[minor] update jupyter notebook demo

sequence-toolbox · Dec 11, 2024 · 116d622 · 116d622
1 parent 5826c44
commit 116d622
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Showing 5 changed files with 47 additions and 57 deletions.
diff --git a/example/qkd.ipynb b/example/qkd.ipynb
@@ -31,10 +31,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
+    "# !pip install ipywidgets   # in case ipywidgets is not installed\n",
     "from ipywidgets import interact\n",
     "from matplotlib import pyplot as plt\n",
     "import time"
@@ -65,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -104,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,10 +135,8 @@
     "    cc1.set_ends(n2, n1.name)\n",
     "    # construct a quantum communication channel\n",
     "    # (with arguments for the channel name, timeline, attenuation (in db/m), and distance (in m))\n",
-    "    qc0 = QuantumChannel(\"qc_n1_n2\", tl, attenuation=1e-5, distance=1e3,\n",
-    "                         polarization_fidelity=0.97)\n",
-    "    qc1 = QuantumChannel(\"qc_n2_n1\", tl, attenuation=1e-5, distance=1e3,\n",
-    "                         polarization_fidelity=0.97)\n",
+    "    qc0 = QuantumChannel(\"qc_n1_n2\", tl, attenuation=1e-5, distance=1e3, polarization_fidelity=0.97)\n",
+    "    qc1 = QuantumChannel(\"qc_n2_n1\", tl, attenuation=1e-5, distance=1e3, polarization_fidelity=0.97)\n",
     "    qc0.set_ends(n1, n2.name)\n",
     "    qc1.set_ends(n2, n1.name)\n",
     "    \n",
@@ -183,13 +182,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "28d22d2059344083b9c46aef7f89a6fc",
+       "model_id": "e8aae143b19945ec903d712d36db68b0",
        "version_major": 2,
        "version_minor": 0
       },
@@ -206,7 +205,7 @@
        "<function __main__.test(sim_time, keysize)>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -240,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -284,10 +283,8 @@
     "    cc1 = ClassicalChannel(\"cc_n2_n1\", tl, distance=1e3)\n",
     "    cc0.set_ends(n1, n2.name)\n",
     "    cc1.set_ends(n2, n1.name)\n",
-    "    qc0 = QuantumChannel(\"qc_n1_n2\", tl, attenuation=1e-5, distance=1e3,\n",
-    "                         polarization_fidelity=0.97)\n",
-    "    qc1 = QuantumChannel(\"qc_n2_n1\", tl, attenuation=1e-5, distance=1e3,\n",
-    "                         polarization_fidelity=0.97)\n",
+    "    qc0 = QuantumChannel(\"qc_n1_n2\", tl, attenuation=1e-5, distance=1e3, polarization_fidelity=0.97)\n",
+    "    qc1 = QuantumChannel(\"qc_n2_n1\", tl, attenuation=1e-5, distance=1e3, polarization_fidelity=0.97)\n",
     "    qc0.set_ends(n1, n2.name)\n",
     "    qc1.set_ends(n2, n1.name)\n",
     "    \n",
@@ -343,13 +340,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d0703f7c810843e7b4e4c3d286b20381",
+       "model_id": "d50c93005ce44aed8e11db898491341c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -366,7 +363,7 @@
        "<function __main__.test(sim_time, keysize)>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -389,7 +386,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "test",
    "language": "python",
    "name": "python3"
   },
@@ -403,7 +400,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,

