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/util.py | 185 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 185 insertions(+)
 create mode 100644 src/neuralnetwork/util.py

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

diff --git a/src/neuralnetwork/util.py b/src/neuralnetwork/util.py
new file mode 100644
index 0000000..268819e
--- /dev/null
+++ b/src/neuralnetwork/util.py
@@ -0,0 +1,185 @@
+import sqlite3
+import tensorflow as tf
+from pincelate import Pincelate
+from multiprocessing import Value
+import random
+
+"""Atomic Number
+A multiprocessing-safe Number that you can increment and set a value to.
+"""
+class AtomicNumber:
+    def __init__(self, initial=0):
+        # set the initial value of the number
+        self._v = Value("d", initial)
+
+        # use python thread locks
+        self._lock = self._v.get_lock()
+
+    def set(self, num):
+        with self._lock:
+            # set the value of the number and return it
+            self._v.value = num
+            return self._v.value
+
+    def increment(self, num=1):
+        with self._lock:
+            # increase the value of the number and then return it
+            self._v.value += num
+            return self._v.value
+
+    def get(self):
+        return self._v.value
+
+
+""" Capitalise the first letter of a name
+    Args:
+        name: (str) the name to transform
+    Returns:
+        name: (str) the output name
+"""
+
+
+def capitalise(name):
+    return str(name).capitalize()
+
+
+""" uncapitalise the first letter of a name
+    Args:
+        name: (str) the name to transform
+    Returns:
+        name: (str) the output name
+"""
+
+
+def uncapitalise(name):
+    return str(name).lower()
+
+
+# import pincelate
+
+# tell tensorflow to only log ERRORS rather than all problems
+tf.get_logger().setLevel('ERROR')
+
+pin = Pincelate()
+
+""" Transliterate names into their phonetic spelling 
+    Args:
+        name: (str) the name to transliterate
+    Returns:
+        name: (str) the pronunciation of the name as an arpabet list
+"""
+
+
+def transliterate(name):
+    output = []
+
+    # iterate through each word and sound out separately
+    for word in name.split(" "):
+        try:
+            for phoneme in pin.soundout(word):
+                output.append(phoneme)
+        except Exception as e:
+            output.append(word)
+        output.append(" ")
+
+    # remove the trailing " "
+    output.pop()
+
+    return output
+
+
+""" Transliterate phonetic spellings back into names
+    Args:
+        name: (str) the pronunciation of the name as an arpabet list
+    Returns:
+        name: (str) a guessed spelling of the given phoneme list
+"""
+
+
+def reverse_transliterate(name):
+    words = []
+
+    current_word = []
+    # iterate through all phonemes, spliting groups between " " into words
+    for phoneme in name:
+        if phoneme == " ":
+            words.append(current_word)
+
+            # reset current word
+            current_word = []
+        else:
+            current_word.append(phoneme)
+
+    # add whats left of the current word to the list of words
+    words.append(current_word)
+
+    # spell each word separately
+    spellings = [pin.spell(word) for word in words]
+    return " ".join(spellings)
+
+
+"""Load random line from a given filename
+"""
+
+
+def get_random_line(file_name):
+    total_bytes = os.stat(file_name).st_size
+    random_point = random.randint(0, total_bytes)
+    file = open(file_name)
+    file.seek(random_point)
+    file.readline()  # skip this line to clear the partial line
+    return file.readline()
+
+
+""" Concatenate elemnts of a list
+    Args:
+        name: (str[]) the letters of a name in an array 
+    Returns:
+        name: (str) 
+"""
+
+
+def deserialise(name):
+    return "".join(name)
+
+
+""" return a random item from a dictionary of weighted items
+    Args:
+        weights: (dict) a dictionary containing the items as keys and float values as weights
+    Returns:
+        item: a random item selected from the dictionary
+"""
+
+
+def weighted_choice(weights):
+    # choose a randm number between 0 and 1
+    choice = random.uniform(0.0, 1.0)
+
+    # iterate through weights, subtracting the weight from the choice each time
+    for item, weight in weights.items():
+        choice -= weight
+
+        # if we are currently on the chosen item, return it
+        if choice < 0:
+            return item
+
+    # in case the input dictionary is incorrectly setup, return the last item
+    return list(weights)[-1]
+
+
+def create_table(database_path):
+    # connect to the database and get the cursor
+    connection = sqlite3.connect(database_path)
+
+    # always close the connection at the end
+    with connection:
+        cursor = connection.cursor()
+
+        cursor.execute("CREATE TABLE IF NOT EXISTS names (\
+                                Name TEXT,\
+                                Origin TEXT,\
+                                Category TEXT\
+                                )")
+
+        # commit the changes, saving them
+        connection.commit()
-- 
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