From 7a904b461643720a46e1708d113baf5e8d0f237a Mon Sep 17 00:00:00 2001 From: luohezhiming Date: Thu, 16 Oct 2025 15:18:16 -0400 Subject: [PATCH 01/11] create a file for new API --- .../parmest_new_API_example.ipynb | 396 ++++++++++++++++++ 1 file changed, 396 insertions(+) create mode 100644 tutorials/parmest_demo/parmest_new_API_example.ipynb diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb new file mode 100644 index 0000000000..f6e2ea287d --- /dev/null +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -0,0 +1,396 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "___\n", + "# Conducting a Parameter Estimation\n", + "___\n", + "\n", + "Author: Savannah Sakhai\n", + "\n", + "For this demonstration, we will be going through how to set up a parameter estimation using the Pyomo tool ***parmest***. This simple case study aims to develop an empirical equation for the vapor pressure of an NaCl solution over a range of temperature and salt mass fractions." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 0: Imports" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd # to create a pandas dataframe to organize the data\n", + "import numpy as np # to manipulate the data into a usable format\n", + "import pyomo.contrib.parmest.parmest as parmest # to perform the parameter estimation\n", + "import pyomo.environ as pyo # to create a pyomo model\n", + "import matplotlib.pyplot as plt # to plot the results\n", + "from watertap.core.solvers import get_solver # to bring in ipopt solver\n", + "solver = get_solver() # this will make the ipopt solver available" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 1: Gather the data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# data obtained using PhreeqC\n", + "# read in csv file to pd.dataframe\n", + "data = pd.read_csv(\n", + " 'P_sat_Data.csv',\n", + " header=None,\n", + ")\n", + "\n", + "display(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Step 2: Prepare the data\n", + "*How does parmest need the data to be formatted?*\n", + "\n", + "\n", + "- **Pandas Dataframe:** each column is an observed quantity (temperature, concentration, vapor pressure, etc.), each row is a distinct scenario (25, 0.02, 31.33)\n", + "\n", + "**Other options:**\n", + "- **List of Pandas Dataframe:** each entry of the list is a distinct scenario, each dataframe an observed quantity\n", + "- **List of dictionaries:** each entry of the list is a distinct scenario, each key an observed quantity \n", + "- **List of json file names:** each entry of the list contains a json file with the distinct scenario (for large datasets in parallel computing)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def get_formatted_data(data):\n", + " # convert dataframe to numpy array for the manipulations\n", + " npdata = data.to_numpy()\n", + "\n", + " # obtain input variables (salt g/kg water, temperature C)\n", + " c = npdata[1:, 0]\n", + " T = npdata[0, 1:]\n", + "\n", + " # repeat each value of temperature for the number of mass fraction entries\n", + " T_col = np.repeat(T, len(c)).T +273 #celsius to kelvin\n", + "\n", + " # repeat the set of mass fraction entries for the number of temperature entries\n", + " c_col = np.tile(c, len(T)).T /1000 #g/kg water to mass frac \n", + "\n", + " # take the output table and create a column\n", + " output_data = npdata[1:, 1:].T.reshape(-1) * 101325 #atm to Pa\n", + "\n", + " # compile into one table where each column is a different observed quantity\n", + " total_data = np.column_stack([c_col, T_col, output_data])\n", + "\n", + " # redefine as a pandas dataframe with named columns\n", + " data = pd.DataFrame(total_data,\n", + " columns=['Comp', 'Temp', 'PropData'],\n", + " )\n", + "\n", + " # delete all rows when column 'PropData' has a value of 0 (scenarios without measured property data)\n", + " index_NA = data[(data['PropData'] == 0)].index\n", + " data.drop(index_NA, inplace=True)\n", + "\n", + " return data\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data_formatted = get_formatted_data(data) \n", + "print(data_formatted.to_markdown())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 3: Propose a model\n", + "*What equation are parameters being fit to?*\n", + "\n", + "***Parmest*** requires a \"model function\" to be defined that takes in the data and returns a Pyomo model.\n", + "\n", + " Set up the Pyomo model defining:\n", + " - Pyomo Vars or Params for each parameter (or 'theta') to be estimated\n", + " - the model equation (a function of the observed data, i.e., temperature, mass fraction)\n", + "\n", + " \n", + "\n", + "For this example, the model we are proposing is:\n", + "\n", + "$$\n", + " (a_0 + a_1*x + a_2*x^2 + a_3*x^3+ a_4*x^4)\n", + "$$\n", + "$$\n", + "+ (b_0 + b_1*x + b_2*x^2 + b_3*x^3+ b_4*x^4)*T\n", + "$$\n", + "$$\n", + "+ (c_0 + c_1*x + c_2*x^2 + c_3*x^3+ c_4*x^4)*T^2\n", + "$$\n", + "$$\n", + "+ (d_0 + d_1*x + d_2*x^2 + d_3*x^3+ d_4*x^4)*T^3\n", + "$$\n", + "$$\n", + "+ (e_0 + e_1*x + e_2*x^2 + e_3*x^3 + e_4*x^4)*T^4 \n", + "$$\n", + "\n", + "*(This was an equation found in [literature](https://www.sciencedirect.com/science/article/pii/S0011916403900683) used when fitting Pitzer NaCl Data).*" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def model_function(data):\n", + " m = pyo.ConcreteModel()\n", + "\n", + " # define variables for the estimated parameters\n", + " m.a0 = pyo.Var(initialize=1)\n", + " m.a1 = pyo.Var(initialize=1)\n", + " m.a2 = pyo.Var(initialize=1)\n", + " m.a3 = pyo.Var(initialize=1)\n", + " m.a4 = pyo.Var(initialize=1)\n", + "\n", + " m.b0 = pyo.Var(initialize=1)\n", + " m.b1 = pyo.Var(initialize=1)\n", + " m.b2 = pyo.Var(initialize=1)\n", + " m.b3 = pyo.Var(initialize=1)\n", + " m.b4 = pyo.Var(initialize=1)\n", + "\n", + " m.c0 = pyo.Var(initialize=1)\n", + " m.c1 = pyo.Var(initialize=1)\n", + " m.c2 = pyo.Var(initialize=1)\n", + " m.c3 = pyo.Var(initialize=1)\n", + " m.c4 = pyo.Var(initialize=1)\n", + "\n", + " m.d0 = pyo.Var(initialize=1)\n", + " m.d1 = pyo.Var(initialize=1)\n", + " m.d2 = pyo.Var(initialize=1)\n", + " m.d3 = pyo.Var(initialize=1)\n", + " m.d4 = pyo.Var(initialize=1)\n", + "\n", + " m.e0 = pyo.Var(initialize=1)\n", + " m.e1 = pyo.Var(initialize=1)\n", + " m.e2 = pyo.Var(initialize=1)\n", + " m.e3 = pyo.Var(initialize=1)\n", + " m.e4 = pyo.Var(initialize=1)\n", + "\n", + " # define the model/equation\n", + " def prop_rule(m, x, T):\n", + " expr = ((m.a0 + m.a1*x + m.a2*x**2 + m.a3*x**3+ m.a4*x**4)\n", + " + (m.b0 + m.b1*x + m.b2*x**2 + m.b3*x**3+ m.b4*x**4)*T\n", + " + (m.c0 + m.c1*x + m.c2*x**2 + m.c3*x**3+ m.c4*x**4)*T**2\n", + " + (m.d0 + m.d1*x + m.d2*x**2 + m.d3*x**3+ m.d4*x**4)*T**3\n", + " + (m.e0 + m.e1 * x + m.e2 * x ** 2 + m.e3 * x ** 3 + m.e4 * x ** 4) * T ** 4\n", + " )\n", + " return expr\n", + "\n", + " m.prop_func = pyo.Expression(data.Comp, data.Temp, rule=prop_rule)\n", + "\n", + " def SSE_rule(m):\n", + " return sum(\n", + " (data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2 for i in data.index\n", + " )\n", + " \n", + " m.SSE = pyo.Objective(rule=SSE_rule, sense=pyo.minimize)\n", + "\n", + " return m\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 4: Create a list of theta names\n", + "\n", + "The variables to be estimated by parmest must be given as a list of strings of the variable names as they are defined in the model_function. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# variables from model to be estimated\n", + "# required format: list with strings of param/var names\n", + "theta_names = ['a0', 'a1', 'a2', 'a3', 'a4',\n", + " 'b0', 'b1', 'b2', 'b3', 'b4',\n", + " 'c0', 'c1', 'c2', 'c3', 'c4',\n", + " 'd0', 'd1', 'd2', 'd3', 'd4',\n", + " 'e0', 'e1', 'e2', 'e3', 'e4']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 5: Define an objective function\n", + "\n", + "Now, we must define an objective function for the parameter estimation. This is the deviation between the observation and the prediction typically chosen to be the sum of squared errors.\n", + "\n", + "$$\n", + "\\sum_{i=0}^n (observation_i - prediction_i)^2 \n", + "$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Sum of Squared Errors function\n", + "def objective_function(m,data):\n", + " \n", + " expr = sum(((data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2) for i in data.index)\n", + "\n", + " return expr" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 6: Solve the parameter estimation problem\n", + "\n", + "Now, we have everything we need for parmest to solve the parameter estimation problem: \n", + "\n", + " - model_function\n", + " - data_formatted\n", + " - theta_names\n", + " - objective_function\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Step 6a: Set up the problem\n", + "\n", + "Set up the parameter estimation problem by creating an instance of the parmest 'Estimator' object and feed it the required inputs." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# create an instance of the parmest estimator\n", + "pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Step 6b: Solve the parameter estimation problem \n", + "\n", + "Solve the parameter estimation problem by calling theta_est. This will use the entire data set to perform the parameter estimation. \n", + "\n", + "There are additional options for solving and testing. Further details can be found in the [parmest documentation](https://pyomo.readthedocs.io/en/stable/contributed_packages/parmest/index.html#index-of-parmest-documentation)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# solve the parameter estimation problem\n", + "obj, theta = pest.theta_est()\n", + "\n", + "# display results\n", + "print('theta:\\n', theta)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 7: Plot results\n", + "\n", + "Finally, we can visualize the results using ***matplotlib*** to create a 3D plot of the data and the parameter estimatation fit. