You down with plt (yeah you know me) [Issue 97]

examples/state_and_process_plots.ipynb

@@ -0,0 +1,351 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# State and Process Plots"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Some states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# python related things\n",
+    "import numpy as np\n",
+    "from matplotlib import pyplot as plt\n",
+    "\n",
+    "# quantum related things\n",
+    "from pyquil.gate_matrices import X, Y, Z, H, CNOT, CZ\n",
+    "from forest.benchmarking.superoperator_tools import *\n",
+    "from forest.benchmarking.utils import n_qubit_pauli_basis\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define some quantum states"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Single qubit quantum states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ZERO = np.array([[1, 0], [0, 0]])\n",
+    "ONE = np.array([[0, 0], [0, 1]])\n",
+    "\n",
+    "plus = np.array([[1], [1]]) / np.sqrt(2)\n",
+    "minus = np.array([[1], [-1]]) / np.sqrt(2)\n",
+    "PLUS = plus @ plus.T.conj()\n",
+    "MINUS = minus @ minus.T.conj()\n",
+    "\n",
+    "plusy = np.array([[1], [1j]]) / np.sqrt(2)\n",
+    "minusy = np.array([[1], [-1j]]) / np.sqrt(2)\n",
+    "PLUSy = plusy @ plusy.T.conj()\n",
+    "MINUSy = minusy @ minusy.T.conj()\n",
+    "\n",
+    "MIXED = np.eye(2)/2\n",
+    "\n",
+    "single_qubit_states = [('0',ZERO),('1',ONE),('+',PLUS),('-',MINUS),('+i',PLUSy),('-i',MINUSy)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Two qubit quantum states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "P00 = np.kron(ZERO, ZERO)\n",
+    "P01 = np.kron(ZERO, ONE)\n",
+    "P10 = np.kron(ONE, ZERO)\n",
+    "P11 = np.kron(ONE, ONE)\n",
+    "\n",
+    "bell = 1/np.sqrt(2) * np.array([[1, 0, 0, 1]])\n",
+    "BELL = np.outer(bell, bell)\n",
+    "\n",
+    "two_qubit_states = [('00',P00), ('01',P01), ('10',P10), ('11',P11),('BELL',BELL)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Two types of Pauli Representation of a quantum state"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# convert to pauli basis\n",
+    "n_qubits = 1\n",
+    "pl_basis_oneq = n_qubit_pauli_basis(n_qubits)\n",
+    "c2p_oneq = computational2pauli_basis_matrix(2*n_qubits)\n",
+    "oneq_states_pl = [ (state[0], np.real(c2p_oneq@vec(state[1]))) for state in single_qubit_states]\n",
+    "\n",
+    "n_qubits = 2\n",
+    "pl_basis_twoq = n_qubit_pauli_basis(n_qubits)\n",
+    "c2p_twoq = computational2pauli_basis_matrix(2*n_qubits)\n",
+    "twoq_states_pl = [ (state[0], np.real(c2p_twoq@vec(state[1]))) for state in two_qubit_states]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from forest.benchmarking.plotting.state_process import plot_pauli_rep_of_state, plot_pauli_bar_rep_of_state"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Single Qubit states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# can plot vertically\n",
+    "fig, ax = plt.subplots(1)\n",
+    "plot_pauli_rep_of_state(oneq_states_pl[0][1], ax, pl_basis_oneq.labels, 'State is |0>')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# or can plot horizontally\n",
+    "for state in oneq_states_pl:\n",
+    "    fig, ax = plt.subplots(1)\n",
+    "    plot_pauli_rep_of_state(state[1].transpose(), ax, pl_basis_oneq.labels, 'State is |'+state[0]+'>')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for state in oneq_states_pl:\n",
+    "    fig, ax = plt.subplots(1)\n",
+    "    plot_pauli_bar_rep_of_state(state[1].flatten(), ax, pl_basis_oneq.labels, 'State is |'+state[0]+'>')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Two qubit states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# can plot vertically \n",
+    "fig, ax = plt.subplots(1)\n",
+    "plot_pauli_rep_of_state(twoq_states_pl[0][1], ax, pl_basis_twoq.labels, 'State is |0>')\n",
+    "# can plot horizontially\n",
+    "fig, ax = plt.subplots(1)\n",
+    "plot_pauli_rep_of_state(twoq_states_pl[0][1].transpose(), ax, pl_basis_twoq.labels, 'State is |0>')\n",
+    "fig, ax = plt.subplots(1)\n",
+    "plot_pauli_rep_of_state(twoq_states_pl[-1][1].transpose(), ax, pl_basis_twoq.labels, 'State is BELL')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Also bar plots \n",
+    "fig, ax = plt.subplots(1)\n",
+    "plot_pauli_bar_rep_of_state(twoq_states_pl[-1][1].flatten(), ax, pl_basis_twoq.labels, 'State is BELL')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Plot a Quantum Process as a Pauli Transfer Matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Xpl = kraus2pauli_liouville(X)\n",
+    "Hpl = kraus2pauli_liouville(H)\n",
