From 6a63196a6767cbbea5b856e7b31d36a3e1d5e9b8 Mon Sep 17 00:00:00 2001
From: Chris Kerr <cjk34@cam.ac.uk>
Date: Tue, 10 Dec 2013 09:44:36 +0000
Subject: [PATCH] Created function to process the list of column types and
 return a numpy dtype

---
 BioLogic.py | 96 +++++++++++++++++++++++++----------------------------
 1 file changed, 45 insertions(+), 51 deletions(-)

diff --git a/BioLogic.py b/BioLogic.py
index 0d7701c..4b9935e 100644
--- a/BioLogic.py
+++ b/BioLogic.py
@@ -8,6 +8,7 @@ import csv
 from os import SEEK_SET, SEEK_CUR
 import time
 from datetime import date
+from collections import OrderedDict
 
 import numpy as np
 
@@ -129,19 +130,28 @@ VMPmodule_hdr = np.dtype([('shortname', 'S10'),
                           ('length', '<u4'),
                           ('version', '<u4'),
                           ('date', 'S8')])
-VMPdata_dtype = np.dtype([('flags', 'u1'),
-                          ("time/s", '<f8'),
-                          ("control/V/mA", '<f4'),
-                          ("Ewe/V", '<f4'),
-                          ("dQ/mA.h", '<f8'),
-                          ("P/W", '<f4')])
-VMPdata_dtype_extra = np.dtype([('flags', '<u2'),
-                                ('blank', 'a1'),
-                                ("time/s", '<f8'),
-                                ("control/V/mA", '<f4'),
-                                ("Ewe/V", '<f4'),
-                                ("dQ/mA.h", '<f8'),
-                                ("P/W", '<f4')])
+
+
+def VMPdata_dtype_from_colIDs(colIDs):
+    dtype_dict = OrderedDict()
+    for colID in colIDs:
+        if colID in (1, 2, 3, 21, 31, 65):
+            dtype_dict['flags'] = 'u1'
+        elif colID in (131,):
+            dtype_dict['flags2'] = '<u2'
+        elif colID == 4:
+            dtype_dict['time/s'] = '<f8'
+        elif colID == 5:
+            dtype_dict['control/V/mA'] = '<f4'
+        elif colID == 6:
+            dtype_dict['Ewe/V'] = '<f4'
+        elif colID == 7:
+            dtype_dict['dQ/mA.h'] = '<f8'
+        elif colID == 70:
+            dtype_dict['P/W'] = '<f4'
+        else:
+            raise NotImplementedError("column type %d not implemented" % colID)
+    return np.dtype(list(dtype_dict.items()))    
 
 
 def read_VMP_modules(fileobj, read_module_data=True):
@@ -210,59 +220,43 @@ class MPRfile:
         self.modules = modules
         settings_mod, = (m for m in modules if m['shortname'] == b'VMP Set   ')
         data_module, = (m for m in modules if m['shortname'] == b'VMP data  ')
-        log_module, = (m for m in modules if m['shortname'] == b'VMP LOG   ')
+        maybe_log_module = [m for m in modules if m['shortname'] == b'VMP LOG   ']
 
         n_data_points = np.fromstring(data_module['data'][:4], dtype='<u4')
-        ## not actually sure if this is the number of columns or if it means
-        ## something else:
         n_columns = int(data_module['data'][4])
+
         if data_module['version'] == 0:
-            ## There is 100 bytes of data before the main array starts
-            assert(n_columns == 11)
             column_types = np.fromstring(data_module['data'][5:], dtype='u1',
                                          count=n_columns)
-            np.testing.assert_array_equal(column_types,
-                                          [1, 2, 3, 21, 31, 65,
-                                           4, 5, 6, 7, 70])
-            assert(data_module['length'] - 100 ==
-                   VMPdata_dtype.itemsize * n_data_points)
-            self.data = np.frombuffer(data_module['data'],
-                                      dtype=VMPdata_dtype,
-                                      offset=100)
+            remaining_headers = data_module['data'][5 + n_columns:100]
+            main_data = data_module['data'][100:]
         elif data_module['version'] == 2:
-            ## There is 405 bytes of data before the main array starts
             column_types = np.fromstring(data_module['data'][5:], dtype='<u2',
                                          count=n_columns)
-            if n_columns == 11:
-                np.testing.assert_array_equal(column_types,
-                                              [1, 2, 3, 21, 31, 65,
-                                               4, 5, 6, 7, 70])
-                assert(data_module['length'] - 405 ==
-                       VMPdata_dtype.itemsize * n_data_points)
-                self.data = np.frombuffer(data_module['data'],
-                                          dtype=VMPdata_dtype,
-                                          offset=405)
-            elif n_columns == 12:
-                np.testing.assert_array_equal(column_types,
-                                              [1, 2, 3, 21, 31, 65,
-                                               131, 4, 5, 6, 7, 70])
-                assert(data_module['length'] - 405 ==
-                       VMPdata_dtype_extra.itemsize * n_data_points)
-                self.data = np.frombuffer(data_module['data'],
-                                          dtype=VMPdata_dtype_extra,
-                                          offset=405)
-                assert(np.all(self.data['blank'] == b'\x00'))
-            else:
-                raise ValueError("Cannot deal with n_columns = %d" % n_columns)
+            ## There is 405 bytes of data before the main array starts
+            remaining_headers = data_module['data'][5 + 2 * n_columns:405]
+            main_data = data_module['data'][405:]
         else:
             raise ValueError("Unrecognised version for data module: %d" %
                              data_module['version'])
+
+        assert(not any(remaining_headers))
+        self.dtype = VMPdata_dtype_from_colIDs(column_types)
+        self.data = np.fromstring(main_data, dtype=self.dtype)
+        assert(self.data.shape[0] == n_data_points)
+
         ## No idea what these 'column types' mean or even if they are actually
         ## column types at all
+        self.version = int(data_module['version'])
+        self.cols = column_types
+        self.npts = n_data_points
 
         tm = time.strptime(str(settings_mod['date'],  encoding='ascii'),
                            '%m/%d/%y')
         self.startdate = date(tm.tm_year, tm.tm_mon, tm.tm_mday)
-        tm = time.strptime(str(log_module['date'],  encoding='ascii'),
-                           '%m/%d/%y')
-        self.enddate = date(tm.tm_year, tm.tm_mon, tm.tm_mday)
+
+        if maybe_log_module:
+            log_module, = maybe_log_module
+            tm = time.strptime(str(log_module['date'],  encoding='ascii'),
+                               '%m/%d/%y')
+            self.enddate = date(tm.tm_year, tm.tm_mon, tm.tm_mday)