Fixes the shape of the data fields on edges. Left edges should be
        column vectors, and top edges should be row vectors, for example.
556610
def fix_shapes(self):
        
        for i in xrange(self.n_chunks):
            for side in ['left', 'right', 'top', 'bottom']:
                edge = getattr(self, side).ravel()[i]
                if side in ['left', 'right']:
                    shp = [edge.todo.size, 1]
                else:
                    shp = [1, edge.todo.size]
                edge.done = edge.done.reshape(shp)
                edge.data = edge.data.reshape(shp)
                edge.todo = edge.todo.reshape(shp)
128381
def AddRow(self, values):
    
    if self._number_of_columns and len(values) != self._number_of_columns:
      raise ValueError('Number of values is out of bounds.')

    self._rows.append(values)

    if not self._number_of_columns:
      self._number_of_columns = len(values)
960829
private void squaresToPositionList() {
		this.positionPatterns.reset();
		List<DetectPolygonFromContour.Info> infoList = squareDetector.getPolygonInfo();
		for (int i = 0; i < infoList.size(); i++) {
			DetectPolygonFromContour.Info info = infoList.get(i);

			// The test below has been commented out because the new external only contour
			// detector discards all information related to internal contours
			// squares with no internal contour cannot possibly be a finder pattern
//			if( !info.hasInternal() )
//				continue;

			// See if the appearance matches a finder pattern
			double grayThreshold = (info.edgeInside+info.edgeOutside)/2;
			if( !checkPositionPatternAppearance(info.polygon,(float)grayThreshold))
				continue;

			// refine the edge estimate
			squareDetector.refine(info);

			PositionPatternNode pp = this.positionPatterns.grow();
			pp.reset();
			pp.square = info.polygon;
			pp.grayThreshold = grayThreshold;

			graph.computeNodeInfo(pp);
		}
	}
1286596
private void addShape(String data)
	{
		if (faces.size() != 0)
		{
			Shape s = new Shape(faces);
			shapes.put(currentShape.toLowerCase(), s);
			faces.clear();
		}

		if (data != "")
			currentShape = data.indexOf('_') != -1 ? data.substring(0, data.indexOf('_')) : data;
	}
1107285
@Override
    public DataSet reshape(int rows, int cols) {
        DataSet ret = new DataSet(getFeatures().reshape(new long[] {rows, cols}), getLabels());
        return ret;
    }
1049674
def set_faces(self, faces):
        
        self._faces = faces
        self._edges = None
        self._edges_indexed_by_faces = None
        self._vertex_faces = None
        self._vertices_indexed_by_faces = None
        self.reset_normals()
        self._vertex_colors_indexed_by_faces = None
        self._face_colors_indexed_by_faces = None
639963
@Override
	public void setEquirectangularShape( int width , int height ) {
		super.setEquirectangularShape(width, height);
		declareVectors(width, height);

		// precompute vectors for each pixel
		for (int y = 0; y < height; y++) {
			for (int x = 0; x < width; x++) {
				tools.equiToNormFV(x,y,vectors[y*width+x]);
			}
		}
	}
456599
def _fix_slice(self, inputs, new_attr):
        """"""
        begin = new_attr.get('begin')
        end = new_attr.get('end')
        axes = new_attr.get('axis', tuple(range(len(begin))))
        slice_op = mx.sym.slice_axis(inputs[0], axis=axes[0], begin=begin[0], end=end[0])
        if len(axes) > 1:
            for i, axis in enumerate(axes):
                slice_op = mx.sym.slice_axis(slice_op, axis=axis, begin=begin[i], end=end[i])
        return slice_op
593328
function edge(a, b) {
  if (a.row > b.row) { var t = a; a = b; b = t; }
  return {
    x0: a.column,
    y0: a.row,
    x1: b.column,
    y1: b.row,
    dx: b.column - a.column,
    dy: b.row - a.row
  };
}
951932
public static boolean isRowVectorShape(DataBuffer shapeInfo) {
        int rank = Shape.rank(shapeInfo);
        DataBuffer shape = Shape.shapeOf(shapeInfo);
        return (rank == 2 && shape.getInt(0) == 1) || rank == 1;

    }
247031
def _shape_text(self, text, colsep=u"\t", rowsep=u"\n",
                    transpose=False, skiprows=0, comments='#'):
        """"""
        assert colsep != rowsep
        out = []
        text_rows = text.split(rowsep)[skiprows:]
        for row in text_rows:
            stripped = to_text_string(row).strip()
            if len(stripped) == 0 or stripped.startswith(comments):
                continue
            line = to_text_string(row).split(colsep)
            line = [try_to_parse(to_text_string(x)) for x in line]
            out.append(line)
        # Replace missing elements with np.nan's or None's
        if programs.is_module_installed('numpy'):
            from numpy import nan
            out = list(zip_longest(*out, fillvalue=nan))
        else:
            out = list(zip_longest(*out, fillvalue=None))
        # Tranpose the last result to get the expected one
        out = [[r[col] for r in out] for col in range(len(out[0]))]
        if transpose:
            return [[r[col] for r in out] for col in range(len(out[0]))]
        return out
610694
public void fixRowsAndCols() {
        rows = (int) Math.round((n - s) / ns_res);
        if (rows < 1)
            rows = 1;
        cols = (int) Math.round((e - w) / we_res);
        if (cols < 1)
            cols = 1;
    }
422648
public void setRow(int row, DoubleVector data) {
        checkIndices(row, data.length() -1);

        if (cols <= data.length())
            cols = data.length();

        Vectors.copy(updateRow(row), data);
    }
1136685
def _dataframe_to_edge_list(df):
    
    cols = df.columns
    if len(cols):
        assert _SRC_VID_COLUMN in cols, "Vertex DataFrame must contain column %s" % _SRC_VID_COLUMN
        assert _DST_VID_COLUMN in cols, "Vertex DataFrame must contain column %s" % _DST_VID_COLUMN
        df = df[cols].T
        ret = [Edge(None, None, _series=df[col]) for col in df]
        return ret
    else:
        return []
1355690
def set_i(self, i, data, field, side):
        
        edge = self.get_i(i, side)
        setattr(edge, field, data[edge.slice])
537326
def update_columns_dict(self, kwargs):
        
        super(Mesh, self).update_columns_dict(kwargs)

        # if kwargs.get('vnormals', None) is not None or kwargs.get('tnormals', None) is not None:
            # self._compute_mus()
        if kwargs.get('triangles', None) is not None:
            # reset visibilities and velocities so that they are reset
            # when next queried
            self.update_columns(visibilities=None, velocities=None)
966043
def matrix_from_edges(edges):
    ''''''
    max_col = 0
    cols = []
    rows = []
    vals = []
    if type(edges) is defaultdict:
        edge_list = []
        for i, neighbors in edges.items():
            for j in neighbors:
                if i <= j:
                    edge_list.append((i,j))
        edges = edge_list
    for i, edge in enumerate(edges):
        s, t = edge[0], edge[1]
        weight = 1 if len(edge) == 2 else edge[2]
        cols.append(min(s,t))
        cols.append(max(s,t))
        rows.append(i)
        rows.append(i)
        vals.append(weight)
        vals.append(-weight)
        if cols[-1] > max_col:
            max_col = cols[-1]
    return coo_matrix((vals, (rows, cols)), shape=(rows[-1]+1, max_col+1))