view controllers in MATLAB,Python,R, etc.

misc/.ipynb_checkpoints/View_Controller-checkpoint.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e320638d-6141-4bca-802f-b5403e563309",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Open the HDF5 file\n",
+    "with h5py.File('controller.h5', 'r') as f:\n",
+    "    # Assuming you have a dataset named 'dataset' in the HDF5 file\n",
+    "    if 'dataset' in f:\n",
+    "        # Access the dataset\n",
+    "        dataset = f['dataset']\n",
+    "        \n",
+    "        # Convert the dataset to a pandas DataFrame and transpose it\n",
+    "        df = pd.DataFrame(dataset[:]).T\n",
+    "        \n",
+    "        # Display the DataFrame\n",
+    "        display(df)\n",
+    "    else:\n",
+    "        print(\"No 'dataset' found in the HDF5 file.\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

misc/View_Controller.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e320638d-6141-4bca-802f-b5403e563309",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Open the HDF5 file\n",
+    "with h5py.File('controller.h5', 'r') as f:\n",
+    "    # Assuming you have a dataset named 'dataset' in the HDF5 file\n",
+    "    if 'dataset' in f:\n",
+    "        # Access the dataset\n",
+    "        dataset = f['dataset']\n",
+    "        \n",
+    "        # Convert the dataset to a pandas DataFrame and transpose it\n",
+    "        df = pd.DataFrame(dataset[:]).T\n",
+    "        \n",
+    "        # Display the DataFrame\n",
+    "        display(df)\n",
+    "    else:\n",
+    "        print(\"No 'dataset' found in the HDF5 file.\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

