[FIX] Minor fixes

.tokeignore

@@ -1,2 +1,2 @@
-cloudy-codes/
-tests/astro_plasma
+./cloudy-codes/
+./example-scripts/

README.md

@@ -12,7 +12,7 @@ Running Cloudy models on the fly, especially when there are lot of models to run
 
 ![GitHub repo size](https://img.shields.io/github/repo-size/dutta-alankar/AstroPlasma) |
 ![GitHub repo file count](https://img.shields.io/github/directory-file-count/dutta-alankar/AstroPlasma) |
-![Lines of code](https://img.shields.io/tokei/lines/github.com/dutta-alankar/AstroPlasma)
+[![Lines of code](https://tokei.rs/b1/github/dutta-alankar/AstroPlasma?category=lines)](https://github.com/dutta-alankar/AstroPlasma)
 
 ![GitHub last commit (branch)](https://img.shields.io/github/last-commit/dutta-alankar/AstroPlasma/main) |
 ![GitHub commit activity](https://img.shields.io/github/commit-activity/m/dutta-alankar/AstroPlasma)

astro_plasma/core/datasift.py

@@ -118,7 +118,7 @@ def _process_arguments_flags(
             flags.
 
         """
-        _argument_type = ["nH", "temperature", "metallicity", "redshift"]
+        # _argument_type = ["nH", "temperature", "metallicity", "redshift"]
         _array_argument = [True, True, True, True]  # array to flag which arguments are arrays
         _array_argument[0] = isinstance(nH, list) or isinstance(nH, np.ndarray)
         _array_argument[1] = isinstance(temperature, list) or isinstance(temperature, np.ndarray)
@@ -233,7 +233,8 @@ def _find_all_batches(
                     _argument.append(argument_collection[arg_pos][0])
                 else:
                     _argument.append(argument_collection[arg_pos][indx])
-            _all_batches_all_data = _all_batches_all_data.union(self._find_all_batches_single(*_argument))
+            nH_val, temp_val, met_val, red_val = _argument
+            _all_batches_all_data = _all_batches_all_data.union(self._find_all_batches_single(nH_val, temp_val, met_val, red_val))
         if _all_batches_all_data == set():
             raise ValueError("Problem identifying batches! Code Aborted!")
         return _all_batches_all_data