add version tag for 1.6.0 (#1190)

+ version: add version tag for 1.6.0

+ utils.transect_yx/lalo(): update comment for example usage

Author: yunjunz

src/mintpy/utils/utils.py

@@ -264,23 +264,25 @@ def transect_yx(z, atr, start_yx, end_yx, interpolation='nearest'):
     """Extract 2D matrix (z) value along the line [x0,y0;x1,y1]
     Link: http://stackoverflow.com/questions/7878398/how-to-extract-an-arbitrary-line-of-values-from-a-numpy-array
 
-    Parameters: z : (np.array) 2D data matrix
-                atr : (dict) attribute
+    Parameters: z        : (np.ndarray) 2D data matrix
+                atr      : (dict) attribute
                 start_yx : (list) y,x coordinate of start point
-                end_yx : (list) y,x coordinate of end   point
+                end_yx   : (list) y,x coordinate of end   point
                 interpolation : str, sampling/interpolation method, including:
                     'nearest' - nearest neighbour
                     'linear'  - linear  spline interpolation (order of 1)
                     'cubic'   - cubic   spline interpolation (order of 3)
                     'quintic' - quintic spline interpolation (order of 5)
 
-    Returns:    transect: (dict) containing 1D matrix:
-                    'X' - 1D np.array for X/column coordinates in float32
-                    'Y' - 1D np.array for Y/row.   coordinates in float32
-                    'value' - 1D np.array for z value in float32
+    Returns:    transect : (dict) containing 1D matrix:
+                    'X'        - 1D np.array for X/column coordinates in float32
+                    'Y'        - 1D np.array for Y/row    coordinates in float32
+                    'value'    - 1D np.array for z value in float32
                     'distance' - 1D np.array for distance in float32
 
-    Example: transect = transect_yx(dem, demRsc, [10,15], [100,115])
+    Example: from mintpy.utils import readfile, utils as ut
+             dem, atr = readfile.read('srtm1.dem.wgs84')
+             txn = transect_yx(dem, atr, [10,15], [100,115])
     """
     interpolation = interpolation.lower()
     [y0, x0] = start_yx
@@ -359,7 +361,28 @@ def transect_yx(z, atr, start_yx, end_yx, interpolation='nearest'):
 
 
 def transect_lalo(z, atr, start_lalo, end_lalo, interpolation='nearest'):
-    """Extract 2D matrix (z) value along the line [start_lalo, end_lalo]"""
+    """Extract 2D matrix (z) value along the line [start_lalo, end_lalo]
+
+    Parameters: z        : (np.ndarray) 2D data matrix
+                atr      : (dict) attribute
+                start_yx : (list) y,x coordinate of start point
+                end_yx   : (list) y,x coordinate of end   point
+                interpolation : str, sampling/interpolation method, including:
+                    'nearest' - nearest neighbour
+                    'linear'  - linear  spline interpolation (order of 1)
+                    'cubic'   - cubic   spline interpolation (order of 3)
+                    'quintic' - quintic spline interpolation (order of 5)
+
+    Returns:    transect : (dict) containing 1D matrix:
+                    'X'        - 1D np.array for X/column coordinates in float32
+                    'Y'        - 1D np.array for Y/row    coordinates in float32
+                    'value'    - 1D np.array for z value in float32
+                    'distance' - 1D np.array for distance in float32
+
+    Example: from mintpy.utils import readfile, utils as ut
+             vel, atr = readfile.read('geo_velocity_msk.h5')
+             txn = transect_yx(vel, atr, [30.0, 110.0], [30.2, 111.3])
+    """
     coord = coordinate(atr)
     [y0, y1], [x0, x1] = coord.lalo2yx([start_lalo[0], end_lalo[0]],
                                        [start_lalo[1], end_lalo[1]])

src/mintpy/version.py

@@ -8,6 +8,7 @@
 ###########################################################################
 Tag = collections.namedtuple('Tag', 'version date')
 release_history = (
+    Tag('1.6.0', '2024-05-09'),
     Tag('1.5.3', '2023-11-23'),
     Tag('1.5.2', '2023-08-09'),
     Tag('1.5.1', '2023-01-03'),