Switch Isilon paths to S3

notebooks/compute_single_unit_metrics.ipynb

@@ -27,6 +27,7 @@
     "import npc_lims\n",
     "from npc_sessions import DynamicRoutingSession\n",
     "from dynamic_routing_analysis import spike_utils, data_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "import os\n",
     "import pickle\n",
     "\n",
@@ -67,15 +68,16 @@
    "source": [
     "except_dict={}\n",
     "overwrite_files=False\n",
-    "save_path = r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\"\n",
+    "save_path = dra.SINGLE_UNIT_METRICS_PATH\n",
     "\n",
     "for session_info in ephys_sessions[:]:\n",
     "    \n",
     "    try:\n",
     "        trials=[]\n",
     "        units=[]\n",
     "        ##skip if file already exists\n",
-    "        if overwrite_files==False and os.path.isfile(os.path.join(save_path,session_info.id+'_stim_context_modulation.pkl')):\n",
+    "        \n",
+    "        if overwrite_files==False and (save_path / f\"{session_info.id}_stim_context_modulation.pkl\").exists():\n",
     "            print('session',session_info.id,'already processed; skipping')\n",
     "            continue\n",
     "        lick_save_path=os.path.join(save_path,'lick_modulation')\n",

notebooks/decode_context_linear_shift_w_repeats_analysis.ipynb

@@ -12,6 +12,7 @@
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "from dynamic_routing_analysis import decoding_utils, plot_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "\n",
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -25,7 +26,7 @@
    "outputs": [],
    "source": [
     "#set path to decoding results\n",
-    "loadpath=r\"\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units\"\n",
+    "loadpath=dra.DECODING_ROOTH_PATH / \"new_annotations\" / \"linear_shift_20_units\"\n",
     "files=glob.glob(os.path.join(loadpath,'*_decoding_results*.pkl'))"
    ]
   },
@@ -620,22 +621,27 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#load all decoding results, option to concatenate all sessions\n",
+    "# load all decoding results, option to concatenate all sessions\n",
     "concat_session_results=False\n",
     "save_table=False\n",
     "return_table=False\n",
     "\n",
     "all_decoder_results_path=os.path.join(loadpath,'combined','all_unit_linear_shift_use_more_trials.csv')\n",
     "\n",
     "if save_table:\n",
-    "    savepath=r\"\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units\\combined\"\n",
+    "    savepath = (\n",
+    "        dra.DECODING_ROOTH_PATH\n",
+    "        / \"new_annotations\"\n",
+    "        / \"linear_shift_20_units\"\n",
+    "        / \"combined\"\n",
+    "    )\n",
     "else:\n",
     "    savepath=None\n",
     "\n",
     "if concat_session_results:\n",
     "    all_decoder_results=decoding_utils.concat_decoder_results(files,savepath=savepath,return_table=return_table)\n",
     "else:\n",
-    "    all_decoder_results=pd.read_csv(all_decoder_results_path)\n"
+    "    all_decoder_results=pd.read_csv(all_decoder_results_path)"
    ]
   },
   {

notebooks/decode_context_linear_shift_w_repeats_trialwise_analysis.ipynb

@@ -14,6 +14,7 @@
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "from dynamic_routing_analysis import decoding_utils, plot_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "\n",
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -26,8 +27,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#set path to decoding results\n",
-    "loadpath=r\"\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units\"\n",
+    "# set path to decoding results\n",
+    "loadpath = dra.DECODING_ROOTH_PATH / \"new_annotations\" / \"linear_shift_20_units\"\n",
     "files=glob.glob(os.path.join(loadpath,'*_decoding_results*.pkl'))"
    ]
   },
@@ -37,11 +38,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#load all trialwise decoding results, option to concatenate all sessions\n",
+    "# load all trialwise decoding results, option to concatenate all sessions\n",
     "concat_session_results=False\n",
     "save_tables=False\n",
     "return_table=False\n",
-    "loadpath=r\"\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units\\combined\\no_normalization\"\n",
+    "loadpath = (\n",
+    "    dra.DECODING_ROOTH_PATH\n",
+    "    / \"new_annotations\"\n",
+    "    / \"linear_shift_20_units\"\n",
+    "    / \"combined\" \n",
+    "    / \"no_normalization\"\n",
+    ")\n",
     "if save_tables:\n",
     "    savepath=loadpath\n",
     "else:\n",
@@ -60,7 +67,7 @@
     "    decoder_confidence_dprime_by_block=pd.read_csv(os.path.join(loadpath,'decoder_confidence_dprime_by_block.csv'))\n",
     "    decoder_confidence_by_switch=pd.read_csv(os.path.join(loadpath,'decoder_confidence_by_switch.csv'))\n",
     "    decoder_confidence_versus_trials_since_rewarded_target=pd.read_csv(os.path.join(loadpath,'decoder_confidence_versus_trials_since_rewarded_target.csv'))\n",
-    "    decoder_confidence_before_after_target=pd.read_csv(os.path.join(loadpath,'decoder_confidence_before_after_target.csv'))\n"
+    "    decoder_confidence_before_after_target=pd.read_csv(os.path.join(loadpath,'decoder_confidence_before_after_target.csv'))"
    ]
   },
   {

