[ENH.STY] add heartrate processing

.gitignore

@@ -1,4 +1,3 @@
 .ipynb_checkpoints
 .DS_Store
-.vscode
 .pytest_cache

.vscode/launch.json

@@ -0,0 +1,16 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: Current File",
+            "type": "python",
+            "request": "launch",
+            "program": "${file}",
+            "args": ["data", "output/testOut"],
+            "console": "integratedTerminal"
+        }
+    ]
+}

.vscode/settings.json

@@ -0,0 +1,12 @@
+{
+    "python.pythonPath": "/opt/miniconda-latest/envs/physio/bin/python",
+    "python.linting.flake8Enabled": true,
+    "gitlens.showWhatsNewAfterUpgrades": false,
+    "python.testing.pytestEnabled": true,
+    "python.testing.unittestEnabled": false,
+    "python.testing.nosetestsEnabled": false,
+    "python.linting.enabled": true,
+    "python.testing.pytestArgs": [],
+    "python.linting.pylintEnabled": false,
+    "python.dataScience.debugJustMyCode": false
+}

Dockerfile

@@ -1,5 +1,5 @@
 # Generated by Neurodocker version 0.5.0
-# Timestamp: 2019-09-13 17:44:50 UTC
+# Timestamp: 2019-09-13 19:33:04 UTC
 # 
 # Thank you for using Neurodocker. If you discover any issues
 # or ways to improve this software, please submit an issue or
@@ -52,6 +52,8 @@ USER neuro
 
 WORKDIR /home/neuro
 
+ENV SHELL="/bin/bash"
+
 RUN mkdir /home/neuro/physioAnalysis
 
 COPY [".", "/home/neuro/physioAnalysis"]
@@ -72,6 +74,8 @@ RUN export PATH="/opt/miniconda-latest/bin:$PATH" \
     && conda env create -q --name physio --file /home/neuro/physioAnalysis/environment.yml \
     && rm -rf ~/.cache/pip/*
 
+RUN conda init
+
 USER root
 
 RUN curl -o /tmp/code-server.tar.gz -SL https://github.com/cdr/code-server/releases/download/2.1472-vsc1.38.1/code-server2.1472-vsc1.38.1-linux-x86_64.tar.gz
@@ -107,6 +111,12 @@ RUN echo '{ \
     \n      "/home/neuro" \
     \n    ], \
     \n    [ \
+    \n      "env", \
+    \n      { \
+    \n        "SHELL": "/bin/bash" \
+    \n      } \
+    \n    ], \
+    \n    [ \
     \n      "run", \
     \n      "mkdir /home/neuro/physioAnalysis" \
     \n    ], \
@@ -125,6 +135,10 @@ RUN echo '{ \
     \n      } \
     \n    ], \
     \n    [ \
+    \n      "run", \
+    \n      "conda init" \
+    \n    ], \
+    \n    [ \
     \n      "user", \
     \n      "root" \
     \n    ], \

code/physio.py

@@ -12,6 +12,7 @@
 import matplotlib
 matplotlib.use('Agg')
 
+
 # functions to analyze gsr data
 def analyze_gsr(acqs, txts, outdir):
     """
@@ -25,9 +26,9 @@ def analyze_gsr(acqs, txts, outdir):
         if acq_txt_dict is None:
             acq_nonmatches.append(acq_nonmatch)
             continue
-        
+
         fname_dict = gen_filenames(acq_txt_dict)
-        
+
         if fname_dict is None:
             warnings.warn("Skipping acq File")
             continue
@@ -36,18 +37,18 @@ def analyze_gsr(acqs, txts, outdir):
             os.path.isfile(fname_dict['data']) and
             os.path.isfile(fname_dict['smry'])
            ):
-            with open(fname_dict['smry']) as json_file:  
+            with open(fname_dict['smry']) as json_file:
                 sub_dict = json.load(json_file)
         else:
             acq_txt_dict_proc = filter_gsr(acq_txt_dict)
             sub_dict = write_results(acq_txt_dict_proc, fname_dict)
-        
+
         group_msr.append(sub_dict)
-  
+
     group_df = pd.DataFrame(group_msr)
     group_df.to_csv(group_tsv, sep="\t")
     txt_nonmatches = txts
-    
+
     return acq_txt_dict_proc, acq_nonmatches, txt_nonmatches, group_df
 
