introduce parameter p_patch

caiman/source_extraction/cnmf/map_reduce.py

@@ -129,6 +129,8 @@ def cnmf_patches(args_in):
         opts.set('patch', {'n_processes': 1, 'rf': None, 'stride': None})
         for group in ('init', 'temporal', 'spatial'):
             opts.set(group, {'nb': params.get('patch', 'nb_patch')})
+        for group in ('preprocess', 'temporal'):
+            opts.set(group, {'p': params.get('patch', 'p_patch')})
 
         cnm = cnmf.CNMF(n_processes=1, params=opts)
 

caiman/source_extraction/cnmf/params.py

@@ -105,6 +105,9 @@ def __init__(self, fnames=None, dims=None, dxy=(1, 1),
             only_init: bool, default: True
                 whether to run only the initialization
 
+            p_patch: int, default: 0
+                order of AR dynamics when processing within a patch
+
             skip_refinement: bool, default: False
                 Whether to skip refinement of components (deprecated?)
 
@@ -575,7 +578,7 @@ def __init__(self, fnames=None, dims=None, dxy=(1, 1),
             'decay_time': decay_time,
             'dxy': dxy,
             'var_name_hdf5': var_name_hdf5,
-            'caiman_version': '1.6.1',
+            'caiman_version': '1.6.2',
             'last_commit': None,
             'mmap_F': None,
             'mmap_C': None
@@ -590,6 +593,7 @@ def __init__(self, fnames=None, dims=None, dxy=(1, 1),
             'n_processes': n_processes,
             'nb_patch': nb_patch,
             'only_init': only_init_patch,
+            'p_patch': 0,                 # AR order within patch
             'remove_very_bad_comps': remove_very_bad_comps,
             'rf': rf,
             'skip_refinement': False,

demos/general/demo_pipeline.py

@@ -170,6 +170,7 @@ def main():
 
     # parameters for component evaluation
     opts_dict = {'fnames': fnames,
+                 'p': p,
                  'fr': fr,
                  'nb': gnb,
                  'rf': rf,
@@ -187,9 +188,11 @@ def main():
     opts.change_params(params_dict=opts_dict);
 # %% RUN CNMF ON PATCHES
     # First extract spatial and temporal components on patches and combine them
-    # for this step deconvolution is turned off (p=0)
+    # for this step deconvolution is turned off (p=0). If you want to have
+    # deconvolution within each patch change params.patch['p_patch'] to a
+    # nonzero value
 
-    opts.change_params({'p': 0})
+    #opts.change_params({'p': 0})
     cnm = cnmf.CNMF(n_processes, params=opts, dview=dview)
     cnm = cnm.fit(images)
 
@@ -209,7 +212,6 @@ def main():
     cnm.save(fname_new[:-5]+'_init.hdf5')
 
 # %% RE-RUN seeded CNMF on accepted patches to refine and perform deconvolution
-    cnm.params.change_params({'p': p})
     cnm2 = cnm.refit(images, dview=dview)
     # %% COMPONENT EVALUATION
     # the components are evaluated in three ways:

demos/notebooks/demo_pipeline.ipynb

@@ -184,7 +184,7 @@
     "            'max_shifts': max_shifts,\n",
     "            'max_deviation_rigid': max_deviation_rigid,\n",
     "            'pw_rigid': pw_rigid,\n",
-    "            'p': 1,\n",
+    "            'p': p,\n",
     "            'nb': gnb,\n",
     "            'rf': rf,\n",
     "            'K': K, \n",
@@ -306,7 +306,7 @@
     "#%% MEMORY MAPPING\n",
     "# memory map the file in order 'C'\n",
     "fname_new = cm.save_memmap(mc.mmap_file, base_name='memmap_', order='C',\n",
-    "                           border_to_0=border_to_0) # exclude borders\n",
+    "                           border_to_0=border_to_0, dview=dview) # exclude borders\n",
     "\n",
     "# now load the file\n",
     "Yr, dims, T = cm.load_memmap(fname_new)\n",
@@ -354,10 +354,10 @@
    "source": [
     "%%capture\n",
     "#%% RUN CNMF ON PATCHES\n",
-    "\n",
     "# First extract spatial and temporal components on patches and combine them\n",
-    "# for this step deconvolution is turned off (p=0)\n",
-    "opts.change_params({'p': 0})\n",
+    "# for this step deconvolution is turned off (p=0). If you want to have\n",
+    "# deconvolution within each patch change params.patch['p_patch'] to a\n",
+    "# nonzero value\n",
     "cnm = cnmf.CNMF(n_processes, params=opts, dview=dview)\n",
     "cnm = cnm.fit(images)"
    ]
@@ -419,7 +419,6 @@
    "source": [
     "%%capture\n",
     "#%% RE-RUN seeded CNMF on accepted patches to refine and perform deconvolution \n",
-    "cnm.params.change_params({'p': p})\n",
     "cnm2 = cnm.refit(images, dview=dview)"
    ]
   },
@@ -648,7 +647,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,