230306-symmetrize-stack

230306-symmetrize-stack.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.,  1.,  0.],\n",
       "       [nan,  2.,  1.],\n",
       "       [nan, nan,  2.]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat = np.ones(shape=(3,3))\n",
    "mat[np.tril_indices_from(mat)] = np.nan\n",
    "mat[np.diag_indices_from(mat)] = 2\n",
    "mat[0,2] = 0\n",
    "mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2., nan,  0.],\n",
       "       [nan, nan, nan],\n",
       "       [nan, nan,  2.]])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mat2 = np.copy(mat)\n",
    "mat2[1,:] = np.nan\n",
    "mat2[:,1] = np.nan\n",
    "display(mat2)\n",
    "\n",
    "stack = np.dstack([mat,mat2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[4., 0., 0.],\n",
       "       [0., 0., 0.],\n",
       "       [0., 0., 4.]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stack_symm_curr = np.nansum([stack, np.transpose(stack, axes=(1, 0, 2))], axis=0)\n",
    "stack_symm_curr[:,:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2., nan,  0.],\n",
       "       [nan, nan, nan],\n",
       "       [ 0., nan,  2.]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stack_symm_new = np.fmax(stack, np.transpose(stack, axes=(1, 0, 2)))\n",
    "stack_symm_new[:,:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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