BOTorch_MOBO_mean_volume_Opentrons.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Optimization of OT2 transfer paramters of viscous liquids guided by Baysesian Optimization"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "This notebook objective is to generate new suggestions of aspiration and dispense rates that will minimize the tansfer error while minimizing the time of transfer of a viscous liquid. The code in this notebook will aim to optimize the liquid transfer parameters  to minimize the mean error from three volumes (default 300, 500, 1000) and the time of transfer to dispense 1000 uL.\n",
    "The code is strucutred as follows:\n",
    "1.  Fisrt section is for importing the relevant packages to perform BO, inclduing Pytorch and BOtorch\n",
    "2.  Second section includes the definition of the BO_LiqTransfer class that includes the method optimized_suggestions() that generates BO optimized aspiration and dispense rate values for a particular data set.\n",
    "3.  Third section includes the code to run in conjuction with the OT2 viscous liquid transfer notebook. The steps for the optimziation are:\n",
    "\n",
    "    i. Initilize a BO_LiTransfer objecet and load initilization data using data_from_csv() method\n",
    "\n",
    "    ii. Run optimized_suggestions() method\n",
    "\n",
    "    iii. Run liquid transfer using the best suggestion for aspiration and dispense rates in OT2 notebook\n",
    "\n",
    "    iv. Update latest %error obtained from the transfer using suggested aspiration and dispense rates.\n",
    "    \n",
    "    v. Iterate through steps ii-iV\n",
    " "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# basic dependencies\n",
    "\n",
    "import numpy as np\n",
    "from numpy import loadtxt\n",
    "from numpy import savetxt\n",
    "\n",
    "import pandas as pd\n",
    "import math\n",
    "import time\n",
    "from datetime import date\n",
    "\n",
    "np.set_printoptions(formatter={'float': lambda x: \"{0:0.3f}\".format(x)})\n",
    "\n",
    "###########\n",
    "\n",
    "# torch dependencies\n",
    "import torch\n",
    "\n",
    "tkwargs = {\"dtype\": torch.double, # set as double to minimize zero error for cholesky decomposition error\n",
    "           \"device\": torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")} # set tensors to GPU, if multiple GPUs please set cuda:x properly\n",
    "\n",
    "torch.set_printoptions(precision=3)\n",
    "\n",
    "###########\n",
    "\n",
    "# botorch dependencies\n",
    "import botorch\n",
    "\n",
    "# data related\n",
    "from botorch.utils.sampling import draw_sobol_samples\n",
    "from botorch.utils.transforms import unnormalize, normalize\n",
    "\n",
    "# surrogate model specific\n",
    "from botorch.models.gp_regression import SingleTaskGP\n",
    "from botorch.models.model_list_gp_regression import ModelListGP\n",
    "from botorch.models.transforms.outcome import Standardize\n",
    "from gpytorch.mlls.sum_marginal_log_likelihood import SumMarginalLogLikelihood\n",
    "from botorch import fit_gpytorch_model\n",
    "\n",
    "# qNEHVI specific\n",
    "from botorch.acquisition.multi_objective.objective import IdentityMCMultiOutputObjective\n",
    "from botorch.acquisition.multi_objective.monte_carlo import qNoisyExpectedHypervolumeImprovement\n",
    "\n",
    "# utilities\n",
    "from botorch.optim.optimize import optimize_acqf\n",
    "from botorch.sampling import SobolQMCNormalSampler\n",
    "from botorch.utils.multi_objective.pareto import is_non_dominated\n",
    "from botorch.utils.multi_objective.hypervolume import Hypervolume\n",
    "from typing import Optional\n",
    "from torch import Tensor\n",
    "from botorch.exceptions import BadInitialCandidatesWarning\n",
    "\n",
    "from gpytorch.constraints import GreaterThan\n",
    "from torch.optim import SGD\n",
    "from gpytorch.mlls import ExactMarginalLogLikelihood\n",
    "\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore', category=BadInitialCandidatesWarning)\n",
    "warnings.filterwarnings('ignore', category=RuntimeWarning)\n",
    "\n",
    "\n",
    "# plotting dependencies\n",
    "import matplotlib\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "SMALL_SIZE = 14\n",
    "MEDIUM_SIZE = 18\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. BO_LiqTransfer class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class BO_LiqTransfer:\n",
    "\n",
    "    def __init__(self, liquid_name):\n",
    "        self.liquid_name = liquid_name\n",
    "        self._data = None\n",
    "        self.features = ['aspiration_rate','dispense_rate']\n",
    "        self.objectives = ['%error','time_asp_1000']\n",
    "        self.bmax = 1.25\n",
    "        self.bmin = 0.1\n",
    "        self._latest_suggestion = None\n",
    "        self._latest_volume = None\n",
    "        self._latest_acq_value = None\n",
    "        self.mean_volumes = [300,500,1000]\n",
    "    \n",
    "   \n",
    "    def set_data(self,df):\n",
    "        df['time_asp_1000'] = 1000/df['aspiration_rate'] + 1000/df['dispense_rate'] + df['delay_aspirate'] + df['delay_dispense']\n",
    "        if 'acq_value' not in df.columns:\n",
    "            df['acq_value'] = None\n",
    "\n",