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# define a function for the model with estimated thetas\n", + "def est(x, T):\n", + " est = ((theta['a0'] + theta['a1']*x + theta['a2']*x**2 + theta['a3']*x**3 + theta['a4']*x**4)\n", + " + (theta['b0'] + theta['b1']*x + theta['b2']*x**2 + theta['b3']*x**3 + theta['b4']*x**4)*T\n", + " + (theta['c0'] + theta['c1']*x + theta['c2']*x**2 + theta['c3']*x**3 + theta['c4']*x**4)*T**2\n", + " + (theta['d0'] + theta['d1']*x + theta['d2']*x**2 + theta['d3']*x**3 + theta['d4']*x**4)*T**3\n", + " + (theta['e0'] + theta['e1']*x + theta['e2']*x**2 + theta['e3']*x**3 + theta['e4']*x**4)*T**4\n", + ")\n", + " return est\n", + "\n", + "# uncommenting the next line makes figure interactive but may need to pip install ipympl\n", + "# %matplotlib ipympl \n", + "\n", + "# plot the results\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(projection='3d')\n", + "ax.scatter(data_formatted.Comp, data_formatted.Temp, data_formatted.PropData, color='b') # experimental data\n", + "ax.scatter(data_formatted.Comp, data_formatted.Temp, est(data_formatted.Comp,data_formatted.Temp), color='r') # parmest fit\n", + "ax.set_xlabel('Mass Fraction')\n", + "ax.set_ylabel('Temperature, K')\n", + "ax.set_zlabel('Vapor Pressure, Pa')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "watertap-dev", + "language": "python", + "name": "watertap-dev" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.17" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 294f35cb28c7f954251126326376026c24a56e58 Mon Sep 17 00:00:00 2001 From: luohezhiming Date: Mon, 20 Oct 2025 10:23:49 -0400 Subject: [PATCH 02/11] add tutorial for new API --- tutorials/parmest_demo/parmest_example.ipynb | 772 +++++++++++++++++- .../parmest_new_API_example.ipynb | 729 +++++++++++++++-- 2 files changed, 1401 insertions(+), 100 deletions(-) diff --git a/tutorials/parmest_demo/parmest_example.ipynb b/tutorials/parmest_demo/parmest_example.ipynb index f6e2ea287d..c1a2baa331 100644 --- a/tutorials/parmest_demo/parmest_example.ipynb +++ b/tutorials/parmest_demo/parmest_example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -45,9 +45,434 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " 0 1 2 3 4 5 \\\n", + "0 NaN 5.000000 10.000000 20.000000 30.000000 40.000000 \n", + "1 35.000000 0.008548 0.011981 0.022664 0.040939 0.070926 \n", + "2 51.071429 0.008447 0.011838 0.022391 0.040441 0.070058 \n", + "3 67.142857 0.008344 0.011692 0.022111 0.039930 0.069167 \n", + "4 83.214286 0.008238 0.011543 0.021823 0.039404 0.068249 \n", + "5 99.285714 0.008130 0.011389 0.021527 0.038862 0.067304 \n", + "6 115.357143 0.008018 0.011230 0.021221 0.038305 0.066332 \n", + "7 131.428571 0.007902 0.011066 0.020906 0.037731 0.065333 \n", + "8 147.500000 0.007782 0.010896 0.020582 0.037140 0.064307 \n", + "9 163.571429 0.007658 0.010722 0.020247 0.036533 0.063254 \n", + "10 179.642857 0.007530 0.010541 0.019903 0.035911 0.062177 \n", + "11 195.714286 0.007398 0.010355 0.019550 0.035273 0.061076 \n", + "12 211.785714 0.007261 0.010163 0.019187 0.034620 0.059952 \n", + "13 227.857143 0.007120 0.009965 0.018815 0.033953 0.058808 \n", + "14 243.928571 0.006975 0.009762 0.018434 0.033273 0.057645 \n", + "15 260.000000 0.006825 0.009554 0.018045 0.032581 0.056464 \n", + "\n", + " 6 7 8 9 10 11 \\\n", + "0 50.000000 60.000000 70.000000 80.000000 90.000000 100.000000 \n", + "1 0.118314 0.190684 0.297821 0.451976 0.668080 0.963854 \n", + "2 0.116862 0.188342 0.294164 0.446437 0.659918 0.952128 \n", + "3 0.115369 0.185932 0.290401 0.440739 0.651523 0.940072 \n", + "4 0.113832 0.183451 0.286529 0.434876 0.642891 0.927682 \n", + "5 0.112250 0.180900 0.282549 0.428853 0.634026 0.914965 \n", + "6 0.110624 0.178278 0.278462 0.422673 0.624938 0.901938 \n", + "7 0.108954 0.175590 0.274275 0.416347 0.615642 0.888625 \n", + "8 0.107242 0.172836 0.269992 0.409884 0.606156 0.875051 \n", + "9 0.105490 0.170023 0.265622 0.403297 0.596498 0.861246 \n", + "10 0.103699 0.167153 0.261172 0.396599 0.586691 0.847243 \n", + "11 0.101874 0.164233 0.256650 0.389805 0.576755 0.833075 \n", + "12 0.100015 0.161267 0.252067 0.382928 0.566714 0.818775 \n", + "13 0.098128 0.158260 0.247430 0.375984 0.556590 0.804376 \n", + "14 0.096214 0.155219 0.242749 0.368986 0.546405 0.789912 \n", + "15 0.094276 0.152148 0.238034 0.361950 0.536181 0.775415 \n", + "\n", + " 12 13 14 15 16 \n", + "0 110.000000 120.000000 130.000000 140.000000 150.000000 \n", + "1 1.360139 1.880266 2.550230 3.398336 4.454784 \n", + "2 1.343665 1.857625 2.519725 3.357989 4.402328 \n", + "3 1.326736 1.834374 2.488425 3.316629 4.348612 \n", + "4 1.309348 1.810509 2.456323 3.274245 4.293618 \n", + "5 1.291514 1.786050 2.423446 3.230873 4.237388 \n", + "6 1.273260 1.761033 2.389844 3.186577 4.180008 \n", + "7 1.254618 1.735505 2.355583 3.141449 4.121594 \n", + "8 1.235629 1.709523 2.320741 3.095592 4.062284 \n", + "9 1.216337 1.683151 2.285405 3.049123 4.002229 \n", + "10 1.196788 1.656453 2.249666 3.002163 3.941589 \n", + "11 1.177031 1.629498 2.213617 2.954839 3.880529 \n", + "12 1.157114 1.602354 2.177352 2.907276 3.819216 \n", + "13 1.137085 1.575091 2.140966 2.859600 3.757814 \n", + "14 1.116993 1.547774 2.104549 2.811934 3.696485 \n", + "15 1.096885 1.520470 2.068193 2.764399 3.635388 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# data obtained using PhreeqC\n", "# read in csv file to pd.dataframe\n", @@ -78,7 +503,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -117,9 +542,258 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "| | Comp | Temp | PropData |\n", + "|----:|----------:|-------:|-----------:|\n", + "| 0 | 0.035 | 278 | 866.079 |\n", + "| 1 | 0.0510714 | 278 | 855.861 |\n", + "| 2 | 0.0671429 | 278 | 845.434 |\n", + "| 3 | 0.0832143 | 278 | 834.74 |\n", + "| 4 | 0.0992857 | 278 | 823.735 |\n", + "| 5 | 0.115357 | 278 | 812.381 |\n", + "| 6 | 0.131429 | 278 | 800.649 |\n", + "| 7 | 0.1475 | 278 | 788.517 |\n", + "| 8 | 0.163571 | 278 | 775.968 |\n", + "| 9 | 0.179643 | 278 | 762.991 |\n", + "| 10 | 0.195714 | 278 | 749.577 |\n", + "| 11 | 0.211786 | 278 | 735.724 |\n", + "| 12 | 0.227857 | 278 | 721.433 |\n", + "| 13 | 0.243929 | 278 | 706.709 |\n", + "| 14 | 0.26 | 278 | 691.56 |\n", + "| 15 | 0.035 | 283 | 1213.93 |\n", + "| 16 | 0.0510714 | 283 | 1199.49 |\n", + "| 17 | 0.0671429 | 283 | 1184.72 |\n", + "| 18 | 0.0832143 | 283 | 1169.56 |\n", + "| 19 | 0.0992857 | 283 | 1153.96 |\n", + "| 20 | 0.115357 | 283 | 1137.86 |\n", + "| 21 | 0.131429 | 283 | 1121.25 |\n", + "| 22 | 0.1475 | 283 | 1104.08 |\n", + "| 23 | 0.163571 | 283 | 1086.36 |\n", + "| 24 | 0.179643 | 283 | 1068.06 |\n", + "| 25 | 0.195714 | 283 | 1049.19 |\n", + "| 26 | 0.211786 | 283 | 1029.74 |\n", + "| 27 | 0.227857 | 283 | 1009.72 |\n", + "| 28 | 0.243929 | 283 | 989.15 |\n", + "| 29 | 0.26 | 283 | 968.035 |\n", + "| 30 | 0.035 | 293 | 2296.45 |\n", + "| 31 | 0.0510714 | 293 | 2268.76 |\n", + "| 32 | 0.0671429 | 293 | 2240.39 |\n", + "| 33 | 0.0832143 | 293 | 2211.22 |\n", + "| 34 | 0.0992857 | 293 | 2181.19 |\n", + "| 35 | 0.115357 | 293 | 2150.23 |\n", + "| 36 | 0.131429 | 293 | 2118.32 |\n", + "| 37 | 0.1475 | 293 | 2085.43 |\n", + "| 38 | 0.163571 | 293 | 2051.56 |\n", + "| 39 | 0.179643 | 293 | 2016.71 |\n", + "| 40 | 0.195714 | 293 | 1980.88 |\n", + "| 41 | 0.211786 | 293 | 1944.11 |\n", + "| 42 | 0.227857 | 293 | 1906.42 |\n", + "| 43 | 0.243929 | 293 | 1867.84 |\n", + "| 44 | 0.26 | 293 | 1828.42 |\n", + "| 45 | 0.035 | 303 | 4148.16 |\n", + "| 46 | 0.0510714 | 303 | 4097.69 |\n", + "| 47 | 0.0671429 | 303 | 4045.89 |\n", + "| 48 | 0.0832143 | 303 | 3992.6 |\n", + "| 49 | 0.0992857 | 303 | 3937.74 |\n", + "| 50 | 0.115357 | 303 | 3881.23 |\n", + "| 51 | 0.131429 | 303 | 3823.06 |\n", + "| 52 | 0.1475 | 303 | 3763.22 |\n", + "| 53 | 0.163571 | 303 | 3701.74 |\n", + "| 54 | 0.179643 | 303 | 3638.65 |\n", + "| 55 | 0.195714 | 303 | 3574 |\n", + "| 56 | 0.211786 | 303 | 3507.86 |\n", + "| 57 | 0.227857 | 303 | 3440.29 |\n", + "| 58 | 0.243929 | 303 | 3371.39 |\n", + "| 59 | 0.26 | 303 | 3301.23 |\n", + "| 60 | 0.035 | 313 | 7186.58 |\n", + "| 61 | 0.0510714 | 313 | 7098.66 |\n", + "| 62 | 0.0671429 | 313 | 7008.31 |\n", + "| 63 | 0.0832143 | 313 | 6915.33 |\n", + "| 64 | 0.0992857 | 313 | 6819.61 |\n", + "| 65 | 0.115357 | 313 | 6721.11 |\n", + "| 66 | 0.131429 | 313 | 6619.85 |\n", + "| 67 | 0.1475 | 313 | 6515.86 |\n", + "| 68 | 0.163571 | 313 | 6409.23 |\n", + "| 69 | 0.179643 | 313 | 6300.06 |\n", + "| 70 | 0.195714 | 313 | 6188.5 |\n", + "| 71 | 0.211786 | 313 | 6074.67 |\n", + "| 72 | 0.227857 | 313 | 5958.74 |\n", + "| 73 | 0.243929 | 313 | 5840.87 |\n", + "| 74 | 0.26 | 313 | 5721.25 |\n", + "| 75 | 0.035 | 323 | 11988.2 |\n", + "| 76 | 0.0510714 | 323 | 11841 |\n", + "| 77 | 0.0671429 | 323 | 11689.7 |\n", + "| 78 | 0.0832143 | 323 | 11534 |\n", + "| 79 | 0.0992857 | 323 | 11373.8 |\n", + "| 80 | 0.115357 | 323 | 11209 |\n", + "| 81 | 0.131429 | 323 | 11039.8 |\n", + "| 82 | 0.1475 | 323 | 10866.3 |\n", + "| 83 | 0.163571 | 323 | 10688.8 |\n", + "| 