andrija: Introduced age and logload as arrays instead of reading them from csv.

data.py

@@ -21,7 +21,6 @@ import nifty7 as ift
 import numpy as np
 
 from binner import bin_1D, bin_2D
-from data_utilities import read_in
 
 
 # define a new metaclass which overrides the "__call__" function
@@ -33,7 +32,7 @@ class ClassLoader(type):
 
 
 class Data(metaclass=ClassLoader):
-    def __init__(self, npix_age, npix_ll, ll_threshold, reshuffle_seed, csv_dataset_path):
+    def __init__(self, npix_age, npix_ll, ll_threshold, reshuffle_seed, age, ll):
         if not isinstance(npix_age, int):
             raise TypeError("Number of pixels argument needs to be of type int.")
 
@@ -46,13 +45,19 @@ class Data(metaclass=ClassLoader):
         if not isinstance(reshuffle_seed, int):
             raise TypeError("Reshuffle iterator argument needs to be of type int.")
 
-        if not isinstance(csv_dataset_path, str):
-            raise TypeError("The dataset file path argument needs to be of type str.")
+        if not isinstance(age, np.ndarray):
+            raise TypeError("The age dataset argument needs to be of type np.ndarray.")
+
+        if not isinstance(ll, np.ndarray):
+            raise TypeError("The ll dataset argument needs to be of type np.ndarray.")
+
+        if not age.size == ll.size:
+            raise TypeError("The dataset has to contain pairs of age and log load data.")
 
         self.npix_age, self.npix_ll = npix_age, npix_ll
         self.ll_threshold = ll_threshold
         self.reshuffle_seed = reshuffle_seed
-        self.csv_dataset_path = csv_dataset_path
+        self.age = age, self.ll = ll
 
         self.age, self.ll = self.filter()
         self.data = None
@@ -65,7 +70,6 @@ class Data(metaclass=ClassLoader):
 
     def filter(self):
         # Loads, filters and reshuffles data
-        self.age, self.ll = read_in(self.csv_dataset_path)
         self.ll, self.age = self.data_filter_x(self.ll_threshold, self.ll, self.age)
 
         if not self.reshuffle_seed == 0: