Update example docstrings to reflect osx64/linux64 timings rather tha…

…n arm64

examples/ivp_2d_rayleigh_benard/rayleigh_benard.py

@@ -3,7 +3,7 @@
 This script demonstrates solving a 2D Cartesian initial value problem. It can
 be ran serially or in parallel, and uses the built-in analysis framework to save
 data snapshots to HDF5 files. The `plot_snapshots.py` script can be used to
-produce plots from the saved data. It should take a few cpu-minutes to run.
+produce plots from the saved data. It should take about 5 cpu-minutes to run.
 
 The problem is non-dimensionalized using the box height and freefall time, so
 the resulting thermal diffusivity and viscosity are related to the Prandtl

examples/ivp_2d_shear_flow/shear_flow.py

@@ -4,7 +4,7 @@
 initial value problem. It can be ran serially or in parallel, and uses the
 built-in analysis framework to save data snapshots to HDF5 files. The
 `plot_snapshots.py` script can be used to produce plots from the saved data.
-The simulation should take a few cpu-minutes to run.
+The simulation should take about 10 cpu-minutes to run.
 
 The initial flow is in the x-direction and depends only on z. The problem is
 non-dimensionalized usign the shear-layer spacing and velocity jump, so the

examples/ivp_ball_internally_heated_convection/internally_heated_convection.py

@@ -3,7 +3,7 @@
 This script demonstrates soving an initial value problem in the ball. It can be
 ran serially or in parallel, and uses the built-in analysis framework to save
 data snapshots to HDF5 files. The `plot_ball.py` script can be used to produce
-plots from the saved data. The simulation should take roughly 15 cpu-minutes to run.
+plots from the saved data. The simulation should take roughly 30 cpu-minutes to run.
 
 The strength of gravity is proportional to radius, as for a constant density ball.
 The problem is non-dimensionalized using the ball radius and freefall time, so
@@ -20,9 +20,9 @@
 For incompressible hydro in the ball, we need one tau term each for the velocity
 and temperature. Here we choose to lift them to the original (k=0) basis.
 
-The simulation will run to t=10, about the time for the first convective plumes
-to hit the top boundary. After running this initial simulation, you can restart
-the simulation with the command line option '--restart'.
+The simulation will run to t=20, about the time for the first convective plumes
+to hit the top boundary. After running this initial simulation, you can run the
+simulation for an addition 20 time units with the command line option '--restart'.
 
 To run, restart, and plot using e.g. 4 processes:
     $ mpiexec -n 4 python3 internally_heated_convection.py

examples/ivp_disk_libration/libration.py

@@ -5,7 +5,7 @@
 It can be ran serially or in parallel, and uses the built-in analysis framework
 to save data snapshots to HDF5 files. The `plot_disk.py` and `plot_scalars.py`
 scripts can be used to produce plots from the saved data. The simulation should
-take roughly 10 cpu-minutes to run.
+take roughly 20 cpu-minutes to run.
 
 The problem is non-dimesionalized using the disk radius and librational frequency,
 so the resulting viscosity is related to the Ekman number as:

examples/ivp_shell_convection/shell_convection.py

@@ -3,7 +3,7 @@
 demonstrates solving an initial value problem in the shell. It can be ran serially
 or in parallel, and uses the built-in analysis framework to save data snapshots
 to HDF5 files. The `plot_shell.py` script can be used to produce plots from the
-saved data. The simulation should take about 10 cpu-minutes to run.
+saved data. The simulation should take about 20 cpu-minutes to run.
 
 The problem is non-dimensionalized using the shell thickness and freefall time, so
 the resulting thermal diffusivity and viscosity are related to the Prandtl

examples/ivp_sphere_shallow_water/shallow_water.py

@@ -3,7 +3,7 @@
 script demonstrates solving an initial value problem on the sphere. It can be
 ran serially or in parallel, and uses the built-in analysis framework to save
 data snapshots to HDF5 files. The `plot_sphere.py` script can be used to produce
-plots from the saved data. The simulation should a few cpu-minutes to run.
+plots from the saved data. The simulation should about 5 cpu-minutes to run.
 
 The script implements the test case of a barotropically unstable mid-latitude
 jet from Galewsky et al. 2004 (https://doi.org/10.3402/tellusa.v56i5.14436).