Adjusted code according to changes within py_tools_ds.

Updated __version__ and __versionalias__.

geoarray/__init__.py

@@ -2,8 +2,8 @@
 
 __author__ = """Daniel Scheffler"""
 __email__ = 'danschef@gfz-potsdam.de'
-__version__ = '0.5.7'
-__versionalias__ = 'v20170819.01'
+__version__ = '0.5.8'
+__versionalias__ = 'v20170819.02'
 
 
 from .baseclasses import GeoArray

geoarray/baseclasses.py

@@ -34,7 +34,6 @@ from py_tools_ds.geo.vector.topology \
     import get_footprint_polygon, polyVertices_outside_poly, fill_holes_within_poly
 from py_tools_ds.geo.vector.geometry import boxObj
 from py_tools_ds.io.raster.gdal import get_GDAL_ds_inmem
-from py_tools_ds.numeric.array import find_noDataVal
 from py_tools_ds.compatibility.python.exceptions \
     import TimeoutError as TimeoutError_comp, FileNotFoundError as FileNotFoundError_comp
 from py_tools_ds.compatibility.gdal import get_gdal_func
@@ -342,7 +341,7 @@ class GeoArray(object):
             if not self.is_inmem:
                 self.set_gdalDataset_meta()
             if self._nodata is None:
-                self._nodata = find_noDataVal(self)
+                self._nodata = self.find_noDataVal()
                 if self._nodata == 'ambiguous':
                     warnings.warn('Nodata value could not be clearly identified. It has been set to None.')
                     self._nodata = None
@@ -451,8 +450,8 @@ class GeoArray(object):
                 self._footprint_poly = self.box.mapPoly
             else:
                 try:
-                    multipolygon = raster2polygon(self, exact=False, progress=self.progress, q=self.q,
-                                                  maxfeatCount=10, timeout=3)
+                    multipolygon = raster2polygon(self.mask_nodata.astype(np.uint8), self.gt, self.prj, exact=False,
+                                                  progress=self.progress, q=self.q, maxfeatCount=10, timeout=3)
                     self._footprint_poly = fill_holes_within_poly(multipolygon)
                 except (RuntimeError, TimeoutError, TimeoutError_comp):
                     if not self.q:
@@ -650,6 +649,37 @@ class GeoArray(object):
                                    np.all(np.where(arr == self.nodata, 0, 1), axis=2).astype(np.bool)
 
 
+    def find_noDataVal(self, bandIdx=0, sz=3):
+        """Tries to derive no data value from homogenious corner pixels within 3x3 windows (by default).
+        :param bandIdx:
+        :param sz: window size in which corner pixels are analysed
+        """
+        get_mean_std = lambda corner_subset: {'mean': np.mean(corner_subset), 'std': np.std(corner_subset)}
+
+        wins = [self[0:sz, 0:sz, bandIdx], self[0:sz, -sz:, bandIdx],
+                self[-sz:, -sz:, bandIdx], self[-sz:, 0:sz, bandIdx]]  # UL, UR, LR, LL
+        means_stds = [get_mean_std(win) for win in wins]
+
+        possVals = [i['mean'] for i in means_stds if i['std'] == 0]
+        # possVals==[]: all corners are filled with data; np.std(possVals)==0: noDataVal clearly identified
+
+        if possVals:
+            if np.std(possVals) != 0:
+                # different possible nodata values have been found in the image corner
+                return 'ambiguous'
+            else:
+                if len(possVals) <= 2:
+                    # each window in each corner
+                    warnings.warn("\nAutomatic nodata value detection returned the value %s for GeoArray '%s' but this "
+                                  "seems to be unreliable (occurs in only %s). To avoid automatic detection, just pass "
+                                  "the correct nodata value." % (possVals[0], self.basename,
+                                                                 ('2 image corners' if len(
+                                                                     possVals) == 2 else '1 image corner')))
+                return possVals[0]
+        else:
+            return None
+
+
     def set_gdalDataset_meta(self):
         """Retrieves GDAL metadata from file. This function is only executed once to avoid overwriting of user defined
          attributes, that are defined after object instanciation.
@@ -1337,6 +1367,8 @@ class GeoArray(object):
         #
         # return sub_gA if return_GeoArray else (sub_gA.arr, sub_gA.gt, sub_gA.prj)
 
+    def reproject(self, **kwargs_warp):
+        raise NotImplementedError() # TODO
 
     def reproject_to_new_grid(self, prototype=None, tgt_prj=None, tgt_xygrid=None, rspAlg='cubic', CPUs=None):
         """Reproject all array-like attributes to a given target grid.

requirements.txt

-py_tools_ds>=0.4.1
+py_tools_ds>=0.4.2
 numpy
 matplotlib
 six

setup.py

@@ -11,17 +11,17 @@ with open('HISTORY.rst') as history_file:
     history = history_file.read()
 
 requirements = [
-    'py_tools_ds>=0.4.1', 'numpy', 'matplotlib', 'six', 'gdal', 'shapely', 'geopandas', 'dill', 'mpld3', 'geojson',
+    'py_tools_ds>=0.4.2', 'numpy', 'matplotlib', 'six', 'gdal', 'shapely', 'geopandas', 'dill', 'mpld3', 'geojson',
     'folium', 'scikit-image'
     #'holoviews', #  conda install --yes -c ioam bokeh holoviews=1.8.0 ; \
-    # git+https://github.com/matplotlib/basemap.git
+    # git+https://github.com/matplotlib/basemap.git  # conda install --yes -c conda-forge basemap
     ]
 
 test_requirements = ["coverage"]
 
 setup(
     name='geoarray',
-    version='0.5.7',
+    version='0.5.8',
     description="Fast Python interface for geodata - either on disk or in memory.",
     long_description=readme + '\n\n' + history,
     author="Daniel Scheffler",