84 | 0.179643 | 323 | 10507.3 |\n", + "| 85 | 0.195714 | 323 | 10322.3 |\n", + "| 86 | 0.211786 | 323 | 10134.1 |\n", + "| 87 | 0.227857 | 323 | 9942.78 |\n", + "| 88 | 0.243929 | 323 | 9748.84 |\n", + "| 89 | 0.26 | 323 | 9552.54 |\n", + "| 90 | 0.035 | 333 | 19321.1 |\n", + "| 91 | 0.0510714 | 333 | 19083.7 |\n", + "| 92 | 0.0671429 | 333 | 18839.5 |\n", + "| 93 | 0.0832143 | 333 | 18588.2 |\n", + "| 94 | 0.0992857 | 333 | 18329.7 |\n", + "| 95 | 0.115357 | 333 | 18064.1 |\n", + "| 96 | 0.131429 | 333 | 17791.6 |\n", + "| 97 | 0.1475 | 333 | 17512.6 |\n", + "| 98 | 0.163571 | 333 | 17227.5 |\n", + "| 99 | 0.179643 | 333 | 16936.8 |\n", + "| 100 | 0.195714 | 333 | 16640.9 |\n", + "| 101 | 0.211786 | 333 | 16340.3 |\n", + "| 102 | 0.227857 | 333 | 16035.7 |\n", + "| 103 | 0.243929 | 333 | 15727.6 |\n", + "| 104 | 0.26 | 333 | 15416.4 |\n", + "| 105 | 0.035 | 343 | 30176.7 |\n", + "| 106 | 0.0510714 | 343 | 29806.1 |\n", + "| 107 | 0.0671429 | 343 | 29424.9 |\n", + "| 108 | 0.0832143 | 343 | 29032.6 |\n", + "| 109 | 0.0992857 | 343 | 28629.3 |\n", + "| 110 | 0.115357 | 343 | 28215.2 |\n", + "| 111 | 0.131429 | 343 | 27790.9 |\n", + "| 112 | 0.1475 | 343 | 27356.9 |\n", + "| 113 | 0.163571 | 343 | 26914.1 |\n", + "| 114 | 0.179643 | 343 | 26463.2 |\n", + "| 115 | 0.195714 | 343 | 26005.1 |\n", + "| 116 | 0.211786 | 343 | 25540.7 |\n", + "| 117 | 0.227857 | 343 | 25070.9 |\n", + "| 118 | 0.243929 | 343 | 24596.6 |\n", + "| 119 | 0.26 | 343 | 24118.8 |\n", + "| 120 | 0.035 | 353 | 45796.5 |\n", + "| 121 | 0.0510714 | 353 | 45235.3 |\n", + "| 122 | 0.0671429 | 353 | 44657.8 |\n", + "| 123 | 0.0832143 | 353 | 44063.8 |\n", + "| 124 | 0.0992857 | 353 | 43453.5 |\n", + "| 125 | 0.115357 | 353 | 42827.4 |\n", + "| 126 | 0.131429 | 353 | 42186.3 |\n", + "| 127 | 0.1475 | 353 | 41531.5 |\n", + "| 128 | 0.163571 | 353 | 40864 |\n", + "| 129 | 0.179643 | 353 | 40185.4 |\n", + "| 130 | 0.195714 | 353 | 39497 |\n", + "| 131 | 0.211786 | 353 | 38800.2 |\n", + "| 132 | 0.227857 | 353 | 38096.5 |\n", + "| 133 | 0.243929 | 353 | 37387.5 |\n", + "| 134 | 0.26 | 353 | 36674.6 |\n", + "| 135 | 0.035 | 363 | 67693.2 |\n", + "| 136 | 0.0510714 | 363 | 66866.2 |\n", + "| 137 | 0.0671429 | 363 | 66015.6 |\n", + "| 138 | 0.0832143 | 363 | 65140.9 |\n", + "| 139 | 0.0992857 | 363 | 64242.6 |\n", + "| 140 | 0.115357 | 363 | 63321.8 |\n", + "| 141 | 0.131429 | 363 | 62379.9 |\n", + "| 142 | 0.1475 | 363 | 61418.7 |\n", + "| 143 | 0.163571 | 363 | 60440.2 |\n", + "| 144 | 0.179643 | 363 | 59446.4 |\n", + "| 145 | 0.195714 | 363 | 58439.7 |\n", + "| 146 | 0.211786 | 363 | 57422.3 |\n", + "| 147 | 0.227857 | 363 | 56396.5 |\n", + "| 148 | 0.243929 | 363 | 55364.5 |\n", + "| 149 | 0.26 | 363 | 54328.5 |\n", + "| 150 | 0.035 | 373 | 97662.5 |\n", + "| 151 | 0.0510714 | 373 | 96474.4 |\n", + "| 152 | 0.0671429 | 373 | 95252.8 |\n", + "| 153 | 0.0832143 | 373 | 93997.3 |\n", + "| 154 | 0.0992857 | 373 | 92708.8 |\n", + "| 155 | 0.115357 | 373 | 91388.9 |\n", + "| 156 | 0.131429 | 373 | 90039.9 |\n", + "| 157 | 0.1475 | 373 | 88664.5 |\n", + "| 158 | 0.163571 | 373 | 87265.8 |\n", + "| 159 | 0.179643 | 373 | 85846.9 |\n", + "| 160 | 0.195714 | 373 | 84411.3 |\n", + "| 161 | 0.211786 | 373 | 82962.3 |\n", + "| 162 | 0.227857 | 373 | 81503.4 |\n", + "| 163 | 0.243929 | 373 | 80037.8 |\n", + "| 164 | 0.26 | 373 | 78569 |\n", + "| 165 | 0.035 | 383 | 137816 |\n", + "| 166 | 0.0510714 | 383 | 136147 |\n", + "| 167 | 0.0671429 | 383 | 134431 |\n", + "| 168 | 0.0832143 | 383 | 132670 |\n", + "| 169 | 0.0992857 | 383 | 130863 |\n", + "| 170 | 0.115357 | 383 | 129013 |\n", + "| 171 | 0.131429 | 383 | 127124 |\n", + "| 172 | 0.1475 | 383 | 125200 |\n", + "| 173 | 0.163571 | 383 | 123245 |\n", + "| 174 | 0.179643 | 383 | 121265 |\n", + "| 175 | 0.195714 | 383 | 119263 |\n", + "| 176 | 0.211786 | 383 | 117245 |\n", + "| 177 | 0.227857 | 383 | 115215 |\n", + "| 178 | 0.243929 | 383 | 113179 |\n", + "| 179 | 0.26 | 383 | 111142 |\n", + "| 180 | 0.035 | 393 | 190518 |\n", + "| 181 | 0.0510714 | 393 | 188224 |\n", + "| 182 | 0.0671429 | 393 | 185868 |\n", + "| 183 | 0.0832143 | 393 | 183450 |\n", + "| 184 | 0.0992857 | 393 | 180972 |\n", + "| 185 | 0.115357 | 393 | 178437 |\n", + "| 186 | 0.131429 | 393 | 175850 |\n", + "| 187 | 0.1475 | 393 | 173217 |\n", + "| 188 | 0.163571 | 393 | 170545 |\n", + "| 189 | 0.179643 | 393 | 167840 |\n", + "| 190 | 0.195714 | 393 | 165109 |\n", + "| 191 | 0.211786 | 393 | 162359 |\n", + "| 192 | 0.227857 | 393 | 159596 |\n", + "| 193 | 0.243929 | 393 | 156828 |\n", + "| 194 | 0.26 | 393 | 154062 |\n", + "| 195 | 0.035 | 403 | 258402 |\n", + "| 196 | 0.0510714 | 403 | 255311 |\n", + "| 197 | 0.0671429 | 403 | 252140 |\n", + "| 198 | 0.0832143 | 403 | 248887 |\n", + "| 199 | 0.0992857 | 403 | 245556 |\n", + "| 200 | 0.115357 | 403 | 242151 |\n", + "| 201 | 0.131429 | 403 | 238679 |\n", + "| 202 | 0.1475 | 403 | 235149 |\n", + "| 203 | 0.163571 | 403 | 231569 |\n", + "| 204 | 0.179643 | 403 | 227947 |\n", + "| 205 | 0.195714 | 403 | 224295 |\n", + "| 206 | 0.211786 | 403 | 220620 |\n", + "| 207 | 0.227857 | 403 | 216933 |\n", + "| 208 | 0.243929 | 403 | 213243 |\n", + "| 209 | 0.26 | 403 | 209560 |\n", + "| 210 | 0.035 | 413 | 344336 |\n", + "| 211 | 0.0510714 | 413 | 340248 |\n", + "| 212 | 0.0671429 | 413 | 336057 |\n", + "| 213 | 0.0832143 | 413 | 331763 |\n", + "| 214 | 0.0992857 | 413 | 327368 |\n", + "| 215 | 0.115357 | 413 | 322880 |\n", + "| 216 | 0.131429 | 413 | 318307 |\n", + "| 217 | 0.1475 | 413 | 313661 |\n", + "| 218 | 0.163571 | 413 | 308952 |\n", + "| 219 | 0.179643 | 413 | 304194 |\n", + "| 220 | 0.195714 | 413 | 299399 |\n", + "| 221 | 0.211786 | 413 | 294580 |\n", + "| 222 | 0.227857 | 413 | 289749 |\n", + "| 223 | 0.243929 | 413 | 284919 |\n", + "| 224 | 0.26 | 413 | 280103 |\n", + "| 225 | 0.035 | 423 | 451381 |\n", + "| 226 | 0.0510714 | 423 | 446066 |\n", + "| 227 | 0.0671429 | 423 | 440623 |\n", + "| 228 | 0.0832143 | 423 | 435051 |\n", + "| 229 | 0.0992857 | 423 | 429353 |\n", + "| 230 | 0.115357 | 423 | 423539 |\n", + "| 231 | 0.131429 | 423 | 417621 |\n", + "| 232 | 0.1475 | 423 | 411611 |\n", + "| 233 | 0.163571 | 423 | 405526 |\n", + "| 234 | 0.179643 | 423 | 399382 |\n", + "| 235 | 0.195714 | 423 | 393195 |\n", + "| 236 | 0.211786 | 423 | 386982 |\n", + "| 237 | 0.227857 | 423 | 380760 |\n", + "| 238 | 0.243929 | 423 | 374546 |\n", + "| 239 | 0.26 | 423 | 368356 |\n" + ] + } + ], "source": [ "data_formatted = get_formatted_data(data) \n", "print(data_formatted.to_markdown())" @@ -163,7 +837,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -234,7 +908,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -262,7 +936,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -299,9 +973,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING: DEPRECATED: You're using the deprecated parmest interface\n", + "(model_function, data, theta_names). This interface will be removed in a\n", + "future release, please update to the new parmest interface using experiment\n", + "lists. (deprecated in 6.7.2) (called from\n", + "C:\\Users\\wcy78\\anaconda3\\envs\\watertap-dev\\Lib\\functools.py:946)\n" + ] + } + ], "source": [ "# create an instance of the parmest estimator\n", "pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)" @@ -320,9 +1006,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "theta:\n", + " a0 8.091276e+06\n", + "a1 -4.525385e+06\n", + "a2 4.636260e+06\n", + "a3 -1.523677e+07\n", + "a4 3.185056e+07\n", + "b0 -1.097568e+05\n", + "b1 6.237744e+04\n", + "b2 -4.915012e+04\n", + "b3 1.780460e+05\n", + "b4 -4.034074e+05\n", + "c0 5.616476e+02\n", + "c1 -3.243432e+02\n", + "c2 1.812149e+02\n", + "c3 -7.674118e+02\n", + "c4 1.919637e+03\n", + "d0 -1.286400e+00\n", + "d1 7.547497e-01\n", + "d2 -2.559027e-01\n", + "d3 1.440646e+00\n", + "d4 -4.074533e+00\n", + "e0 1.114049e-03\n", + "e1 -6.639096e-04\n", + "e2 8.723880e-05\n", + "e3 -9.890969e-04\n", + "e4 3.262400e-03\n", + "dtype: float64\n" + ] + } + ], "source": [ "# solve the parameter estimation problem\n", "obj, theta = pest.theta_est()\n", @@ -342,9 +1062,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# define a function for the model with estimated thetas\n", "def est(x, T):\n", @@ -373,9 +1104,9 @@ ], "metadata": { "kernelspec": { - "display_name": "watertap-dev", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "watertap-dev" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -387,10 +1118,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.17" - }, - "orig_nbformat": 4 + "version": "3.11.11" + } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index f6e2ea287d..cc46339b03 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -31,6 +31,7 @@ "import numpy as np # to manipulate the data into a usable format\n", "import pyomo.contrib.parmest.parmest as parmest # to perform the parameter estimation\n", "import pyomo.environ as pyo # to create a pyomo model\n", + "from pyomo.contrib.parmest.experiment import Experiment\n", "import matplotlib.pyplot as plt # to plot the results\n", "from watertap.core.solvers import get_solver # to bring in ipopt solver\n", "solver = get_solver() # this will make the ipopt solver available" @@ -45,9 +46,434 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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0.009762 0.018434 0.033273 0.057645 \n", + "15 260.000000 0.006825 0.009554 0.018045 0.032581 0.056464 \n", + "\n", + " 6 7 8 9 10 11 \\\n", + "0 50.000000 