jreadey/DMI_Read.ipynb

## DMI_Read.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import h5pyd as h5py\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = h5py.File(\"/home/jreadey/GE/DMI_5R_Annulus.3D_200M.SINO0000\", \"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DeadtimeCoefficients',\n",
       " 'DetectorPeriodic',\n",
       " 'DetectorSerialNumbers',\n",
       " 'DetectorTemperatures',\n",
       " 'DetectorValidFlags',\n",
       " 'HeaderData',\n",
       " 'SegmentData',\n",
       " 'SorterData']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "detector_group = f[\"/DetectorSerialNumbers/ModuleSerialNumbers\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dmod0',\n",
       " 'dmod1',\n",
       " 'dmod10',\n",
       " 'dmod11',\n",
       " 'dmod12',\n",
       " 'dmod13',\n",
       " 'dmod14',\n",
       " 'dmod15',\n",
       " 'dmod16',\n",
       " 'dmod17',\n",
       " 'dmod18',\n",
       " 'dmod19',\n",
       " 'dmod2',\n",
       " 'dmod20',\n",
       " 'dmod21',\n",
       " 'dmod22',\n",
       " 'dmod23',\n",
       " 'dmod24',\n",
       " 'dmod25',\n",
       " 'dmod26',\n",
       " 'dmod27',\n",
       " 'dmod28',\n",
       " 'dmod29',\n",
       " 'dmod3',\n",
       " 'dmod30',\n",
       " 'dmod31',\n",
       " 'dmod32',\n",
       " 'dmod33',\n",
       " 'dmod4',\n",
       " 'dmod5',\n",
       " 'dmod6',\n",
       " 'dmod7',\n",
       " 'dmod8',\n",
       " 'dmod9']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(detector_group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "dmod3 = detector_group[\"dmod3\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1,)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dmod3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'ALB626'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dmod3[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sinogram = f[\"/SegmentData/Prompts/Static/Sinogram\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(272, 1981, 415)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinogram.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('uint16')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinogram.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 1981, 415)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinogram.chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'gzip'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinogram.compression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinogram[0,0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/opt/conda/bin/h5ls\n"
     ]
    }
   ],
   "source": [
    "! which h5ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8 ms, sys: 4 ms, total: 12 ms\n",
      "Wall time: 35.5 ms\n"
     ]
    }
   ],
   "source": [
    "%time arr = sinogram[0,:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f68be5b6f60>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize=(4,4),dpi=200)\n",
    "plt.imshow(arr, origin=\"lower\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "singles = f[\"/DetectorPeriodic/Singles\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 45, 544)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "singles.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr = singles[0,:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>534</th>\n",
       "      <th>535</th>\n",
       "      <th>536</th>\n",
       "      <th>537</th>\n",
       "      <th>538</th>\n",
       "      <th>539</th>\n",
       "      <th>540</th>\n",
       "      <th>541</th>\n",
       "      <th>542</th>\n",
       "      <th>543</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39209</td>\n",
       "      <td>39516</td>\n",
       "      <td>41401</td>\n",
       "      <td>39338</td>\n",
       "      <td>38374</td>\n",
       "      <td>39162</td>\n",
       "      <td>39113</td>\n",
       "      <td>39214</td>\n",
       "      <td>38781</td>\n",
       "      <td>39989</td>\n",
       "      <td>...</td>\n",
       "      <td>37907</td>\n",
       "      <td>39809</td>\n",
       "      <td>38777</td>\n",
       "      <td>39183</td>\n",
       "      <td>38968</td>\n",
       "      <td>39261</td>\n",
       "      <td>39275</td>\n",
       "      <td>37884</td>\n",
       "      <td>39888</td>\n",
       "      <td>41128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>39705</td>\n",