notebooks/decoding_example_egm.ipynb

@@ -35,6 +35,7 @@
     "import npc_lims\n",
     "from npc_sessions import DynamicRoutingSession\n",
     "from dynamic_routing_analysis import decoding_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "\n",
     "import os\n",
     "\n",
@@ -222,7 +223,7 @@
    ],
    "source": [
     "#2 set savepath and filename\n",
-    "savepath=r'\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units_re_run'\n",
+    "savepath=dra.DECODING_ROOTH_PATH / \"new_annotations\" / \"linear_shift_20_units_re_run\"\n",
     "filename='decoding_results_linear_shift_20_units_re_run.pkl'\n",
     "\n",
     "except_list={}\n",

notebooks/decoding_timebins_egm.ipynb

@@ -11,6 +11,8 @@
     "import npc_lims\n",
     "from npc_sessions import DynamicRoutingSession\n",
     "from dynamic_routing_analysis import decoding_utils\n",
+    "import dynamic_routing_analysis as dra\n",
+    "\n",
     "\n",
     "import os"
    ]
@@ -727,7 +729,7 @@
     "                          if s.is_uploaded and s.is_annotated and \n",
     "                          s.project=='DynamicRouting')\n",
     "\n",
-    "savepath=r'C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\DR decoding results\\by_session\\decode_timebins'\n",
+    "savepath= dra.DECODING_ROOTH_PATH / \"decode_timebins\"\n",
     "filename='decode_timebins.pkl'\n",
     "\n",
     "except_list={}\n",

notebooks/plot_decoder_accuracy_on_CCF.ipynb

@@ -11,6 +11,7 @@
     "import numpy as np\n",
     "import os\n",
     "from pathlib import Path\n",
+    "import dynamic_routing_analysis as dra\n",
     "\n",
     "from allensdk.core.reference_space_cache import ReferenceSpaceCache\n",
     "\n",
@@ -23,24 +24,23 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "output_dir=r\"D:\\CCF\\cache\"\n",
-    "reference_space_key = 'annotation/ccf_2022'\n",
+    "output_dir = dra.ANALYSIS_ROOT_PATH / \"ccf_cache\"\n",
+    "reference_space_key = \"annotation/ccf_2022\"\n",
     "resolution = 10\n",
     "rspc = ReferenceSpaceCache(resolution, reference_space_key, manifest=Path(output_dir) / 'manifest.json')\n",
     "\n",
     "# get structure tree\n",
     "# ID 1 is the adult mouse structure graph\n",
     "tree = rspc.get_structure_tree(structure_graph_id=1) \n",
     "\n",
-    "#get id_acronym map\n",
+    "# get id_acronym map\n",
     "id_acronym_map = tree.get_id_acronym_map()\n",
     "\n",
-    "#make reference space object\n",
+    "# make reference space object\n",
     "rsp = rspc.get_reference_space()\n",
     "\n",
-    "#get annotation volume\n",
-    "annotation, meta = rspc.get_annotation_volume()\n",
-    "\n"
+    "# get annotation volume\n",
+    "annotation, meta = rspc.get_annotation_volume()"
    ]
   },
   {
@@ -238,9 +238,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#load deocder accuracy by CCF area\n",
+    "# load deocder accuracy by CCF area\n",
     "\n",
-    "ccf_coords_by_session_area=pd.read_csv(r\"\\\\allen\\programs\\mindscope\\workgroups\\templeton\\TTOC\\decoding results\\new_annotations\\linear_shift_20_units\\combined\\all_unit_linear_shift_use_more_trials.csv\")\n"
+    "ccf_coords_by_session_area = pd.read_csv(\n",
+    "    dra.DECODING_ROOTH_PATH\n",
+    "    / \"new_annotations\"\n",
+    "    / \"linear_shift_20_units/combined/all_unit_linear_shift_use_more_trials.csv\"\n",
+    ")"
    ]
   },
   {