    "        if df.loc[:,self.features].duplicated().sum()==0:\n",
    "            df_mean = df\n",
    "        else:\n",
    "            df_duplicates = df.where(df.duplicated(self.features,keep=False)==True).dropna(how='all')\n",
    "            df_incomplete = df.where(df.duplicated(self.features,keep=False)==False).dropna(how='all')\n",
    "            df_mean = pd.DataFrame(columns= df.columns)\n",
    "            for index,values in df_duplicates.drop_duplicates(self.features).iterrows():\n",
    "                if len(df_duplicates.loc[index:index+2]) == len(self.mean_volumes):\n",
    "                    mean_error =df_duplicates.loc[index:index+2,'%error'].abs().mean()\n",
    "                    df_duplicates.loc[index,'%error'] = -mean_error\n",
    "                    df_duplicates.loc[index, 'volume'] ='mean'+str(self.mean_volumes)\n",
    "                    df_mean = pd.concat([df_mean,df.loc[index:index+2],df_duplicates.loc[[index]]])\n",
    "                else:\n",
    "                    df_incomplete = pd.concat([df_incomplete,df_duplicates.loc[index:index+2]]).drop_duplicates()\n",
    "            df_mean = pd.concat([df_mean,df_incomplete])\n",
    "            df_mean = df_mean.reset_index(drop=True)    \n",
    "        self._data = df_mean\n",
    " \n",
    "        \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "    def data_from_csv(self,file_name):\n",
    "        data = pd.read_csv(file_name)\n",
    "        data = data.loc[:,['liquid','pipette','volume','aspiration_rate','dispense_rate','blow_out_rate','delay_aspirate','delay_dispense','delay_blow_out','%error']]\n",
    "        self.set_data(data)\n",
    "\n",
    "\n",
    "    def update_data(self,error,volume= 1000):\n",
    "        self._latest_volume = volume\n",
    "        updated_data = pd.concat([self._data,self._data.iloc[[-1]]],ignore_index=True)\n",
    "        updated_data.loc[updated_data.last_valid_index(),'volume'] = self._latest_volume\n",
    "        updated_data.loc[updated_data.last_valid_index(),'aspiration_rate']  = self._latest_suggestion['aspiration_rate']\n",
    "        updated_data.loc[updated_data.last_valid_index(),'dispense_rate']  = self._latest_suggestion['dispense_rate']\n",
    "        updated_data.loc[updated_data.last_valid_index(),'%error'] = error\n",
    "        self.set_data(updated_data)\n",
    "        return self._data\n",
    "                                \n",
    "\n",
    "    def xy_split(self):\n",
    "        df_train = self._data.where(self._data['volume']=='mean'+str(self.mean_volumes)).dropna(how='all')\n",
    "        x_train = df_train[self.features]\n",
    "        y_train = df_train[self.objectives]\n",
    "        return x_train,y_train\n",
    "\n",
    "    def set_bounds(self, x_train):\n",
    "        return torch.vstack([x_train[0]*self.bmin, x_train[0]*self.bmax])\n",
    "\n",
    "\n",
    "\n",
    "    def fit_surrogate(self):\n",
    "        x_train, y_train = self.xy_split()\n",
    "        x_train = torch.tensor(x_train.to_numpy(dtype=float), **tkwargs)\n",
    "        y_train = torch.tensor(y_train.to_numpy(dtype=float), **tkwargs)\n",
    "        y_train[:,0] = -torch.absolute(y_train[:,0])\n",
    "        y_train[:,1] = -torch.absolute(y_train[:,1])\n",
    "\n",
    "        problem_bounds = self.set_bounds(x_train)\n",
    "        time_upper = 1000/problem_bounds[0][0] +1000/problem_bounds[0][1] + 10\n",
    "        error_upper = y_train[:,0].abs().min()*1.25\n",
    "        ref_point = torch.tensor([-error_upper,-time_upper], **tkwargs)\n",
    "\n",
    "        train_x_gp = normalize(x_train, problem_bounds)\n",
    "        models = []\n",
    "        for i in range(y_train.shape[-1]):\n",
    "            models.append(SingleTaskGP(train_x_gp, y_train[..., i : i + 1], outcome_transform=Standardize(m=1)))\n",
    "        model1 = ModelListGP(*models)\n",
    "        mll1 = SumMarginalLogLikelihood(model1.likelihood, model1)\n",
    "\n",
    "        fit_gpytorch_model(mll1)\n",
    "    \n",
    "        return model1, ref_point, train_x_gp, problem_bounds\n",
    "    \n",
    "    def optimized_suggestions(self, random_state= 42):\n",
    "        if random_state != None:\n",
    "            torch.manual_seed(random_state) \n",
    "        standard_bounds = torch.zeros(2, len(self.features), **tkwargs)\n",
    "        standard_bounds[1] = 1\n",
    "        model1, ref_point, train_x_gp, problem_bounds = self.fit_surrogate()\n",
    "        acq_func1 = qNoisyExpectedHypervolumeImprovement(\n",
    "        model=model1,\n",
    "        ref_point=ref_point, # for computing HV, must flip for BoTorch\n",
    "        X_baseline=train_x_gp, # feed total list of train_x for this current iteration\n",
    "        sampler=SobolQMCNormalSampler(sample_shape=512),  # determines how candidates are randomly proposed before selection\n",
    "        objective=IdentityMCMultiOutputObjective(outcomes=np.arange(len(self.objectives)).tolist()), # optimize first n_obj col \n",
    "        prune_baseline=True, cache_pending=True)  # options for improving qNEHVI, keep these on\n",
    "        sobol1 = draw_sobol_samples(bounds=standard_bounds,n=512, q=1).squeeze(1)\n",
    "        sobol2 = draw_sobol_samples(bounds=standard_bounds,n=512, q=1).squeeze(1)\n",