60.000000 70.000000 80.000000 90.000000 100.000000 \n", + "1 0.118314 0.190684 0.297821 0.451976 0.668080 0.963854 \n", + "2 0.116862 0.188342 0.294164 0.446437 0.659918 0.952128 \n", + "3 0.115369 0.185932 0.290401 0.440739 0.651523 0.940072 \n", + "4 0.113832 0.183451 0.286529 0.434876 0.642891 0.927682 \n", + "5 0.112250 0.180900 0.282549 0.428853 0.634026 0.914965 \n", + "6 0.110624 0.178278 0.278462 0.422673 0.624938 0.901938 \n", + "7 0.108954 0.175590 0.274275 0.416347 0.615642 0.888625 \n", + "8 0.107242 0.172836 0.269992 0.409884 0.606156 0.875051 \n", + "9 0.105490 0.170023 0.265622 0.403297 0.596498 0.861246 \n", + "10 0.103699 0.167153 0.261172 0.396599 0.586691 0.847243 \n", + "11 0.101874 0.164233 0.256650 0.389805 0.576755 0.833075 \n", + "12 0.100015 0.161267 0.252067 0.382928 0.566714 0.818775 \n", + "13 0.098128 0.158260 0.247430 0.375984 0.556590 0.804376 \n", + "14 0.096214 0.155219 0.242749 0.368986 0.546405 0.789912 \n", + "15 0.094276 0.152148 0.238034 0.361950 0.536181 0.775415 \n", + "\n", + " 12 13 14 15 16 \n", + "0 110.000000 120.000000 130.000000 140.000000 150.000000 \n", + "1 1.360139 1.880266 2.550230 3.398336 4.454784 \n", + "2 1.343665 1.857625 2.519725 3.357989 4.402328 \n", + "3 1.326736 1.834374 2.488425 3.316629 4.348612 \n", + "4 1.309348 1.810509 2.456323 3.274245 4.293618 \n", + "5 1.291514 1.786050 2.423446 3.230873 4.237388 \n", + "6 1.273260 1.761033 2.389844 3.186577 4.180008 \n", + "7 1.254618 1.735505 2.355583 3.141449 4.121594 \n", + "8 1.235629 1.709523 2.320741 3.095592 4.062284 \n", + "9 1.216337 1.683151 2.285405 3.049123 4.002229 \n", + "10 1.196788 1.656453 2.249666 3.002163 3.941589 \n", + "11 1.177031 1.629498 2.213617 2.954839 3.880529 \n", + "12 1.157114 1.602354 2.177352 2.907276 3.819216 \n", + "13 1.137085 1.575091 2.140966 2.859600 3.757814 \n", + "14 1.116993 1.547774 2.104549 2.811934 3.696485 \n", + "15 1.096885 1.520470 2.068193 2.764399 3.635388 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# data obtained using PhreeqC\n", "# read in csv file to pd.dataframe\n", @@ -78,7 +504,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -117,12 +543,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data_formatted = get_formatted_data(data) \n", - "print(data_formatted.to_markdown())" + "# print(data_formatted.to_markdown())" ] }, { @@ -163,66 +589,154 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ - "def model_function(data):\n", + "def model_function():\n", " m = pyo.ConcreteModel()\n", "\n", " # define variables for the estimated parameters\n", - " m.a0 = pyo.Var(initialize=1)\n", - " m.a1 = pyo.Var(initialize=1)\n", - " m.a2 = pyo.Var(initialize=1)\n", - " m.a3 = pyo.Var(initialize=1)\n", - " m.a4 = pyo.Var(initialize=1)\n", - "\n", - " m.b0 = pyo.Var(initialize=1)\n", - " m.b1 = pyo.Var(initialize=1)\n", - " m.b2 = pyo.Var(initialize=1)\n", - " m.b3 = pyo.Var(initialize=1)\n", - " m.b4 = pyo.Var(initialize=1)\n", - "\n", - " m.c0 = pyo.Var(initialize=1)\n", - " m.c1 = pyo.Var(initialize=1)\n", - " m.c2 = pyo.Var(initialize=1)\n", - " m.c3 = pyo.Var(initialize=1)\n", - " m.c4 = pyo.Var(initialize=1)\n", - "\n", - " m.d0 = pyo.Var(initialize=1)\n", - " m.d1 = pyo.Var(initialize=1)\n", - " m.d2 = pyo.Var(initialize=1)\n", - " m.d3 = pyo.Var(initialize=1)\n", - " m.d4 = pyo.Var(initialize=1)\n", - "\n", - " m.e0 = pyo.Var(initialize=1)\n", - " m.e1 = pyo.Var(initialize=1)\n", - " m.e2 = pyo.Var(initialize=1)\n", - " m.e3 = pyo.Var(initialize=1)\n", - " m.e4 = pyo.Var(initialize=1)\n", - "\n", - " # define the model/equation\n", - " def prop_rule(m, x, T):\n", - " expr = ((m.a0 + m.a1*x + m.a2*x**2 + m.a3*x**3+ m.a4*x**4)\n", - " + (m.b0 + m.b1*x + m.b2*x**2 + m.b3*x**3+ m.b4*x**4)*T\n", - " + (m.c0 + m.c1*x + m.c2*x**2 + m.c3*x**3+ m.c4*x**4)*T**2\n", - " + (m.d0 + m.d1*x + m.d2*x**2 + m.d3*x**3+ m.d4*x**4)*T**3\n", - " + (m.e0 + m.e1 * x + m.e2 * x ** 2 + m.e3 * x ** 3 + m.e4 * x ** 4) * T ** 4\n", + " m.a0 = pyo.Param(initialize=1, mutable=True)\n", + " m.a1 = pyo.Param(initialize=1, mutable=True)\n", + " m.a2 = pyo.Param(initialize=1, mutable=True)\n", + " m.a3 = pyo.Param(initialize=1, mutable=True)\n", + " m.a4 = pyo.Param(initialize=1, mutable=True)\n", + "\n", + " m.b0 = pyo.Param(initialize=1, mutable=True)\n", + " m.b1 = pyo.Param(initialize=1, mutable=True)\n", + " m.b2 = pyo.Param(initialize=1, mutable=True)\n", + " m.b3 = pyo.Param(initialize=1, mutable=True)\n", + " m.b4 = pyo.Param(initialize=1, mutable=True)\n", + "\n", + " m.c0 = pyo.Param(initialize=1, mutable=True)\n", + " m.c1 = pyo.Param(initialize=1, mutable=True)\n", + " m.c2 = pyo.Param(initialize=1, mutable=True)\n", + " m.c3 = pyo.Param(initialize=1, mutable=True)\n", + " m.c4 = pyo.Param(initialize=1, mutable=True)\n", + "\n", + " m.d0 = pyo.Param(initialize=1, mutable=True)\n", + " m.d1 = pyo.Param(initialize=1, mutable=True)\n", + " m.d2 = pyo.Param(initialize=1, mutable=True)\n", + " m.d3 = pyo.Param(initialize=1, mutable=True)\n", + " m.d4 = pyo.Param(initialize=1, mutable=True)\n", + "\n", + " m.e0 = pyo.Param(initialize=1, mutable=True)\n", + " m.e1 = pyo.Param(initialize=1, mutable=True)\n", + " m.e2 = pyo.Param(initialize=1, mutable=True)\n", + " m.e3 = pyo.Param(initialize=1, mutable=True)\n", + " m.e4 = pyo.Param(initialize=1, mutable=True)\n", + "\n", + " # define mass fraction as an input variable\n", + " m.x = pyo.Param(initialize=0.1, mutable=True)\n", + "\n", + " # define temperature as an input variable\n", + " m.T = pyo.Param(initialize=278, mutable=True)\n", + "\n", + " # # define mass fraction as an input variable\n", + " # m.x = pyo.Var(initialize=0.1)\n", + "\n", + " # # define temperature as an input variable\n", + " # m.T = pyo.Var(initialize=300)\n", + "\n", + " # define output observation as a variable\n", + " m.y = pyo.Var(initialize=10000)\n", + "\n", + " # define constraints for the model\n", + " m.prop_rule = pyo.Constraint(\n", + " expr=(\n", + " m.y == ((m.a0 + m.a1*m.x + m.a2*m.x**2 + m.a3*m.x**3+ m.a4*m.x**4) \n", + " + (m.b0 + m.b1*m.x + m.b2*m.x**2 + m.b3*m.x**3+ m.b4*m.x**4)*m.T\n", + " + (m.c0 + m.c1*m.x + m.c2*m.x**2 + m.c3*m.x**3+ m.c4*m.x**4)*m.T**2\n", + " + (m.d0 + m.d1*m.x + m.d2*m.x**2 + m.d3*m.x**3+ m.d4*m.x**4)*m.T**3\n", + " + (m.e0 + m.e1 * m.x + m.e2 * m.x ** 2 + m.e3 * m.x ** 3 + m.e4 * m.x ** 4) * m.T ** 4\n", + " )\n", " )\n", - " return expr\n", - "\n", - " m.prop_func = pyo.Expression(data.Comp, data.Temp, rule=prop_rule)\n", + " )\n", + " \n", "\n", - " def SSE_rule(m):\n", - " return sum(\n", - " (data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2 for i in data.index\n", - " )\n", + " # # define the model/equation\n", + " # def prop_rule(m, x, T):\n", + " # expr = ((m.a0 + m.a1*x + m.a2*x**2 + m.a3*x**3+ m.a4*x**4)\n", + " # + (m.b0 + m.b1*x + m.b2*x**2 + m.b3*x**3+ m.b4*x**4)*T\n", + " # + (m.c0 + m.c1*x + m.c2*x**2 + m.c3*x**3+ m.c4*x**4)*T**2\n", + " # + (m.d0 + m.d1*x + m.d2*x**2 + m.d3*x**3+ m.d4*x**4)*T**3\n", + " # + (m.e0 + m.e1 * x + m.e2 * x ** 2 + m.e3 * x ** 3 + m.e4 * x ** 4) * T ** 4\n", + " # )\n", + " # return expr\n", + "\n", + " # m.prop_func = pyo.Expression(data.Comp, data.Temp, rule=prop_rule)\n", + "\n", + " # def SSE_rule(m):\n", + " # return sum(\n", + " # (data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2 for i in data.index\n", + " # )\n", " \n", - " m.SSE = pyo.Objective(rule=SSE_rule, sense=pyo.minimize)\n", + " # m.SSE = pyo.Objective(rule=SSE_rule, sense=pyo.minimize)\n", "\n", " return m\n" ] }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "class DesignExperiment(Experiment):\n", + "\n", + " def __init__(self, data, experiment_number):\n", + " self.data = data\n", + " self.experiment_number = experiment_number\n", + " self.data_i = data.loc[experiment_number, :]\n", + " self.model = None\n", + "\n", + " def create_model(self):\n", + " self.model = m = model_function()\n", + " return m\n", + "\n", + " def finalize_model(self):\n", + " m = self.model\n", + "\n", + " # Experiment inputs values\n", + " m.x = self.data_i['Comp']\n", + " m.T = self.data_i['Temp']\n", + "\n", + " # Experiment output values\n", + " m.y = self.data_i['PropData']\n", + "\n", + " return m\n", + "\n", + " def label_model(self):\n", + " m = self.model\n", + "\n", + " m.experiment_outputs = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", + " m.experiment_outputs.update(\n", + " [\n", + " (m.y, self.data_i['PropData']),\n", + " ]\n", + " )\n", + "\n", + " m.unknown_parameters = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", + " parameter_set = [m.a0, m.a1, m.a2, m.a3, m.a4, \n", + " m.b0, m.b1, m.b2, m.b3, m.b4, \n", + " m.c0, m.c1, m.c2, m.c3, m.c4,\n", + " m.d0, m.d1, m.d2, m.d3, m.d4,\n", + " m.e0, m.e1, m.e2, m.e3, m.e4]\n", + " m.unknown_parameters.update(\n", + " (k, pyo.ComponentUID(k)) for k in [m.a0, m.a1, m.a2, m.a3, m.a4, m.b0, m.b1, m.b2, m.b3, m.b4, m.c0, m.c1, m.c2, m.c3, m.c4, m.d0, m.d1, m.d2, m.d3, m.d4, m.e0, m.e1, m.e2, m.e3, m.e4]\n", + " )\n", + "\n", + " return m\n", + "\n", + " def get_labeled_model(self):\n", + " m = self.create_model()\n", + " m = self.finalize_model()\n", + " m = self.label_model()\n", + "\n", + " return m" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -234,17 +748,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "# variables from model to be estimated\n", - "# required format: list with strings of param/var names\n", - "theta_names = ['a0', 'a1', 'a2', 'a3', 'a4',\n", - " 'b0', 'b1', 