ci template

Author: scivision

.flake8

@@ -1,5 +1,3 @@
 [flake8]
 max-line-length = 132
 exclude = .git,__pycache__,.eggs/,doc/,docs/,build/,dist/,archive/
-per-file-ignores =
-    __init__.py:F401

.github/workflows/ci.yml

@@ -8,14 +8,19 @@ on:
 
 jobs:
 
-  linux:
-    runs-on: windows-latest
+  core:
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        python-version: ["3.10", "3.13"]
+        os: [windows-latest, ubuntu-latest]
 
     steps:
     - uses: actions/checkout@v4
-    - uses: actions/setup-python@v4
+    - uses: actions/setup-python@v5
       with:
-        python-version: 3.x
+        python-version: ${{ matrix.python-version }}
 
     - run: pip install .[tests,lint]
 

README.md

@@ -5,7 +5,7 @@
 
 Utilities for working with Incoherent Scatter Radar data, especially from Poker Flat AMISR.
 
-We work with the complex I+jQ voltage samples, the lowest level data
+We work with the complex `I + jQ` voltage samples, the lowest level data
 available from the radar, on a single pulse basis. Depending on the beam
 pattern and pulse modulation, the per-beam pulse cadence is perhaps on
 the 75 milliscond time scale.

src/isrraw/plots.py

@@ -330,7 +330,7 @@ def plotsnr(snr, fn, P, azel, ctxt=""):
             vmin=vlim[0],
             vmax=vlim[1],
             cmap="cubehelix_r",
-            shading="nearest"
+            shading="nearest",
         )
     except ValueError as e:
         print(e, file=stderr)
@@ -469,7 +469,7 @@ def plotacf(spec: xarray.DataArray, fn: Path, azel, t, dt, P: dict):
         vmin=P["vlimacf"][0],
         vmax=P["vlimacf"][1],
         cmap="cubehelix_r",
-        shading="nearest"
+        shading="nearest",
     )
 
     ytop = min(z[-1], P["zlim"][1]) if P["zlim"][1] is not None else z[-1]
@@ -680,7 +680,7 @@ def plotplasmatime(spec: xarray.DataArray, t, fg, ax, P: dict, ctxt):
         vmin=P["vlim_pl"][0],
         vmax=P["vlim_pl"][1],
         cmap="cubehelix_r",
-        shading="nearest"
+        shading="nearest",
     )
 
     #    h=ax.imshow(spec.freq.data/1e6,srng[zgood],10*log10(spec[zgood,:].data),