Source code for kaleidoscope.interactive.bloch.bloch3d

# -*- coding: utf-8 -*-

# This code is part of Kaleidoscope.
#
# (C) Copyright IBM 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""Interactive Bloch sphere"""

import numpy as np
import plotly.graph_objects as go
from kaleidoscope.colors import COLORS14
from kaleidoscope.colors.utils import hex_to_rgb
from kaleidoscope.interactive.plotly_wrapper import PlotlyFigure, PlotlyWidget
from kaleidoscope.interactive.bloch.primitives import (BSPHERE, LATS, LONGS, ZAXIS, YAXIS, XAXIS,
                                                       Z0LABEL, Z1LABEL, YLABEL, XLABEL)
from kaleidoscope.interactive.bloch.utils import bloch_components
from kaleidoscope.errors import KaleidoscopeError


[docs]def bloch_sphere(vectors=None, vectors_color=None, vectors_alpha=None, vectors_annotation=False, points=None, points_color=None, points_alpha=None, figsize=(350, 350), label_fontsize=16, annotation_fontsize=10, as_widget=False): """Generates a Bloch sphere from a given collection of vector and/or points data expressed in cartesian coordinates, [x, y, z]. Parameters: vectors (list, ndarray): Collection of one or more vectors to display. vectors_color (str or list): List of colors to use when plotting vectors. vectors_alpha (float or list): List of alphas to use when plotting vectors. vectors_annotation (bool or list): Boolean values to determine if a annotation should be displayed. points (list, ndarray): Collection of one or more points to display. points_color (str or list): List of colors to use when plotting points. points_alpha (float or list): List of alphas to use when plotting points. figsize (tuple): Figure size in pixels. label_fontsize (int): Font size for axes labels. annotation_fontsize (int): Font size for annotations. as_widget (bool): Return plot as a widget. Returns: PlotlyFigure or PlotlyWidget: A Plotly figure or widget instance Raises: ValueError: Input lengths do not match. KaleidoscopeError: Invalid vector input. Example: .. jupyter-execute:: import numpy as np from matplotlib.colors import LinearSegmentedColormap, rgb2hex from kaleidoscope.interactive import bloch_sphere cm = LinearSegmentedColormap.from_list('graypurple', ["#999999", "#AA00FF"]) pointsx = [[0, -np.sin(th), np.cos(th)] for th in np.linspace(0, np.pi/2, 20)] pointsz = [[np.sin(th), -np.cos(th), 0] for th in np.linspace(0, 3*np.pi/4, 30)] points = pointsx + pointsz points_alpha = [np.linspace(0.8, 1, len(points))] points_color = [[rgb2hex(cm(kk)) for kk in np.linspace(-1,1,len(points))]] vectors_color = ["#777777", "#AA00FF"] bloch_sphere(points=points, vectors=[[0, 0, 1], [1/np.sqrt(2), 1/np.sqrt(2), 0]], vectors_color=vectors_color, points_alpha=points_alpha, points_color=points_color) """ # Output figure instance fig = go.Figure() # List for vector annotations, if any fig_annotations = [] idx = 0 if points is not None: nest_depth = nest_level(points) # Take care of single point passed if nest_depth == 1: points = [[points]] # A single list of points passes elif nest_depth == 2: points = [points] # nest_depth = 3 means multiple lists passed if points_color is None: # passed a single point if nest_depth == 1: points_color = [COLORS14[0]] elif nest_depth == 2: points_color = [[COLORS14[kk % 14] for kk in range(len(points[0]))]] elif nest_depth == 3: points_color = [] for kk, pnts in enumerate(points): points_color.append(COLORS14[kk % 14]*len(pnts)) if nest_depth == 2 and nest_level(points_color) == 1: points_color = [points_color] if isinstance(points_color, str): points_color = [points_color] if points_alpha is None: points_alpha = [[1.0]*len(p) for p in points] if nest_depth == 2 and nest_level(points_alpha) == 1: points_alpha = [points_alpha] if isinstance(points_alpha, (int, float)): points_alpha = [[points_alpha]] for idx, point_collection in enumerate(points): x_pnts = [] y_pnts = [] z_pnts = [] if isinstance(points_color[idx], str): _colors = [points_color[idx]]*len(point_collection) else: _colors = points_color[idx] if len(points_alpha[idx]) != len(point_collection): err_str = 'number of alpha values ({}) does not equal number of points ({})' raise ValueError(err_str.format(len(points_alpha[idx]), len(x_pnts))) mcolors = [] for kk, point in enumerate(point_collection): x_pnts.append(point[0]) y_pnts.append(point[1]) z_pnts.append(point[2]) mcolors.append("rgba({},{},{},{})".format(*hex_to_rgb(_colors[kk]), points_alpha[idx][kk])) fig.add_trace(go.Scatter3d(x=x_pnts, y=y_pnts, z=z_pnts, mode='markers', marker=dict(size=7, color=mcolors), ) ) idx += 1 if vectors is not None: if vectors.