Fix imports and indentation

pyzebra/__init__.py

@@ -5,6 +5,7 @@ from pyzebra.comm_export import export_comm
 from pyzebra.fit2 import fitccl
 from pyzebra.h5 import *
 from pyzebra.load_1D import load_1D, parse_1D
+from pyzebra.param_study_moduls import add_dict, auto, merge, scan_dict
 from pyzebra.xtal import *
 
 __version__ = "0.1.1"

pyzebra/param_study_moduls.py

@@ -1,12 +1,14 @@
-from load_1D import load_1D
-import pandas as pd
-from mpl_toolkits.mplot3d import Axes3D  # dont delete, otherwise waterfall wont work
-import matplotlib.pyplot as plt
-import matplotlib as mpl
-import numpy as np
 import pickle
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
 import scipy.io as sio
 import uncertainties as u
+from mpl_toolkits.mplot3d import Axes3D  # dont delete, otherwise waterfall wont work
+
+from .load_1D import load_1D
 
 
 def create_tuples(x, y, y_err):
@@ -211,7 +213,7 @@ def save_table(data, filetype, name, path=None):
     if filetype == "json":
         data.to_json((path + name + ".json"))
 
-    def normalize(dict, key, monitor):
+def normalize(dict, key, monitor):
     """Normalizes the measurement to monitor, checks if sigma exists, otherwise creates it
     :arg dict : dictionary to from which to tkae the scan
     :arg key : which scan to normalize from dict1
@@ -227,7 +229,7 @@ def save_table(data, filetype, name, path=None):
 
     return scaled_counts, scaled_sigma
 
-    def merge(dict1, dict2, scand_dict_result, keep=True, monitor=100000):
+def merge(dict1, dict2, scand_dict_result, keep=True, monitor=100000):
     """merges the two tuples and sorts them, if om value is same, Counts value is average
     averaging is propagated into sigma if dict1 == dict2, key[1] is deleted after merging
     :arg dict1 : dictionary to which measurement will be merged