    "        sobol_all = torch.vstack([sobol1, sobol2])\n",
    "            \n",
    "        acq_value_list = []\n",
    "        for i in range(0, sobol_all.shape[0]):\n",
    "            with torch.no_grad():\n",
    "                acq_value = acq_func1(sobol_all[i].unsqueeze(dim=0))\n",
    "                acq_value_list.append(acq_value.item())\n",
    "                \n",
    "        # filter the best 12 QMC candidates first\n",
    "        sorted_x = sobol_all.cpu().numpy()[np.argsort((acq_value_list))]\n",
    "        qnehvi_x = torch.tensor(sorted_x[-12:], **tkwargs)  \n",
    "        # unormalize our training inputs back to original problem bounds\n",
    "        new_x =  unnormalize(qnehvi_x, bounds=problem_bounds)\n",
    "        new_x = pd.DataFrame(new_x.numpy(),columns=['aspiration_rate','dispense_rate'])\n",
    "        new_x['acq_values'] = sorted(acq_value_list, reverse=True)[:12]\n",
    "        self._latest_suggestion = new_x[['aspiration_rate','dispense_rate']].iloc[0]\n",
    "        return new_x\n",
    "        \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "        \n",
    "    \n",
    "    \n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Guided BO optimization\n",
    "i.   Create BO_LiqTransfer object and load data set.\n",
    "\n",
    "Please set liquid name and volume to transfer according to the experiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>liquid</th>\n",
       "      <th>pipette</th>\n",
       "      <th>volume</th>\n",
       "      <th>aspiration_rate</th>\n",
       "      <th>dispense_rate</th>\n",
       "      <th>blow_out_rate</th>\n",
       "      <th>delay_aspirate</th>\n",
       "      <th>delay_dispense</th>\n",
       "      <th>delay_blow_out</th>\n",
       "      <th>%error</th>\n",
       "      <th>time_asp_1000</th>\n",
       "      <th>acq_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
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       "      <td>None</td>\n",
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       "      <th>1</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-37.843407</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-41.926129</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-34.926994</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-63.415751</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-52.533578</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.086742</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-25.022894</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-25.480769</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-23.271520</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.277473</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-21.909341</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-27.960928</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.049247</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.090659</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.554945</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.713675</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.786427</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                liquid pipette                volume  aspiration_rate  \\\n",
       "0   Viscosity_std_1275   p1000                1000.0        36.685933   \n",
       "1   Viscosity_std_1275   p1000                 500.0        36.685933   \n",
       "2   Viscosity_std_1275   p1000                 300.0        36.685933   \n",
       "3   Viscosity_std_1275   p1000  mean[300, 500, 1000]        36.685933   \n",
       "4   Viscosity_std_1275   p1000                 500.0        45.857416   \n",
       "5   Viscosity_std_1275   p1000                 300.0        45.857416   \n",
       "6   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "7   Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "8   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "9   Viscosity_std_1275   p1000                 500.0        45.857416   \n",
       "10  Viscosity_std_1275   p1000                 300.0        45.857416   \n",
       "11  Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "12  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "13  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "14  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "15  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "16  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "17  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "18  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "19  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "\n",
       "    dispense_rate  blow_out_rate  delay_aspirate  delay_dispense  \\\n",
       "0       36.685933            0.0             5.0             5.0   \n",
       "1       36.685933            0.0             5.0             5.0   \n",
       "2       36.685933            0.0             5.0             5.0   \n",
       "3       36.685933            0.0             5.0             5.0   \n",
       "4       45.857416            0.0             5.0             5.0   \n",
       "5       45.857416            0.0             5.0             5.0   \n",