'b2', 'b3', 'b4',\n", - " 'c0', 'c1', 'c2', 'c3', 'c4',\n", - " 'd0', 'd1', 'd2', 'd3', 'd4',\n", - " 'e0', 'e1', 'e2', 'e3', 'e4']" + "# # variables from model to be estimated\n", + "# # required format: list with strings of param/var names\n", + "# theta_names = ['a0', 'a1', 'a2', 'a3', 'a4',\n", + "# 'b0', 'b1', 'b2', 'b3', 'b4',\n", + "# 'c0', 'c1', 'c2', 'c3', 'c4',\n", + "# 'd0', 'd1', 'd2', 'd3', 'd4',\n", + "# 'e0', 'e1', 'e2', 'e3', 'e4']" ] }, { @@ -262,16 +776,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ - "# Sum of Squared Errors function\n", - "def objective_function(m,data):\n", + "# # Sum of Squared Errors function\n", + "# def SSE(m,data):\n", " \n", - " expr = sum(((data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2) for i in data.index)\n", + "# expr = sum(((data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2) for i in data.index)\n", "\n", - " return expr" + "# return expr" ] }, { @@ -299,12 +813,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240\n" + ] + } + ], "source": [ "# create an instance of the parmest estimator\n", - "pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)" + "exp_list = []\n", + "for i in range(data_formatted.shape[0]):\n", + " exp_list.append(DesignExperiment(data_formatted, i))\n", + "pest = parmest.Estimator(exp_list, obj_function='SSE')\n", + "# pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)\n", + "print(data_formatted.shape[0])" ] }, { @@ -320,9 +847,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "theta:\n", + " c4 1.919639e+03\n", + "e1 -6.639097e-04\n", + "d4 -4.074538e+00\n", + "d1 7.547498e-01\n", + "a0 8.091276e+06\n", + "e2 8.723920e-05\n", + "a3 -1.523680e+07\n", + "b4 -4.034080e+05\n", + "c3 -7.674132e+02\n", + "b0 -1.097568e+05\n", + "b2 -4.915019e+04\n", + "d2 -2.559033e-01\n", + "c2 1.812152e+02\n", + "c0 5.616476e+02\n", + "e3 -9.890988e-04\n", + "a2 4.636265e+06\n", + "d0 -1.286400e+00\n", + "b3 1.780463e+05\n", + "a4 3.185061e+07\n", + "e4 3.262403e-03\n", + "c1 -3.243432e+02\n", + "a1 -4.525385e+06\n", + "e0 1.114049e-03\n", + "b1 6.237744e+04\n", + "d3 1.440649e+00\n", + "dtype: float64\n" + ] + } + ], "source": [ "# solve the parameter estimation problem\n", "obj, theta = pest.theta_est()\n", @@ -342,9 +903,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# define a function for the model with estimated thetas\n", "def est(x, T):\n", @@ -373,9 +945,9 @@ ], "metadata": { "kernelspec": { - "display_name": "watertap-dev", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "watertap-dev" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -387,10 +959,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.17" - }, - "orig_nbformat": 4 + "version": "3.11.11" + } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } From 189dd716a5cc77d392def5cd040de668710bd2a7 Mon Sep 17 00:00:00 2001 From: luohezhiming Date: Fri, 24 Oct 2025 12:05:37 -0400 Subject: [PATCH 03/11] new API for parmest --- .../parmest_new_API_example.ipynb | 231 ++++++++---------- 1 file changed, 103 insertions(+), 128 deletions(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index cc46339b03..ee741de27d 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -9,7 +9,7 @@ "# Conducting a Parameter Estimation\n", "___\n", "\n", - "Author: Savannah Sakhai\n", + "Author: Savannah Sakhai, Chenyu Wang\n", "\n", "For this demonstration, we will be going through how to set up a parameter estimation using the Pyomo tool ***parmest***. This simple case study aims to develop an empirical equation for the vapor pressure of an NaCl solution over a range of temperature and salt mass fractions." ] @@ -543,11 +543,33 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Comp Temp PropData\n", + "0 0.035000 278.0 866.078781\n", + "1 0.051071 278.0 855.860864\n", + "2 0.067143 278.0 845.433914\n", + "3 0.083214 278.0 834.740479\n", + "4 0.099286 278.0 823.734861\n", + ".. ... ... ...\n", + "235 0.195714 423.0 393194.608930\n", + "236 0.211786 423.0 386982.037389\n", + "237 0.227857 423.0 380760.491594\n", + "238 0.243929 423.0 374546.383155\n", + "239 0.260000 423.0 368355.661236\n", + "\n", + "[240 rows x 3 columns]\n" + ] + } + ], "source": [ "data_formatted = get_formatted_data(data) \n", + "print(data_formatted)\n", "# print(data_formatted.to_markdown())" ] }, @@ -560,16 +582,13 @@ "\n", "***Parmest*** requires a \"model function\" to be defined that takes in the data and returns a Pyomo model.\n", "\n", - " Set up the Pyomo model defining:\n", - " - Pyomo Vars or Params for each parameter (or 'theta') to be estimated\n", - " - the model equation (a function of the observed data, i.e., temperature, mass fraction)\n", - "\n", - " \n", + "Set up the Pyomo model defining:\n", + "- Pyomo Vars or Params for input variables, output variables and parameters to be estimated\n", + "- the model equation (a function of the observed data, i.e. mass fraction and temprature)\n", "\n", "For this example, the model we are proposing is:\n", - "\n", "$$\n", - " (a_0 + a_1*x + a_2*x^2 + a_3*x^3+ a_4*x^4)\n", + "y = (a_0 + a_1*x + a_2*x^2 + a_3*x^3+ a_4*x^4)\n", "$$\n", "$$\n", "+ (b_0 + b_1*x + b_2*x^2 + b_3*x^3+ b_4*x^4)*T\n", @@ -583,13 +602,14 @@ "$$\n", "+ (e_0 + e_1*x + e_2*x^2 + e_3*x^3 + e_4*x^4)*T^4 \n", "$$\n", + "where $y$ is the output variables, $x$ (mass fraction) and $T$ (temperature) are the input variables, and $a_0$ to $e_4$ are parameters to be estimated\n", "\n", "*(This was an equation found in [literature](https://www.sciencedirect.com/science/article/pii/S0011916403900683) used when fitting Pitzer NaCl Data).*" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -627,18 +647,12 @@ " m.e3 = pyo.Param(initialize=1, mutable=True)\n", " m.e4 = pyo.Param(initialize=1, mutable=True)\n", "\n", - " # define mass fraction as an input variable\n", + " # define mass fraction as an input parameter\n", " m.x = pyo.Param(initialize=0.1, mutable=True)\n", "\n", - " # define temperature as an input variable\n", + " # define temperature as an input parameter\n", " m.T = pyo.Param(initialize=278, mutable=True)\n", "\n", - " # # define mass fraction as an input variable\n", - " # m.x = pyo.Var(initialize=0.1)\n", - "\n", - " # # define temperature as an input variable\n", - " # m.T = pyo.Var(initialize=300)\n", - "\n", " # define output observation as a variable\n", " m.y = pyo.Var(initialize=10000)\n", "\n", @@ -654,32 +668,28 @@ " )\n", " )\n", " \n", + " return m\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Step 4: Define list of experiment objects\n", + "We need to define a list of experiment objects which is used to create one labeled model for each expeirment. The template ``Experiment`` can be used to generate a list of experiment objects.\n", "\n", - " # # define the model/equation\n", - " # def prop_rule(m, x, T):\n", - " # expr = ((m.a0 + m.a1*x + m.a2*x**2 + m.a3*x**3+ m.a4*x**4)\n", - " # + (m.b0 + m.b1*x + m.b2*x**2 + m.b3*x**3+ m.b4*x**4)*T\n", - " # + (m.c0 + m.c1*x + m.c2*x**2 + m.c3*x**3+ m.c4*x**4)*T**2\n", - " # + (m.d0 + m.d1*x + m.d2*x**2 + m.d3*x**3+ m.d4*x**4)*T**3\n", - " # + (m.e0 + m.e1 * x + m.e2 * x ** 2 + m.e3 * x ** 3 + m.e4 * x ** 4) * T ** 4\n", - " # )\n", - " # return expr\n", - "\n", - " # m.prop_func = pyo.Expression(data.Comp, data.Temp, rule=prop_rule)\n", - "\n", - " # def SSE_rule(m):\n", - " # return sum(\n", - " # (data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2 for i in data.index\n", - " # )\n", - " \n", - " # m.SSE = pyo.Objective(rule=SSE_rule, sense=pyo.minimize)\n", + "A labeled Pyomo model $m$ has two additional suffixes (Pyomo Suffix):\n", "\n", - " return m\n" + "- ``m.experiment_outputs`` defines experiment output (Pyomo Param, Var, or Expression) and their associated data values (float, int).\n", + "\n", + "- ``m.unknown_parameters`` defines the mutable parameters or variables (Pyomo Param or Var) to estimate along with their component unique identifier (Pyomo ComponentUID).\n", + "\n", + "In the experiment class, ``get_labeled_model`` returns the labeled Pyomo model mapping model variables to the data." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -711,11 +721,7 @@ " m = self.model\n", "\n", " m.experiment_outputs = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", - " m.experiment_outputs.update(\n", - " [\n", - " (m.y, self.data_i['PropData']),\n", - " ]\n", - " )\n", + " m.experiment_outputs.update([(m.y, self.data_i['PropData'])])\n", "\n", " m.unknown_parameters = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", " parameter_set = [m.a0, m.a1, m.a2, m.a3, m.a4, \n", @@ -724,7 +730,7 @@ " m.d0, m.d1, m.d2, m.d3, m.d4,\n", " m.e0, m.e1, m.e2, m.e3, m.e4]\n", " m.unknown_parameters.update(\n", - " (k, pyo.ComponentUID(k)) for k in [m.a0, m.a1, m.a2, m.a3, m.a4, m.b0, m.b1, m.b2, m.b3, m.b4, m.c0, m.c1, m.c2, m.c3, m.c4, m.d0, m.d1, m.d2, m.d3, m.d4, m.e0, m.e1, m.e2, m.e3, m.e4]\n", + " (k, pyo.ComponentUID(k)) for k in parameter_set\n", " )\n", "\n", " return m\n", @@ -741,113 +747,83 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Step 4: Create a list of theta names\n", + "### Step 5: Solve the parameter estimation problem\n", "\n", - "The variables to be estimated by parmest must be given as a list of strings of the variable names as they are defined in the model_function. " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# # variables from model to be estimated\n", - "# # required format: list with strings of param/var names\n", - "# theta_names = ['a0', 'a1', 'a2', 'a3', 'a4',\n", - "# 'b0', 'b1', 'b2', 'b3', 'b4',\n", - "# 'c0', 'c1', 'c2', 'c3', 'c4',\n", - "# 'd0', 'd1', 'd2', 'd3', 'd4',\n", - "# 'e0', 'e1', 'e2', 'e3', 'e4']" + "Now, we need to define the following items for parmest to solve the parameter estimation problem: \n", + "\n", + " - exp_list\n", + " - objective_function\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Step 5: Define an objective function\n", + "#### Step 5a: Set up the experimental list\n", "\n", - "Now, we must define an objective function for the parameter estimation. This is the deviation between the observation and the prediction typically chosen to be the sum of squared errors.