{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sankey Plot"
   ]
  },  
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>number</th>\n",
       "      <th>remain</th>\n",
       "      <th>label</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0hpa1_Nb2</td>\n",
       "      <td>12hpa2_Nb2</td>\n",
       "      <td>69</td>\n",
       "      <td>True</td>\n",
       "      <td>Nb2</td>\n",
       "      <td>0hpa1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0hpa1_cathepsin</td>\n",
       "      <td>12hpa2_cathepsin</td>\n",
       "      <td>1744</td>\n",
       "      <td>True</td>\n",
       "      <td>cathepsin</td>\n",
       "      <td>0hpa1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0hpa1_cathepsin</td>\n",
       "      <td>12hpa2_gut</td>\n",
       "      <td>210</td>\n",
       "      <td>True</td>\n",
       "      <td>cathepsin</td>\n",
       "      <td>0hpa1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0hpa1_epidermal</td>\n",
       "      <td>12hpa2_epidermal</td>\n",
       "      <td>1589</td>\n",
       "      <td>True</td>\n",
       "      <td>epidermal</td>\n",
       "      <td>0hpa1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0hpa1_epidermal</td>\n",
       "      <td>12hpa2_muscle</td>\n",
       "      <td>97</td>\n",
       "      <td>True</td>\n",
       "      <td>epidermal</td>\n",
       "      <td>0hpa1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              From                To  number  remain      label   time\n",
       "0        0hpa1_Nb2        12hpa2_Nb2      69    True        Nb2  0hpa1\n",
       "1  0hpa1_cathepsin  12hpa2_cathepsin    1744    True  cathepsin  0hpa1\n",
       "2  0hpa1_cathepsin        12hpa2_gut     210    True  cathepsin  0hpa1\n",
       "3  0hpa1_epidermal  12hpa2_epidermal    1589    True  epidermal  0hpa1\n",
       "4  0hpa1_epidermal     12hpa2_muscle      97    True  epidermal  0hpa1"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##################################\n",
    "# loading data\n",
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv('E:/wochong/s40. MetaCell/sankey/strong.csv',sep='\\t',header=0)\n",
    "data['label'] = data.apply(lambda row : row['From'].split('_')[1],axis=1)\n",
    "data['time'] = data.apply(lambda row : row['From'].split('_')[0],axis=1)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sankey.')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from matplotlib.sankey import Sankey\n",
    "\n",
    "Sankey(flows=[0.25, 0.15, 0.60, -0.20, -0.15, -0.05, -0.50, -0.10],\n",
    "       labels=['', '', '', 'First', 'Second', 'Third', 'Fourth', 'Fifth'],\n",
    "       orientations=[-1, 1, 0, 1, 1, 1, 0, -1]).finish()\n",
    "plt.title(\"Sankey.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Nb2', 'cathepsin', 'epidermal', 'gut', 'muscle', 'neural',\n",
       "       'parenchymal', 'protonephridia', 'pharynx'], dtype=object)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['label'].unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "############################\n",
    "#  config x.y,color\n",
    "import numpy as np\n",
    "X_pos = {\n",
    "    'WT'    : 0.01,\n",
    "    '0hpa1' : 0.06,\n",
    "    '12hpa2': 0.13,\n",
    "    '36hpa2': 0.26,\n",
    "    '3dpa2' : 0.39,\n",
    "    '5dpa1' : 0.51,\n",
    "    '7dpa2' : 0.64,\n",
    "    '10dpa1': 0.77,\n",
    "    '14dpa1': 0.9\n",
    "}\n",
    "Depths = {\n",
    "    '0hpa1' : 0,\n",
    "    '12hpa2': 1,\n",
    "    '36hpa2': 2,\n",
    "    '3dpa2' : 3,\n",
    "    '5dpa1' : 4,\n",
    "    '7dpa2' : 5,\n",
    "    '10dpa1': 6,\n",
    "    '14dpa1': 7\n",
    "}\n",
    "colors = [\n",
    "'#1EA51D',\n",
    "'#FBD26A',\n",
    "'#002FA7',\n",
    "'#BB86FC',\n",
    "'#03DAC6',\n",
    "'#CF6679',\n",
    "'#A51DA5',\n",
    "'#B0B0B0',\n",
    "'#D62237',\n",
    "'#333333',\n",
    "]\n",
    "Y_pos = {}\n",
    "Cmap = {}\n",
    "for i,x in enumerate(data['label'].unique()):\n",
    "    Y_pos[x] =  float(i)/10.0\n",
    "    Cmap[x] = colors[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_pos = {\n",
    " 'cathepsin': 0.1,\n",
    " 'gut': 0.2,\n",
    " 'epidermal': 0.3,\n",
    " 'muscle': 0.4,\n",
    " 'neural': 0.5,\n",
    " 'Nb2': 0.6,\n",
    " 'parenchymal': 0.7,\n",
    " 'protonephridia': 0.8,\n",
    " 'pharynx': 0.9,\n",
    " 'other':0.91,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Cmap = { 'other':'#000000',\n",
    "         'neural': '#BB86FC',\n",
    "         'cathepsin': '#03DAC6',\n",
    "         'epidermal': '#002FA7',\n",
    "         'gut': '#1EA51D',\n",
    "         'muscle': '#CF6679',\n",
    "         'Nb2': '#D62237',\n",
    "         'parenchymal': '#FBD26A',\n",
    "         'pharynx':'#B0B0B0' ,\n",
    "         'protonephridia': '#A51DA5'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "def get_nodes_links(data):\n",
    "    node1 = data['From'].unique()\n",
    "    node2 = data['To'].unique()\n",
    "    nodes = np.union1d(node1,node2)\n",
    "    node_id = {}\n",
    "    i = 0;\n",