       "6        3.668593            0.0             5.0             5.0   \n",
       "7       45.857416            0.0             5.0             5.0   \n",
       "8        3.668593            0.0             5.0             5.0   \n",
       "9        3.668593            0.0             5.0             5.0   \n",
       "10       3.668593            0.0             5.0             5.0   \n",
       "11       3.668593            0.0             5.0             5.0   \n",
       "12      45.857416            0.0             5.0             5.0   \n",
       "13      45.857416            0.0             5.0             5.0   \n",
       "14      45.857416            0.0             5.0             5.0   \n",
       "15      45.857416            0.0             5.0             5.0   \n",
       "16       3.668593            0.0             5.0             5.0   \n",
       "17       3.668593            0.0             5.0             5.0   \n",
       "18       3.668593            0.0             5.0             5.0   \n",
       "19       3.668593            0.0             5.0             5.0   \n",
       "\n",
       "    delay_blow_out     %error  time_asp_1000 acq_value  \n",
       "0              0.0 -25.011447      64.516809      None  \n",
       "1              0.0 -37.843407      64.516809      None  \n",
       "2              0.0 -41.926129      64.516809      None  \n",
       "3              0.0 -34.926994      64.516809      None  \n",
       "4              0.0 -63.415751      53.613447      None  \n",
       "5              0.0 -52.533578      53.613447      None  \n",
       "6              0.0 -19.310897     304.390768      None  \n",
       "7              0.0 -45.086742      53.613447      None  \n",
       "8              0.0 -19.310897     304.390768      None  \n",
       "9              0.0 -25.022894     304.390768      None  \n",
       "10             0.0 -25.480769     304.390768      None  \n",
       "11             0.0 -23.271520     304.390768      None  \n",
       "12             0.0 -16.277473     304.390768      None  \n",
       "13             0.0 -21.909341     304.390768      None  \n",
       "14             0.0 -27.960928     304.390768      None  \n",
       "15             0.0 -22.049247     304.390768      None  \n",
       "16             0.0   3.090659     555.168089      None  \n",
       "17             0.0   7.554945     555.168089      None  \n",
       "18             0.0  12.713675     555.168089      None  \n",
       "19             0.0  -7.786427     555.168089      None  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Change according to experiment\n",
    "liquid_name = 'Viscosity_std_1275' \n",
    "\n",
    "# Do not change\n",
    "liq = BO_LiqTransfer(liquid_name)\n",
    "liq.data_from_csv(r'Opentrons_experiments\\BOTorch_optimization\\Selina_results\\Bryant\\liquid_4_selina_initialization.csv')\n",
    "liq._data = liq._data.loc[:19]\n",
    "liq._data['liquid']=liquid_name\n",
    "liq._data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "ii.   Run BO_LiqTransfer.optimized_suggestions() method to obtain optimized aspiration and dispense rates.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>aspiration_rate</th>\n",
       "      <th>dispense_rate</th>\n",
       "      <th>acq_values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9.646460</td>\n",
       "      <td>20.330151</td>\n",
       "      <td>383.998186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.521603</td>\n",
       "      <td>21.682557</td>\n",
       "      <td>383.981062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.601327</td>\n",
       "      <td>19.646497</td>\n",
       "      <td>383.210696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.751097</td>\n",
       "      <td>22.156882</td>\n",
       "      <td>383.075409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.195849</td>\n",
       "      <td>21.105319</td>\n",
       "      <td>382.713506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.711350</td>\n",
       "      <td>22.547097</td>\n",
       "      <td>382.451981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13.371186</td>\n",
       "      <td>19.722719</td>\n",
       "      <td>382.334151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12.448938</td>\n",
       "      <td>22.216720</td>\n",
       "      <td>381.739306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.460242</td>\n",
       "      <td>21.988904</td>\n",
       "      <td>380.931913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.304604</td>\n",
       "      <td>21.745217</td>\n",
       "      <td>380.925960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>12.041722</td>\n",
       "      <td>20.644147</td>\n",
       "      <td>380.723629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12.710489</td>\n",
       "      <td>21.096379</td>\n",
       "      <td>380.451198</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    aspiration_rate  dispense_rate  acq_values\n",
       "0          9.646460      20.330151  383.998186\n",
       "1          8.521603      21.682557  383.981062\n",
       "2         14.601327      19.646497  383.210696\n",
       "3          8.751097      22.156882  383.075409\n",
       "4         14.195849      21.105319  382.713506\n",
