{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "30e34fff-ac77-4a38-8b83-8043ca4e3d77",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.lines import Line2D\n",
    "import uncertainties\n",
    "import numpy as np\n",
    "import scipy.stats\n",
    "from cycler import cycler\n",
    "import seaborn as sns\n",
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "import itertools\n",
    "\n",
    "FLUX_DATA_SOURCE = \"gerosa\"\n",
    "#FLUX_DATA_SOURCE = \"davidi\"\n",
    "\n",
    "\n",
    "color_palettes = [\"bright\", \"Set2\", \"Set3\", \"Purples\", \"Greens\", \"Greys\", \"Blues\", \"Reds\", \"Oranges\"]\n",
    "COLORS = list(itertools.chain(*map(sns.color_palette, color_palettes)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fe5e4c9b-a57c-48d8-adc7-37951fe839b0",
   "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>gene</th>\n",
       "      <th>cycling_pool</th>\n",
       "      <th>kcat_1_per_sec</th>\n",
       "      <th>compilation</th>\n",
       "      <th>literature for kcat</th>\n",
       "      <th>Km_uM</th>\n",
       "      <th>Km_metabolite</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reaction</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>UAAGDS</th>\n",
       "      <td>murE</td>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>1.1</td>\n",
       "      <td>Davidi et al</td>\n",
       "      <td>PMID:11722566</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>C00692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAMAS</th>\n",
       "      <td>murC</td>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>6.9</td>\n",
       "      <td>Davidi et al</td>\n",
       "      <td>PMID:8550531</td>\n",
       "      <td>51.971567</td>\n",
       "      <td>C01050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSK</th>\n",
       "      <td>thrB</td>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>17.0</td>\n",
       "      <td>Davidi et al</td>\n",
       "      <td>PMID:17559838</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>C00263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIRC2</th>\n",
       "      <td>purK</td>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>130.0</td>\n",
       "      <td>Davidi et al</td>\n",
       "      <td>PMID:10572016</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>C03373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRAIS</th>\n",
       "      <td>purM</td>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>4.1</td>\n",
       "      <td>Davidi et al</td>\n",
       "      <td>PMID:3530323;10508786</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>C04640</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          gene     cycling_pool  kcat_1_per_sec   compilation  \\\n",
       "reaction                                                        \n",
       "UAAGDS    murE  AMP + ADP + ATP             1.1  Davidi et al   \n",
       "UAMAS     murC  AMP + ADP + ATP             6.9  Davidi et al   \n",
       "HSK       thrB  AMP + ADP + ATP            17.0  Davidi et al   \n",
       "AIRC2     purK  AMP + ADP + ATP           130.0  Davidi et al   \n",
       "PRAIS     purM  AMP + ADP + ATP             4.1  Davidi et al   \n",
       "\n",
       "            literature for kcat       Km_uM Km_metabolite  \n",
       "reaction                                                   \n",
       "UAAGDS            PMID:11722566   76.000000        C00692  \n",
       "UAMAS              PMID:8550531   51.971567        C01050  \n",
       "HSK               PMID:17559838  150.000000        C00263  \n",
       "AIRC2             PMID:10572016   66.000000        C03373  \n",
       "PRAIS     PMID:3530323;10508786   27.000000        C04640  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def eval_Km(value):\n",
    "    if pd.isnull(value):\n",
    "        return np.nan\n",