    "    node = {\n",
    "        \"label\":[],\n",
    "        \"x\":[],\n",
    "        \"y\":[],\n",
    "        \"color\":[],\n",
    "        \n",
    "    };\n",
    "    link = {\n",
    "        \"source\": [],\n",
    "        \"target\": [],\n",
    "        \"value\": [],\n",
    "        \"color\" :[],\n",
    "    }\n",
    "    #create nodes\n",
    "    for x in nodes:\n",
    "        time = x.split('_')[0]\n",
    "        anno = x.split('_')[1]\n",
    "        node_id[x] = i;\n",
    "        i = i + 1 ;\n",
    "        node['label'].append(\"\")\n",
    "        node['x'].append(X_pos[time])\n",
    "        node['y'].append(Y_pos[anno])\n",
    "        node['color'].append(Cmap[anno])\n",
    "    #create links\n",
    "    for _ , row in data.iterrows():\n",
    "        anno = row['label']\n",
    "        fromkey = row['From']\n",
    "        tokey= row['To']\n",
    "        link['source'].append(node_id[fromkey])\n",
    "        link['target'].append(node_id[tokey])\n",
    "        link['value'].append(row['number'])\n",
    "        link['color'].append(Cmap[anno])\n",
    "    return node,link\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "arrangement": "perpendicular",
         "link": {
          "color": [
           "#D62237",
           "#03DAC6",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#CF6679",
           "#CF6679",
           "#BB86FC",
           "#FBD26A",
           "#D62237",
           "#D62237",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#1EA51D",
           "#CF6679",
           "#CF6679",
           "#BB86FC",
           "#FBD26A",
           "#FBD26A",
           "#A51DA5",
           "#D62237",
           "#D62237",
           "#03DAC6",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#CF6679",
           "#CF6679",
           "#BB86FC",
           "#BB86FC",
           "#BB86FC",
           "#FBD26A",
           "#FBD26A",
           "#B0B0B0",
           "#A51DA5",
           "#D62237",
           "#D62237",
           "#D62237",
           "#D62237",
           "#03DAC6",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#CF6679",
           "#CF6679",
           "#CF6679",
           "#BB86FC",
           "#BB86FC",
           "#FBD26A",
           "#FBD26A",
           "#B0B0B0",
           "#A51DA5",
           "#D62237",
           "#D62237",
           "#03DAC6",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#CF6679",
           "#BB86FC",
           "#BB86FC",
           "#FBD26A",
           "#B0B0B0",
           "#D62237",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#1EA51D",
           "#CF6679",
           "#CF6679",
           "#BB86FC",
           "#BB86FC",
           "#FBD26A",
           "#B0B0B0",
           "#D62237",
           "#03DAC6",
           "#03DAC6",
           "#002FA7",
           "#002FA7",
           "#1EA51D",
           "#CF6679",
           "#BB86FC",
           "#FBD26A",
           "#B0B0B0"
          ],
          "source": [
           0,
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             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Test"
        },
        "width": 700
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "import plotly.io as pio\n",
    "#pio.kaleido.scope.default_format = \"svg\"\n",
    "\n",
    "nodes , links = get_nodes_links(data)\n",
    "\n",
    "fig = go.Figure(go.Sankey(node = nodes,arrangement='perpendicular',\n",
    "    link = links ) )\n",
    "\n",
    "fig.update_layout(\n",
    "    title=\"Test\",\n",
    "    font=dict(size = 10, color = 'white'),\n",
    "    plot_bgcolor='black',\n",
    "    paper_bgcolor='black'\n",
    ")\n",
    "fig.update_layout(\n",
    "    autosize=False,\n",
    "    width=700,\n",
    "    height=700,\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import kaleido\n",
    "fig.write_image(\"E:/wochong/fig1.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "arrangement": "perpendicular",
         "link": {
          "color": [
           "#D62237",
           "#03DAC6",
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          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Test"
        },
        "width": 1000
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "nodes , links = get_nodes_links(data)\n",
    "\n",
    "fig = go.Figure(go.Sankey(node = nodes,arrangement='perpendicular',\n",
    "    link = links ) )\n",
    "\n",
    "fig.update_layout(\n",
    "    title=\"Test\",\n",
    "    font=dict(size = 10, color = 'white'),\n",
    "    plot_bgcolor='black',\n",
    "    paper_bgcolor='black'\n",
    ")\n",
    "fig.update_layout(\n",
    "    autosize=False,\n",
    "    width=1000,\n",
    "    height=700,\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the interactive image in above cell:\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.write_image(\"E:/wochong/fig1.pdf\")\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "stereopy1",
   "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": "3.8.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}