 
@@ -65,38 +66,38 @@ def match_acq_txt(acq, txts):
     # there should be enough rows in the dataframes
     if acq_df.shape[0] < min_len:
         return None, acq, txts
-            
+
     # big loop to see which txt file goes with the acknowledge file
     for txt in txts:
         # only look at txt files in the same directory as acknowledge file
         if os.path.dirname(acq) != os.path.dirname(txt):
             continue
         # attempt 1 to read the txt file
         # assumes no header information and no time column
-        txt_df = pd.read_csv(txt,
-        header=None,
-        index_col=False,
-        names=acq_df.columns,
-        sep="\t")
+        txt_df = pd.read_csv(txt, header=None,
+                             index_col=False,
+                             names=acq_df.columns,
+                             sep="\t")
 
         # the file may have a header
-        if np.any(txt_df.iloc[0,:].isnull()):
+        if np.any(txt_df.iloc[0, :].isnull()):
             # assume the txt file has a header
             try:
                 txt_df = pd.read_csv(txt,
-                    header=14,
-                    index_col=0,
-                    delim_whitespace=True,
-                    names=acq_df.columns)
+                                     header=14,
+                                     index_col=0,
+                                     delim_whitespace=True,
+                                     names=acq_df.columns)
             except:
-                # assume the acknowledge file does not have the "Scanner TTl column"
+                # assume the acknowledge file does
+                # not have the "Scanner TTl column"
                 columns = list(acq_df.columns)
                 columns.insert(-1, "Scanner TTL")
                 txt_df = pd.read_csv(txt,
-                    header=14,
-                    index_col=0,
-                    delim_whitespace=True,
-                    names=columns)
+                                     header=14,
+                                     index_col=0,
+                                     delim_whitespace=True,
+                                     names=columns)
             # assume in the two above cases,
             # there is a time column being treated as the index
             txt_df.reset_index(drop=True, inplace=True)
@@ -111,7 +112,7 @@ def match_acq_txt(acq, txts):
             acq_txt_dict[acq] = {'txt': txt, 'df': acq_df}
             txts.remove(txt)
             return acq_txt_dict, None, txts
-    
+
     # nothing matches
     return None, acq, txts
 
@@ -121,21 +122,28 @@ def filter_gsr(acq_txt_dict):
     Filter/Preprocess the GSR data
     """
     key = list(acq_txt_dict.keys())[0]
-    
+
     acq_df = acq_txt_dict[key]['df']
     # where the Scanner Trigger is 0 initiates a slice acquition in the scanner
     # this may be false in some scenerios (e.g. when scan trigger is always 0)
-    start = acq_df["Scanner Trigger"].where(acq_df["Scanner Trigger"]==0.0).first_valid_index()
-    end = acq_df["Scanner Trigger"].where(acq_df["Scanner Trigger"]==0.0).last_valid_index()
+    start = acq_df["Scanner Trigger"].where(
+        acq_df["Scanner Trigger"] == 0.0).first_valid_index()
+    end = acq_df["Scanner Trigger"].where(
+        acq_df["Scanner Trigger"] == 0.0).last_valid_index()
     if start is None or end is None:
         warnings.warn("Scan Trigger Not Recognized, keeping all rows")
         acq_cut_df = acq_df
     else:
-        acq_cut_df = acq_df.iloc[(acq_df.index >= start) & (acq_df.index <= end)]
+        acq_cut_df = acq_df.iloc[(acq_df.index >= start) &
+                                 (acq_df.index <= end)]
 
     # process the GSR data
-    res = nk.bio_eda.eda_process(acq_df['GSR100C'], filter_type='butter',
-                                 band="lowpass", order=1, frequency=1,
+    res = nk.bio_ecg.ecg_process(acq_cut_df['PPG100C'],
+                                 rsp=None,
+                                 filter_type='FIR',
+                                 band="bandpass",
+                                 order=1,
+                                 frequency=[3, 45],
                                  sampling_rate=200)
 
     acq_txt_dict[key]['df'] = res['df']
@@ -162,7 +170,7 @@ def gen_filenames(acq_txt_dict):
     for acq, tgt_dct in acq_txt_dict.items():
         atrain_mch = atrain_ptrn.match(tgt_dct['txt'])
         extend_mch = extend_ptrn.match(tgt_dct['txt'])
-        
+
         if atrain_mch:
             fdict = atrain_mch.groupdict()
             # make task lowercase
@@ -176,30 +184,41 @@ def gen_filenames(acq_txt_dict):
             if fdict["run_id"]:
                 fdict["run_id"] = int(fdict["run_id"].lstrip("run-"))
         else:
-            warnings.warn("FileName did not match either atrain or extend pattern")
+            warnings.warn("FileName did not match either "
+                          "atrain or extend pattern")
             return None
 
