def test_bokeh():
from bokeh.io import output_notebook, show
from bokeh.plotting import figure
import ipyvolume.bokeh
x, y, z = np.random.random((3, 100))
p3.figure()
scatter = p3.scatter(x, y, z)
tools = "wheel_zoom,box_zoom,box_select,lasso_select,help,reset,"
p = figure(title="E Lz space",
tools=tools,
webgl=True,
width=500,
height=500)
r = p.circle(x, y, color="navy", alpha=0.2)
ipyvolume.bokeh.link_data_source_selection_to_widget(
r.data_source, scatter, 'selected')
from bokeh.resources import CDN
from bokeh.embed import components
script, div = components(p)
ipyvolume.embed.embed_html(
"tmp/bokeh.html", [p3.gcc(), ipyvolume.bokeh.wmh],
all=True,
extra_script_head=script + CDN.render_js() + CDN.render_css(),
body_pre="<h2>Do selections in 2d (bokeh)<h2>" + div +
"<h2>And see the selection in ipyvolume<h2>")
def create_widget(self, output, plot, dataset, limits):
self.output = output
self.plot = plot
self.dataset = dataset
self.limits = np.array(limits).tolist()
self._first_time = True
self._first_time_vector = True
self.figure = p3.figure()
self.widget = p3.gcc()
def create_widget(self, output, plot, dataset, limits):
self.output = output
self.plot = plot
self.dataset = dataset
self.limits = np.array(limits).tolist()
self._first_time = True
self._first_time_vector = True
self.figure = p3.figure()
self.widget = p3.gcc()
self.figure.observe(self._update_limits, 'xlim ylim zlim'.split())
def create_widget(self, output, plot, dataset, limits):
self.output = output
self.plot = plot
self.dataset = dataset
self.limits = np.array(limits).tolist()
self._first_time = True
self._first_time_vector = True
self.figure = p3.figure()
self.widget = p3.gcc()
self.figure.observe(self._update_limits, 'xlim ylim zlim'.split())
def interactive_plot(self):
import ipyvolume.pylab as p3
self._create_widgets()
self.scatters = {}
self.vectors = {}
self.legend = widgets.Output()
with self.legend:
self.pltfigure = plt.figure(figsize=(8, 8))
# creating a dummy figure, so that 'self.pltfigure.clf()'
# in self._legend_handler() does not throw an error
# during initialization
p3.clear()
data = self.get_frame(self._widgets.frame.value)['arrays']
for array_name in self._widgets.particles.keys():
pa_widgets = self._widgets.particles[array_name]
if pa_widgets.scalar.value != 'None':
colormap = getattr(mpl.cm, pa_widgets.scalar_cmap.value)
c = colormap(getattr(data[array_name],
pa_widgets.scalar.value))
self.scatters[array_name] = p3.scatter(
data[array_name].x,
data[array_name].y,
data[array_name].z,
color=c,
size=pa_widgets.scalar_size.value,
)
self.plot_container = p3.gcc()
self.plot = p3.gcf() # used in 'self._save_figure_handler()'
self._legend_handler(None)
display(
widgets.HBox(
[widgets.VBox([self.plot]),
widgets.VBox([self.legend])]))
# HBox does not allow custom layout, therefore using an HBox
# of two VBoxes to place 'plot' and 'legend' next to each other
display(self._widgets._create_vbox())
def interactive_plot(self):
self._create_widgets()
self.scatters = {}
display(self._widgets._create_vbox())
self.vectors = {}
self.legend = widgets.Output()
import ipyvolume.pylab as p3
p3.clear()
data = self.get_frame(self._widgets.frame.value)['arrays']
for array_name in self._widgets.particles.keys():
pa_widgets = self._widgets.particles[array_name]
colormap = getattr(mpl.cm, pa_widgets.scalar_cmap.value)
c = colormap(getattr(data[array_name], pa_widgets.scalar.value))
self.scatters[array_name] = p3.scatter(
data[array_name].x,
data[array_name].y,
data[array_name].z,
color=c,
size=pa_widgets.scalar_size.value,
)
self._legend_handler(None)
display(widgets.VBox((p3.gcc(), self.legend)))
def show(self):
container = p3.gcc()
vbox = widgets.VBox([container, self.progress, widgets.VBox(self.tools), self.output])
display(vbox)
def create_ivol(vstruct,
width=500,
height=400,
ssize=5,
min_voxels=None,
max_voxels=None,
**volargs):
"""
Parameters
----------
vstruct: dict
width: int
height: int
ssize: int
min_voxels : int
minimum number of voxels in density cube
max_voxels : int
maximum number of voxels in density cube
volargs: dict
Returns
-------
Examples
--------
>>> from jsonextended import edict
>>> dstruct = {
... 'type': 'repeat_density',
... 'dtype': 'charge',
... 'name': '',
... 'dcube':np.ones((3,3,3)),
... 'centre':[0,0,0],
... 'cell_vectors':{