    "    Km = eval(value)\n",
    "    if type(Km) == list:\n",
    "        return scipy.stats.gmean(Km)\n",
    "    else:\n",
    "        return float(Km)\n",
    "\n",
    "kinetics_df = pd.read_csv('data/enzyme_kinetics.csv', index_col=0)\n",
    "kinetics_df[\"Km_uM\"] = kinetics_df.Km_uM.apply(eval_Km)\n",
    "kinetics_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8d6d900d-c2e6-42b4-99be-8aa076f73f8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "        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>reaction</th>\n",
       "      <th>gene</th>\n",
       "      <th>condition</th>\n",
       "      <th>protein_abundance_mmol_per_gCDW</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>ICDHyr</td>\n",
       "      <td>icd</td>\n",
       "      <td>galactose</td>\n",
       "      <td>0.000170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>ICDHyr</td>\n",
       "      <td>icd</td>\n",
       "      <td>pyruvate</td>\n",
       "      <td>0.000140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>PRAGSr</td>\n",
       "      <td>purD</td>\n",
       "      <td>glycerol</td>\n",
       "      <td>0.000006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>AKGDH</td>\n",
       "      <td>lpd,sucA,sucB</td>\n",
       "      <td>succinate</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>MTHFR2</td>\n",
       "      <td>metF</td>\n",
       "      <td>galactose</td>\n",
       "      <td>0.000005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    reaction           gene  condition  protein_abundance_mmol_per_gCDW\n",
       "92    ICDHyr            icd  galactose                         0.000170\n",
       "227   ICDHyr            icd   pyruvate                         0.000140\n",
       "214   PRAGSr           purD   glycerol                         0.000006\n",
       "277    AKGDH  lpd,sucA,sucB  succinate                              NaN\n",
       "112   MTHFR2           metF  galactose                         0.000005"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protein_df = pd.read_csv('data/protein_abundance_mmol_per_gCDW.csv', index_col=0)\n",
    "protein_df = protein_df.reset_index().melt(id_vars=[\"reaction\", \"gene\"], var_name=\"condition\", value_name=\"protein_abundance_mmol_per_gCDW\")\n",
    "protein_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "768597e3-667e-47b0-bc07-763982719ad1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>metabolite</th>\n",
       "      <th>KEGG_ID</th>\n",
       "      <th>condition</th>\n",
       "      <th>metabolite_concentration_umol_per_gCDW</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>G6P</td>\n",
       "      <td>C00092</td>\n",
       "      <td>succinate</td>\n",
       "      <td>3.09+/-0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>AMP + ADP + ATP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>succinate</td>\n",
       "      <td>10.15+/-0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>NADP + NADPH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>glycerol</td>\n",
       "      <td>0.190+/-0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>NADP</td>\n",
       "      <td>C00006</td>\n",
       "      <td>succinate</td>\n",
       "      <td>0.0260+/-0.0010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>ICIT</td>\n",
       "      <td>C00311</td>\n",
       "      <td>glycerol</td>\n",
       "      <td>0.019+/-0.004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          metabolite KEGG_ID  condition metabolite_concentration_umol_per_gCDW\n",
       "147              G6P  C00092  succinate                            3.09+/-0.06\n",
       "133  AMP + ADP + ATP     NaN  succinate                           10.15+/-0.23\n",
       "78      NADP + NADPH     NaN   glycerol                          0.190+/-0.010\n",
       "142             NADP  C00006  succinate                        0.0260+/-0.0010\n",