       "5         11.711350      22.547097  382.451981\n",
       "6         13.371186      19.722719  382.334151\n",
       "7         12.448938      22.216720  381.739306\n",
       "8         10.460242      21.988904  380.931913\n",
       "9         10.304604      21.745217  380.925960\n",
       "10        12.041722      20.644147  380.723629\n",
       "11        12.710489      21.096379  380.451198"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "liq.optimized_suggestions()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "iii. Run liquid transfer using the best suggestion for aspiration and dispense rates in OT2 notebook.\n",
    "\n",
    "iv. Update volume and latest %error obtained from the transfer using suggested aspiration and dispense rates. Repeat for 1000, 500, 100 uL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>liquid</th>\n",
       "      <th>pipette</th>\n",
       "      <th>volume</th>\n",
       "      <th>aspiration_rate</th>\n",
       "      <th>dispense_rate</th>\n",
       "      <th>blow_out_rate</th>\n",
       "      <th>delay_aspirate</th>\n",
       "      <th>delay_dispense</th>\n",
       "      <th>delay_blow_out</th>\n",
       "      <th>%error</th>\n",
       "      <th>time_asp_1000</th>\n",
       "      <th>acq_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-25.011447</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-37.843407</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-41.926129</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-34.926994</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-63.415751</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-52.533578</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.086742</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.086742</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-27.902846</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.277473</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-21.909341</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-27.960928</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.049247</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.090659</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.554945</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.713675</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.786427</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300</td>\n",
       "      <td>18.769053</td>\n",
       "      <td>9.529554</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.833639</td>\n",
       "      <td>168.215904</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>10.460242</td>\n",
       "      <td>21.988904</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.034799</td>\n",
       "      <td>151.077565</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500</td>\n",
       "      <td>10.460242</td>\n",
       "      <td>21.988904</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.369048</td>\n",
       "      <td>151.077565</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                liquid pipette                volume  aspiration_rate  \\\n",
       "0   Viscosity_std_1275   p1000                1000.0        36.685933   \n",
       "1   Viscosity_std_1275   p1000                 500.0        36.685933   \n",
       "2   Viscosity_std_1275   p1000                 300.0        36.685933   \n",
       "3   Viscosity_std_1275   p1000  mean[300, 500, 1000]        36.685933   \n",
       "4   Viscosity_std_1275   p1000                 500.0        45.857416   \n",
       "5   Viscosity_std_1275   p1000                 300.0        45.857416   \n",
       "6   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "7   Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "8   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "9   Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "10  Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "11  Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "12  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "13  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "14  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "15  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "16  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "17  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "18  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "19  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "20  Viscosity_std_1275   p1000                   300        18.769053   \n",
       "21  Viscosity_std_1275   p1000                  1000        10.460242   \n",
       "22  Viscosity_std_1275   p1000                   500        10.460242   \n",
       "\n",
       "    dispense_rate  blow_out_rate  delay_aspirate  delay_dispense  \\\n",
       "0       36.685933            0.0             5.0             5.0   \n",
       "1       36.685933            0.0             5.0             5.0   \n",
       "2       36.685933            0.0             5.0             5.0   \n",
       "3       36.685933            0.0             5.0             5.0   \n",
       "4       45.857416            0.0             5.0             5.0   \n",
       "5       45.857416            0.0             5.0             5.0   \n",
