Merge remote-tracking branch 'origin/master'

docs/source/input.rst

@@ -264,7 +264,7 @@ Allows you to introduce a material into the model described by a set of constitu
 * ``f1`` is the relative permittivity, :math:`\epsilon_r`
 * ``f2`` is the conductivity (Siemens/metre), :math:`\sigma`
 * ``f3`` is the relative permeability, :math:`\mu_r`
-* ``f4`` is the magnetic conductivity, :math:`\sigma_*`
+* ``f4`` is the magnetic loss (Ohms/metre), :math:`\sigma_*`
 * ``str1`` is an identifier for the material.
 
 For example ``#material: 3 0.01 1 0 my_sand`` creates a material called ``my_sand`` which has a relative permittivity (frequency independent) of :math:`\epsilon_r = 3`, a conductivity of :math:`\sigma = 0.01` S/m, and is non-magnetic, i.e. :math:`\mu_r = 1` and :math:`\sigma_* = 0`

gprMax/gprMax.py

@@ -258,7 +258,7 @@ def run_model(args, modelrun, numbermodelruns, inputfile, inputdirectory):
                 dielectricsmoothing = 'dielectric smoothing permitted.'
             else:
                 dielectricsmoothing = 'dielectric smoothing not permitted.'
-            print('{:3}\t{:12}\tepsr={:4.2f}, sig={:.3e} S/m; mur={:4.2f}, sig*={:.3e} S/m; '.format(material.numID, material.ID, material.er, material.se, material.mr, material.sm) + tmp + dielectricsmoothing)
+            print('{:3}\t{:12}\tepsr={:4.2f}, sig={:.3e} S/m; mur={:4.2f}, sig*={:.3e} Ohms/m; '.format(material.numID, material.ID, material.er, material.se, material.mr, material.sm) + tmp + dielectricsmoothing)
     
     # Write files for any geometry views
     if G.geometryviews:

gprMax/waveforms.py

@@ -43,10 +43,14 @@ class Waveform:
         Returns:
             waveform (float): Calculated value for waveform.
         """
-        
+        if self.type == 'gaussiandotdot' or self.type == 'gaussiandotdotnorm' or self.type == "ricker":
-        chi = 1 / self.freq
+            chi = np.sqrt(2) / self.freq
-        zeta = 2 * np.pi * np.pi * self.freq * self.freq
+            zeta = 2 * np.pi * np.pi * self.freq * self.freq /2
-        delay = time - chi
+            delay = time - chi
+        else:
+            chi = 1 / self.freq
+            zeta = 2 * np.pi * np.pi * self.freq * self.freq
+            delay = time - chi
 
         if self.type == 'gaussian':
             waveform = np.exp(-zeta * delay * delay)