RIP fortran

.coveragerc

@@ -1,8 +1,9 @@
 [run]
 omit = examples/*
        test.py
-       incompressible/setup.py
-       compressible/setup.py
-       lm_atm/setup.py
-       advection_fv4/setup.py
-       plot.py
+       plot.py
+
+[report]
+omit = examples/*
+       test.py
+       plot.py

.travis.yml

@@ -3,13 +3,6 @@ language: python
 python:
   - "3.6"
 
-matrix:
-    include:
-    - env:
-        - MK_ARGS=""
-    - env:
-        - MK_ARGS=fortran
-
 before_install:
   - export PATH=$(echo $PATH | tr ':' "\n" | sed '/\/opt\/python/d' | tr "\n" ":" | sed "s|::|:|g")
 
@@ -26,7 +19,6 @@ install:
 before_script:
   - export PYTHONPATH=$PYTHONPATH:$(pwd)
   - export PYRO_HOME=$(pwd)
-  - ./mk.sh $MK_ARGS
 
 script:
   - flake8 .

README.md

@@ -42,13 +42,13 @@ http://python-hydro.github.io/pyro2/
 	switch to python 3.x
 
   - There are a few steps to take to get things running. You need to
-    make sure you have `numpy`, `f2py`, `matplotlib`, and `h5py`
+    make sure you have `numpy`, `numba`, `matplotlib`, and `h5py`
     installed. On a Fedora system, this can be accomplished by doing:
 
-       `dnf install python3-numpy python3-numpy-f2py python3-matplotlib python3-matplotlib-tk python3-h5py`
+       `dnf install python3-numpy python3-numba python3-matplotlib python3-matplotlib-tk python3-h5py`
 
     (note, for older Fedora releases, replace `dnf` with `yum`.  For
-	python 2.x, leave off the `2` in the package names.)
+	python 2.x, leave off the `3` in the package names.)
 
   - You also need to make sure gfortran is present on you system. On a
     Fedora system, it can be installed as:
@@ -79,10 +79,6 @@ http://python-hydro.github.io/pyro2/
       * Define the environment variable `PYRO_HOME` to point to the
         `pyro2/` directory (only needed for regression testing)
 
-      * Build the Fortran source. In `pyro2/` type
-
-          `./mk.sh`
-
       * Run a quick test of the advection solver:
 
           `./pyro.py advection smooth inputs.smooth`

advection_fv4/fluxes.py

@@ -1,4 +1,4 @@
-import advection_fv4.interface as interface_f
+import advection_fv4.interface as interface
 import mesh.array_indexer as ai
 
 
@@ -77,13 +77,13 @@ def fluxes(my_data, rp, dt):
                              1./12.*(a.jp(-2, buf=1) + a.jp(1, buf=1))
 
     else:
-        a_l, a_r = interface_f.states(a, myg.qx, myg.qy, myg.ng, 1)
+        a_l, a_r = interface.states(a, myg.ng, 1)
         if u > 0:
             a_x = ai.ArrayIndexer(d=a_l, grid=myg)
         else:
             a_x = ai.ArrayIndexer(d=a_r, grid=myg)
 
-        a_l, a_r = interface_f.states(a, myg.qx, myg.qy, myg.ng, 2)
+        a_l, a_r = interface.states(a, myg.ng, 2)
         if v > 0:
             a_y = ai.ArrayIndexer(d=a_l, grid=myg)
         else:

advection_fv4/interface.py

@@ -3,7 +3,7 @@
 
 
 @njit(cache=True)
-def states(a, qx, qy, ng, idir):
+def states(a, ng, idir):
     r"""
     Predict the cell-centered state to the edges in one-dimension using the
     reconstructed, limited slopes. We use a fourth-order Godunov method.
@@ -18,8 +18,6 @@ def states(a, qx, qy, ng, idir):
     ----------
     a : ndarray
         The cell-centered state.
-    qx, qy : int
-        The dimensions of `a`.
     ng : int
         The number of ghost cells
     idir : int
@@ -31,6 +29,8 @@ def states(a, qx, qy, ng, idir):
         The state predicted to the left and right edges.
     """
 
+    qx, qy = a.shape
+
     al = np.zeros((qx, qy))
     ar = np.zeros((qx, qy))
 
@@ -250,8 +250,6 @@ def states_nolimit(a, qx, qy, ng, idir):
     ----------
     a : ndarray
         The cell-centered state.
-    qx, qy : int
-        The dimensions of `a`.
     ng : int
         The number of ghost cells
     idir : int