How to use the nglview.show_asetraj function in nglview

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github rosswhitfield / ase / ase / visualize / ngl.py View on Github external
def __init__(self, atoms, xsize=500, ysize=500):
        import nglview
        import nglview.color

        from ipywidgets import Dropdown, FloatSlider, IntSlider, HBox, VBox
        self.atoms = atoms
        if isinstance(atoms[0], Atoms):
            # Assume this is a trajectory or struct list
            self.view = nglview.show_asetraj(atoms)
            self.frm = IntSlider(value=0, min=0, max=len(atoms) - 1)
            self.frm.observe(self._update_frame)
            self.struct = atoms[0]
        else:
            # Assume this is just a single structure
            self.view = nglview.show_ase(atoms)
            self.struct = atoms
            self.frm = None

        self.colors = {}
        self.view._remote_call('setSize', target='Widget',
                               args=['%dpx' % (xsize,), '%dpx' % (ysize,)])
        self.view.add_unitcell()
        self.view.add_spacefill()
        self.view.remove_ball_and_stick()
        self.view.camera = 'orthographic'
github pyiron / pyiron / pyiron / atomistics / job / atomistic.py View on Github external
use value >1 to make animation faster
                           default=1
            center_of_mass (bool):

        Returns:
            animation: nglview IPython widget

        """
        if not self.status.finished:
            raise ValueError("This job can't be animated until it is finished")
        try:
            import nglview
        except ImportError:
            raise ImportError("The animate() function requires the package nglview to be installed")

        animation = nglview.show_asetraj(self.trajectory(stride=stride, center_of_mass=center_of_mass))
        if spacefill:
            animation.add_spacefill(radius_type='vdw', scale=0.5, radius=particle_size)
            animation.remove_ball_and_stick()
        else:
            animation.add_ball_and_stick()
        if show_cell:
            if self.structure.cell is not None:
                animation.add_unitcell()
        return animation
github pyiron / pyiron / pyiron / atomistics / job / atomistic.py View on Github external
use value >1 to make animation faster
                           default=1
            center_of_mass (bool):

        Returns:
            animation: nglview IPython widget

        """
        try:
            import nglview
        except ImportError:
            raise ImportError(
                "The animate() function requires the package nglview to be installed"
            )

        animation = nglview.show_asetraj(
            self.trajectory(stride=stride, center_of_mass=center_of_mass)
        )
        if spacefill:
            animation.add_spacefill(radius_type="vdw", scale=0.5, radius=particle_size)
            animation.remove_ball_and_stick()
        else:
            animation.add_ball_and_stick()
        if show_cell:
            if self.structure.cell is not None:
                animation.add_unitcell()
        return animation
github pyiron / pyiron / pyiron / gaussian / gaussian.py View on Github external
if self.nma.masses3 is not None:
            mode /= np.sqrt(self.nma.masses3)
        mode /= np.linalg.norm(mode)

        positions = np.zeros((frames,len(symbols),3))

        for frame in range(frames):
            factor = amplitude*np.sin(2*np.pi*float(frame)/frames)
            positions[frame] = coordinates + factor*mode.reshape((-1,3))

        try:
            import nglview
        except ImportError:
            raise ImportError("The animate_nma_mode() function requires the package nglview to be installed")

        animation = nglview.show_asetraj(Trajectory(positions,self.structure))
        if spacefill:
            animation.add_spacefill(radius_type='vdw', scale=0.5, radius=particle_size)
            animation.remove_ball_and_stick()
        else:
            animation.add_ball_and_stick()
        return animation

nglview

IPython widget to interactively view molecular structures and trajectories.

MIT
Latest version published 9 months ago

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75 / 100
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