       "6        3.668593            0.0             5.0             5.0   \n",
       "7       45.857416            0.0             5.0             5.0   \n",
       "8        3.668593            0.0             5.0             5.0   \n",
       "9       45.857416            0.0             5.0             5.0   \n",
       "10       3.668593            0.0             5.0             5.0   \n",
       "11       3.668593            0.0             5.0             5.0   \n",
       "12      45.857416            0.0             5.0             5.0   \n",
       "13      45.857416            0.0             5.0             5.0   \n",
       "14      45.857416            0.0             5.0             5.0   \n",
       "15      45.857416            0.0             5.0             5.0   \n",
       "16       3.668593            0.0             5.0             5.0   \n",
       "17       3.668593            0.0             5.0             5.0   \n",
       "18       3.668593            0.0             5.0             5.0   \n",
       "19       3.668593            0.0             5.0             5.0   \n",
       "20       9.529554            0.0             5.0             5.0   \n",
       "21      21.988904            0.0             5.0             5.0   \n",
       "22      21.988904            0.0             5.0             5.0   \n",
       "\n",
       "    delay_blow_out     %error  time_asp_1000 acq_value  \n",
       "0              0.0 -25.011447      64.516809      None  \n",
       "1              0.0 -37.843407      64.516809      None  \n",
       "2              0.0 -41.926129      64.516809      None  \n",
       "3              0.0 -34.926994      64.516809      None  \n",
       "4              0.0 -63.415751      53.613447      None  \n",
       "5              0.0 -52.533578      53.613447      None  \n",
       "6              0.0 -19.310897     304.390768      None  \n",
       "7              0.0 -45.086742      53.613447      None  \n",
       "8              0.0 -19.310897     304.390768      None  \n",
       "9              0.0 -45.086742      53.613447      None  \n",
       "10             0.0 -19.310897     304.390768      None  \n",
       "11             0.0 -27.902846     304.390768      None  \n",
       "12             0.0 -16.277473     304.390768      None  \n",
       "13             0.0 -21.909341     304.390768      None  \n",
       "14             0.0 -27.960928     304.390768      None  \n",
       "15             0.0 -22.049247     304.390768      None  \n",
       "16             0.0   3.090659     555.168089      None  \n",
       "17             0.0   7.554945     555.168089      None  \n",
       "18             0.0  12.713675     555.168089      None  \n",
       "19             0.0  -7.786427     555.168089      None  \n",
       "20             0.0 -19.833639     168.215904      None  \n",
       "21             0.0 -11.034799     151.077565      None  \n",
       "22             0.0 -16.369048     151.077565      None  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "volume= 300\n",
    "liq.update_data(-19.833639,volume)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#save after each standard-experiment iteration\n",
    "liq._data.to_csv('C:\\\\Users\\\\amdm_\\\\OneDrive\\\\Documents\\\\GitHub\\\\viscosity_liquid_transfer_Pablo\\\\Opentrons_experiments\\\\BOTorch_optimization\\\\VS_code_csv\\\\'+liquid_name+'_'+'optimization_2.csv', index = False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "v. Iterate trhough last two code cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>liquid</th>\n",
       "      <th>pipette</th>\n",
       "      <th>volume</th>\n",
       "      <th>aspiration_rate</th>\n",
       "      <th>dispense_rate</th>\n",
       "      <th>blow_out_rate</th>\n",
       "      <th>delay_aspirate</th>\n",
       "      <th>delay_dispense</th>\n",
       "      <th>delay_blow_out</th>\n",
       "      <th>%error</th>\n",
       "      <th>time_asp_1000</th>\n",
       "      <th>acq_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-25.011447</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-37.843407</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-41.926129</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>36.685933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-34.926994</td>\n",
       "      <td>64.516809</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-63.415751</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-52.533578</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.086742</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.086742</td>\n",
       "      <td>53.613447</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.310897</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-27.902846</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.277473</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-21.909341</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-27.960928</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>45.857416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.049247</td>\n",
       "      <td>304.390768</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.090659</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.554945</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.713675</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Viscosity_std_1275</td>\n",