... 'a':[2.,0,0],
... 'b':[0,2.,0],
... 'c':[0,0,2.]},
... 'color_bbox': 'black',
... 'transforms': []
... }
>>> cstruct = {
... 'type': 'repeat_cell',
... 'name': '',
... 'centre':[0,0,0],
... 'cell_vectors':{
... 'a':[2.,0,0],
... 'b':[0,2.,0],
... 'c':[0,0,2.]},
... 'color_bbox': 'black',
... 'sites': [{
... 'label': "Fe",
... 'ccoord': [1,1,1],
... 'color_fill': "red",
... 'color_outline': None,
... 'transparency': 1,
... 'radius': 1,
... }],
... 'bonds': [],
... 'transforms': []
... }
>>> vstruct = {"elements": [dstruct, cstruct], "transforms": []}
>>> new_struct, fig, controls = create_ivol(vstruct)
>>> print(edict.apply(edict.filter_keys(new_struct, ["ivol"], list_of_dicts=True),
... "ivol", lambda x: [v.__class__.__name__ for v in x], list_of_dicts=True))
{'elements': [{'ivol': ['Figure', 'Mesh']}, {'ivol': ['Mesh', 'Scatter']}]}
"""
new_struct = apply_transforms(vstruct)
bonds = compute_bonds(
new_struct
) #edict.filter_keyvals(vstruct, {"type": "repeat_cell"}, keep_siblings=True))
# ivolume currently only allows one volume rendering per plot
# voltypes = edict.filter_keyvals(vstructs,[('type','repeat_density')])
vol_index = [
i for i, el in enumerate(vstruct['elements'])
if el['type'] == 'repeat_density'
]
assert len(
vol_index) <= 1, "ipyvolume only allows one volume rendering per scene"
p3.clear()
fig = p3.figure(width=width, height=height, controls=True)
fig.screen_capture_enabled = True
# the volume rendering must be created first,
# for appropriately scaled axis
if vol_index:
volstruct = new_struct['elements'][vol_index[0]]
a = volstruct['cell_vectors']['a']
b = volstruct['cell_vectors']['b']
c = volstruct['cell_vectors']['c']
centre = volstruct['centre']
#print(centre)
# convert dcube to cartesian
out = cube_frac2cart(volstruct['dcube'],
a,
b,
c,
centre,
max_voxels=max_voxels,
min_voxels=min_voxels,
make_cubic=True)
new_density, (xmin, ymin, zmin), (xmax, ymax, zmax) = out
vol = p3.volshow(new_density, **volargs)
if volstruct["color_bbox"] is not None:
a = np.asarray(a)
b = np.asarray(b)
c = np.asarray(c)
o = np.asarray(centre) - 0.5 * (a + b + c)
mesh = _create_mesh([
o, o + a, o + b, o + c, o + a + b, o + a + c, o + c + b,
o + a + b + c
],
color=volstruct["color_bbox"],
line_indices=[[0, 1], [0, 2], [0, 3], [2, 4],
[2, 6], [1, 4], [1, 5], [3, 5],
[3, 6], [7, 6], [7, 4], [7, 5]])
vol = [vol, mesh]
# todo better way of storing ivol components?
volstruct['ivol'] = vol
# appropriately scale axis
p3.xlim(xmin, xmax)
p3.ylim(ymin, ymax)
p3.zlim(zmin, zmax)
for element in new_struct['elements']:
if element['type'] == 'repeat_density':
continue
elif element['type'] == 'repeat_cell':
scatters = []
if element["color_bbox"] is not None:
a = np.asarray(element['cell_vectors']['a'])
b = np.asarray(element['cell_vectors']['b'])
c = np.asarray(element['cell_vectors']['c'])
centre = element['centre']
o = np.asarray(centre) - 0.5 * (a + b + c)
mesh = _create_mesh([
o, o + a, o + b, o + c, o + a + b, o + a + c, o + c + b,
o + a + b + c
],
color=element["color_bbox"],
line_indices=[[0, 1], [0, 2], [0,
3], [2, 4],
[2, 6], [1, 4], [1,
5], [3, 5],
[3, 6], [7, 6], [7, 4],
[7, 5]])
scatters.append(mesh)
for color, radius in set([(s['color_fill'], s['radius'])
for s in element["sites"]]):
scatter = edict.filter_keyvals(element, {
"color_fill": color,
"radius": radius
},
"AND",
keep_siblings=True,
list_of_dicts=True)
scatter = edict.combine_lists(scatter, ["sites"],
deepcopy=False)
scatter = edict.remove_keys(scatter, ["sites"], deepcopy=False)
x, y, z = np.array(scatter['ccoord']).T
s = p3.scatter(x,
y,
z,
marker='sphere',
size=ssize * radius,
color=color)
scatters.append(s)
element['ivol'] = scatters
elif element['type'] == 'repeat_poly':
polys = []
for poly in element['polys']:
mesh = _create_mesh(poly, element['color'], element['solid'])
polys.append(mesh)
element['ivol'] = polys
else:
raise ValueError("unknown element type: {}".format(
element['type']))
for bond in bonds:
p1, p2, c1, c2, radius = bond
meshes = _create_bond(p1, p2, c1, c2, radius)
# split up controls
if vol_index:
(level_ctrls, figbox, extractrl1, extractrl2) = p3.gcc().children
controls = OrderedDict([('transfer function', [level_ctrls]),
('lighting', [extractrl1, extractrl2])])
else:
# figbox = p3.gcc().children
controls = {}
return new_struct, fig, controls