notebooks/single_unit_metrics_CCF_plot.ipynb

@@ -25,6 +25,7 @@
     "from pathlib import Path\n",
     "from allensdk.core.reference_space_cache import ReferenceSpaceCache\n",
     "from dynamic_routing_analysis import spike_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "\n",
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -40,7 +41,7 @@
     "#load CCF\n",
     "\n",
     "#set this to the directory where you want the CCF to be downloaded\n",
-    "output_dir=r\"D:\\CCF\\cache\"\n",
+    "output_dir=dra.ANALYSIS_ROOT_PATH / \"ccf_cache\"\n",
     "reference_space_key = 'annotation/ccf_2022'\n",
     "resolution = 10\n",
     "rspc = ReferenceSpaceCache(resolution, reference_space_key, manifest=Path(output_dir) / 'manifest.json')\n",
@@ -62,7 +63,7 @@
    "outputs": [],
    "source": [
     "#load single cell metric data\n",
-    "all_data_path=r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\\combined\\all_data_plus_performance.pkl\"\n",
+    "all_data_path=dra.SINGLE_UNIT_METRICS_PATH / \"new_annotations/single unit metrics/combined/all_data_plus_performance.pkl\"\n",
     "all_data=pd.read_pickle(all_data_path)"
    ]
   },
@@ -1119,7 +1120,7 @@
     }
    ],
    "source": [
-    "#plot histogram on successive coronal slices\n",
+    "# plot histogram on successive coronal slices\n",
     "\n",
     "# plot slices\n",
     "dprime_thresh=1.0\n",
@@ -1128,7 +1129,9 @@
     "\n",
     "slice_size=500\n",
     "slice_pos_array=np.arange(2000+slice_size/2,10500,slice_size)\n",
-    "savepath=r\"C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\quick figures\\2024-05-23-single_unit_topography\"\n",
+    "savepath = (\n",
+    "    dra.ANALYSIS_ROOT_PATH / \"quick-figures/2024-05-23-single_unit_topography\"\n",
+    ")\n",
     "\n",
     "# plot_variable='context_roc_auc'\n",
     "# plot_variable='sound1_roc_auc'\n",
@@ -1172,7 +1175,7 @@
     "\n",
     "    # filesavepath=os.path.join(savepath,plot_variable+'_coronal_slice_'+str(int(slice_pos))+'.png')\n",
     "    # plt.savefig(filesavepath,dpi=300)\n",
-    "    # plt.close(fig)\n"
+    "    # plt.close(fig)"
    ]
   },
   {
@@ -1607,7 +1610,7 @@
     }
    ],
    "source": [
-    "#plot multiple unit metrics on one figure\n",
+    "# plot multiple unit metrics on one figure\n",
     "\n",
     "# plot slices\n",
     "dprime_thresh=1.0\n",
@@ -1616,8 +1619,7 @@
     "\n",
     "slice_size=500\n",
     "slice_pos_array=np.arange(2000+slice_size/2,10500,slice_size)\n",
-    "savepath=r\"C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\quick figures\\2024-05-23-single_unit_topography\"\n",
-    "\n",
+    "savepath = dra.ANALYSIS_ROOT_PATH / \"quick-figures/2024-05-23-single_unit_topography\"\n",
     "plot_variables=['context_roc_auc','lick_roc_auc','sound1_roc_auc','vis1_roc_auc']\n",
     "\n",
     "\n",
@@ -1670,7 +1672,7 @@
     "\n",
     "    # filesavepath=os.path.join(savepath,'combined','combined_coronal_slice_'+str(int(slice_pos))+'.png')\n",
     "    # plt.savefig(filesavepath,dpi=300)\n",
-    "    # plt.close(fig)\n"
+    "    # plt.close(fig)"
    ]
   },
   {
@@ -2117,8 +2119,9 @@
     "\n",
     "slice_size=500\n",
     "slice_pos_array=np.arange(2000+slice_size/2,10500,slice_size)\n",
-    "savepath=r\"C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\quick figures\\2024-05-23-single_unit_topography\"\n",
-    "\n",
+    "savepath = (\n",
+    "    dra.ANALYSIS_ROOT_PATH / \"quick-figures/2024-05-23-single_unit_topography\"\n",
+    ")\n",
     "plot_variables=['context','lick','sound1','vis1']\n",
     "\n",
     "\n",
@@ -2588,7 +2591,7 @@
     }
    ],
    "source": [
-    "#plot histogram on successive horizontal slices\n",
+    "# plot histogram on successive horizontal slices\n",
     "\n",
     "# plot slices\n",
     "dprime_thresh=1.0\n",
@@ -2597,8 +2600,7 @@
     "\n",
     "slice_size=500\n",
     "slice_pos_array=np.arange(slice_size/2,8000+slice_size/2,slice_size)\n",
-    "savepath=r\"C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\quick figures\\2024-05-23-single_unit_topography\"\n",
-    "\n",
+    "savepath = dra.ANALYSIS_ROOT_PATH / \"quick-figures/2024-05-23-single_unit_topography\"\n",
     "plot_variable='context_roc_auc'\n",
     "# plot_variable='sound1_roc_auc'\n",
     "# plot_variable='vis1_roc_auc'\n",
@@ -2639,7 +2641,7 @@
     "\n",
     "    # filesavepath=os.path.join(savepath,plot_variable+'_horizontal_slice_'+str(int(slice_pos))+'.png')\n",
     "    # plt.savefig(filesavepath,dpi=300)\n",
-    "    # plt.close(fig)\n"
+    "    # plt.close(fig)"
    ]
   },
   {
@@ -3056,7 +3058,7 @@
     }
    ],
    "source": [
-    "#plot histogram on successive horizontal slices\n",
+    "# plot histogram on successive horizontal slices\n",
     "\n",
     "# plot slices\n",
     "dprime_thresh=1.0\n",
@@ -3065,8 +3067,7 @@
     "\n",
     "slice_size=500\n",
     "slice_pos_array=np.arange(slice_size/2,8000+slice_size/2,slice_size)\n",
-    "savepath=r\"C:\\Users\\ethan.mcbride\\OneDrive - Allen Institute\\quick figures\\2024-05-23-single_unit_topography\"\n",
-    "\n",
+    "savepath = dra.ANALYSIS_ROOT_PATH / \"quick-figures/2024-05-23-single_unit_topography\"\n",
     "plot_variable='context_roc_auc'\n",
     "# plot_variable='sound1_roc_auc'\n",
     "# plot_variable='vis1_roc_auc'\n",
@@ -3106,7 +3107,7 @@
     "\n",
     "    # filesavepath=os.path.join(savepath,plot_variable+'_sagittal_slice_'+str(int(slice_pos))+'.png')\n",
     "    # plt.savefig(filesavepath,dpi=300)\n",
-    "    # plt.close(fig)\n"
+    "    # plt.close(fig)"
    ]
   },
   {

