145 lines
7.7 KiB
Python
145 lines
7.7 KiB
Python
"""Generates bar plots for gate fusion comparisons."""
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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import seaborn as sns
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from matplotlib.patches import Patch
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matplotlib.rcParams['mathtext.fontset'] = 'cm'
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matplotlib.rcParams['font.family'] = 'STIXGeneral'
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def plot_fusion_nqubits(data, circuit, quantity, precision="double", width=0.1, fontsize=30, legend=False, logscale=False, save=False):
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matplotlib.rcParams["font.size"] = fontsize
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# Set plot params
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hatches = ['/', '\\', 'o', '-', 'x', '.', '*']
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nqubits = [20, 22, 24, 26, 28]
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widths = [-5 * width / 2, - 3 * width / 2, -width / 2, width / 2, 3 * width / 2, 5 * width / 2]
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oranges = sns.color_palette("Oranges", 2)
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purples = sns.color_palette("Purples", 2)
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greens = sns.color_palette("Greens", 2)
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# Plot the results
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plt.figure(figsize=(25, 9))
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plt.title(f"qibojit - Gate fusion - {circuit}")
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xvalues = np.array(range(len(nqubits)))
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plt.xticks(xvalues, nqubits)
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base_condition = ((data["precision"] == precision) & (data["circuit"] == circuit))
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=numba")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[0], heights, color=oranges[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=numba,max_qubits=2")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[1], heights, color=oranges[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cupy")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[2], heights, color=purples[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cupy,max_qubits=2")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[3], heights, color=purples[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cuquantum")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[4], heights, color=greens[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cuquantum,max_qubits=2")
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heights = np.array([float(data[condition & (data["nqubits"] == n)][quantity]) for n in nqubits])
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plt.bar(xvalues + widths[5], heights, color=greens[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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plt.xlabel("Number of qubits")
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if quantity == "total_dry_time":
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plt.ylabel("Total dry run time (sec)")
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elif quantity == "total_simulation_time":
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plt.ylabel("Total simulation time (sec)")
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if legend:
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legend_elements = [
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Patch(facecolor="w", edgecolor="k", hatch=hatches[0], label="No fusion"),
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Patch(facecolor="w", edgecolor="k", hatch=hatches[1], label="Two-qubit fusion"),
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Patch(color=oranges[1], label="numba"),
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Patch(color=purples[1], label="cupy"),
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Patch(color=greens[1], label="cuquantum")
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]
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plt.legend(handles=legend_elements)
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if save:
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plt.savefig(f"qibojit_fusion_{precision}_{circuit}_{quantity}.pdf", bbox_inches="tight")
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else:
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plt.show()
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def plot_fusion_circuits(data, nqubits, quantity, precision="double", width=0.1, fontsize=30, legend=False, logscale=False, save=False):
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matplotlib.rcParams["font.size"] = fontsize
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# Set plot params
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hatches = ['/', '\\', 'o', '-', 'x', '.', '*']
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circuits = ["qft", "variational", "supremacy", "qv", "bv"]
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widths = [-5 * width / 2, - 3 * width / 2, -width / 2, width / 2, 3 * width / 2, 5 * width / 2]
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oranges = sns.color_palette("Oranges", 2)
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purples = sns.color_palette("Purples", 2)
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greens = sns.color_palette("Greens", 2)
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# Plot the results
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plt.figure(figsize=(25, 9))
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plt.title(f"qibojit - Gate fusion - {nqubits} qubits")
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xvalues = np.array(range(len(circuits)))
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plt.xticks(xvalues, circuits)
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base_condition = ((data["precision"] == precision) & (data["nqubits"] == nqubits))
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=numba")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[0], heights, color=oranges[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=numba,max_qubits=2")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[1], heights, color=oranges[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cupy")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[2], heights, color=purples[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cupy,max_qubits=2")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[3], heights, color=purples[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cuquantum")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[4], heights, color=greens[0], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[0], edgecolor='w')
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condition = base_condition & (data["library_options"] == "backend=qibojit,platform=cuquantum,max_qubits=2")
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heights = np.array([float(data[condition & (data["circuit"] == c)][quantity]) for c in circuits])
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plt.bar(xvalues + widths[5], heights, color=greens[1], align="center", width=width,
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log=logscale, alpha=1, hatch=hatches[1], edgecolor='w')
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if quantity == "total_dry_time":
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plt.ylabel("Total dry run time (sec)")
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elif quantity == "total_simulation_time":
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plt.ylabel("Total simulation time (sec)")
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if legend:
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legend_elements = [
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Patch(facecolor="w", edgecolor="k", hatch=hatches[0], label="No fusion"),
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Patch(facecolor="w", edgecolor="k", hatch=hatches[1], label="Two-qubit fusion"),
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Patch(color=oranges[1], label="numba"),
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Patch(color=purples[1], label="cupy"),
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Patch(color=greens[1], label="cuquantum")
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]
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plt.legend(handles=legend_elements, bbox_to_anchor=(1,1))
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if save:
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plt.savefig(f"qibojit_fusion_{precision}_{nqubits}qubits_{quantity}.pdf", bbox_inches="tight")
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else:
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plt.show() |