+    "from forest.benchmarking.plotting.state_process import plot_pauli_transfer_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f, (ax1) = plt.subplots(1, 1, figsize=(5, 4.2))\n",
+    "plot_pauli_transfer_matrix(np.real(Xpl), ax1, pl_basis_oneq.labels, 'X gate')\n",
+    "\n",
+    "f, (ax1) = plt.subplots(1, 1, figsize=(5, 4.2))\n",
+    "plot_pauli_transfer_matrix(np.real(Hpl), ax1, pl_basis_oneq.labels, 'H gate')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "CNOTpl = kraus2pauli_liouville(CNOT)\n",
+    "CZpl = kraus2pauli_liouville(CZ)\n",
+    "\n",
+    "f, (ax1) = plt.subplots(1, 1, figsize=(5, 4.2))\n",
+    "plot_pauli_transfer_matrix(np.real(CNOTpl), ax1, pl_basis_twoq.labels, 'CNOT')\n",
+    "f, (ax1) = plt.subplots(1, 1, figsize=(5, 4.2))\n",
+    "plot_pauli_transfer_matrix(np.real(CZpl), ax1, pl_basis_twoq.labels, 'CZ')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hinton Plots for states and processes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The warning here is the `hinton_real` function only works for plotting a real matrix so the user has to be careful. It will take the absolute value of complex numbers."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualize a real state in the computational basis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from forest.benchmarking.utils import n_qubit_computational_basis\n",
+    "from forest.benchmarking.plotting.hinton import hinton_real\n",
+    "oneq = n_qubit_computational_basis(1)\n",
+    "oneq_latex_labels = [r'$|{}\\rangle$'.format(''.join(j)) for j in oneq.labels]\n",
+    "\n",
+    "_ = hinton_real(ZERO, max_weight=1.0, xlabels=oneq_latex_labels, ylabels=oneq_latex_labels, ax=None, title=r'$|0\\rangle$')\n",
+    "_ = hinton_real(MINUS, max_weight=1.0, xlabels=oneq_latex_labels, ylabels=oneq_latex_labels, ax=None, title=r'$|-\\rangle$')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualize a Process Pauli basis\n",
+    "The Pauli representation is real so we can plot any process"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "_ = hinton_real(Xpl, max_weight=1.0, xlabels=pl_basis_oneq.labels, ylabels=pl_basis_oneq.labels, ax=None, title='X gate')\n",
+    "_ = hinton_real(Hpl, max_weight=1.0, xlabels=pl_basis_oneq.labels, ylabels=pl_basis_oneq.labels, ax=None, title='H gate')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So far things look the same as the `plot_pauli_transfer_matrix` but we can plot using the traditional Hinton diagram colors, now the size of the squares makes a difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import cm\n",
+    "_ = hinton_real(Hpl, max_weight=1.0, xlabels=pl_basis_oneq.labels, ylabels=pl_basis_oneq.labels,cmap = cm.Greys_r, ax=None, title='Good H gate')\n",
+    "_ = hinton_real(Hpl-0.3, max_weight=1.0, xlabels=pl_basis_oneq.labels, ylabels=pl_basis_oneq.labels, cmap = cm.Greys_r, ax=None, title='Bad H gate')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

examples/tomography_process.ipynb

@@ -130,13 +130,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'process_choi_ideal' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m--------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-7-cb314dff65b7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0max1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max2\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m12\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mplot_pauli_transfer_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchoi2pauli_liouville\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocess_choi_ideal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Ideal'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0mplot_pauli_transfer_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchoi2pauli_liouville\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocess_choi_est\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Estimate'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtight_layout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'process_choi_ideal' is not defined"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12c740240>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "from forest.benchmarking.superoperator_tools import choi2pauli_liouville\n",
-    "from forest.benchmarking.tomography import plot_pauli_transfer_matrix\n",
+    "from forest.benchmarking.plotting.state_process import plot_pauli_transfer_matrix\n",
     "\n",
     "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,5))\n",
     "plot_pauli_transfer_matrix(choi2pauli_liouville(process_choi_ideal), ax1, title='Ideal')\n",