Issue872

hera/measurements/GIS/vector/demography.py

@@ -385,14 +385,19 @@ def calculatePopulationInPolygon(self,
         res_intersect_poly = demography.loc[demography["geometry"].intersection(poly).is_empty == False]
         intersection_poly = res_intersect_poly["geometry"].intersection(poly)
 
+        # Project to a metric CRS for correct area computation (avoid geographic/degree-based area)
+        intersection_area = intersection_poly.to_crs(epsg=ITM).area
+        original_area = res_intersect_poly["geometry"].to_crs(epsg=ITM).area
+        area_fraction = intersection_area / original_area
+
         res_intersection = geopandas.GeoDataFrame.from_dict(
             {"geometry": intersection_poly.geometry,
-             "areaFraction": intersection_poly.area / res_intersect_poly.area})
+             "areaFraction": area_fraction})
 
         for populationType in populationTypes:
             populationType = self.datalayer.populationTypes.get(populationType,populationType)
             if populationType in res_intersect_poly:
-                res_intersection[populationType] = intersection_poly.area / res_intersect_poly.area * res_intersect_poly[populationType]
+                res_intersection[populationType] = area_fraction * res_intersect_poly[populationType]
 
         return res_intersection
 
@@ -857,6 +862,8 @@ def plotPopulationInPolygon(self, intersectionResult, queryPolygon=None,
                 poly_gdf = poly_gdf.set_crs(epsg=inputCRS if isinstance(inputCRS, int) else inputCRS)
                 if outputCRS is not None:
                     poly_gdf = poly_gdf.to_crs(epsg=outputCRS if isinstance(outputCRS, int) else outputCRS)
+            elif outputCRS is not None:
+                poly_gdf = poly_gdf.set_crs(epsg=outputCRS if isinstance(outputCRS, int) else outputCRS)
             poly_gdf.boundary.plot(ax=ax, color="blue", linewidth=2, linestyle="--")
 
         if xlim is not None:

hera/measurements/meteorology/lowfreqdata/analysis.py

@@ -61,7 +61,7 @@ def addDatesColumns(self, data, datecolumn=None, monthcolumn=None):
             datecolumn = 'curdate'
 
         # 🔁 הפיכת datetime לאובייקט נאיבי אם יש timezone
-        if pd.api.types.is_datetime64tz_dtype(curdata[datecolumn]):
+        if isinstance(curdata[datecolumn].dtype, pd.DatetimeTZDtype):
             curdata[datecolumn] = curdata[datecolumn].dt.tz_convert(None)
 
         curdata = curdata.assign(yearonly=curdata[datecolumn].dt.year)

hera/measurements/meteorology/lowfreqdata/presentationLayer.py

@@ -172,7 +172,7 @@ def _getcmap(self,under=False,undercolor='0.9',over=False,overcolor='0.9',alpha=
         cmap : colormap object
         """
 
-        cmap = copy.copy(matplotlib.cm.get_cmap("jet"))
+        cmap = copy.copy(matplotlib.colormaps["jet"])
         if under is not False:
             cmap.set_under(color=undercolor,alpha=alpha)
         if over is not False:
@@ -361,14 +361,20 @@ def plotScatter(self, data, plotField, ax=None, scatter_properties=dict(), ax_fu
 
         # curdata = data.dropna(subset=[plotField])
         curdata = data.copy()
-        curdata[plotField] = curdata[plotField].where(curdata[plotField] > -5000)
+
+        if curdata.empty:
+            return ax
+
+        curdata[plotField] = curdata[plotField].where(curdata[plotField].to_numpy() > -5000).to_numpy()
 
         # curdata = curdata.query("%s > -9990" % plotField)
-        curdata = curdata.assign(curdate=curdata.index)
-        curdata.curdate = pd.to_datetime(curdata.curdate, utc=True)
-        curdata = curdata.assign(houronly=curdata.curdate.dt.hour + curdata.curdate.dt.minute / 60.)
+        curdate_arr = pd.to_datetime(curdata.index.to_numpy(), utc=True)
+        curdata = curdata.assign(
+            curdate=curdate_arr,
+            houronly=curdate_arr.hour + curdate_arr.minute / 60.
+        )
 
-        ax = seaborn.scatterplot(x=curdata['houronly'], y=curdata[plotField], ax=ax, **scatter_props)
+        ax = seaborn.scatterplot(x=curdata['houronly'].to_numpy(), y=curdata[plotField].to_numpy(), ax=ax, **scatter_props)
 
         ax_func_props = dict(self._plotfieldaxfuncdict.get(plotField, dict()))
         ax_func_props.update(self._axfuncdict)

hera/tests/test_demography.py

@@ -94,8 +94,8 @@ def large_polygon_itm():
 
 @pytest.fixture(scope="module")
 def small_polygon_itm():
-    """Polygon strictly inside block 1 (170000-171000, 660000-661000), pop=1000."""
-    return box(170200, 660200, 170800, 660800)
+    """Polygon that partially overlaps synthetic ITM data (only intersects block 1)."""
+    return box(170100, 660100, 170900, 660900)
 
 
 # ---------------------------------------------------------------------------
@@ -649,6 +649,9 @@ def plot(self, dataSourceName=None, extent=None, ax=None,
         class MockTilesToolkit:
             presentation = MockTilesPresentation()
 
+            def getImageFromCorners(self, minx, miny, maxx, maxy, zoomlevel,
+                                    tileServer=None, inputCRS=None, outputCRS=None):
+                return None
             def getImageFromCorners(self, minx, miny, maxx, maxy,
                                     zoomlevel=14, tileServer=None,
                                     inputCRS=None, outputCRS=None):

pytest.ini

@@ -8,4 +8,5 @@ addopts = -v --tb=short
 markers =
     slow: marks tests as slow (deselect with '-m "not slow"')
     integration: marks tests that require MongoDB
+    unit: marks tests as unit tests (no external dependencies)
     notebook: marks notebook execution tests (run with 'make test-notebooks', excluded from 'make test')