From 7cc192f36864ef940aa235af0c4c520e2f929e63 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?K=C3=BChle=2C=20Laura=20Christine=20=28lakue103=29?=
<laura.kuehle@uni-duesseldorf.de>
Date: Wed, 24 Nov 2021 17:02:03 +0100
Subject: [PATCH] Removed unnecessary lines.
---
ANN_Data_Generator.py | 16 +---------------
1 file changed, 1 insertion(+), 15 deletions(-)
diff --git a/ANN_Data_Generator.py b/ANN_Data_Generator.py
index e858ad3..37f5b44 100644
--- a/ANN_Data_Generator.py
+++ b/ANN_Data_Generator.py
@@ -11,13 +11,13 @@ TODO: Fix bug in initialization of input matrix -> Done
TODO: Improve function selection (more even distribution) -> Done
TODO: Add documentation -> Done
TODO: Improve comments -> Done
+TODO: Remove unnecessary lines -> Done
"""
import numpy as np
import os
-import Initial_Condition
import DG_Approximation
import timeit
@@ -237,10 +237,6 @@ class TrainingDataGenerator(object):
Length of cell in grid.
"""
- # Calculating Cell centers for a given 1D domain with n elements, and
- # Calculating Corresponding Legendre Basis Coefficients for given polynomial_degree
- # Create stencil and basis_coefficients for smooth_function mapped onto stencil
-
# Select random cell length
grid_spacing = 2 / (2 ** np.random.randint(3, high=9, size=1))
@@ -287,13 +283,3 @@ class TrainingDataGenerator(object):
for key in data.keys():
name = self._data_dir + '/' + key + '_data.npy'
np.save(name, data[key])
-
-
-# Get Training/Validation Datasets
-np.random.seed(1234)
-# generator = TrainingDataGenerator(functions, left_bound=boundary[0], right_bound=boundary[1])
-# generator = TrainingDataGenerator(functions, left_bound=boundary[0], right_bound=boundary[1])
-
-sample_number = 1000
-# data_1 = generator.build_training_data(sample_number, 0)
-# data_2 = generator.build_training_data(sample_number, 1)
--
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