notebooks/single_unit_metrics_analysis.ipynb

@@ -9,6 +9,7 @@
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "from dynamic_routing_analysis import spike_utils, plot_utils\n",
+    "import dynamic_routing_analysis as dra\n",
     "import os\n",
     "\n",
     "%load_ext autoreload\n",
@@ -22,19 +23,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#load data\n",
+    "# load data\n",
     "regenerate_table=False\n",
-    "all_data_loadpath=r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\\combined\\all_data_plus_performance.pkl\"\n",
+    "all_data_loadpath=dra.SINGLE_UNIT_METRICS_PATH / \"combined\" / \"all_data_plus_performance.pkl\"\n",
     "\n",
     "if regenerate_table:\n",
-    "    savepath=r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\\combined\"\n",
-    "    stim_context_loadpath = r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\"\n",
-    "    lick_loadpath = r\"\\\\allen\\programs\\mindscope\\workgroups\\dynamicrouting\\Ethan\\new_annotations\\single unit metrics\\lick_modulation\"\n",
+    "    savepath = dra.SINGLE_UNIT_METRICS_PATH / \"combined\"\n",
+    "    stim_context_loadpath = dra.SINGLE_UNIT_METRICS_PATH\n",
+    "    lick_loadpath = dra.SINGLE_UNIT_METRICS_PATH / \"lick_modulation\"\n",
     "    performance_loadpath = os.path.join(savepath,\"performance_dict.pkl\")\n",
     "    spike_utils.concat_single_unit_metrics_across_sessions(stim_context_loadpath=stim_context_loadpath,lick_loadpath=lick_loadpath,\n",
     "                                                           performance_loadpath=None,savepath=savepath)\n",
     "\n",
-    "all_data = pd.read_pickle(all_data_loadpath)\n"
+    "all_data = pd.read_pickle(all_data_loadpath)"
    ]
   },
   {