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Assignment 2 #2

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01f0c4e
Assignment-1 Python Revised
drdhennessy Dec 7, 2024
0a2cf67
Assignment 2 Python
drdhennessy Dec 8, 2024
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107 changes: 107 additions & 0 deletions Assignment-1.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n",
"False\n",
"True\n"
]
}
],
"source": [
"# Part 1: Building the base Anagram Checker\n",
"# Given two valid strings, check to see if they are anagrams of each other. \n",
"# If it is, return True, else False. For this part, we can assume that \n",
"# uppercase letters are the same as if it was a lowercase character.\n",
"\n",
"# define a function to check if two strings are anagrams or not: \n",
"def anagram_checker(word_a: str, word_b: str) -> bool:\n",
" # Convert both words to lowercase to ignore case sensitivity\n",
" word_a = word_a.lower()\n",
" word_b = word_b.lower()\n",
"\n",
" # Sort the characters of both words\n",
" word_a_normalized = sorted(word_a)\n",
" word_b_normalized = sorted(word_b)\n",
"\n",
" # Compare the normalized strings\n",
" return word_a_normalized == word_b_normalized\n",
"\n",
"# run the code to check using words below:\n",
"print(anagram_checker(\"Silent\", \"listen\")) # True\n",
"print(anagram_checker(\"Silent\", \"Night\")) # False\n",
"print(anagram_checker(\"night\", \"Thing\")) # True"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n",
"False\n"
]
}
],
"source": [
"# Part 2: Expanding the functionality of the Anagram Checker\n",
"# Using your existing and functional anagram checker, let's add a boolean \n",
"# option called is_case_sensitive, which will return True or False based on if\n",
"# the two compared words are anagrams and if we are checking for case \n",
"# sensitivity. \n",
"\n",
"\n",
"# define a function to check if two strings are anagrams or not using a boolean:\n",
"def anagram_checker(word_a: str, word_b: str, is_case_sensitive: bool) -> bool:\n",
" \n",
" # if not case sensitive, convert both words to lowercase:\n",
" if not is_case_sensitive:\n",
" word_a = word_a.lower()\n",
" word_b = word_b.lower()\n",
" \n",
" # sort the characters of both words:\n",
" word_a_normalized = sorted(word_a)\n",
" word_b_normalized = sorted(word_b)\n",
" \n",
" # compare the normalized strings:\n",
" return word_a_normalized == word_b_normalized\n",
"\n",
"# run the code to check using words below:\n",
"print(anagram_checker(\"Silent\", \"listen\", False)) # True\n",
"print(anagram_checker(\"Silent\", \"listen\", True)) # False"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "dsi_participant",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
199 changes: 199 additions & 0 deletions Assignment-2.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"#1. Reading and Displaying Data from the First File: \n",
"\n",
"all_paths = [\n",
" \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_02.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_03.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_04.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_05.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_06.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_07.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_08.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_09.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_10.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_11.csv\",\n",
" \"../../05_src/data/assignment_2_data/inflammation_12.csv\"\n",
"]\n",
"\n",
"# Reading and displaying data from the first file\n",
"with open(all_paths[0], 'r') as f:\n",
" contents = f.readlines()\n",
"\n",
" for line in contents:\n",
" print(line.strip()) # strip is used to remove whitespaces"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"60\n"
]
}
],
"source": [
"#2. Data Summarization Function: \n",
"\n",
"import numpy as np\n",
"\n",
"def patient_summary(file_path, operation):\n",
" # Load the data from the file\n",
" data = np.loadtxt(fname=file_path, delimiter=',')\n",
" ax = 1 # This specifies that the operation should be done for each row (patient)\n",
"\n",
" # Implement the specific operation based on the 'operation' argument\n",
" if operation == 'mean':\n",
" summary_values = np.mean(data, axis=ax)\n",
" elif operation == 'max':\n",
" summary_values = np.max(data, axis=ax)\n",
" elif operation == 'min':\n",
" summary_values = np.min(data, axis=ax)\n",
" else:\n",
" # If the operation is not one of the expected values, raise an error\n",
" raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\")\n",
"\n",
" return summary_values\n",
"\n",
"# Test it out on the data file we read in and make sure the size is \n",
"# what we expect i.e., 60\n",
"data_min = patient_summary(all_paths[0], 'min')\n",
"print(len(data_min)) "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"#3. Error Detection in Patient Data:\n",
"\n",
"def check_zeros(x):\n",
" '''\n",
" Given an array, x, check whether any values in x equal 0.\n",
" Return True if any values found, else returns False.\n",
" '''\n",
" flag = np.where(x == 0)[0]\n",
" return len(flag) > 0\n",
"\n",
"def detect_problems(file_path):\n",
" # Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
" means = patient_summary(file_path, 'mean')\n",
" return check_zeros(means)\n",
"\n",
"# Test out your code here\n",
"# Your output for the first file should be False\n",
"print(detect_problems(all_paths[0])) \n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "dsi_participant",
"language": "python",
"name": "python3"
},
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"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
}
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"nbformat": 4,
"nbformat_minor": 2
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