       "      <td>41748</td>\n",
       "      <td>42780</td>\n",
       "      <td>41743</td>\n",
       "      <td>41072</td>\n",
       "      <td>41786</td>\n",
       "      <td>42334</td>\n",
       "      <td>42612</td>\n",
       "      <td>40158</td>\n",
       "      <td>41963</td>\n",
       "      <td>...</td>\n",
       "      <td>41577</td>\n",
       "      <td>41498</td>\n",
       "      <td>40467</td>\n",
       "      <td>41333</td>\n",
       "      <td>41910</td>\n",
       "      <td>42194</td>\n",
       "      <td>40046</td>\n",
       "      <td>42418</td>\n",
       "      <td>41955</td>\n",
       "      <td>42239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41088</td>\n",
       "      <td>41165</td>\n",
       "      <td>42679</td>\n",
       "      <td>44144</td>\n",
       "      <td>41301</td>\n",
       "      <td>41534</td>\n",
       "      <td>42832</td>\n",
       "      <td>42801</td>\n",
       "      <td>41099</td>\n",
       "      <td>43515</td>\n",
       "      <td>...</td>\n",
       "      <td>42431</td>\n",
       "      <td>44600</td>\n",
       "      <td>41522</td>\n",
       "      <td>43043</td>\n",
       "      <td>41999</td>\n",
       "      <td>43353</td>\n",
       "      <td>41422</td>\n",
       "      <td>42313</td>\n",
       "      <td>42984</td>\n",
       "      <td>43791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42589</td>\n",
       "      <td>42435</td>\n",
       "      <td>42230</td>\n",
       "      <td>42499</td>\n",
       "      <td>41093</td>\n",
       "      <td>41469</td>\n",
       "      <td>42084</td>\n",
       "      <td>42584</td>\n",
       "      <td>42181</td>\n",
       "      <td>42319</td>\n",
       "      <td>...</td>\n",
       "      <td>42130</td>\n",
       "      <td>43561</td>\n",
       "      <td>42492</td>\n",
       "      <td>42174</td>\n",
       "      <td>42288</td>\n",
       "      <td>41163</td>\n",
       "      <td>42366</td>\n",
       "      <td>42144</td>\n",
       "      <td>41988</td>\n",
       "      <td>42167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40682</td>\n",
       "      <td>41865</td>\n",
       "      <td>42713</td>\n",
       "      <td>44183</td>\n",
       "      <td>39734</td>\n",
       "      <td>43182</td>\n",
       "      <td>40816</td>\n",
       "      <td>42885</td>\n",
       "      <td>41195</td>\n",
       "      <td>41915</td>\n",
       "      <td>...</td>\n",
       "      <td>43563</td>\n",
       "      <td>42559</td>\n",
       "      <td>39488</td>\n",
       "      <td>42677</td>\n",
       "      <td>44329</td>\n",
       "      <td>42471</td>\n",
       "      <td>39928</td>\n",
       "      <td>43198</td>\n",
       "      <td>43222</td>\n",
       "      <td>43540</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 544 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0      1      2      3      4      5      6      7      8      9    \\\n",
       "0  39209  39516  41401  39338  38374  39162  39113  39214  38781  39989   \n",
       "1  39705  41748  42780  41743  41072  41786  42334  42612  40158  41963   \n",
       "2  41088  41165  42679  44144  41301  41534  42832  42801  41099  43515   \n",
       "3  42589  42435  42230  42499  41093  41469  42084  42584  42181  42319   \n",
       "4  40682  41865  42713  44183  39734  43182  40816  42885  41195  41915   \n",
       "\n",
       "   ...      534    535    536    537    538    539    540    541    542    543  \n",
       "0  ...    37907  39809  38777  39183  38968  39261  39275  37884  39888  41128  \n",
       "1  ...    41577  41498  40467  41333  41910  42194  40046  42418  41955  42239  \n",
       "2  ...    42431  44600  41522  43043  41999  43353  41422  42313  42984  43791  \n",
       "3  ...    42130  43561  42492  42174  42288  41163  42366  42144  41988  42167  \n",
       "4  ...    43563  42559  39488  42677  44329  42471  39928  43198  43222  43540  \n",
       "\n",
       "[5 rows x 544 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(arr)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f68b284fe10>]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = range(arr.shape[1])\n",
    "plt.plot(x, arr[0,:])"
   ]
  },
  {
   "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}