       "89              ICIT  C00311   glycerol                          0.019+/-0.004"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metabolite_df = pd.read_csv('data/metabolite_concentration_umol_per_gCDW.csv', index_col=(0,1))\n",
    "metabolite_df = metabolite_df.applymap(lambda x: uncertainties.ufloat_fromstr(x) if type(x)==str else np.nan)\n",
    "metabolite_df = metabolite_df.reset_index().melt(id_vars=[\"metabolite\", \"KEGG_ID\"], var_name=\"condition\", value_name=\"metabolite_concentration_umol_per_gCDW\")\n",
    "metabolite_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e3f96078-1625-4466-bdf7-2cf81f521452",
   "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>reaction</th>\n",
       "      <th>condition</th>\n",
       "      <th>flux_mmol_per_gCDW_h</th>\n",
       "      <th>flux_mmol_per_gCDW_sec</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>FBP</td>\n",
       "      <td>galactose</td>\n",
       "      <td>0.0+/-0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288</th>\n",
       "      <td>Pyr_Ex</td>\n",
       "      <td>pyruvate</td>\n",
       "      <td>26.7+/-0.8</td>\n",
       "      <td>7.420556e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Lac_Ex</td>\n",
       "      <td>glycerol</td>\n",
       "      <td>0.0+/-0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>ME1</td>\n",
       "      <td>galactose</td>\n",
       "      <td>0.0010+/-0.0030</td>\n",
       "      <td>2.777778e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>Glc_Ex</td>\n",
       "      <td>galactose</td>\n",
       "      <td>0.0+/-0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    reaction  condition flux_mmol_per_gCDW_h  flux_mmol_per_gCDW_sec\n",
       "105      FBP  galactose              0.0+/-0            0.000000e+00\n",
       "288   Pyr_Ex   pyruvate           26.7+/-0.8            7.420556e-03\n",
       "197   Lac_Ex   glycerol              0.0+/-0            0.000000e+00\n",
       "137      ME1  galactose      0.0010+/-0.0030            2.777778e-07\n",
       "97    Glc_Ex  galactose              0.0+/-0            0.000000e+00"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if FLUX_DATA_SOURCE == \"davidi\":\n",
    "    flux_df = pd.read_csv('data/flux_mmol_per_gCDW_s_davidi.csv', index_col=0)\n",
    "    flux_df = flux_df.reset_index().melt(id_vars=\"reaction\", var_name=\"condition\", value_name=\"flux_mmol_per_gCDW_sec\")\n",
    "elif FLUX_DATA_SOURCE == \"gerosa\":\n",
    "    flux_df = pd.read_csv('data/flux_mmol_per_gCDW_h_gerosa.csv', index_col=0)\n",
    "    flux_df = flux_df.applymap(lambda x: uncertainties.ufloat_fromstr(x) if type(x)==str else np.nan)\n",
    "    flux_df = flux_df.reset_index().melt(id_vars=\"reaction\", var_name=\"condition\", value_name=\"flux_mmol_per_gCDW_h\")\n",
    "    flux_df[\"flux_mmol_per_gCDW_sec\"] = flux_df.flux_mmol_per_gCDW_h.apply(lambda x: x.nominal_value) / 3600.0\n",
    "flux_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9b11caaa-a353-43d4-a71d-c384f803102c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# join the kcat upper bound with the flux data\n",
    "# calculate the flux upper bound based on abundance and kcat\n",
    "# the resulting units are mmol_per_gCDW x 1_per_sec = mmol_per_gCDW_sec\n",
    "\n",
    "kcat_ub = protein_df.join(kinetics_df.drop(\"gene\", axis=\"columns\"), on=\"reaction\")\n",
    "kcat_ub[\"kcat_x_adunbance_mmol_per_gCDW_sec\"] = kcat_ub.kcat_1_per_sec * kcat_ub.protein_abundance_mmol_per_gCDW\n",
    "joined_df = pd.merge(kcat_ub, flux_df, on=[\"reaction\", \"condition\"], how=\"inner\")\n",
    "joined_df[\"kapp_1_per_sec\"] = joined_df.flux_mmol_per_gCDW_sec / joined_df.protein_abundance_mmol_per_gCDW\n",