         # strip the keys from the labels
         fdict["sub_id"] = fdict["sub_id"].lstrip("sub-")
         fdict["ses_id"] = fdict["ses_id"].lstrip("ses-")
         fdict["task_id"] = fdict["task_id"].lstrip("task-")
-        
+
         # template output file changes depending if run is a key or not
         if not fdict["run_id"]:
-            tmplt = os.path.join(outdir,
-                                 "sub-{sub_id}",
-                                 "ses-{ses_id}",
-                                 "sub-{sub_id}_ses-{ses_id}_task-{task_id}_{typ}.{ext}")
+            tmplt = os.path.join(
+                outdir,
+                "sub-{sub_id}",
+                "ses-{ses_id}",
+                "sub-{sub_id}_ses-{ses_id}_task-{task_id}_{typ}.{ext}"
+            )
+
         elif fdict["run_id"]:
-            tmplt = os.path.join(outdir,
-                                 "sub-{sub_id}",
-                                 "ses-{ses_id}",
-                                 "sub-{sub_id}_ses-{ses_id}_task-{task_id}_run-{run_id}_{typ}.{ext}")
+            tmplt = os.path.join(
+                outdir,
+                "sub-{sub_id}",
+                "ses-{ses_id}",
+                ("sub-{sub_id}_ses-{ses_id}_"
+                 "task-{task_id}_run-{run_id}_{typ}.{ext}")
+            )
+
         fig_file = tmplt.format(**fdict, typ="qa", ext="svg")
         data_file = tmplt.format(**fdict, typ="physio", ext="tsv")
         sum_file = tmplt.format(**fdict, typ="summary", ext="json")
-
-        return {'fig': fig_file, 'data': data_file, 'smry': sum_file, 'fdict': fdict}
+
+        return {'fig': fig_file,
+                'data': data_file,
+                'smry': sum_file,
+                'fdict': fdict}
 
 
 def write_results(acq_txt_dict, filenames):
@@ -209,7 +228,7 @@ def write_results(acq_txt_dict, filenames):
     # make directory to place results
     os.makedirs(os.path.dirname(filenames['data']), exist_ok=True)
     key = list(acq_txt_dict.keys())[0]
-    
+
     fdict = filenames['fdict']
     out_df = acq_txt_dict[key]['df']
     out_df.to_csv(filenames['data'], sep="\t", index=False)
@@ -229,12 +248,12 @@ def write_results(acq_txt_dict, filenames):
         "EDA_std": out_df["EDA_Filtered"].std()
     }
 
-    with open(filenames['smry'], 'w') as outfile:  
+    with open(filenames['smry'], 'w') as outfile:
         json.dump(sub_dict, outfile)
-    
+
     return sub_dict
 
-        
+
 if __name__ == '__main__':
     from argparse import ArgumentParser
     from glob import glob
@@ -245,9 +264,10 @@ def write_results(acq_txt_dict, filenames):
                         help='path to the top level of the data directory')
     parser.add_argument('outdir', action='store',
                         help='path to output directory')
-    parser.add_argument('--participant_label', '--participant-label', action='store',
-                        help='a single participant identifier ')
-
+    parser.add_argument('--participant_label', '--participant-label',
+                        action='store',
+                        help='a single participant identifier')
+
     opts = parser.parse_args()
 
     participant_label = "sub-*"

generate_physio_images.sh

@@ -10,10 +10,12 @@ generate_docker() {
     --install net-tools git \
     --user=neuro \
     --workdir="/home/neuro" \
+    --env "SHELL=/bin/bash" \
     --run 'mkdir /home/neuro/physioAnalysis' \
     --copy . /home/neuro/physioAnalysis \
     --miniconda create_env='physio' \
                 yaml_file='/home/neuro/physioAnalysis/environment.yml' \
+    --run "conda init" \
     --user=root \
     --run 'curl -o /tmp/code-server.tar.gz -SL https://github.com/cdr/code-server/releases/download/2.1472-vsc1.38.1/code-server2.1472-vsc1.38.1-linux-x86_64.tar.gz' \
     --run 'mkdir -p /opt/codeserver && tar -xvf /tmp/code-server.tar.gz -C /opt/codeserver --strip-components=1' \