diff --git a/example/random_request_network.ipynb b/example/random_request_network.ipynb
@@ -32,8 +32,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
+    "# !pip install ipywidgets   # in case ipywidgets is not installed\n",
     "from ipywidgets import interact\n",
+    "import pandas as pd\n",
     "import time"
    ]
   },
@@ -78,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -138,7 +139,7 @@
     "    memory_sizes = []\n",
     "    for node in network_topo.get_nodes_by_type(RouterNetTopo.QUANTUM_ROUTER):\n",
     "        node_name = node.name\n",
-    "        for reservation in node.network_manager.protocol_stack[1].accepted_reservation:\n",
+    "        for reservation in node.network_manager.protocol_stack[1].accepted_reservations:\n",
     "            s_t, e_t, size = reservation.start_time, reservation.end_time, reservation.memory_size\n",
     "            if reservation.initiator != node.name and reservation.responder != node.name:\n",
     "                size *= 2\n",
@@ -170,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -238,20 +239,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e5b30c59d8854386a190d0ee3d9e6169",
+       "model_id": "3696019279184c42bc92a3ba929865fa",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "interactive(children=(FloatSlider(value=50000.0, description='sim_time', max=150000.0, min=-50000.0), Dropdown…"
+       "interactive(children=(IntSlider(value=3000, description='sim_time', max=4000, min=2000, step=500), Dropdown(de…"
       ]
      },
      "metadata": {},
@@ -263,13 +264,13 @@
        "<function __main__.test(sim_time, qc_atten)>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "interact(test, sim_time=50e3, qc_atten=[0, 1e-5, 2e-5])"
+    "interact(test, sim_time=(2000, 4000, 500), qc_atten=[0, 1e-5, 2e-5])"
    ]
   },
   {
@@ -282,9 +283,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "venv",
+   "display_name": "test",
    "language": "python",
-   "name": "venv"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -296,7 +297,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.2"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,

diff --git a/example/three_node_eg_ep_es.ipynb b/example/three_node_eg_ep_es.ipynb
@@ -40,6 +40,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# !pip install ipywidgets   # in case ipywidgets is not installed\n",
     "from ipywidgets import interact\n",
     "from matplotlib import pyplot as plt\n",
     "import time"
@@ -288,7 +289,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ae7c189c50ff4b7fab644d454646e5b6",
+       "model_id": "3ac58091b34a48859e6116198cda0bd3",
        "version_major": 2,
        "version_minor": 0
       },
@@ -327,9 +328,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "venv",
+   "display_name": "test",
    "language": "python",
-   "name": "venv"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -341,7 +342,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.2"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,

diff --git a/example/two_node_eg.ipynb b/example/two_node_eg.ipynb
@@ -36,6 +36,7 @@
    },
    "outputs": [],
    "source": [
+    "# !pip install ipywidgets   # in case ipywidgets is not installed\n",
     "from ipywidgets import interact\n",
     "from matplotlib import pyplot as plt\n",
     "import time"
@@ -238,15 +239,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
     "tags": []
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ace2a2b9901c45e5adbf82cf44f4bd3a",
+       "model_id": "9ea2b2a6f968415396064e10de53449d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -263,7 +264,7 @@
        "<function __main__.test(sim_time, cc_delay, qc_atten, qc_dist)>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -285,18 +286,11 @@
     "\n",
     "In this example, we note that the number of entangled memories increases at a roughly linear rate with a slope inversely proportional to the quantum channel length and attenuation. We also see clusters of memories entangled at roughly the same time, based on entanglement processes that are started at the same time and encounter similar errors. The time intervals between these events roughly corresponds to the classical channel delay."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "test",
    "language": "python",
    "name": "python3"
   },
@@ -310,7 +304,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,

diff --git a/sequence/gui/user_templates.json b/sequence/gui/user_templates.json
@@ -1,7 +1,8 @@
 {
-    "BSM_node": {
+    "BSMNode": {
         "default_BSM": {
-            "detector_type": "default_detector"
+            "detector_1": "default_detector",
+            "detector_2": "default_detector"
         }
     },
     "Detector": {
@@ -26,21 +27,17 @@
             "raw_fidelity": 0.85
         }
     },
-    "Photon_Source": {},
-    "Protocol": {},
-    "QKD": {
+    "PhotonSource": {},
+    "QKDNode": {
         "default_QKD": {
             "encoding": "polarization",
             "stack_size": 5
         }
     },
-    "QuantumErrorCorrection": {},
-    "QuantumRepeater": {},
     "QuantumRouter": {
         "default_router": {
             "mem_type": "default_memory",
             "memo_size": 50
         }
-    },
-    "Temp": {}
+    }
 }