\n", - "\n", - "$$\n", - "\\sum_{i=0}^n (observation_i - prediction_i)^2 \n", - "$$\n" + "Set up the experimental list by appending the object in the ``Design Experiment`` to a list" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ - "# # Sum of Squared Errors function\n", - "# def SSE(m,data):\n", - " \n", - "# expr = sum(((data.PropData[i] - m.prop_func[data.Comp[i], data.Temp[i]]) ** 2) for i in data.index)\n", - "\n", - "# return expr" + "# create a experiment list\n", + "exp_list = []\n", + "for i in range(data_formatted.shape[0]):\n", + " exp_list.append(DesignExperiment(data_formatted, i))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Step 6: Solve the parameter estimation problem\n", + "#### Step 5b: Define an objective function\n", "\n", - "Now, we have everything we need for parmest to solve the parameter estimation problem: \n", + "Now, we should define an objective function for the parameter estimation. This is the deviation between the observation and the prediction typically chosen to be the sum of squared errors.\n", "\n", - " - model_function\n", - " - data_formatted\n", - " - theta_names\n", - " - objective_function\n" + "$$\n", + "\\sum_{i=0}^n (observation_i - prediction_i)^2 \n", + "$$\n", + "\n", + "We can use the built-in objective function in Parmest to compute the sum of squared errors (``“SSE”``) between the ``m.experiment_outputs`` model values and data values." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Step 6a: Set up the problem\n", + "#### Step 5c: Set up the problem\n", "\n", - "Set up the parameter estimation problem by creating an instance of the parmest 'Estimator' object and feed it the required inputs." + "Set up the parameter estimation problem by creating an instance of the parmest ``Estimator`` object and feed it the required inputs." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 8, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "240\n" - ] - } - ], + "outputs": [], "source": [ - "# create an instance of the parmest estimator\n", - "exp_list = []\n", - "for i in range(data_formatted.shape[0]):\n", - " exp_list.append(DesignExperiment(data_formatted, i))\n", - "pest = parmest.Estimator(exp_list, obj_function='SSE')\n", - "# pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)\n", - "print(data_formatted.shape[0])" + "# create an instance of the parmest estimator \n", + "pest = parmest.Estimator(exp_list, obj_function='SSE')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Step 6b: Solve the parameter estimation problem \n", + "#### Step 5d: Solve the parameter estimation problem \n", "\n", "Solve the parameter estimation problem by calling theta_est. This will use the entire data set to perform the parameter estimation. \n", "\n", - "There are additional options for solving and testing. Further details can be found in the [parmest documentation](https://pyomo.readthedocs.io/en/stable/contributed_packages/parmest/index.html#index-of-parmest-documentation)." + "There are additional options for solving and testing. Further details can be found in the [parmest documentation](https://pyomo.readthedocs.io/en/6.8.0/contributed_packages/parmest/index.html)." ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -855,31 +831,31 @@ "output_type": "stream", "text": [ "theta:\n", - " c4 1.919639e+03\n", - "e1 -6.639097e-04\n", - "d4 -4.074538e+00\n", - "d1 7.547498e-01\n", - "a0 8.091276e+06\n", - "e2 8.723920e-05\n", - "a3 -1.523680e+07\n", - "b4 -4.034080e+05\n", - "c3 -7.674132e+02\n", + " a0 8.091276e+06\n", + "a1 -4.525386e+06\n", + "a2 4.636278e+06\n", + "a3 -1.523686e+07\n", + "a4 3.185071e+07\n", "b0 -1.097568e+05\n", - "b2 -4.915019e+04\n", - "d2 -2.559033e-01\n", - "c2 1.812152e+02\n", + "b1 6.237745e+04\n", + "b2 -4.915034e+04\n", + "b3 1.780470e+05\n", + "b4 -4.034092e+05\n", "c0 5.616476e+02\n", - "e3 -9.890988e-04\n", - "a2 4.636265e+06\n", + "c1 -3.243433e+02\n", + "c2 1.812158e+02\n", + "c3 -7.674163e+02\n", + "c4 1.919645e+03\n", "d0 -1.286400e+00\n", - "b3 1.780463e+05\n", - "a4 3.185061e+07\n", - "e4 3.262403e-03\n", - "c1 -3.243432e+02\n", - "a1 -4.525385e+06\n", + "d1 7.547499e-01\n", + "d2 -2.559045e-01\n", + "d3 1.440655e+00\n", + "d4 -4.074548e+00\n", "e0 1.114049e-03\n", - "b1 6.237744e+04\n", - "d3 1.440649e+00\n", + "e1 -6.639097e-04\n", + "e2 8.724007e-05\n", + "e3 -9.891031e-04\n", + "e4 3.262410e-03\n", "dtype: float64\n" ] } @@ -887,8 +863,7 @@ "source": [ "# solve the parameter estimation problem\n", "obj, theta = pest.theta_est()\n", - "\n", - "# display results\n", + "theta = theta.sort_index()\n", "print('theta:\\n', theta)" ] }, @@ -896,14 +871,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Step 7: Plot results\n", + "### Step 6: Plot results\n", "\n", "Finally, we can visualize the results using ***matplotlib*** to create a 3D plot of the data and the parameter estimatation fit. " ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 10, "metadata": {}, "outputs": [ { From c5567f956902e935b31951a858551fd63d349dda Mon Sep 17 00:00:00 2001 From: luohezhiming <98901358+luohezhiming@users.noreply.github.com> Date: Fri, 31 Oct 2025 13:37:29 -0400 Subject: [PATCH 04/11] Update tutorials/parmest_demo/parmest_new_API_example.ipynb Co-authored-by: MarcusHolly <96305519+MarcusHolly@users.noreply.github.com> --- tutorials/parmest_demo/parmest_new_API_example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index ee741de27d..209f9c790a 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -676,7 +676,7 @@ "metadata": {}, "source": [ "### Step 4: Define list of experiment objects\n", - "We need to define a list of experiment objects which is used to create one labeled model for each expeirment. The template ``Experiment`` can be used to generate a list of experiment objects.\n", + "We need to define a list of experiment objects which is used to create one labeled model for each experiment. The template ``Experiment`` can be used to generate a list of experiment objects.\n", "\n", "A labeled Pyomo model $m$ has two additional suffixes (Pyomo Suffix):\n", "\n", From f03107fbc93abb77bf4c3a3a21408a00d9441dca Mon Sep 17 00:00:00 2001 From: luohezhiming <98901358+luohezhiming@users.noreply.github.com> Date: Fri, 31 Oct 2025 13:37:39 -0400 Subject: [PATCH 05/11] Update tutorials/parmest_demo/parmest_new_API_example.ipynb Co-authored-by: MarcusHolly <96305519+MarcusHolly@users.noreply.github.com> --- tutorials/parmest_demo/parmest_new_API_example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index 209f9c790a..017d4c60cc 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -616,7 +616,7 @@ "def model_function():\n", " m = pyo.ConcreteModel()\n", "\n", - " # define variables for the estimated parameters\n", + " # initialize values for the estimated parameters\n", " m.a0 = pyo.Param(initialize=1, mutable=True)\n", " m.a1 = pyo.Param(initialize=1, mutable=True)\n", " m.a2 = pyo.Param(initialize=1, mutable=True)\n", From 2bf0fe7bb970959493ecda4f99e6c572f748d7e4 Mon Sep 17 00:00:00 2001 From: luohezhiming <98901358+luohezhiming@users.noreply.github.com> Date: Fri, 31 Oct 2025 13:38:04 -0400 Subject: [PATCH 06/11] Update tutorials/parmest_demo/parmest_new_API_example.ipynb Co-authored-by: MarcusHolly <96305519+MarcusHolly@users.noreply.github.com> --- tutorials/parmest_demo/parmest_new_API_example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index 017d4c60cc..2f7bf440b4 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -816,7 +816,7 @@ "source": [ "#### Step 5d: Solve the parameter estimation problem \n", "\n", - "Solve the parameter estimation problem by calling theta_est. This will use the entire data set to perform the parameter estimation. \n", + "Solve the parameter estimation problem by calling ``theta_est``. This will use the entire data set to perform the parameter estimation. \n", "\n", "There are additional options for solving and testing. Further details can be found in the [parmest documentation](https://pyomo.readthedocs.io/en/6.8.0/contributed_packages/parmest/index.html)." ] From 3e60d522979c40a2b76dbee8c5942633d85b518b Mon Sep 17 00:00:00 2001 From: luohezhiming <98901358+luohezhiming@users.noreply.github.com> Date: Fri, 31 Oct 2025 13:38:16 -0400 Subject: [PATCH 07/11] Update tutorials/parmest_demo/parmest_new_API_example.ipynb Co-authored-by: MarcusHolly <96305519+MarcusHolly@users.noreply.github.com> --- tutorials/parmest_demo/parmest_new_API_example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index 2f7bf440b4..0aeb0a0f6a 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -708,7 +708,7 @@ " def finalize_model(self):\n", " m = self.model\n", "\n", - " # Experiment inputs values\n", + " # Experiment input values\n", " m.x = self.data_i['Comp']\n", " m.T = self.data_i['Temp']\n", "\n", From 01197b57b43ea234d09a43ef8196d25aa60ec415 Mon Sep 17 00:00:00 2001 From: luohezhiming <98901358+luohezhiming@users.noreply.github.com> Date: Fri, 31 Oct 2025 13:38:24 -0400 Subject: [PATCH 08/11] Update tutorials/parmest_demo/parmest_new_API_example.ipynb Co-authored-by: MarcusHolly <96305519+MarcusHolly@users.noreply.github.com> --- tutorials/parmest_demo/parmest_new_API_example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index 0aeb0a0f6a..77989bf8c8 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -680,7 +680,7 @@ "\n", "A labeled Pyomo model $m$ has two additional suffixes (Pyomo Suffix):\n", "\n", - "- ``m.experiment_outputs`` defines experiment output (Pyomo Param, Var, or Expression) and their associated data values (float, int).