changes

gprMax/cmds_geometry/fractal_box.py

@@ -1,93 +1,93 @@
-"""Class for surface roughness command."""
-from .cmds_geometry import UserObjectGeometry
-from ..exceptions import CmdInputError
-from ..fractals import FractalVolume
-import gprMax.config as config
-
-from tqdm import tqdm
-import numpy as np
-
-
-class FractalBox(UserObjectGeometry):
-    """User class for edge command."""
-
-    def __init__(self, **kwargs):
-        """Constructor."""
-        super().__init__(**kwargs)
-        self.order = 9
-        self.hash = '#fractal_box'
-
-    def create(self, grid, uip):
-        try:
-            p1 = self.kwargs['p1']
-            p2 = self.kwargs['p2']
-            frac_dim = self.kwargs['frac_dim']
-            weighting = np.array(self.kwargs['weighting'])
-            n_materials = self.kwargs['n_materials']
-            mixing_model_id = self.kwargs['mixing_model_id']
-            ID = self.kwargs['id']
-
-        except KeyError:
-            raise CmdInputError(self.__str__() + ' Incorrect parameters')
-
-        try:
-            seed = self.kwargs['seed']
-        except KeyError:
-            seed = None
-
-        # Default is no dielectric smoothing for a fractal box
-        averagefractalbox = False
-
-        # check averaging
-        try:
-            # go with user specified averaging
-            averagefractalbox = self.kwargs['averaging']
-        except KeyError:
-            # if they havent specfied - go with the grid default
-            averagefractalbox = False
-
-        p1, p2 = uip.check_box_points(p1, p2, self.__str__())
-        xs, ys, zs = p1
-        xf, yf, zf = p2
-
-        if frac_dim < 0:
-            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal dimension')
-        if weighting[0] < 0:
-            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the x direction')
-        if weighting[1] < 0:
-            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the y direction')
-        if weighting[2] < 0:
-            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the z direction')
-        if n_materials < 0:
-            raise CmdInputError(self.__str__() + ' requires a positive value for the number of bins')
-
-        # Find materials to use to build fractal volume, either from mixing models or normal materials
-        mixingmodel = next((x for x in grid.mixingmodels if x.ID == mixing_model_id), None)
-        material = next((x for x in grid.materials if x.ID == mixing_model_id), None)
-        nbins = n_materials
-
-        if mixingmodel:
-            if nbins == 1:
-                raise CmdInputError(self.__str__() + ' must be used with more than one material from the mixing model.')
-            # Create materials from mixing model as number of bins now known from fractal_box command
-            mixingmodel.calculate_debye_properties(nbins, grid)
-        elif not material:
-            raise CmdInputError(self.__str__() + ' mixing model or material with ID {} does not exist'.format(mixing_model_id))
-
-        volume = FractalVolume(xs, xf, ys, yf, zs, zf, frac_dim)
-        volume.ID = ID
-        volume.operatingonID = mixing_model_id
-        volume.nbins = nbins
-        volume.seed = seed
-        volume.weighting = weighting
-        volume.averaging = averagefractalbox
-        volume.mixingmodel = mixingmodel
-
-        if config.is_messages():
-            if volume.averaging:
-                dielectricsmoothing = 'on'
-            else:
-                dielectricsmoothing = 'off'
-            tqdm.write('Fractal box {} from {:g}m, {:g}m, {:g}m, to {:g}m, {:g}m, {:g}m with {}, fractal dimension {:g}, fractal weightings {:g}, {:g}, {:g}, fractal seeding {}, with {} material(s) created, dielectric smoothing is {}.'.format(volume.ID, xs * grid.dx, ys * grid.dy, zs * grid.dz, xf * grid.dx, yf * grid.dy, zf * grid.dz, volume.operatingonID, volume.dimension, volume.weighting[0], volume.weighting[1], volume.weighting[2], volume.seed, volume.nbins, dielectricsmoothing))
-
-        grid.fractalvolumes.append(volume)
+"""Class for surface roughness command."""
