README.md

Funz plugin: Jupyter

This plugin is dedicated to launch Jupyter calculations from Funz. It supports the following syntax and features:

• Input

  • file type supported: '*.ipynb', any other format for resources
  • parameter syntax:
    • variable syntax: ?[...]
    • formula syntax: ${...}
    • comment char: #
  • example input file:

  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [{
      "def branin(x1,x2):\n",
      "    x1 = x1*15-5\n",
      "    x2 = x2*15\n",
      "\n",
      "    return (x2 - 5/(4*m.pi**2)*(x1**2) + 5/m.pi*x1 -6 )**2 + 10*(1-1/(8*m.pi))*m.cos(x1) +10"
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "then, eval branin:"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     "metadata": {},
     "outputs": [],
     "source": [
      "print('z={0}'.format( branin( ?[x1~[1,2]] , ${?[x2] +1.23} ) ) )"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     "metadata": {},
     "outputs": [],
     "source": []
    }
   ],
   "metadata": {
    "kernelspec": {
     "display_name": "Python 3",
     "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": "3.7.6"
    }
   },
   "nbformat": 4,
   "nbformat_minor": 4
  }
  

  • will identify input:
    • x1, expected to vary inside [1,2]
    • x2, expected to vary inside [0,1] (by default)
  • replace ${?[x2] + 1.23} expression by its evaluation

• Output

  • file type supported: '*.ipynb'
  • read any named value printed with =, like print("z={0}".format(1.234))
  • example output file:

  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Branin in jupyter"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": 1,
     "metadata": {
      "execution": {
       "iopub.execute_input": "2022-01-07T13:37:11.375854Z",
       "iopub.status.busy": "2022-01-07T13:37:11.374259Z",
       "iopub.status.idle": "2022-01-07T13:37:11.395234Z",
       "shell.execute_reply": "2022-01-07T13:37:11.392893Z"
      }
     },
     "outputs": [],
     "source": [
      "import math as m\n",
      "def branin(x1,x2):\n",
      "    x1 = x1*15-5\n",
      "    x2 = x2*15\n",
      "\n",
      "    return (x2 - 5/(4*m.pi**2)*(x1**2) + 5/m.pi*x1 -6 )**2 + 10*(1-1/(8*m.pi))*m.cos(x1) +10"
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "then, eval branin:"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": 2,
     "metadata": {
      "execution": {
       "iopub.execute_input": "2022-01-07T13:37:11.405704Z",
       "iopub.status.busy": "2022-01-07T13:37:11.404308Z",
       "iopub.status.idle": "2022-01-07T13:37:11.411921Z",
       "shell.execute_reply": "2022-01-07T13:37:11.413079Z"
      }
     },
     "outputs": [
      {
       "name": "stdout",
       "output_type": "stream",
       "text": [
        "z=3.000715003051446\n"
       ]
      }
     ],
     "source": [
      "print('z={0}'.format( branin( 0.5, 0.132) ) )"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     "metadata": {},
     "outputs": [],
     "source": []
    }
   ],
   "metadata": {
    "kernelspec": {
     "display_name": "Python 3",
     "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": "3.9.7"
    }
   },
   "nbformat": 4,
   "nbformat_minor": 4
  }
  

  • will return output:
    • z=3.000715