\n", + "- ``m.experiment_outputs`` defines experiment outputs (Pyomo Param, Var, or Expression) and their associated data values (float, int).\n", "\n", "- ``m.unknown_parameters`` defines the mutable parameters or variables (Pyomo Param or Var) to estimate along with their component unique identifier (Pyomo ComponentUID).\n", "\n", From 731f3028007be869e9e038e15ad792f35acf831f Mon Sep 17 00:00:00 2001 From: luohezhiming Date: Mon, 3 Nov 2025 10:14:36 -0500 Subject: [PATCH 09/11] revise flowsheet --- .../parmest_new_API_example.ipynb | 179 ++++++++++++++---- 1 file changed, 138 insertions(+), 41 deletions(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index 77989bf8c8..db1a69729e 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -543,34 +543,131 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - " Comp Temp PropData\n", - "0 0.035000 278.0 866.078781\n", - "1 0.051071 278.0 855.860864\n", - "2 0.067143 278.0 845.433914\n", - "3 0.083214 278.0 834.740479\n", - "4 0.099286 278.0 823.734861\n", - ".. ... ... ...\n", - "235 0.195714 423.0 393194.608930\n", - "236 0.211786 423.0 386982.037389\n", - "237 0.227857 423.0 380760.491594\n", - "238 0.243929 423.0 374546.383155\n", - "239 0.260000 423.0 368355.661236\n", - "\n", - "[240 rows x 3 columns]\n" - ] + "data": { + "text/html": [ + "
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"15 1.096885 1.520470 2.068193 2.764399 3.635388 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# data obtained using PhreeqC\n", "# read in csv file to pd.dataframe\n", @@ -503,7 +78,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -542,261 +117,12 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "| | Comp | Temp | PropData |\n", - "|----:|----------:|-------:|-----------:|\n", - "| 0 | 0.035 | 278 | 866.079 |\n", - "| 1 | 0.0510714 | 278 | 855.861 |\n", - "| 2 | 0.0671429 | 278 | 845.434 |\n", - "| 3 | 0.0832143 | 278 | 834.74 |\n", - "| 4 | 0.0992857 | 278 | 823.735 |\n", - "| 5 | 0.115357 | 278 | 812.381 |\n", - "| 6 | 0.131429 | 278 | 800.649 |\n", - "| 7 | 0.1475 | 278 | 788.517 |\n", - "| 8 | 0.163571 | 278 | 775.968 |\n", - "| 9 | 0.179643 | 278 | 762.991 |\n", - "| 10 | 0.195714 | 278 | 749.577 |\n", - "| 11 | 0.211786 | 278 | 735.724 |\n", - "| 12 | 0.227857 | 278 | 721.433 |\n", - "| 13 | 0.243929 | 278 | 706.709 |\n", - "| 14 | 0.26 | 278 | 691.56 |\n", - "| 15 | 0.035 | 283 | 1213.93 |\n", - "| 16 | 0.0510714 | 283 | 1199.49 |\n", - "| 17 | 0.0671429 | 283 | 1184.72 |\n", - "| 18 | 0.0832143 | 283 | 1169.56 |\n", - "| 19 | 0.0992857 | 283 | 1153.96 |\n", - "| 20 | 0.115357 | 283 | 1137.86 |\n", - "| 21 | 0.131429 | 283 | 1121.25 |\n", - "| 22 | 0.1475 | 283 | 1104.08 |\n", - "| 23 | 0.163571 | 283 | 1086.36 |\n", - "| 24 | 0.179643 | 283 | 1068.06 |\n", - "| 25 | 0.195714 | 283 | 1049.19 |\n", - "| 26 | 0.211786 | 283 | 1029.74 |\n", - "| 27 | 0.227857 | 283 | 1009.72 |\n", - "| 28 | 0.243929 | 283 | 989.15 |\n", - "| 29 | 0.26 | 283 | 968.035 |\n", - "| 30 | 0.035 | 293 | 2296.45 |\n", - "| 31 | 0.0510714 | 293 | 2268.76 |\n", - "| 32 | 0.0671429 | 293 | 2240.39 |\n", - "| 33 | 0.0832143 | 293 | 2211.22 |\n", - "| 34 | 0.0992857 | 293 | 2181.19 |\n", - "| 35 | 0.115357 | 293 | 2150.23 |\n", - "| 36 | 0.131429 | 293 | 2118.32 |\n", - "| 37 | 0.1475 | 293 | 2085.43 |\n", - "| 38 | 0.163571 | 293 | 2051.56 |\n", - "| 39 | 0.179643 | 293 | 2016.71 |\n", - "| 40 | 0.195714 | 293 | 1980.88 |\n", - "| 41 | 0.211786 | 293 | 1944.11 |\n", - "| 42 | 0.227857 | 293 | 1906.42 |\n", - "| 43 | 0.243929 | 293 | 1867.84 |\n", - "| 44 | 0.26 | 293 | 1828.42 |\n", - "| 45 | 0.035 | 303 | 4148.16 |\n", - "| 46 | 0.0510714 | 303 | 4097.69 |\n", - "| 47 | 0.0671429 | 303 | 4045.89 |\n", - "| 48 | 0.0832143 | 303 | 3992.6 |\n", - "| 49 | 0.0992857 | 303 | 3937.74 |\n", - "| 50 | 0.115357 | 303 | 3881.23 |\n", - "| 51 | 0.131429 | 303 | 3823.06 |\n", - "| 52 | 0.1475 | 303 | 3763.22 |\n", - "| 53 | 0.163571 | 303 | 3701.74 |\n", - "| 54 | 0.179643 | 303 | 3638.65 |\n", - "| 55 | 0.195714 | 303 | 3574 |\n", - "| 56 | 0.211786 | 303 | 3507.86 |\n", - "| 57 | 0.227857 | 303 | 3440.29 |\n", - "| 58 | 0.243929 | 303 | 3371.39 |\n", - "| 59 | 0.26 | 303 | 3301.23 |\n", - "| 60 | 0.035 | 313 | 7186.58 |\n", - "| 61 | 0.0510714 | 313 | 7098.66 |\n", - "| 62 | 0.0671429 | 313 | 7008.31 |\n", - "| 63 | 0.0832143 | 313 | 6915.33 |\n", - "| 64 | 0.0992857 | 313 | 6819.61 |\n", - "| 65 | 0.115357 | 313 | 6721.11 |\n", - "| 66 | 0.131429 | 313 | 6619.85 |\n", - "| 67 | 0.1475 | 313 | 6515.86 |\n", - "| 68 | 0.163571 | 313 | 6409.23 |\n", - "| 69 | 0.179643 | 313 | 6300.06 |\n", - "| 70 | 0.195714 | 313 | 6188.5 |\n", - "| 71 | 0.211786 | 313 | 6074.67 |\n", - "| 72 | 0.227857 | 313 | 5958.74 |\n", - "| 73 | 0.243929 | 313 | 5840.87 |\n", - "| 74 | 0.26 | 313 | 5721.25 |\n", - "| 75 | 0.035 | 323 | 11988.2 |\n", - "| 76 | 0.0510714 | 323 | 11841 |\n", - "| 77 | 0.0671429 | 323 | 11689.7 |\n", - "| 78 | 0.0832143 | 323 | 11534 |\n", - "| 79 | 0.0992857 | 323 | 11373.8 |\n", - "| 80 | 0.115357 | 323 | 11209 |\n", - "| 81 | 0.131429 | 323 | 11039.8 |\n", - "| 82 | 0.1475 | 323 | 10866.3 |\n", - "| 83 | 0.163571 | 323 | 10688.8 |\n", - "| 84 | 0.179643 | 323 | 10507.3 |\n", - "| 85 | 0.195714 | 323 | 10322.3 |\n", - "| 86 | 0.211786 | 323 | 10134.1 |\n", - "| 87 | 0.227857 | 323 | 9942.78 |\n", - "| 88 | 0.243929 | 323 | 9748.84 |\n", - "| 89 | 0.26 | 323 | 9552.54 |\n", - "| 90 | 0.035 | 333 | 19321.1 |\n", - "| 91 | 0.0510714 | 333 | 19083.7 |\n", - "| 92 | 0.0671429 | 333 | 18839.5 |\n", - "| 93 | 0.0832143 | 333 | 18588.2 |\n", - "| 94 | 0.0992857 | 333 | 18329.7 |\n", - "| 95 | 0.115357 | 333 | 18064.1 |\n", - "| 96 | 0.131429 | 333 | 17791.6 |\n", - "| 97 | 0.1475 | 333 | 17512.6 |\n", - "| 98 | 0.163571 | 333 | 17227.5 |\n", - "| 99 | 0.179643 | 333 | 16936.8 |\n", - "| 100 | 0.195714 | 333 | 16640.9 |\n", - "| 101 | 0.211786 | 333 | 16340.3 |\n", - "| 102 | 0.227857 | 333 | 16035.7 |\n", - "| 103 | 0.243929 | 333 | 15727.6 |\n", - "| 104 | 0.26 | 333 | 15416.4 |\n", - "| 105 | 0.035 | 343 | 30176.7 |\n", - "| 106 | 0.0510714 | 343 | 29806.1 |\n", - "| 107 | 0.0671429 | 343 | 29424.9 |\n", - "| 108 | 0.0832143 | 343 | 29032.6 |\n", - "| 109 | 0.0992857 | 343 | 28629.3 |\n", - "| 110 | 0.115357 | 343 | 28215.2 |\n", - "| 111 | 0.131429 | 343 | 27790.9 |\n", - "| 112 | 0.1475 | 343 | 27356.9 |\n", - "| 113 | 0.163571 | 343 | 26914.1 |\n", - "| 114 | 0.179643 | 343 | 26463.2 |\n", - "| 115 | 0.195714 | 343 | 26005.1 |\n", - "| 116 | 0.211786 | 343 | 25540.7 |\n", - "| 117 | 0.227857 | 343 | 25070.9 |\n", - "| 118 | 0.243929 | 343 | 24596.6 |\n", - "| 119 | 0.26 | 343 | 24118.8 |\n", - "| 120 | 0.035 | 353 | 45796.5 |\n", - "| 121 | 0.0510714 | 353 | 45235.3 |\n", - "| 122 | 0.0671429 | 353 | 44657.8 |\n", - "| 123 | 0.0832143 | 353 | 44063.8 |\n", - "| 124 | 0.0992857 | 353 | 43453.5 |\n", - "| 125 | 0.115357 | 353 | 42827.4 |\n", - "| 126 | 0.131429 | 353 | 42186.3 |\n", - "| 127 | 0.1475 | 353 | 41531.5 |\n", - "| 128 | 0.163571 | 353 | 40864 |\n", - "| 129 | 0.179643 | 353 | 40185.4 |\n", - "| 130 | 0.195714 | 353 | 39497 |\n", - "| 131 | 0.211786 | 353 | 38800.2 |\n", - "| 132 | 0.227857 | 353 | 38096.5 |\n", - "| 133 | 0.243929 | 353 | 37387.5 |\n", - "| 134 | 0.26 | 353 | 36674.6 |\n", - "| 135 | 0.035 | 363 | 67693.2 |\n", - "| 136 | 0.0510714 | 363 | 66866.2 |\n", - "| 137 | 0.0671429 | 363 | 66015.6 |\n", - "| 138 | 0.0832143 | 363 | 65140.9 |\n", - "| 139 | 0.0992857 | 363 | 64242.6 |\n", - "| 140 | 0.115357 | 363 | 63321.8 |\n", - "| 141 | 0.131429 | 363 | 62379.9 |\n", - "| 142 | 0.1475 | 363 | 61418.7 |\n", - "| 143 | 0.163571 | 363 | 60440.2 |\n", - "| 144 | 0.179643 | 363 | 59446.4 |\n", - "| 145 | 0.195714 | 363 | 58439.7 |\n", - "| 146 | 0.211786 | 363 | 57422.3 |\n", - "| 147 | 0.227857 | 363 | 56396.5 |\n", - "| 148 | 0.243929 | 363 | 55364.5 |\n", - "| 149 | 0.26 | 363 | 54328.5 |\n", - "| 150 | 0.035 | 373 | 97662.5 |\n", - "| 151 | 0.0510714 | 373 | 96474.4 |\n", - "| 152 | 0.0671429 | 373 | 95252.8 |\n", - "| 153 | 0.0832143 | 373 | 93997.3 |\n", - "| 154 | 0.0992857 | 373 | 92708.8 |\n", - "| 155 | 0.115357 | 373 | 91388.9 |\n", - "| 156 | 0.131429 | 373 | 90039.9 |\n", - "| 157 | 0.1475 | 373 | 88664.5 |\n", - "| 158 | 0.163571 | 373 | 87265.8 |\n", - "| 159 | 0.179643 | 373 | 85846.9 |\n", - "| 160 | 0.195714 | 373 | 84411.3 |\n", - "| 161 | 0.211786 | 373 | 82962.3 |\n", - "| 162 | 0.227857 | 373 | 81503.4 |\n", - "| 163 | 0.243929 | 373 | 80037.8 |\n", - "| 164 | 0.26 | 373 | 78569 |\n", - "| 165 | 0.035 | 383 | 137816 |\n", - "| 166 | 0.0510714 | 383 | 136147 |\n", - "| 167 | 0.0671429 | 383 | 134431 |\n", - "| 168 | 0.0832143 | 383 | 132670 |\n", - "| 169 | 0.0992857 | 383 | 130863 |\n", - "| 170 | 0.115357 | 383 | 129013 |\n", - "| 171 | 0.131429 | 383 | 127124 |\n", - "| 172 | 0.1475 | 383 | 125200 |\n", - "| 173 | 0.163571 | 383 | 123245 |\n", - "| 174 | 0.179643 | 383 | 121265 |\n", - "| 175 | 0.195714 | 383 | 119263 |\n", - "| 176 | 0.211786 | 383 | 117245 |\n", - "| 177 | 0.227857 | 383 | 115215 |\n", - "| 178 | 0.243929 | 383 | 113179 |\n", - "| 179 | 0.26 | 383 | 111142 |\n", - "| 180 | 0.035 | 393 | 190518 |\n", - "| 181 | 0.0510714 | 393 | 188224 |\n", - "| 182 | 0.0671429 | 393 | 185868 |\n", - "| 183 | 0.0832143 | 393 | 183450 |\n", - "| 184 | 0.0992857 | 393 | 180972 |\n", - "| 185 | 0.115357 | 393 | 178437 |\n", - "| 186 | 0.131429 | 393 | 175850 |\n", - "| 187 | 0.1475 | 393 | 173217 |\n", - "| 188 | 0.163571 | 393 | 170545 |\n", - "| 189 | 0.179643 | 393 | 167840 |\n", - "| 190 | 0.195714 | 393 | 165109 |\n", - "| 191 | 0.211786 | 393 | 162359 |\n", - "| 192 | 0.227857 | 393 | 159596 |\n", - "| 193 | 0.243929 | 393 | 156828 |\n", - "| 194 | 0.26 | 393 | 154062 |\n", - "| 195 | 0.035 | 403 | 258402 |\n", - "| 196 | 0.0510714 | 403 | 255311 |\n", - "| 197 | 0.0671429 | 403 | 252140 |\n", - "| 198 | 0.0832143 | 403 | 248887 |\n", - "| 199 | 0.0992857 | 403 | 245556 |\n", - "| 200 | 0.115357 | 403 | 242151 |\n", - "| 201 | 0.131429 | 403 | 238679 |\n", - "| 202 | 0.1475 | 403 | 235149 |\n", - "| 203 | 0.163571 | 403 | 231569 |\n", - "| 204 | 0.179643 | 403 | 227947 |\n", - "| 205 | 0.195714 | 403 | 224295 |\n", - "| 206 | 0.211786 | 403 | 220620 |\n", - "| 207 | 0.227857 | 403 | 216933 |\n", - "| 208 | 0.243929 | 403 | 213243 |\n", - "| 209 | 0.26 | 403 | 209560 |\n", - "| 210 | 0.035 | 413 | 344336 |\n", - "| 211 | 0.0510714 | 413 | 340248 |\n", - "| 212 | 0.0671429 | 413 | 336057 |\n", - "| 213 | 0.0832143 | 413 | 331763 |\n", - "| 214 | 0.0992857 | 413 | 327368 |\n", - "| 215 | 0.115357 | 413 | 322880 |\n", - "| 216 | 0.131429 | 413 | 318307 |\n", - "| 217 | 0.1475 | 413 | 313661 |\n", - "| 218 | 0.163571 | 413 | 308952 |\n", - "| 219 | 0.179643 | 413 | 304194 |\n", - "| 220 | 0.195714 | 413 | 299399 |\n", - "| 221 | 0.211786 | 413 | 294580 |\n", - "| 222 | 0.227857 | 413 | 289749 |\n", - "| 223 | 0.243929 | 413 | 284919 |\n", - "| 224 | 0.26 | 413 | 280103 |\n", - "| 225 | 0.035 | 423 | 451381 |\n", - "| 226 | 0.0510714 | 423 | 446066 |\n", - "| 227 | 0.0671429 | 423 | 440623 |\n", - "| 228 | 0.0832143 | 423 | 435051 |\n", - "| 229 | 0.0992857 | 423 | 429353 |\n", - "| 230 | 0.115357 | 423 | 423539 |\n", - "| 231 | 0.131429 | 423 | 417621 |\n", - "| 232 | 0.1475 | 423 | 411611 |\n", - "| 233 | 0.163571 | 423 | 405526 |\n", - "| 234 | 0.179643 | 423 | 399382 |\n", - "| 235 | 0.195714 | 423 | 393195 |\n", - "| 236 | 0.211786 | 423 | 386982 |\n", - "| 237 | 0.227857 | 423 | 380760 |\n", - "| 238 | 0.243929 | 423 | 374546 |\n", - "| 239 | 0.26 | 423 | 368356 |\n" - ] - } - ], + "outputs": [], "source": [ "data_formatted = get_formatted_data(data) \n", - "print(data_formatted.to_markdown())" + "display(data_formatted)" ] }, { @@ -837,7 +163,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -908,7 +234,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -936,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -973,21 +299,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: DEPRECATED: You're using the deprecated parmest interface\n", - "(model_function, data, theta_names). This interface will be removed in a\n", - "future release, please update to the new parmest interface using experiment\n", - "lists. (deprecated in 6.7.2) (called from\n", - "C:\\Users\\wcy78\\anaconda3\\envs\\watertap-dev\\Lib\\functools.py:946)\n" - ] - } - ], + "outputs": [], "source": [ "# create an instance of the parmest estimator\n", "pest = parmest.Estimator(model_function, data_formatted, theta_names, objective_function, tee=False)" @@ -1006,43 +320,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "theta:\n", - " a0 8.091276e+06\n", - "a1 -4.525385e+06\n", - "a2 4.636260e+06\n", - "a3 -1.523677e+07\n", - "a4 3.185056e+07\n", - "b0 -1.097568e+05\n", - "b1 6.237744e+04\n", - "b2 -4.915012e+04\n", - "b3 1.780460e+05\n", - "b4 -4.034074e+05\n", - "c0 5.616476e+02\n", - "c1 -3.243432e+02\n", - "c2 1.812149e+02\n", - "c3 -7.674118e+02\n", - "c4 1.919637e+03\n", - "d0 -1.286400e+00\n", - "d1 7.547497e-01\n", - "d2 -2.559027e-01\n", - "d3 1.440646e+00\n", - "d4 -4.074533e+00\n", - "e0 1.114049e-03\n", - "e1 -6.639096e-04\n", - "e2 8.723880e-05\n", - "e3 -9.890969e-04\n", - "e4 3.262400e-03\n", - "dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "# solve the parameter estimation problem\n", "obj, theta = pest.theta_est()\n", @@ -1062,20 +342,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# define a function for the model with estimated thetas\n", "def est(x, T):\n", @@ -1104,9 +373,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "watertap-dev", "language": "python", - "name": "python3" + "name": "watertap-dev" }, "language_info": { "codemirror_mode": { @@ -1118,9 +387,10 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.11" - } + "version": "3.8.17" + }, + "orig_nbformat": 4 }, "nbformat": 4, - "nbformat_minor": 4 -} + "nbformat_minor": 2 +} \ No newline at end of file From 2187a5e75168594f3f097baea531d2c68c51114a Mon Sep 17 00:00:00 2001 From: Chenyu Date: Sun, 14 Dec 2025 11:18:16 -0500 Subject: [PATCH 11/11] test data reconciliation --- .../parmest_new_API_example.ipynb | 232 +++++++++++++++++- 1 file changed, 220 insertions(+), 12 deletions(-) diff --git a/tutorials/parmest_demo/parmest_new_API_example.ipynb b/tutorials/parmest_demo/parmest_new_API_example.ipynb index db1a69729e..98153de8ee 100644 --- a/tutorials/parmest_demo/parmest_new_API_example.ipynb +++ b/tutorials/parmest_demo/parmest_new_API_example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -504,7 +504,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -543,7 +543,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -706,7 +706,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -786,7 +786,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -863,7 +863,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -899,7 +899,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -920,7 +920,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -975,12 +975,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1013,6 +1013,214 @@ "ax.set_zlabel('Vapor Pressure, Pa')\n", "plt.show()" ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "# Data reconciliation\n", + "class DesignExperimentDataRec(DesignExperiment):\n", + "\n", + " def __init__(self, data, data_std, experiment_number):\n", + " super().__init__(data, experiment_number)\n", + " self.data_std = data_std\n", + "\n", + " def create_model(self):\n", + " self.model = m = model_function()\n", + " m.x.fixed = False\n", + " m.T.fixed = False\n", + " return m\n", + "\n", + " def label_model(self):\n", + " m = self.model\n", + "\n", + " # experiment outputs\n", + " m.experiment_outputs = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", + " m.experiment_outputs.update([(m.y, self.data_i['PropData'])])\n", + "\n", + " # experiment standard deviations\n", + " m.experiment_outputs_std = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", + " m.experiment_outputs_std.update([(m.y, self.data_i['PropData'])])\n", + "\n", + " # no unknowns (theta names)\n", + " m.unknown_parameters = pyo.Suffix(direction=pyo.Suffix.LOCAL)\n", + " \n", + " return m\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CompTempPropData
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240 rows × 3 columns

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" + ], + "text/plain": [ + " Comp Temp PropData\n", + "0 0.035000 278.0 866.078781\n", + "1 0.051071 278.0 855.860864\n", + "2 0.067143 278.0 845.433914\n", + "3 0.083214 278.0 834.740479\n", + "4 0.099286 278.0 823.734861\n", + ".. ... ... ...\n", + "235 0.195714 423.0 393194.608930\n", + "236 0.211786 423.0 386982.037389\n", + "237 0.227857 423.0 380760.491594\n", + "238 0.243929 423.0 374546.383155\n", + "239 0.260000 423.0 368355.661236\n", + "\n", + "[240 rows x 3 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "ca 5.001797e+02\n", + "cb 2.783092e+02\n", + "cc 4.254196e+02\n", + "cd 4.119319e+02\n", + "sv 2.226018e-16\n", + "caf 0.000000e+00\n", + "dtype: float64" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240\n" + ] + } + ], + "source": [ + "data_formatted_std = data.std()\n", + "display(data_formatted)\n", + "display(data_formatted_std)\n", + "\n", + "# Create an experiment list\n", + "exp_list = []\n", + "print(data_formatted.shape[0])\n", + "for i in range(data_formatted.shape[0]):\n", + " exp_list.append(DesignExperimentDataRec(data_formatted, data_formatted_std, i))\n", + " \n", + "# Define sum of squared error objective function for data rec\n", + "def SSE_with_std(model):\n", + " expr = sum(\n", + " ((y - y_hat) / model.experiment_outputs_std[y]) ** 2\n", + " for y, y_hat in model.experiment_outputs.items()\n", + " )\n", + " return expr\n", + "\n", + "### Data reconciliation\n", + "pest = parmest.Estimator(exp_list, obj_function=SSE_with_std)\n", + "obj, theta, data_rec = pest.theta_est(return_values=[\"ca\", \"cb\", \"cc\", \"cd\", \"caf\"])\n", + "print(obj)\n", + "print(theta)" + ] } ], "metadata": { @@ -1031,7 +1239,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.11" + "version": "3.11.13" } }, "nbformat": 4,