extend fmri types + ctbi ga 2017 feedback (floating tr + non normaliz…

…ed type)

Signed-off-by: Stephen L. <[email protected]>

center-tbi-statistics-from-full-rest-dump.ipynb

@@ -496,7 +496,7 @@
    "outputs": [],
    "source": [
     "# Extract only resting state data\n",
-    "rsfMRI_filter = ['rs fMRI FE EPI', 'rs fMRI FE_EPI', 'rs fMRI FE_EPI SENSE', 'rs-fMRI', 'rs_fMRI', 'rsfMRI', 'rsfMRI 60CM']\n",
+    "rsfMRI_filter = ['rs fMRI FE EPI', 'rs fMRI FE_EPI', 'rs fMRI FE_EPI SENSE', 'rs-fMRI', 'rs_fMRI', 'rsfMRI', 'rsfMRI 60CM', 'Resting State fMRI', ' rsfMRI', 'RESTING STATE']\n",
     "df_rest = df.loc[df['@type'].isin(rsfMRI_filter), :]\n",
     "#df_rest = df.loc[df['@type'] == 'rs_fMRI', :]  # deprecated, only for rs_fmri, does not include all variants of the name in db\n",
     "df_rest[['@UID', 'project.id', 'qa.protocol_check_global']]"
@@ -1681,10 +1681,50 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "# Extract scans non normalized type\n",
+    "df_rest_notnormtype = df_rest[df_rest['@type'] != 'rs_fMRI']\n",
+    "save_df_as_csv(df_rest_notnormtype.fillna(''), 'xnat_data_extract_rest-notnormtype.csv', index=False, encoding='utf-8')\n",
+    "print(len(df_rest_notnormtype))\n",
+    "df_rest_notnormtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Extract only scans with an exact TR (with a floating value)\n",
+    "import numpy as np\n",
+    "df_rest_floattr = df_rest[df_rest['xnat:parameters.xnat:tr'].astype('float').apply(lambda x: not x.is_integer() and not pd.isnull(x))]\n",
+    "print('List of scanners with floating TR values:')\n",
+    "print(df_rest_floattr['experiment.xnat:scanner'].value_counts())\n",
+    "print('\\nList of unique floating TR values:')\n",
+    "print(df_rest_floattr['xnat:parameters.xnat:tr'].unique())\n",
+    "print('\\nList of subjects ids with floating TR value:')\n",
+    "print(df_rest_floattr['subject.@ID'].unique())\n",
+    "print('\\nList of experiments with floating TR values:')\n",
+    "print(df_rest_floattr.ix[:, ('experiment.id', 'subject.id', 'xnat:parameters.xnat:tr')])\n",
+    "save_df_as_csv(df_rest_floattr.ix[:, ('experiment.id', 'subject.id', 'xnat:parameters.xnat:tr')].fillna(''), 'xnat_data_extract_rest-floattr.csv', index=False, encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Print all scanners unique names with scans counts (to compare with the scanners with floating TR)\n",
+    "df_rest['experiment.xnat:scanner'].value_counts()"
+   ]
   }
  ],
  "metadata": {