def load_csv(self, filename):
'''Populates the grid with the the data in a CSV file.
filename -- the path to a CSV file to load
'''
#
# XXX: try using linecache so we don't need to load the whole file.
#
# infer types
r = csv.reader(open(filename))
dtable = dbconnect.get_data_table_from_csv_reader(r)
first_row_types = db.InferColTypesFromData([dtable[0]], len(dtable[0]))
coltypes = db.InferColTypesFromData(dtable[1:], len(dtable[0]))
has_header_row = False
if (not all([a == b for a, b in zip(first_row_types, coltypes)])
and all([a.startswith('VARCHAR') for a in first_row_types])
and not all([b.startswith('VARCHAR') for b in coltypes])):
has_header_row = True
for i in range(len(coltypes)):
if coltypes[i] == 'INT': coltypes[i] = int
elif coltypes[i] == 'FLOAT': coltypes[i] = np.float32
else: coltypes[i] = str
# read data
r = csv.reader(open(filename))
if has_header_row:
labels = r.next()
else:
labels = None
data = []
for row in r:
data += [[coltypes[i](v) for i, v in enumerate(row)]]
data = np.array(data, dtype=object)
table_base = PlainTable(self, data, labels)
self.grid.SetTable(table_base, True)
self.grid.Refresh()
self.SetTitle(filename)
self.RescaleGrid()
self.grid.SetSelectionMode(self.grid.wxGridSelectColumns)
def load_csv(self, filename):
'''Populates the grid with the the data in a CSV file.
filename -- the path to a CSV file to load
'''
#
# XXX: try using linecache so we don't need to load the whole file.
#
# infer types
r = csv.reader(open(filename))
dtable = dbconnect.get_data_table_from_csv_reader(r)
first_row_types = db.InferColTypesFromData([dtable[0]], len(dtable[0]))
coltypes = db.InferColTypesFromData(dtable[1:], len(dtable[0]))
has_header_row = False
if (not all([a == b for a, b in zip(first_row_types, coltypes)]) and
all([a.startswith('VARCHAR') for a in first_row_types]) and
not all([b.startswith('VARCHAR') for b in coltypes])):
has_header_row = True
for i in range(len(coltypes)):
if coltypes[i] == 'INT': coltypes[i] = int
elif coltypes[i] == 'FLOAT': coltypes[i] = np.float32
else: coltypes[i] = str
# read data
r = csv.reader(open(filename))
if has_header_row:
labels = r.next()
else:
labels = None
data = []
for row in r:
data += [[coltypes[i](v) for i,v in enumerate(row)]]
data = np.array(data, dtype=object)
table_base = PlainTable(self, data, labels)
self.grid.SetTable(table_base, True)
self.grid.Refresh()
self.SetTitle(filename)
self.RescaleGrid()
self.grid.SetSelectionMode(self.grid.wxGridSelectColumns)
def LoadCSV(self, csvfile, group='Image'):
try:
self.grid.Destroy()
except: pass
try:
# Remove the previous column show/hide menu (should be the third menu)
self.GetMenuBar().Remove(2)
self.colmenu.Destroy()
except: pass
r = csv.reader(open(csvfile))
labels = r.next()
dtable = dbconnect.get_data_table_from_csv_reader(r)
coltypes = db.InferColTypesFromData(dtable, len(labels))
for i in range(len(coltypes)):
if coltypes[i] == 'INT': coltypes[i] = int
elif coltypes[i] == 'FLOAT': coltypes[i] = float
else: coltypes[i] = str
r = csv.reader(open(csvfile))
r.next() # skip col-headers
data = []
for row in r:
data += [[coltypes[i](v) for i,v in enumerate(row)]]
data = np.array(data, dtype=object)
if group == DO_NOT_LINK_TO_IMAGES:
keycols = []
elif group == 'Image':
keycols = range(len(dbconnect.image_key_columns()))
else:
keycols = range(len(dm.GetGroupColumnNames(group)))
self.grid = HugeTableGrid(self, data, labels, key_col_indices=keycols, grouping=group, chMap=p.image_channel_colors)
self.Title = '%s (%s)'%(csvfile, group)
self.file = csvfile
self.CreateColumnMenu()
self.RescaleGrid()
