update to Keras 2.15

README.md

@@ -23,13 +23,13 @@ $ pip3 install git+https://github.com/tomasplsek/CADET.git
 
 The `pycadet` package requires the following libraries (which should be installed automatically with the package):
 ```
+keras<=2.12
+tensorflow
 numpy
 scipy
 astropy
 matplotlib
-pyds9
 scikit-learn>=1.1
-tensorflow>=2.8
 ```
 
 For Conda environments, it is recommended to install the dependencies beforehand as some of the packages can be tricky to install in an existing environment (especially `tensorflow`) and on some machines (especially new Macs). For machines with dedicated NVIDIA GPUs, `tensorflow-gpu` can be installed to allow the CADET model to leverage the GPU for faster inference.

pycadet/pycadet.py

@@ -505,7 +505,7 @@ def CADET(galaxy, scales=[1,2,3,4], ra="", dec="", th1=0.4, th2=0.7, shift=False
                 ax.quiver(center[0], center[1], np.cos(angle)*a, np.sin(angle)*a, 
                         color='cyan', scale=1, scale_units='xy', angles='xy', zorder=1)
                 ax.quiver(center[0], center[1], -np.sin(angle)*b, np.cos(angle)*b, 
-                        color='cyan', scale=1, scale_units='xy', angles='xy', zorder=1)
+                        color='white', scale=1, scale_units='xy', angles='xy', zorder=1)
 
             ccd = CCDData(cav, unit="adu", wcs=wcs)
             ccd.write(f"{galaxy}/decomposed/{galaxy}_{size}_{i+1}.fits", overwrite=True)

setup.py

@@ -1,9 +1,9 @@
 from pathlib import Path
 from setuptools import setup, find_packages
 
-requirements = ["keras == 2.12",
-                "tensorflow-cpu == 2.12",
-                "scikit-learn >= 1.2",
+requirements = ["keras <= 2.15",
+                "tensorflow",
+                "scikit-learn",
                 "numpy >=1.8",
                 "pandas",
                 "matplotlib", # >= 3.1.1",
@@ -18,7 +18,7 @@
 
 MAJOR = "0"
 MINOR = "2"
-MICRO = "0"
+MICRO = "7"
 version = "%s.%s.%s" % (MAJOR, MINOR, MICRO)
 
 setup(