       "      <td>p1000</td>\n",
       "      <td>mean[300, 500, 1000]</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>3.668593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.786427</td>\n",
       "      <td>555.168089</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                liquid pipette                volume  aspiration_rate  \\\n",
       "0   Viscosity_std_1275   p1000                1000.0        36.685933   \n",
       "1   Viscosity_std_1275   p1000                 500.0        36.685933   \n",
       "2   Viscosity_std_1275   p1000                 300.0        36.685933   \n",
       "3   Viscosity_std_1275   p1000  mean[300, 500, 1000]        36.685933   \n",
       "4   Viscosity_std_1275   p1000                 500.0        45.857416   \n",
       "5   Viscosity_std_1275   p1000                 300.0        45.857416   \n",
       "6   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "7   Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "8   Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "9   Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "10  Viscosity_std_1275   p1000                1000.0        45.857416   \n",
       "11  Viscosity_std_1275   p1000  mean[300, 500, 1000]        45.857416   \n",
       "12  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "13  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "14  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "15  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "16  Viscosity_std_1275   p1000                1000.0         3.668593   \n",
       "17  Viscosity_std_1275   p1000                 500.0         3.668593   \n",
       "18  Viscosity_std_1275   p1000                 300.0         3.668593   \n",
       "19  Viscosity_std_1275   p1000  mean[300, 500, 1000]         3.668593   \n",
       "\n",
       "    dispense_rate  blow_out_rate  delay_aspirate  delay_dispense  \\\n",
       "0       36.685933            0.0             5.0             5.0   \n",
       "1       36.685933            0.0             5.0             5.0   \n",
       "2       36.685933            0.0             5.0             5.0   \n",
       "3       36.685933            0.0             5.0             5.0   \n",
       "4       45.857416            0.0             5.0             5.0   \n",
       "5       45.857416            0.0             5.0             5.0   \n",
       "6        3.668593            0.0             5.0             5.0   \n",
       "7       45.857416            0.0             5.0             5.0   \n",
       "8        3.668593            0.0             5.0             5.0   \n",
       "9       45.857416            0.0             5.0             5.0   \n",
       "10       3.668593            0.0             5.0             5.0   \n",
       "11       3.668593            0.0             5.0             5.0   \n",
       "12      45.857416            0.0             5.0             5.0   \n",
       "13      45.857416            0.0             5.0             5.0   \n",
       "14      45.857416            0.0             5.0             5.0   \n",
       "15      45.857416            0.0             5.0             5.0   \n",
       "16       3.668593            0.0             5.0             5.0   \n",
       "17       3.668593            0.0             5.0             5.0   \n",
       "18       3.668593            0.0             5.0             5.0   \n",
       "19       3.668593            0.0             5.0             5.0   \n",
       "\n",
       "    delay_blow_out     %error  time_asp_1000 acq_value  \n",
       "0              0.0 -25.011447      64.516809      None  \n",
       "1              0.0 -37.843407      64.516809      None  \n",
       "2              0.0 -41.926129      64.516809      None  \n",
       "3              0.0 -34.926994      64.516809      None  \n",
       "4              0.0 -63.415751      53.613447      None  \n",
       "5              0.0 -52.533578      53.613447      None  \n",
       "6              0.0 -19.310897     304.390768      None  \n",
       "7              0.0 -45.086742      53.613447      None  \n",
       "8              0.0 -19.310897     304.390768      None  \n",
       "9              0.0 -45.086742      53.613447      None  \n",
       "10             0.0 -19.310897     304.390768      None  \n",
       "11             0.0 -27.902846     304.390768      None  \n",
       "12             0.0 -16.277473     304.390768      None  \n",
       "13             0.0 -21.909341     304.390768      None  \n",
       "14             0.0 -27.960928     304.390768      None  \n",
       "15             0.0 -22.049247     304.390768      None  \n",
       "16             0.0   3.090659     555.168089      None  \n",
       "17             0.0   7.554945     555.168089      None  \n",
       "18             0.0  12.713675     555.168089      None  \n",
       "19             0.0  -7.786427     555.168089      None  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "liq._data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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