Edit readme

README.md

@@ -4,9 +4,6 @@ Welcome to the MACE repository!
 
 ***MACE, a Machine-learning Approach to Chemistry Emulation***, by [Maes et al. (*in press.*)](https://ui.adsabs.harvard.edu/abs/2024arXiv240503274M/abstract), is a surrogate model for chemical kinetics. It is developed in the contexts of circumstellar envelopes (CSEs) of asymptotic giant branch (AGB) stars, i.e. evolved low-mass stars.
 
-Currently it still under development.
-Planned release: Sept 2024
-
 MACE is implemented in Python and uses [PyTorch](https://pytorch.org/), together with [torchode](https://github.com/martenlienen/torchode) [(Lienen & Gunnemann, 2022)](https://openreview.net/pdf?id=uiKVKTiUYB0), to be trained.
 
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@@ -38,4 +35,4 @@ The script run.py trains the model, as explained by [Maes et al. (*in press.*)](
 
 
 
-(version 0.0.7)
+(version 0.0.7)

src/mace/utils.py

@@ -115,7 +115,7 @@ def get_specs():
 
     loc_specs = parentpath+'data/rate16.specs'
 
-    specs = np.loadtxt(loc_specs, usecols=(1), dtype=str, skiprows = 1, max_rows=466)  
+    specs = np.loadtxt(loc_specs, usecols=(1), dtype=str, skiprows = 1, max_rows=469)  
 
     specs_dict = dict()
     idx_specs  = dict()