Add max scattering option (#76)

* Fixed some incorrect units in the metadata generator.
* Added a max_diameter option
* Switched to conda-forge for most software installs.

continuous_integration/install.sh

@@ -31,8 +31,9 @@ conda create -n testenv --yes pip python=$PYTHON_VERSION
 source activate testenv
 
 # Install dependencies
-conda install -c conda-forge numpy
-conda install -c conda-forge pytest pytest-cov sphinx_rtd_theme numpy scipy matplotlib netcdf4 nose sphinx numpydoc hdf4=4.2.12 pytmatrix
+
+conda install -c conda-forge pytmatrix pytest pytest-cov sphinx_rtd_theme numpy scipy matplotlib netcdf4 nose sphinx numpydoc hdf4=4.2.12
+
 pip install sphinx-gallery nose-cov
 
 if [[ $PYTHON_VERSION == '2.7' ]]; then

pydsd/DropSizeDistribution.py

@@ -144,7 +144,9 @@ def set_scattering_temperature_and_frequency(
         self.scattering_temp = scattering_temp
         self.m_w = dielectric.get_refractivity(scattering_freq, scattering_temp)
 
-    def calculate_radar_parameters(self, dsr_func=DSR.bc, scatter_time_range=None):
+    def calculate_radar_parameters(
+        self, dsr_func=DSR.bc, scatter_time_range=None, max_diameter=9.0
+    ):
         """ Calculates radar parameters for the Drop Size Distribution.
 
         Calculates the radar parameters and stores them in the object.
@@ -164,7 +166,9 @@ def calculate_radar_parameters(self, dsr_func=DSR.bc, scatter_time_range=None):
                 Parameter to restrict the scattering to a time interval. The first element is the start time,
                 while the second is the end time.
         """
-        self._setup_scattering(SPEED_OF_LIGHT / self.scattering_freq * 1000.0, dsr_func)
+        self._setup_scattering(
+            SPEED_OF_LIGHT / self.scattering_freq * 1000.0, dsr_func, max_diameter
+        )
         self._setup_empty_fields()
 
         if scatter_time_range is None:
@@ -221,28 +225,31 @@ def _setup_empty_fields(self):
                 param, np.ma.zeros(self.numt)
             )
 
-    def _setup_scattering(self, wavelength, dsr_func):
+    def _setup_scattering(self, wavelength, dsr_func, max_diameter):
         """ Internal Function to create scattering tables.
 
         This internal function sets up the scattering table. It takes a
         wavelength as an argument where wavelength is one of the pytmatrix
         accepted wavelengths.
 
         Parameters:
-        -----------
+
             wavelength : tmatrix wavelength
                 PyTmatrix wavelength.
             dsr_func : function
                 Drop Shape Relationship function. Several built-in are available in the `DSR` module.
+            max_diameter: float
+                Maximum drop diameter to generate scattering table for. 
 
         """
         self.scatterer = Scatterer(wavelength=wavelength, m=self.m_w)
         self.scatterer.psd_integrator = PSDIntegrator()
         self.scatterer.psd_integrator.axis_ratio_func = lambda D: 1.0 / dsr_func(D)
         self.dsr_func = dsr_func
-        self.scatterer.psd_integrator.D_max = 10.0
+        self.scatterer.psd_integrator.D_max = max_diameter
         self.scatterer.psd_integrator.geometries = (
-            tmatrix_aux.geom_horiz_back, tmatrix_aux.geom_horiz_forw
+            tmatrix_aux.geom_horiz_back,
+            tmatrix_aux.geom_horiz_forw,
         )
         self.scatterer.or_pdf = orientation.gaussian_pdf(20.0)
         self.scatterer.orient = orientation.orient_averaged_fixed
@@ -316,8 +323,12 @@ def calculate_dsd_parameterization(self, method="bringi"):
                 np.array(self.diameter["data"]) ** 3,
             )
             self.fields["D0"]["data"][t] = self._calculate_D0(self.Nd["data"][t])
-            self.fields["Nw"]["data"][t] = 256.0 / (np.pi * rho_w) * np.divide(
-                self.fields["W"]["data"][t], self.fields["Dm"]["data"][t] ** 4
+            self.fields["Nw"]["data"][t] = (
+                256.0
+                / (np.pi * rho_w)
+                * np.divide(
+                    self.fields["W"]["data"][t], self.fields["Dm"]["data"][t] ** 4
+                )
             )
 
             self.fields["Dmax"]["data"][t] = self.__get_last_nonzero(self.Nd["data"][t])
@@ -426,12 +437,17 @@ def calculate_RR(self):
             #    np.array(self.diameter['data'])**3)
             velocity = 9.65 - 10.3 * np.exp(-0.6 * self.diameter["data"])
             velocity[0] = 0.5
-            self.fields["rain_rate"]["data"][t] = 0.6 * np.pi * 1e-03 * np.sum(
-                self._mmultiply(
-                    velocity,
-                    self.Nd["data"][t],
-                    self.spread["data"],
-                    np.array(self.diameter["data"]) ** 3,
+            self.fields["rain_rate"]["data"][t] = (
+                0.6
+                * np.pi
+                * 1e-03
+                * np.sum(
+                    self._mmultiply(
+                        velocity,
+                        self.Nd["data"][t],
+                        self.spread["data"],
+                        np.array(self.diameter["data"]) ** 3,
+                    )
                 )
             )
 

pydsd/utility/metadata.json

@@ -20,7 +20,7 @@
     "Nw":
     {
         "standard_name": "normalized_intercept_parameter",
-        "units": "?",
+        "units": "mm-1 m-3",
         "long_name" :"Normalized Intercept Parameter of a Normalized Gaussian Distribution"
     },
     "Nt":
@@ -32,7 +32,7 @@
     "N0":
     {
         "standard_name": "intercept_parameter",
-        "units": "?",
+        "units": "mm-1 m-3",
         "long_name" :"Intercept Parameter of Modeled Drop Size Distribution"
     },
     "W":
@@ -79,7 +79,7 @@
     "Kdp":
     {
         "standard_name": "specific_differential_phase",
-        "units": "deg",
+        "units": "deg/km",
         "long_name" :"Specific Differential Phase from Drop Size Distribution"
     },
     "Ai":