    "joined_df.rename(columns={\"Km_metabolite\": \"KEGG_ID\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "17a3e237-df16-4f4a-9c84-47179df44209",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate the saturation level of the non-cycling substrate\n",
    "joined_df = pd.merge(joined_df, metabolite_df[[\"KEGG_ID\", \"metabolite\", \"condition\", \"metabolite_concentration_umol_per_gCDW\"]], on=[\"KEGG_ID\", \"condition\"], how=\"left\")\n",
    "\n",
    "CELL_DENSITY = 1.1e3 # gr/L\n",
    "CELL_DRY_FRACTION = 0.3 # gCDW/gr\n",
    "CELL_DRY_DENSITY = CELL_DRY_FRACTION * CELL_DENSITY # (gr/L) * (gCDW/gr) = gCDW/L\n",
    "\n",
    "joined_df[\"Km_umol_per_gCDW\"] = joined_df.Km_uM / CELL_DRY_DENSITY  # (μmol/L) / (gCDW/L) = μmol/gCDW\n",
    "\n",
    "# we need to convert uM into mmol/gCDW for the Km values first\n",
    "joined_df[\"saturation\"] = joined_df.metabolite_concentration_umol_per_gCDW / (joined_df.metabolite_concentration_umol_per_gCDW + joined_df.Km_umol_per_gCDW)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f79e161a-7c0f-45fc-8a51-ace7879f0e9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the data about the total concentration of the cycling (cofactor) pools\n",
    "cycling_pools = joined_df[[\"cycling_pool\"]].drop_duplicates()\n",
    "cycling_pools[\"metabolites\"] = cycling_pools.cycling_pool.str.findall(\"[^\\s^+]+\")\n",
    "cycling_pools = cycling_pools.explode(\"metabolites\").set_index(\"metabolites\")\n",
    "\n",
    "cycling_pool_df = metabolite_df.join(cycling_pools, on=\"metabolite\", how=\"right\").groupby([\"condition\", \"cycling_pool\"]).metabolite_concentration_umol_per_gCDW.sum().reset_index()\n",
    "cycling_pool_df.rename(columns={\"metabolite_concentration_umol_per_gCDW\": \"cofactor_concentration_umol_per_gCDW\"}, inplace=True)\n",
    "joined_df = pd.merge(joined_df, cycling_pool_df, on=[\"condition\", \"cycling_pool\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "27cb3cf2-5be7-41f3-84a3-b370e556bcb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1, axs = plt.subplots(1, 2, figsize=(10, 5), dpi=150, sharey=True)\n",
    "\n",
    "conditions = sorted(joined_df.condition.unique())\n",
    "markers = [\"x\", \"+\", \"o\", \"v\", \"^\", \"*\", \"h\"]\n",
    "condition2marker = dict(zip(conditions, markers))\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "ax = axs[0]\n",
    "for row in joined_df.itertuples():\n",
    "    marker = condition2marker[row.condition]\n",
    "    color = reaction2color[row.reaction]\n",
    "    ax.plot(row.kcat_x_adunbance_mmol_per_gCDW_sec, row.flux_mmol_per_gCDW_sec, marker=marker, color=color, alpha=1)\n",
    "ax.plot([1e-10, 1], [1e-10, 1], \"k:\", label=\"upper bound\")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(r\"$V_{max} = E_0 \\cdot k_{cat}$ [mmol / gCDW / s]\")\n",
    "ax.set_ylabel(\"flux [mmol / gCDW / s]\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=\"s\", linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=condition2marker[c], markersize=4, linewidth=0) for c in conditions\n",
    "]\n",
    "legend_labels = reactions + conditions\n",
    "ax.legend(legend_elements, legend_labels, fontsize=4, bbox_to_anchor=(1,1))\n",
    "\n",
    "\n",
    "# same plot with markers based on cycling compound rather than condition\n",
    "cycling_pools = sorted(joined_df.cycling_pool.unique())\n",
    "markers = [\"x\", \".\", \"+\"]\n",
    "cycling_pool2marker = dict(zip(cycling_pools, markers))\n",
    "reaction2cycling_pool = kinetics_df.cycling_pool\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "ax = axs[1]\n",
    "for row in joined_df.itertuples():\n",
    "    marker = cycling_pool2marker[row.cycling_pool]\n",
    "    color = reaction2color[row.reaction]\n",
    "    ax.plot(row.kcat_x_adunbance_mmol_per_gCDW_sec, row.flux_mmol_per_gCDW_sec, marker=marker, color=color, alpha=1)\n",
    "ax.plot([1e-10, 1], [1e-10, 1], \"k:\", label=\"upper bound\")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(r\"$V_{max} = E_0 \\cdot k_{cat}$ [mmol / gCDW / s]\")\n",
