added batch spreadsheet tool

MEAPapp.py

@@ -11,6 +11,7 @@ class MEAPGreeter(HasTraits):
     preproc = Button("Preprocess")
     analyze = Button("Analyze")
     configure = Button("Configure MEAP")
+    batch_spreadsheet = Button("Create Batch Spreadsheet")
     register_dZdt = Button("Batch Register dZ/dt")    
 
     def _preproc_fired(self):
@@ -28,13 +29,19 @@ def _register_dZdt_fired(self):
         batch = BatchGroupRegisterDZDT()
         batch.configure_traits()
 
+    def _batch_spreadsheet_fired(self):
+        from meap.make_batch_spreadsheet import BatchFileTool
+        bft = BatchFileTool()
+        bft.configure_traits()
+
     def _configure_fired(self):
         print "Not implemented yet!"
 
     traits_view=MEAPView(
         VGroup(
             Item("preproc"),
             Item("analyze"),
+            Item("batch_spreadsheet"),
             Item("register_dZdt"),
             Item("configure"),
             show_labels=False

meap/__init__.py

@@ -19,7 +19,7 @@
 SEARCH_WINDOW=30 #samples
 BLOOD_RESISTIVITY=135. # Ohms cm
 n_regions=0
-__version__= "1.5.0"
+__version__= "1.5.1"
 
 # MEAP only knows what to do with a couple of signals
 SUPPORTED_SIGNALS=["ecg", "ecg2", "dzdt", "z0", "bp",

meap/make_batch_spreadsheet.py

@@ -0,0 +1,113 @@
+#!/usr/bin/env python
+from traits.api import (HasTraits,  Array,  File, cached_property,
+          Bool, Enum, Instance, on_trait_change, Property,
+          DelegatesTo, Int, Button, List, Set, Float, Str,Directory)
+import os
+# Needed for Tabular adapter
+from meap.gui_tools import (Item,HGroup,VGroup, HSplit, ObjectColumn, 
+                           TableEditor, ProgressDialog)
+from traitsui.menu import OKButton, CancelButton
+import numpy as np
+import time
+from meap.gui_tools import MEAPView, messagebox
+from meap.io import load_from_disk, PhysioData
+from glob import glob
+import pandas as pd
+
+import logging
+logger = logging.getLogger(__name__)
+
+class FileToProcess(HasTraits):
+    input_file = File()
+    output_file = File()
+    finished = Bool(False)
+
+    def _output_file_changed(self):
+        self.finished = os.path.exists(self.output_file)
+
+class PhysioFileColumn(ObjectColumn):
+    def get_cell_color(self,object):
+        if object.finished: return "light blue"
+        return
+
+
+files_table = TableEditor(
+    columns = [ 
+        PhysioFileColumn(name="input_file", width=1.0, 
+                         editable=False,label="Input File"),
+        PhysioFileColumn(name="output_file", width=1.0, 
+                         editable=False,label="Output File"),
+        ],
+    auto_size  = True
+)
+
+class BatchFileTool(HasTraits):
+
+    # For saving outputs
+    file_suffix = Str("_finished.mea.mat")
+    input_file_extension = Enum(".mea.mat", ".acq", ".mat")
+    overwrite = Bool(False)
+    input_directory = Directory()
+    output_directory = Directory()
+    files = List(Instance(FileToProcess))
+    spreadsheet_file = File(exists=False)
+    save = Button("Save Spreadsheet")
+
+    def _input_file_extension_changed(self):
+        self._input_directory_changed()
+
+    def _input_directory_changed(self):
+        potential_files = glob(self.input_directory +"/*" + self.input_file_extension)
+        potential_files = [f for f in potential_files if not \
+                           f.endswith(self.file_suffix) ]
+
+        # Check if the output already exists
+        def make_output_file(input_file):
+            return input_file[:-len(self.input_file_extension)] + self.file_suffix
+
+        self.files = [
+            FileToProcess(input_file = f, output_file=make_output_file(f)) \
+            for f in potential_files
+        ]
+
+        # If no output directory is set, use the input directory
+        if self.output_directory == '':
+            self.output_directory = self.input_directory
+
+
+    def _b_save_fired(self):
+        def get_row():
+            return {"file":"", "outfile":"", "weight":"",
+                    "height_ft":"", "weight":"", "electrode_distance_front":"",
+                    "electrode_distance_back":"", "electrode_distance_left":"",
+                    "electrode_distance_right":"", "resp_max":"", "resp_min":"",
+                    "in_mri":"", "control_base_impedance":""}
+        rows = []
+        for f in self.files:
+            row = get_row()
+            row['file'] = f.input_file
+            row['outfile'] = f.output_file
+            rows.append(row)
+        df = pd.DataFrame(rows)
+        df.to_excel(self.spreadsheet_file, index=False)
+
+
+
+    mean_widgets =VGroup(
+            Item("input_file_extension"),
+            Item("input_directory"),
+            Item("output_directory"),
+            Item("file_suffix"),
+            Item("spreadsheet_file"),
+            Item("save",show_label=False)
+    )
+
+    traits_view = MEAPView(
+        HSplit(
+            Item("files",editor=files_table,show_label=False),
+            mean_widgets),
+        resizable=True,
+        win_title="Create Batch Spreadsheet",
+        width=800, height=700,
+        buttons = [OKButton,CancelButton]
+    )