From 290c68795d8100cc97b8b53d80f331e536fc71b1 Mon Sep 17 00:00:00 2001
From: davidovski <david@sendula.com>
Date: Wed, 30 Nov 2022 10:06:56 +0000
Subject: Added files to repository

---
 src/neuralnetwork/clean_data.py | 59 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 59 insertions(+)
 create mode 100644 src/neuralnetwork/clean_data.py

(limited to 'src/neuralnetwork/clean_data.py')

diff --git a/src/neuralnetwork/clean_data.py b/src/neuralnetwork/clean_data.py
new file mode 100644
index 0000000..345218e
--- /dev/null
+++ b/src/neuralnetwork/clean_data.py
@@ -0,0 +1,59 @@
+import training
+import os
+import sys
+
+if __name__ == "__main__":
+
+    countries = training.get_countries()
+
+    for c, country in countries.items():
+        if c == "uk" or c == "usa":
+
+            # iterate through each dataset separately
+            for dataset, path in country.datasets.items():
+
+                # print information
+                print(f"filtering through {c}'s {dataset}...")
+                sys.stdout.flush()
+
+                names = country.get_names(dataset)
+
+                # store the names that are valid in a seperate list
+                names_output = []
+
+                # load the alphabet file for the country
+                alphabet = []
+
+                with open(os.path.join(country.path, "alphabet.txt"), "r") as file:
+                    for l in file.read().split("\n"):
+                        alphabet.append(l)
+
+                c = 0
+                t = len(names)
+                # iterate through names in the dataset
+                for name in names:
+                    name = country.preprocess(name)
+
+                    valid = True
+
+                    # invalidate the name if a single letter is not in the alphabet
+                    for letter in name:
+                        if not letter in alphabet:
+                            valid = False
+                            break
+
+                    if valid:
+                        names_output.append(name)
+
+                    c += 1
+                    if c % 128 == 0:
+                        print(f"\r{c}/{t}", end="")
+
+                # print how many names are left
+                print(f"kept {len(names_output)}/{len(names)} names")
+
+                # save dataset
+                with open(path, "w") as file:
+                    for name in names_output:
+                        file.write(name)
+                        file.write("\n")
-- 
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