Sweep: finish visualisation about php-dna

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🚀 Here's the PR! #98

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Step 1: 🔎 Searching

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I think are relevant in decreasing order of relevance (click to expand). If some file is missing from here, you can mention the path in the ticket description.

https://github.com/liberu-genealogy/php-dna/blob/a1ce9fbaa7cc46670b2cf5df4ea0dc356cc6f835/src/Visualization.php#L1-L181

php-dna/phpconvcount.py

Lines 1 to 85 in a1ce9fb

	import re
	import ast
	pycodefile = '../Projects/geneology/snps/tests/test_snps.py'
	phpcodefile = 'tests/Snps/SnpsTest.php'
	def normalize_function_name(name):
	# Check if the name is already in camelCase with mixed case
	if any(c.islower() and name[i+1:i+2].isupper() for i, c in enumerate(name[:-1])):
	return name
	# Handle snake_case to camelCase conversion
	name_parts = name.split('_')
	name = name_parts[0] + ''.join(word.strip().capitalize() for word in name_parts[1:])
	return name
	def get_function_names_in_class(python_code, class_name):
	# Parse the Python code using the ast module
	parsed_code = ast.parse(python_code)
	# Initialize variables to track function names
	function_names = []
	# Helper function to extract function names from a class node
	def extract_function_names(class_node):
	names = []
	for node in ast.walk(class_node):
	if isinstance(node, ast.FunctionDef):
	names.append(node.name)
	return names
	# Traverse the parsed code and extract function names within the specified class
	for node in ast.walk(parsed_code):
	if isinstance(node, ast.ClassDef) and node.name == class_name:
	function_names.extend(extract_function_names(node))
	# Return the list of function names
	return function_names
	# Step 1: Read Python Code from the File
	with open(pycodefile, 'r') as python_file:
	python_code = python_file.read()
	# Step 2: Extract Functions within the TestSnps Class
	# Extract function names from the TestSnps class
	python_functions = get_function_names_in_class(python_code, "TestSnps")
	# Step 3: Normalize Python Function Names
	normalized_python_functions = list(set(normalize_function_name(func) for func in python_functions))
	# Step 4: Read PHP Code from the File
	with open(phpcodefile, 'r') as php_file:
	php_code = php_file.read()
	# Step 5: Extract PHP Function Names
	php_functions = re.findall(r'(public|private|protected) function ([a-zA-Z_][a-zA-Z0-9_]*)\(', php_code)
	php_functions = [name for (visibility, name) in php_functions]
	# Step 6: Normalize PHP Function Names
	normalized_php_functions = [normalize_function_name(func) for func in php_functions]
	# Step 7: Compare Python and PHP Function Names
	missing_functions = set(normalized_python_functions) - set(normalized_php_functions)
	extra_functions = set(normalized_php_functions) - set(normalized_python_functions)
	# Count of functions in Python and PHP
	python_function_count = len(normalized_python_functions)
	php_function_count = len(normalized_php_functions)
	# Print the count of functions
	print("Number of Functions in Python:", python_function_count)
	print("Number of Functions in PHP:", php_function_count)
	# print(normalized_python_functions)
	# Print missing functions in PHP compared to Python
	print("\nMissing Functions in PHP:")
	for func in missing_functions:
	print(func)
	print("\nExtra Functions in PHP:")

I also found the following external resources that might be helpful:

Summaries of links found in the content:

https://github.com/apriha/lineage/blob/master/src%2Flineage%2Fvisualization.py:

The page is a Python file named visualization.py from the lineage repository on GitHub. The file contains code for plotting chromosome features. It includes functions like plot_chromosomes, _chromosome_collections, and _patch_chromosomal_features. The code uses the matplotlib library for plotting and pandas and numpy for data manipulation. The file also includes a license and references to the original source of the code. The user wants to convert this Python file to a PHP file named Visualization.php.

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Step 2: ⌨️ Coding

• Create src/Visualization.php ✓ d6a0d56 Edit

Create src/Visualization.php with contents:
• Add necessary PHP libraries or packages at the top of the file for data manipulation and image drawing. Since PHP does not have direct equivalents to `pandas` or `matplotlib`, consider using `league/csv` for CSV manipulation and PHP's built-in `GD` library for image drawing. Use `composer` to require these packages if not already included.
• Implement the `_chromosome_collections` function in PHP within `src/Visualization.php`. This function should iterate over chromosome data and prepare it for visualization. Since PHP does not have a direct equivalent to Python's `pandas.DataFrame`, use associative arrays to represent data frames. Manipulate these arrays to achieve the desired data structure for visualization.
• Implement the `_patch_chromosomal_features` function in PHP within `src/Visualization.php`. This function should manipulate the input data to highlight positions for each chromosome segment or feature. Use associative arrays and standard PHP functions for array manipulation.
• Modify the `plot_chromosomes` function to use PHP's `GD` library for drawing the visualization instead of `matplotlib`. This will involve creating an image resource, setting colors, and drawing rectangles or lines to represent the chromosomes and their features. Use the `image*` functions provided by the `GD` library, such as `imagecreatetruecolor`, `imagecolorallocate`, and `imagerectangle`.
• Ensure that the PHP version of `plot_chromosomes` can save the generated image to a file. Use `imagepng` or `imagejpeg` functions from the `GD` library to save the image.
• Add comments throughout the modified and newly implemented code to explain the logic, especially where PHP's handling of data structures and image drawing differs significantly from Python's approach.

• Running GitHub Actions for src/Visualization.php ✓ Edit

Check src/Visualization.php with contents:

Ran GitHub Actions for d6a0d56d08ab1cb03dc6d074e54d00fa695ec2c7:

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Step 3: 🔁 Code Review

I have finished reviewing the code for completeness. I did not find errors for sweep/finish_visualisation.

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