Merge branch 'gh3'

CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.18)
 
 project(campo
-  VERSION 0.3.10
+  VERSION 0.3.11
   DESCRIPTION "Modelling framework for fields and agents"
   HOMEPAGE_URL "https://campo.computationalgeography.org/"
   LANGUAGES NONE
@@ -15,7 +15,7 @@ set(CMAKE_MODULE_PATH
 
 set(DEV_CURRENT_YEAR "2024")
 
-set(${PROJECT_NAME}_ORGANISATION_NAME "Computational Geography group, Dept of Physical Geography, Utrecht University")
+set(${PROJECT_NAME}_ORGANISATION_NAME "Computational Geography group, Dept. of Physical Geography, Utrecht University")
 set(${PROJECT_NAME}_COPYRIGHT
      "2020 - ${DEV_CURRENT_YEAR}, ${${PROJECT_NAME}_ORGANISATION_NAME}")
 

source/campo/dataset.py

@@ -393,9 +393,10 @@ def write(self, timestep=None):
             if not p in dataset_phenomena:
                 self._generate_lue_phenomenon(self._phenomena[p])
 
-        for pset in self._phenomena[p].property_sets.values():
-            for prop in pset.properties.values():
-                self._lue_write_property(p, pset, prop, timestep)
+        for phen in self._phenomena:
+            for pset in self._phenomena[phen].property_sets.values():
+                for prop in pset.properties.values():
+                    self._lue_write_property(phen, pset, prop, timestep)
 
     def set_time(self, start, unit, stepsize, nrTimeSteps):
         """  """

source/test/test_dynamic_model.py

@@ -18,42 +18,40 @@ def tearDownClass(self):
     def setUpClass(self):
 
         # Some dummy spatial domain
-        with open('locations.csv', 'w') as content:
-            content.write('1,2\n3,4\n5,6\n7,8')
+        with open("locations.csv", "w") as content:
+            content.write("1,2\n3,4\n5,6\n7,8")
 
-        with open('extent.csv', 'w') as content:
+        with open("extent.csv", "w") as content:
             content.write("0,0,30,20,2,3\n")
             content.write("0,0,30,20,2,3\n")
             content.write("0,0,30,20,2,3\n")
             content.write("0,0,30,20,2,3\n")
 
         self.ds = campo.Campo(seed=13)
 
-        self.phen = self.ds.add_phenomenon('phen')
-        self.phen.add_property_set('point', 'locations.csv')
-        self.phen.add_property_set('field', 'extent.csv')
-
+        self.phen = self.ds.add_phenomenon("phen")
+        self.phen.add_property_set("point", "locations.csv")
+        self.phen.add_property_set("field", "extent.csv")
 
+        # dummy time
+        date = datetime.date(2000, 1, 1)
+        time = datetime.time(0, 0)
+        self.start = datetime.datetime.combine(date, time)
+        self.unit = campo.TimeUnit.month
+        self.stepsize = 1
+        self.timesteps = 5
 
     def test_1(self):
-        """ Dynamic model, stationary points and fields """
+        """ Stationary points and fields """
 
         # initial section
         self.phen.point.pdata = 500
         self.phen.field.fdata = 300
 
-        # dummy time
-        date = datetime.date(2000, 1, 1)
-        time = datetime.time(0, 0)
-        start = datetime.datetime.combine(date, time)
-        unit = campo.TimeUnit.month
-        stepsize = 1
-        timesteps = 5
-
         # create the output lue data set
-        self.ds.create_dataset("TestDynamicModel_test_1.lue")
-        self.ds.set_time(start, unit, stepsize, timesteps)
-
+        filename = "TestDynamicModel_test_1.lue"
+        self.ds.create_dataset(filename)
+        self.ds.set_time(self.start, self.unit, self.stepsize, self.timesteps)
 
         self.phen.point.pdata.is_dynamic = True
         self.phen.field.fdata.is_dynamic = True
@@ -62,8 +60,62 @@ def test_1(self):
         self.ds.write()
 
         # dynamic section
-        for timestep in range(1, timesteps + 1):
+        for timestep in range(1, self.timesteps + 1):
             self.phen.point.pdata += 200
             self.phen.field.fdata += 100
 
             self.ds.write(timestep)
+
+        # ldm.assert_is_valid(filename)
+
+    def test_2(self):
+        """ Points and fields different phenomena """
+
+        # initial section
+        ds = campo.Campo(seed=13)
+
+        phen1 = ds.add_phenomenon("phen1")
+        phen2 = ds.add_phenomenon("phen2")
+
+        phen1.add_property_set("point", "locations.csv")
+        phen2.add_property_set("field", "extent.csv")
+
+        phen1.point.pdata = 500
+        phen2.field.fdata = 300
+
+        # create the output lue data set
+        filename = "TestDynamicModel_test_2.lue"
+        ds.create_dataset(filename)
+        ds.set_time(self.start, self.unit, self.stepsize, self.timesteps)
+
+        phen1.point.pdata.is_dynamic = True
+        phen2.field.fdata.is_dynamic = True
+
+        # write after modifying coordinates
+        ds.write()
+
+        # dynamic section
+        for timestep in range(1, self.timesteps + 1):
+            phen1.point.pdata += 200
+            phen2.field.fdata += 100
+            ds.write(timestep)
+
+        dataset = ldm.open_dataset(filename, "r")
+        pset_points = dataset.phenomena["phen1"].property_sets["point"]
+        pset_fields = dataset.phenomena["phen2"].property_sets["field"]
+
+        nr_pagents = len(dataset.phenomena["phen1"].object_id[:])
+        nr_fagents = len(dataset.phenomena["phen2"].object_id[:])
+        self.assertTrue(nr_pagents == 4)
+        self.assertTrue(nr_fagents == 4)
+
+        pvalues = pset_points.pdata.value[:]
+        fvalues = pset_fields.fdata.value[0][:]
+
+        pvalid = np.repeat([700, 900, 1100, 1300, 1500], nr_pagents).reshape(self.timesteps, nr_pagents).T
+        rows = 2
+        cols = 3
+        fvalid = np.repeat([400, 500, 600, 700, 800], rows * cols).reshape(self.timesteps, rows, cols)
+
+        self.assertTrue(np.array_equal(fvalues, fvalid))
+        self.assertTrue(np.array_equal(pvalues, pvalid))