use spectres_numba if possible

.github/workflows/python-package.yml

@@ -28,8 +28,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip Cython
-        python -m pip install flake8 pytest pytest-cov coverage psutil requests setuptools wheel
-        python -m pip install -r requirements.txt
+        python -m pip install -r requirements-dev.txt
         python -m pip install -e .
     - name: Lint with flake8
       run: |

requirements-dev.txt

@@ -0,0 +1,20 @@
+astropy>=4.3
+astroscrappy>=1.1
+ccdproc>= 2.3
+coverage>=0.38.4
+flake8>=5.0.4
+kaleido>=0.2
+numba>=0.48
+numpy>=1.18
+plotly>=5.6
+psutil>=5.9.4
+pytest>=5.3
+pytest-cov>=2.8
+rascal>=0.3.4
+requests>=2.27
+requests>=2.28.1
+scipy>=1.7
+setuptools>=47.1
+spectres>=2.2.0
+statsmodels>=0.13
+wheel>=0.38.4

src/aspired/flux_calibration.py

@@ -11,7 +11,12 @@
 from plotly import io as pio
 from scipy import signal
 from scipy import interpolate as itp
-from spectres import spectres
+
+try:
+    from spectres import spectres_numba as spectres
+except ImportError as err:
+    print(err)
+    from spectres import spectres
 
 from .spectrum1D import Spectrum1D
 from .util import get_continuum

src/aspired/onedspec.py

@@ -8,7 +8,12 @@
 import numpy as np
 from plotly import graph_objects as go
 from plotly import io as pio
-from spectres import spectres
+
+try:
+    from spectres import spectres_numba as spectres
+except ImportError as err:
+    print(err)
+    from spectres import spectres
 from scipy import optimize
 from scipy.interpolate import interp1d
 

src/aspired/twodspec.py

@@ -15,7 +15,12 @@
 from scipy import ndimage
 from scipy import signal
 from scipy.optimize import curve_fit
-from spectres import spectres
+
+try:
+    from spectres import spectres_numba as spectres
+except ImportError as err:
+    print(err)
+    from spectres import spectres
 from statsmodels.nonparametric.smoothers_lowess import lowess
 
 from .image_reduction import ImageReduction