+from .cmds_geometry import UserObjectGeometry
+from ..exceptions import CmdInputError
+from ..fractals import FractalVolume
+import gprMax.config as config
+
+from tqdm import tqdm
+import numpy as np
+
+
+class FractalBox(UserObjectGeometry):
+    """User class for edge command."""
+
+    def __init__(self, **kwargs):
+        """Constructor."""
+        super().__init__(**kwargs)
+        self.order = 9
+        self.hash = '#fractal_box'
+
+    def create(self, grid, uip):
+        try:
+            p1 = self.kwargs['p1']
+            p2 = self.kwargs['p2']
+            frac_dim = self.kwargs['frac_dim']
+            weighting = np.array(self.kwargs['weighting'])
+            n_materials = self.kwargs['n_materials']
+            mixing_model_id = self.kwargs['mixing_model_id']
+            ID = self.kwargs['id']
+
+        except KeyError:
+            raise CmdInputError(self.__str__() + ' Incorrect parameters')
+
+        try:
+            seed = self.kwargs['seed']
+        except KeyError:
+            seed = None
+
+        # Default is no dielectric smoothing for a fractal box
+        averagefractalbox = False
+
+        # check averaging
+        try:
+            # go with user specified averaging
+            averagefractalbox = self.kwargs['averaging']
+        except KeyError:
+            # if they havent specfied - go with the grid default
+            averagefractalbox = False
+
+        p1, p2 = uip.check_box_points(p1, p2, self.__str__())
+        xs, ys, zs = p1
+        xf, yf, zf = p2
+
+        if frac_dim < 0:
+            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal dimension')
+        if weighting[0] < 0:
+            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the x direction')
+        if weighting[1] < 0:
+            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the y direction')
+        if weighting[2] < 0:
+            raise CmdInputError(self.__str__() + ' requires a positive value for the fractal weighting in the z direction')
+        if n_materials < 0:
+            raise CmdInputError(self.__str__() + ' requires a positive value for the number of bins')
+
+        # Find materials to use to build fractal volume, either from mixing models or normal materials
+        mixingmodel = next((x for x in grid.mixingmodels if x.ID == mixing_model_id), None)
+        material = next((x for x in grid.materials if x.ID == mixing_model_id), None)
+        nbins = n_materials
+
+        if mixingmodel:
+            if nbins == 1:
+                raise CmdInputError(self.__str__() + ' must be used with more than one material from the mixing model.')
+            # Create materials from mixing model as number of bins now known from fractal_box command
+            mixingmodel.calculate_debye_properties(nbins, grid)
+        elif not material:
+            raise CmdInputError(self.__str__() + ' mixing model or material with ID {} does not exist'.format(mixing_model_id))
+
+        volume = FractalVolume(xs, xf, ys, yf, zs, zf, frac_dim)
+        volume.ID = ID
+        volume.operatingonID = mixing_model_id
+        volume.nbins = nbins
+        volume.seed = seed
+        volume.weighting = weighting
+        volume.averaging = averagefractalbox
+        volume.mixingmodel = mixingmodel
+
+        if config.is_messages():
+            if volume.averaging:
+                dielectricsmoothing = 'on'
+            else:
+                dielectricsmoothing = 'off'
+            tqdm.write('Fractal box {} from {:g}m, {:g}m, {:g}m, to {:g}m, {:g}m, {:g}m with {}, fractal dimension {:g}, fractal weightings {:g}, {:g}, {:g}, fractal seeding {}, with {} material(s) created, dielectric smoothing is {}.'.format(volume.ID, xs * grid.dx, ys * grid.dy, zs * grid.dz, xf * grid.dx, yf * grid.dy, zf * grid.dz, volume.operatingonID, volume.dimension, volume.weighting[0], volume.weighting[1], volume.weighting[2], volume.seed, volume.nbins, dielectricsmoothing))
+
+        grid.fractalvolumes.append(volume)