coefficient: lighting parameter
# :param diffuse_coefficient: lighting parameter
# :param specular_coefficient: lighting parameter
# :param specular_exponent: lighting parameter
# :param downscale: downscale the rendering for better performance, for instance when set to 2, a 512x512 canvas will show a 256x256 rendering upscaled, but it will render twice as fast.
# :param level: level(s) for the where the opacity in the volume peaks, maximum sequence of length 3
# :param opacity: opacity(ies) for each level, scalar or sequence of max length 3
# :param level_width: width of the (gaussian) bumps where the opacity peaks, scalar or sequence of max length 3
# :param kwargs: extra argument passed to Volume and default transfer function
# DEFAULT:
# lighting=False, data_min=None, data_max=None, tf=None, stereo=False,
# width=400, height=500,
# ambient_coefficient=0.5, diffuse_coefficient=0.8,
# specular_coefficient=0.5, specular_exponent=5,
# downscale=1,
# level=[0.1, 0.5, 0.9], opacity=[0.01, 0.05, 0.1], level_width=0.1,
level = [0.2]
#opacity = [0.05, 0.0, 0.0]
opacity = [0.08, 0.0, 0.0]
level_width = 0.2
level_width = [level_width] * 3
kwargs = dict()
kwargs["width"] = width
kwargs["height"] = height
kwargs["stereo"] = False
kwargs["level"] = level
kwargs["opacity"] = opacity
kwargs["level_width"] = level_width
kwargs["downscale"] = 1
# Create transfer function arguments
tf_kwargs = {}
# Clip off lists
min_length = min(len(level), len(level_width), len(opacity))
level = list(level[:min_length])
opacity = list(opacity[:min_length])
level_width = list(level_width[:min_length])
# append with zeros
while len(level) < 3:
level.append(0)
while len(opacity) < 3:
opacity.append(0)
while len(level_width) < 3:
level_width.append(0)
for i in range(1, 4):
tf_kwargs["level" + str(i)] = level[i - 1]
tf_kwargs["opacity" + str(i)] = opacity[i - 1]
tf_kwargs["width" + str(i)] = level_width[i - 1]
tf = TransferFunctionWidgetJs3(**tf_kwargs)
# Set the transfer function
kwargs["tf"] = tf
# Set style
if style == "dark": kwargs["style"] = dark
elif style == "light": kwargs["style"] = light
elif style == "minimal": kwargs["style"] = minimal
else: raise ValueError("Invalid style: " + style)
# Create the volume plot
vol = ipyvolume.quickvolshow(data=data.T, **kwargs)
#vol = p3.volshow(data=data, **kwargs)
# SHOW?
if show:
#p3.volshow()
vol.show()
return vol
# ONLY RETURN THE DATA
else:
return data
def show3d(self, channel=0, controls=False, **kwargs):
v = self.v[channel] if len(self.v.shape) > 3 else self.v
ipv.quickvolshow(v, controls=controls, **kwargs)
ipv.show()