    "ax.set_ylabel(\"flux [mmol / gCDW / s]\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=cycling_pool2marker[reaction2cycling_pool[r]], linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=cycling_pool2marker[c], markersize=4, linewidth=0) for c in cycling_pools\n",
    "]\n",
    "legend_labels = reactions + cycling_pools\n",
    "ax.legend(legend_elements, legend_labels, fontsize=4, bbox_to_anchor=(1,1))\n",
    "fig1.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b263676f-82d2-467c-bbbf-ef400d33f6ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f13a44287f0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x750 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2, ax = plt.subplots(1, 1, figsize=(5, 5), dpi=150, sharey=True)\n",
    "saturation_df = joined_df[(~pd.isnull(joined_df.Km_uM)) & ~(pd.isnull(joined_df.metabolite_concentration_umol_per_gCDW))]\n",
    "conditions = sorted(saturation_df.condition.unique())\n",
    "markers = [\"x\", \"+\", \"o\", \"v\", \"^\", \"*\", \"h\"]\n",
    "condition2marker = dict(zip(conditions, markers))\n",
    "\n",
    "reactions = sorted(saturation_df.reaction.unique())\n",
    "colors = sns.color_palette(\"bright\").as_hex() + sns.color_palette(\"colorblind\").as_hex()\n",
    "colors = colors[0:len(reactions)]\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "reaction2substrate = saturation_df[[\"reaction\", \"metabolite\"]].drop_duplicates().set_index(\"reaction\").to_dict()[\"metabolite\"]\n",
    "\n",
    "for row in saturation_df.itertuples():\n",
    "    marker = condition2marker[row.condition]\n",
    "    color = reaction2color[row.reaction]\n",
    "    ax.plot(row.saturation.nominal_value * row.kcat_x_adunbance_mmol_per_gCDW_sec, row.flux_mmol_per_gCDW_sec, marker=marker, color=color, alpha=1)\n",
    "ax.set_xlabel(r\"$E_0 \\cdot k_{cat} \\cdot \\frac{s}{K_M + s}$ [mmol / gCDW / s]\")\n",
    "ax.plot([1e-10, 1], [1e-10, 1], \"k:\", label=\"upper bound\")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=\"s\", linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=condition2marker[c], markersize=4, linewidth=0) for c in conditions\n",
    "]\n",
    "legend_labels = [\n",
    "    r + \" (\" + reaction2substrate[r] + \")\" for r in reactions\n",
    "] + conditions\n",
    "ax.legend(legend_elements, legend_labels, loc=\"upper left\", fontsize=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "25f93b04-8de5-4e84-9455-2581b5bb8335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig3, axs = plt.subplots(1, 2, figsize=(10, 5), dpi=150, sharey=False)\n",
    "\n",
    "conditions = sorted(joined_df.condition.unique())\n",
    "markers = [\"x\", \"+\", \"o\", \"v\", \"^\", \"*\", \"h\"]\n",
    "condition2marker = dict(zip(conditions, markers))\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "colors = colors[0:len(reactions)]\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "ax = axs[0]\n",
    "for row in joined_df.itertuples():\n",
    "    marker = condition2marker[row.condition]\n",
    "    color = reaction2color[row.reaction]\n",
    "    ax.plot(row.kcat_x_adunbance_mmol_per_gCDW_sec, row.flux_mmol_per_gCDW_sec, marker=marker, color=color, alpha=1)\n",
    "ax.plot([1e-10, 1], [1e-10, 1], \"k:\", label=\"upper bound\")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(r\"$V_{max} = E_0 \\cdot k_{cat}$ [mmol / gCDW / s]\")\n",
    "ax.set_ylabel(\"$v$ [mmol / gCDW / s]\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=\"s\", linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=condition2marker[c], markersize=4, linewidth=0) for c in conditions\n",
    "]\n",
    "legend_labels = reactions + conditions\n",
    "ax.legend(legend_elements, legend_labels, fontsize=4, bbox_to_anchor=(1,1))\n",
    "\n",
    "\n",
    "# same plot with markers based on cycling compound rather than condition\n",
