Python库 | qctrl-visualizer-2.4.0.tar.gz

# Copyright 2020 Q-CTRL Pty Ltd & Q-CTRL Inc. All rights reserved. # # Licensed under the Q-CTRL Terms of service (the "License"). Unauthorized # copying or use of this file, via any medium, is strictly prohibited. # Proprietary and confidential. You may not use this file except in compliance # with the License. You may obtain a copy of the License at # # https://q-ctrl.com/terms # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS. See the # License for the specific language. """ Functions for plotting control pulses. """ from collections import namedtuple from typing import ( Any, List, ) import numpy as np from matplotlib.ticker import ScalarFormatter from .style import qctrl_style @qctrl_style() def plot_controls(figure, controls, polar=True, smooth=False): """ Creates a plot of the specified controls. Parameters ---------- figure : matplotlib.figure.Figure The matplotlib Figure in which the plots should be placed. The dimensions of the Figure will be overridden by this method. controls : dict The dictionary of controls to plot. The keys should be the names of the controls, and the values the list of segments representing the pulse of that control. Each such segment must be a dictionary with 'value' and 'duration' keys, giving the value (in Hertz, possibly complex) and duration (in seconds) of that segment of the pulse. For example, the following would be a valid ``controls`` input:: { 'Clock': [ {'duration': 1.0, 'value': -0.5}, {'duration': 1.0, 'value': 0.5}, {'duration': 2.0, 'value': -1.5}, ], 'Microwave': [ {'duration': 0.5, 'value': 0.5 + 1.5j}, {'duration': 1.0, 'value': 0.2 - 0.3j}, ], } polar : bool, optional The mode of the plot when the values appear to be complex numbers. Plot magnitude and angle in two figures if set to True, otherwise plot I and Q in two figures. Defaults to True. smooth : bool, optional Whether to plot the controls as samples joined by straight lines, rather than as piecewise-constant segments. Defaults to False. Raises ------ ValueError If any of the input parameters are invalid. """ plots_data: List[Any] = [] for name, segments in controls.items(): durations = [] values = [] for segment in segments: durations.append(segment["duration"]) values.append(segment["value"]) values = np.array(values) plots_data = plots_data + _create_plots_data_from_control( name, durations, values, polar ) axes_list = _create_axes(figure, len(plots_data), width=7.0, height=2.0) if smooth: for axes, plot_data in zip(axes_list, plots_data): # Convert the list of durations into a list of times at the midpoints of each segment, # with a leading zero and trailing total time. # Length of 'times' is m+2 (m is the number of segments). end_points = np.cumsum(plot_data.xdata) times = np.concatenate( [[0.0], end_points - np.array(plot_data.xdata) * 0.5, [end_points[-1]]] ) # Pad each values array with leading and trailing zeros, to indicate that the pulse is # zero outside the plot domain. Length of 'values' is m+2. values = np.pad(plot_data.values, ((1, 1)), "constant") axes.plot(times, values, linewidth=2) axes.fill(times, values, alpha=0.3) axes.axhline(y=0, linewidth=1, zorder=-1) axes.set_ylabel(plot_data.ylabel) else: for axes, plot_data in zip(axes_list, plots_data): # Convert the list of durations into times, including a leading zero. Length of 'times' # is m+1 (m is the number of segments). times = np.insert(np.cumsum(plot_data.xdata), 0, 0.0) # Pad each values array with leading and trailing zeros, to indicate that the pulse is # zero outside the plot domain. Length of 'values' is m+2. values = np.pad(plot_data.values, ((1, 1)), "constant") # *---v2--* # | | # *--v1--* | *-v4-* # | | | | # | *---v3---* | # --v0--* *---v5-- # t0 t1 t2 t3 t4 # To plot a piecewise-constant pulse, we need to sample from the times array at indices # [0, 0, 1, 1, ..., m-1, m-1, m, m ], and from the values arrays at indices # [0, 1, 1, 2, ..., m-1, m, m, m+1]. time_indices = np.repeat(np.arange(len(times)), 2) value_indices = np.repeat(np.arange(len(values)), 2)[1:-1] axes.plot(times[time_indices], values[value_indices], linewidth=2) axes.fill(times[time_indices], values[value_indices], alpha=0.3) axes.axhline(y=0, linewidth=1, zorder=-1) for time in times: axes.axvline(x=time, linestyle="--", linewidth=1, zorder=-1) axes.set_ylabel(plot_data.ylabel) axes_list[-1].set_xlabel(plots_data[-1].xlabel) @qctrl_style() def plot_smooth_controls(figure, controls, polar=True): """ Creates a plot of the specified smooth controls. Parameters ---------- figure : matplotlib.figure.Figure The matplotlib Figure in which the plots should be placed. The dimensions of the Figure will be overridden by this method. controls : dict The dictionary of controls to plot. The keys should be the names of the controls, and the values the list of samples representing the pulse of that control. Each such sample must be a dictionary with 'value' and 'time' keys, giving the value (in Hertz, possibly complex) and time (in seconds) of that sample of the pulse. The times must be in increasing order. For example, the following would be a valid ``controls`` input:: { 'Clock': [ {'time': 0.0, 'value': -0.5}, {'time': 1.0, 'value': 0.5}, {'time': 3.0, 'value': -1.5}, ], 'Microwave': [ {'time': 0.5, 'value': 0.5 + 1.5j}, {'time': 2.0, 'value': 0.2 - 0.3j}, ], } polar : bool, optional The mode of the plot when the values appear to be complex numbers. Plot magnitude and angle in two figures if set to True, otherwise plot I and Q in two figures. Defaults to True. Raises ------ ValueError If any of the input parameters are invalid. """ plots_data: List[Any] = [] for name, samples in controls.items(): times = [] values = [] for sample in samples: times.append(sample["time"]) values.append(sample["value"]) values = np.array(values) plots_data = plots_data + _create_plots_data_from_control( name, times, values, polar ) axes_list = _create_axes(figure, len(plots_data), width=7.0, height=2.0) for axes, plot_data in zip(axes_list, plots_data): # Pad with leading and trailing zeros, to indicate that the pulse is zero outside the plot # domain. times = np.pad(plot_data.xdata, ((1, 1)), "edge") values = np.pad(plot_data.values, ((1, 1)), "constant") axes.plot(times, values, linewidth=2) axes.fill(times, values, alpha=0.3) axes.axhline(y=0, linewidth=1, zorder=-1) axes.set_ylabel(plot_data.ylabel)