misc/plots.m

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+clear
+close all
+clc
+
+%% read in files
+ss = h5read('ss.h5','/dataset');
+target = h5read('ts.h5','/dataset');
+is = h5read('is.h5','/dataset');
+controller = h5read('controller.h5','/dataset');
+
+%% figure 1 - state space with target/avoid regions
+boxSize = 1; % Eta_x
+
+%plot the state space with target set and avoid set
+figure
+plot(ss(:,1),ss(:,2),'.',"Color", "blue")
+hold on
+x = target(:,1);
+y = target(:,2);
+% Plotting boxes around each point
+for i = 1:length(x)
+    rectangle('Position', [x(i)-boxSize/2, y(i)-boxSize/2, boxSize, boxSize], 'FaceColor', 'g');
+end
+
+hold on
+x = avoid(:,1);
+y = avoid(:,2);
+% Plotting boxes around each point
+for i = 1:length(x)
+    rectangle('Position', [x(i)-boxSize/2, y(i)-boxSize/2, boxSize, boxSize], 'FaceColor', 'r');
+end
+
+%% Figure 2 - Plot lower bound satisfaction probabilities
+C = [controller(:,1:2), controller(:,5)];
+X = C(:,1) ; Y = C(:,2) ; Z = C(:,3);
+dt = delaunayTriangulation(X,Y);
+Tri = dt.ConnectivityList;
+
+figure
+trisurf(Tri, X, Y, Z, 'FaceColor', 'interp'); 
+colormap('cool');
+colorbar;
+hold on;
+
+% Plotting boxes around each point (target)
+for i = 1:length(target)
+    x = target(i, 1);
+    y = target(i, 2);
+    z = 1;
+    patch([x-boxSize x+boxSize x+boxSize x-boxSize],[y-boxSize y-boxSize y+boxSize y+boxSize],[z z z z],'g');
+end
+
+% Plotting boxes around each point (avoid)
+for i = 1:length(avoid)
+    x = avoid(i, 1);
+    y = avoid(i, 2);
+    z = 1;
+    patch([x-boxSize x+boxSize x+boxSize x-boxSize],[y-boxSize y-boxSize y+boxSize y+boxSize],[z z z z],'r');
+end
+
+%% Figure 3 - Plot uppoer bound satisfaction probabilities
+C = [controller(:,1:2), controller(:,6)];
+X = C(:,1) ; Y = C(:,2) ; Z = C(:,3);
+dt = delaunayTriangulation(X,Y);
+Tri = dt.ConnectivityList;
+
+figure
+trisurf(Tri, X, Y, Z, 'FaceColor', 'interp'); 
+colormap('cool');
+colorbar;
+hold on;
+
+% Plotting boxes around each point (target)
+for i = 1:length(target)
+    x = target(i, 1);
+    y = target(i, 2);
+    z = 1;
+    patch([x-boxSize x+boxSize x+boxSize x-boxSize],[y-boxSize y-boxSize y+boxSize y+boxSize],[z z z z],'g');
+end
+
+% Plotting boxes around each point (avoid)
+for i = 1:length(avoid)
+    x = avoid(i, 1);
+    y = avoid(i, 2);
+    z = 1;
+    patch([x-boxSize x+boxSize x+boxSize x-boxSize],[y-boxSize y-boxSize y+boxSize y+boxSize],[z z z z],'r');
+end
+%% Figure 4 - Run Trace of Controller
+init_x = [-6, -6];
+init_u = [0, 0];
+trace = [init_x, init_u];
+while ~((trace(end, 1) >= 5 && trace(end, 1) <= 8) && (trace(end, 2) >= 5 && trace(end, 2) <= 8))
+%for t= 1:5
+    x = trace(end, 1:2);
+    u = getInput(controller, x);
+    trace = [trace; dynamics(x, u), u];
+end
+
+%plot the state space with target set and avoid set
+figure
+plot(ss(:,1),ss(:,2),'.',"Color", "blue")
+hold on
+x = target(:,1);
+y = target(:,2);
+% Plotting boxes around each point (target)
+for i = 1:length(x)
+    rectangle('Position', [x(i)-boxSize/2, y(i)-boxSize/2, boxSize, boxSize], 'FaceColor', 'g');
+end
+
+hold on
+x = avoid(:,1);
+y = avoid(:,2);
+% Plotting boxes around each point (avoid)
+for i = 1:length(x)
+    rectangle('Position', [x(i)-boxSize/2, y(i)-boxSize/2, boxSize, boxSize], 'FaceColor', 'r');
+end
+
+hold on
+% Plot arrows connecting each row
+for i = 1:size(trace, 1)-1
+    x = trace(i, 1);
+    y = trace(i, 2);
+    dx = trace(i+1, 1) - x;
+    dy = trace(i+1, 2) - y;
+    quiver(x, y, dx, dy, 0,'LineWidth', 4);
+end
+
+%% functions
+
+function u = getInput(controller,x)
+% Calculate the Euclidean distances between each row of the array and the given value
+distances = sqrt(sum((controller(:,1:2) - x).^2, 2));
+% Find the index of the row with the minimum distance
+[~, closestRow] = min(distances);
+u = controller(closestRow, 3:4);
+end
+
+function xx = dynamics(x,u)
+sigma = [1.3333,1.3333];
+xx(1) = x(1) + 2 * u(1) * cos(u(2)) + normrnd(0,sigma(1));
+xx(2) = x(2) + 2 * u(1) * sin(u(2)) + normrnd(0,sigma(2));
+end

misc/view_controller.R

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+# Install and load the rhdf5 package if you haven't already
+if (!require("BiocManager", quietly = TRUE))
+  install.packages("BiocManager")
+
+BiocManager::install("rhdf5")
+
+library(rhdf5)
+
+#set working directory to the location of the file
+setwd("../HDF5_file_location/../")
+
+#check you are in the location you think you are
+getwd()
+
+# Open the HDF5 file
+h5file <- H5Fopen("controller.h5")
+
+# List the datasets in the HDF5 file
+h5ls(h5file)
+
+# Read a dataset from the HDF5 file (replace "dataset_name" with the actual dataset name)
+data <- h5read(h5file, "dataset")
+
+#print dataset
+print(data)
+
+# Close the HDF5 file
+H5Fclose(h5file)