Derive number of columns and rows from filenames.
325144
def get_columns_rows(filenames):
    """"""
    tiles = []
    for filename in filenames:
        row, column = os.path.splitext(filename)[0][-5:].split('_')
        tiles.append((int(row), int(column)))
    rows = [pos[0] for pos in tiles]; columns = [pos[1] for pos in tiles]
    num_rows = max(rows); num_columns = max(columns)
    return (num_columns, num_rows)
707587
def DatabaseDirectorySize(root_path, extension):
  """"""
  directories = collections.deque([root_path])
  total_size = 0
  total_files = 0
  while directories:
    directory = directories.popleft()
    try:
      items = os.listdir(directory)
    except OSError:
      continue
    for comp in items:
      path = os.path.join(directory, comp)
      try:
        statinfo = os.lstat(path)
        if stat.S_ISLNK(statinfo.st_mode):
          continue
        if stat.S_ISDIR(statinfo.st_mode):
          directories.append(path)
        elif stat.S_ISREG(statinfo.st_mode):
          if comp.endswith(extension):
            total_size += statinfo.st_size
            total_files += 1
      except OSError:
        continue
  return total_size, total_files
274004
def _extract_colnums(self, columns=None):
        
        if columns is None:
            return numpy.arange(self._ncol, dtype='i8')

        if not isinstance(columns, (tuple, list, numpy.ndarray)):
            # is a scalar
            return self._extract_colnum(columns)

        colnums = numpy.zeros(len(columns), dtype='i8')
        for i in xrange(colnums.size):
            colnums[i] = self._extract_colnum(columns[i])

        # returns unique sorted
        colnums = numpy.unique(colnums)
        return colnums
725387
def _subset_filenames(dl_paths, split):
  """"""
  assert isinstance(dl_paths, dict), dl_paths
  # Get filenames for a split.
  if split == tfds.Split.TRAIN:
    urls = _get_url_hashes(dl_paths['train_urls'])
  elif split == tfds.Split.VALIDATION:
    urls = _get_url_hashes(dl_paths['val_urls'])
  elif split == tfds.Split.TEST:
    urls = _get_url_hashes(dl_paths['test_urls'])
  else:
    logging.fatal('Unsupported split: %s', split)
  cnn = _find_files(dl_paths, 'cnn', urls)
  dm = _find_files(dl_paths, 'dm', urls)
  return cnn + dm
1254244
def columnCount(self, qindex=QModelIndex()):
        """"""
        if self.total_cols <= self.cols_loaded:
            return self.total_cols
        else:
            return self.cols_loaded
587618
def combine_count_files(files, out_file=None, ext=".fpkm"):
    
    files = list(files)
    if not files:
        return None
    assert all([file_exists(x) for x in files]), \
        "Some count files in %s do not exist." % files
    for f in files:
        assert file_exists(f), "%s does not exist or is empty." % f
    col_names = [os.path.basename(x.replace(ext, "")) for x in files]
    if not out_file:
        out_dir = os.path.join(os.path.dirname(files[0]))
        out_file = os.path.join(out_dir, "combined.counts")

    if file_exists(out_file):
        return out_file
    logger.info("Combining count files into %s." % out_file)
    row_names = []
    col_vals = defaultdict(list)
    for i, f in enumerate(files):
        vals = []
        if i == 0:
            with open(f) as in_handle:
                for line in in_handle:
                    rname, val = line.strip().split("\t")
                    row_names.append(rname)
                    vals.append(val)
        else:
            with open(f) as in_handle:
                for line in in_handle:
                    _, val = line.strip().split("\t")
                    vals.append(val)
        col_vals[col_names[i]] = vals

    df = pd.DataFrame(col_vals, index=row_names)
    df.to_csv(out_file, sep="\t", index_label="id")
    return out_file
589602
public int getNumberOfRows(final String fileName, final String sheetName)
			throws IOException {
		LOG.info("Getting the number of rows from:" + fileName + " sheet: "
				+ sheetName);
		Workbook workbook = getWorkbook(fileName);
		Sheet sheets = workbook.getSheet(sheetName);
		return sheets.getPhysicalNumberOfRows();
	}
513585
def _get_data(filenames):
    
    if filenames:
        data = ""
        for filename in filenames:
            with open(filename, "rb") as f:
                data += f.read()
    else:
        data = sys.stdin.read()

    return data
78754
def build_dataset(filename, sequence_length, alphabet_size, max_lines=-1):
    """"""
    with open(filename) as f:
        content = f.readlines()
    content = content[:max_lines]
    content = [line for line in content if len(line) > 2]   # Remove blank lines
    seqs = np.zeros((sequence_length, len(content), alphabet_size))
    for ix, line in enumerate(content):
        padded_line = (line + " " * sequence_length)[:sequence_length]
        seqs[:, ix, :] = string_to_one_hot(padded_line, alphabet_size)
    return seqs
588505
def table_repr(columns, rows, data, padding=2):
    """"""
    padding = ' ' * padding
    column_lengths = [len(column) for column in columns]
    for row in rows:
        for i, column in enumerate(columns):
            item = str(data[row][column])
            column_lengths[i] = max(len(item), column_lengths[i])
    max_row_length = max(len(row) for row in rows) if len(rows) else 0
    table_row = ' ' * max_row_length
    for i, column in enumerate(columns):
        table_row += padding + column.rjust(column_lengths[i])
    table_rows = [table_row]
    for row in rows:
        table_row = row.rjust(max_row_length)
        for i, column in enumerate(columns):
            item = str(data[row][column])
            table_row += padding + item.rjust(column_lengths[i])
        table_rows.append(table_row)
    return '\n'.join(table_rows)
921127
def get_row_headers(rows, row_headers_count_value=0, column_headers_count=1):
    
    # TODO: REFACTOR ALGORITHM NEEDED
    partial_headers = []

    if row_headers_count_value:

        # Take partial data
        for k_index in range(0, len(rows) - column_headers_count):
            header = rows[k_index + column_headers_count][
                :row_headers_count_value]
            partial_headers.append(remove_list_duplicates(force_list(header)))

        # Populate headers
        populated_headers = populate_csv_headers(
            rows,
            partial_headers,
            column_headers_count)

        return populated_headers
144709
def extract_data(filename, num_images):
  
  print('Extracting', filename)
  with gzip.open(filename) as bytestream:
    bytestream.read(16)
    buf = bytestream.read(IMAGE_SIZE * IMAGE_SIZE * num_images)
    data = np.frombuffer(buf, dtype=np.uint8).astype(np.float32)
    data = (data - (PIXEL_DEPTH / 2.0)) / PIXEL_DEPTH
    data = data.reshape(num_images, IMAGE_SIZE, IMAGE_SIZE, 1)
    return data
965717
def _get_columns_as_string(self):
        """"""
        columnslist = []
        for rowidx, row in self.columns.iterrows():
            columnslist.append("#%s = %s" % (rowidx, row.description))
        return "\n".join(columnslist)
233451
def load_data(self, idx):
        """"""
        for name in self:
            ndim = getattr(self, '_%s_ndim' % name)
            diskflag = getattr(self, '_%s_diskflag' % name)
            ramflag = getattr(self, '_%s_ramflag' % name)
            if diskflag:
                file_ = getattr(self, '_%s_file' % name)
                length_tot = 1
                shape = []
                for jdx in range(ndim):
                    length = getattr(self, '_%s_length_%s' % (name, jdx))
                    length_tot *= length
                    shape.append(length)
                raw = file_.read(length_tot*8)
                values = struct.unpack(length_tot*'d', raw)
                if ndim:
                    values = numpy.array(values).reshape(shape)
                else:
                    values = values[0]
            elif ramflag:
                array = getattr(self, '_%s_array' % name)
                values = array[idx]
            if diskflag or ramflag:
                if ndim == 0:
                    setattr(self, name, values)
                else:
                    getattr(self, name)[:] = values
182341
def MakeExpandedTrace(frame_records):
  """"""
  dump = []
  for (frame_obj, filename, line_num, fun_name, context_lines,
       context_index) in frame_records:
    dump.append('File "%s", line %d, in %s\n' % (filename, line_num,
                                                 fun_name))
    if context_lines:
      for (i, line) in enumerate(context_lines):
        if i == context_index:
          dump.append(' --> %s' % line)
        else:
          dump.append('     %s' % line)
    for local_name, local_val in frame_obj.f_locals.items():
      try:
        local_type_name = type(local_val).__name__
      except Exception as e:
        local_type_name = '    Exception in type({}).__name__: {}'.format(local_name, e)
      try:
        truncated_val = repr(local_val)[0:500]
      except Exception as e:
        dump.append('    Exception in repr({}): {}\n'.format(local_name, e))
      else:
        if len(truncated_val) >= 500:
          truncated_val = '%s...' % truncated_val[0:499]
        dump.append('    {} = {} ({})\n'.format(local_name, truncated_val, local_type_name))
    dump.append('\n')
  return dump
644158
def number_of_sub_file_entries(self):
    """"""
    if self._directory is None:
      self._directory = self._GetDirectory()

    if self._directory is None:
      return 0

    # We cannot use len(self._directory.entries) since entries is a generator.
    return sum(1 for path_spec in self._directory.entries)
596040
def load(self, filename=None):
        '''
        
        '''
        fields = []
        with open(filename, 'r') as f:
            format_data = f.read().strip()

        lines = format_data.split('\n')
        self._sql_version = lines.pop(0)
        self._num_fields = int(lines.pop(0))

        for line in lines:
            # Get rid of mulitple spaces
            line = re.sub(' +', ' ', line.strip())
            row_format = BCPFormatRow(line.split(' '))
            fields.append(row_format)

        self.fields = fields
        self.filename = filename