Merge pull request #81 from SeregaKR/master

Temperature support (updated)

README.md

@@ -83,3 +83,4 @@ Licensed under the BSD 3-Clause "New" or "Revised" License. For details, please
 - [OpenDreamKit](http://opendreamkit.org/) – Horizon 2020 European Research Infrastructure project (676541)
 
 - EPSRC Programme Grant on [Skyrmionics](http://www.skyrmions.ac.uk) (EP/N032128/1)
+- 

mumax3c/scripts/driver.py

@@ -9,6 +9,7 @@ def driver_script(driver, system, compute=None, ovf_format="bin4", **kwargs):
     mx3 = "tableadd(E_total)\n"
     mx3 += "tableadd(dt)\n"
     mx3 += "tableadd(maxtorque)\n"
+
     if isinstance(driver, mc.MinDriver):
         for attr, value in driver:
             if attr != "evolver":
@@ -32,6 +33,9 @@ def driver_script(driver, system, compute=None, ovf_format="bin4", **kwargs):
         mx3 += "tablesave()\n\n"
 
     if isinstance(driver, mc.TimeDriver):
+        # Need temperature only here
+        if system.T > 0:
+            mx3 += f"Temp = {system.T}\n"
         # Extract dynamics equation parameters.
         gamma0 = (
             precession[0].gamma0

mumax3c/tests/test_micromagnetictests.py

@@ -1 +1,32 @@
+import discretisedfield as df
+import micromagneticmodel as mm
+import numpy as np
 from micromagnetictests.calculatortests import *  # noqa: F401,F403
+
+import mumax3c as mc
+
+
+def test_temperature():
+    p1 = (0, 0, 0)
+    p2 = (5e-9, 5e-9, 5e-9)
+    n = (2, 2, 2)
+    Ms = 1e6
+    A = 1e-13
+    region = df.Region(p1=p1, p2=p2)
+    mesh = df.Mesh(region=region, n=n)
+
+    system = mm.System(name="mumax3_temperature")
+    system.energy = mm.Exchange(A=A)
+    system.dynamics = mm.Precession(gamma0=mm.consts.gamma0) + mm.Damping(alpha=1)
+    system.m = df.Field(mesh, nvdim=3, value=(0, 0.1, 1), norm=Ms)
+    system.T = 1000  # Set a high temperature so it is almost random
+    assert f"Temp = {system.T}" in mc.scripts.driver_script(
+        mc.TimeDriver(), system, compute=None, t=1, n=1
+    )
+
+    td = mc.TimeDriver()
+    td.drive(system, t=0.2e-9, n=1)
+
+    # If random then there should be no overall direction
+    assert np.linalg.norm(system.m.orientation.mean()) < 0.5
+    mc.delete(system)