    "cycling_pools = sorted(joined_df.cycling_pool.unique())\n",
    "markers = [\"x\", \".\", \"+\"]\n",
    "cycling_pool2marker = dict(zip(cycling_pools, markers))\n",
    "reaction2cycling_pool = kinetics_df.cycling_pool\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "colors = colors[0:len(reactions)]\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "ax = axs[1]\n",
    "for row in joined_df.itertuples():\n",
    "    marker = cycling_pool2marker[row.cycling_pool]\n",
    "    color = reaction2color[row.reaction]\n",
    "    ax.plot(\n",
    "        np.abs(row.flux_mmol_per_gCDW_sec / row.kcat_x_adunbance_mmol_per_gCDW_sec),\n",
    "        row.cofactor_concentration_umol_per_gCDW.nominal_value,\n",
    "        marker=marker,\n",
    "        color=color,\n",
    "        alpha=1\n",
    "    )\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(r\"$v / V_{max}$\")\n",
    "ax.set_ylabel(\"cofactor pool size [μmol / gCDW]\")\n",
    "ax.set_xlim([None, 50])\n",
    "ax.plot([1, 1], [0, 12], \"k:\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=cycling_pool2marker[reaction2cycling_pool[r]], linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=cycling_pool2marker[c], markersize=4, linewidth=0) for c in cycling_pools\n",
    "]\n",
    "legend_labels = reactions + cycling_pools\n",
    "ax.legend(legend_elements, legend_labels, fontsize=4, bbox_to_anchor=(1,1))\n",
    "fig3.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9cec7f03-cb78-429b-ad0a-89800bf04fe5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x750 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4, ax = plt.subplots(1, 1, figsize=(6, 5), dpi=150)\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "colors = colors[0:len(reactions)]\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "# same plot with markers based on cycling compound rather than condition\n",
    "cycling_pools = sorted(joined_df.cycling_pool.unique())\n",
    "markers = [\"x\", \".\", \"+\"]\n",
    "cycling_pool2marker = dict(zip(cycling_pools, markers))\n",
    "reaction2cycling_pool = kinetics_df.cycling_pool\n",
    "\n",
    "reactions = sorted(joined_df.reaction.unique())\n",
    "colors = colors[0:len(reactions)]\n",
    "reaction2color = dict(zip(reactions, COLORS))\n",
    "\n",
    "for reaction, group_df in joined_df.groupby(\"reaction\"):\n",
    "    color = reaction2color[reaction]\n",
    "    c = group_df.cycling_pool.iat[0]\n",
    "    ax.plot(\n",
    "        group_df.cofactor_concentration_umol_per_gCDW.apply(lambda x: x.nominal_value),\n",
    "        group_df.flux_mmol_per_gCDW_sec.abs(),\n",
    "        color=color,\n",
    "        markersize=6,\n",
    "        marker=cycling_pool2marker[c],\n",
    "        linewidth=0\n",
    "    )\n",
    "ax.set_xlabel(\"cofactor pool size [μmol / gCDW]\")\n",
    "ax.set_xscale(\"log\")\n",
    "\n",
    "ax.set_ylabel(\"v [mmol / gCDW / s]\")\n",
    "ax.set_yscale(\"log\")\n",
    "#ax.set_ylim([0, 0.01])\n",
    "#ax.plot([1, 1], [0, 12], \"k:\")\n",
    "\n",
    "legend_elements = [\n",
    "    Line2D([0], [0], color=reaction2color[r], marker=cycling_pool2marker[reaction2cycling_pool[r]], linewidth=0, markersize=4) for r in reactions\n",
    "] + [\n",
    "    Line2D([0], [0], color=\"k\", marker=cycling_pool2marker[c], markersize=4, linewidth=0) for c in cycling_pools\n",
    "]\n",
    "legend_labels = reactions + cycling_pools\n",
    "ax.legend(legend_elements, legend_labels, fontsize=8, bbox_to_anchor=(1,1))\n",
    "fig4.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aab55337-e366-41a9-a30c-0850cb2a2a3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "with PdfPages(f\"{FLUX_DATA_SOURCE}.pdf\") as pdf:\n",
    "    pdf.savefig(fig1)\n",
    "    pdf.savefig(fig2)\n",
    "    pdf.savefig(fig3)\n",
    "    pdf.savefig(fig4)    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}