__class__.__name__ in ['Statevector'] \ and 'qiskit' in vectors.__class__.__module__: vectors = bloch_components(vectors.data) elif vectors.__class__.__name__ in ['DensityMatrix'] \ and 'qiskit' in vectors.__class__.__module__: vectors = bloch_components(vectors.data) elif not isinstance(vectors[0], (list, np.ndarray)): if vectors[0].__class__.__name__ not in ['Statevector']: vectors = [[vectors[0], vectors[1], vectors[2]]] new_vecs = [] for vec in vectors: if vec.__class__.__name__ in ['Statevector'] and 'qiskit' in vec.__class__.__module__: # pylint: disable=no-member new_vecs.append(bloch_components(vec.data)[0]) else: nst_lvl = nest_level(vec) if nst_lvl == 1: new_vecs.append(vec) elif nst_lvl == 2: new_vecs.append(vec[0]) else: raise KaleidoscopeError("Invalid vector input.") if vectors_color is None: vectors_color = [COLORS14[kk+idx % 14] for kk in range(len(new_vecs))] if isinstance(vectors_color, str): vectors_color = [vectors_color] if vectors_alpha is None: vectors_alpha = [1.0]*len(new_vecs) if isinstance(vectors_alpha, (int, float)): vectors_alpha = [vectors_alpha] if vectors_annotation is True: vectors_annotation = [True]*len(new_vecs) elif not vectors_annotation: vectors_annotation = [False]*len(new_vecs) eps = 1e-12 for idx, vec in enumerate(new_vecs): vec = np.asarray(vec) if np.linalg.norm(vec) > 1.0 + eps: raise ValueError('Vector norm must be <= 1.') # So that line does not go out of arrow head vec_line = vec / 1.05 color_str = "rgba({},{},{},{})".format(*hex_to_rgb(vectors_color[idx]), vectors_alpha[idx]) fig.add_trace(go.Scatter3d(x=[0, vec_line[0]], y=[0, vec_line[1]], z=[0, vec_line[2]], mode="lines", hoverinfo=None, line=dict(color=color_str, width=10) ) ) fig.add_trace(go.Cone(x=[vec[0]], y=[vec[1]], z=[vec[2]], u=[vec[0]], v=[vec[1]], w=[vec[2]], sizemode="absolute", showscale=False, opacity=vectors_alpha[idx], colorscale=[vectors_color[idx], vectors_color[idx]], sizeref=0.25, anchor="tip") ) if vectors_annotation[idx]: fig_annotations.append(dict(showarrow=False, x=vec[0]*1.05, y=vec[1]*1.05, z=vec[2]*1.05, text="[{},<br> {},<br> {}]".format(round(vec[0], 3), round(vec[1], 3), round(vec[2], 3)), align='left', borderpad=3, xanchor='right' if vec[1] <= 0 else "left", xshift=10, bgcolor="#53565F", font=dict(size=annotation_fontsize, color="#ffffff", family="Courier New, monospace", ), ) ) # Start construction of sphere # Sphere fig.add_trace(BSPHERE()) # latitudes for kk in LATS: fig.add_trace(kk) # longitudes for kk in LONGS: fig.add_trace(kk) # z-axis fig.add_trace(ZAXIS) # x-axis fig.add_trace(XAXIS) # y-axis fig.add_trace(YAXIS) # zaxis label fig.add_trace(Z0LABEL(fontsize=label_fontsize)) fig.add_trace(Z1LABEL(fontsize=label_fontsize)) # xaxis label fig.add_trace(XLABEL(fontsize=label_fontsize)) # yaxis label fig.add_trace(YLABEL(fontsize=label_fontsize)) fig.update_layout(width=figsize[0], height=figsize[1], autosize=False, hoverdistance=50, showlegend=False, scene_aspectmode='cube', margin=dict(r=0, b=0, l=0, t=0), scene=dict(annotations=fig_annotations, xaxis=dict(showbackground=False, range=[-1.2, 1.2], showspikes=False, visible=False), yaxis=dict(showbackground=False, range=[-1.2, 1.2], showspikes=False, visible=False), zaxis=dict(showbackground=False, range=[-1.2, 1.2], showspikes=False, visible=False)), scene_camera=dict(eye=dict(x=1.5, y=0.4, z=0.4) ) ) if as_widget: return PlotlyWidget(fig) return PlotlyFigure(fig, modebar=True)
def nest_level(lst): """Determine how much nesting is in a list/ ndarray. Parameters: lst (list or ndarray): Input array-like object. Returns: int: Level of nesting. """ if not isinstance(lst, (list, np.ndarray)): return 0 if isinstance(lst, list): if not lst: return 1 else: if isinstance(lst, np.ndarray): if not all(lst): return 1 return max(nest_level(item) for item in lst) + 1