renoir.analyzer

Artist analysis module for renoir.

This module provides functions for extracting and analyzing artist-specific works from the WikiArt dataset, designed for educational use in computational design and digital humanities courses.

class renoir.analyzer.ArtistAnalyzer(cache_dir=None)

Bases: object

Analyze artist-specific works from the WikiArt dataset.

This class provides methods to extract works by specific artists and analyze their metadata (genres, styles, periods). Designed for teaching data analysis to art and design students.

Examples

>>> analyzer = ArtistAnalyzer()
>>> works = analyzer.extract_artist_works('claude-monet')
>>> print(f"Found {len(works)} works by Monet")
>>> genres = analyzer.analyze_genres(works)
>>> print(f"Main genre: {genres[0]}")

extract_artist_works(artist_name, limit=None)

Extract all works by a specific artist from WikiArt.

Parameters:

• artist_name (str) – Artist name as it appears in WikiArt (e.g., ‘claude-monet’)

• limit (Optional[int]) – Optional maximum number of works to return

Return type:

List[Dict[str, Any]]

Returns:

List of dictionaries containing artwork data (image, metadata)

Raises:

• ValueError – If artist_name is empty or invalid

• ValueError – If limit is negative

Examples

>>> analyzer = ArtistAnalyzer()
>>> monet_works = analyzer.extract_artist_works('claude-monet', limit=10)
>>> print(monet_works[0].keys())
dict_keys(['image', 'artist', 'title', 'style', 'genre', 'date'])

analyze_genres(works)

Analyze genre distribution in a collection of works.

Parameters:

works (List[Dict[str, Any]]) – List of artwork dictionaries

Return type:

List[tuple]

Returns:

List of (genre, count) tuples, sorted by frequency

Raises:

• ValueError – If works is not a list

• TypeError – If works contains non-dict elements

Examples

>>> works = analyzer.extract_artist_works('claude-monet')
>>> genres = analyzer.analyze_genres(works)
>>> print(f"Most common genre: {genres[0][0]} ({genres[0][1]} works)")

analyze_styles(works)

Analyze style distribution in a collection of works.

Parameters:

works (List[Dict[str, Any]]) – List of artwork dictionaries

Return type:

List[tuple]

Returns:

List of (style, count) tuples, sorted by frequency

Raises:

• ValueError – If works is not a list

• TypeError – If works contains non-dict elements

Examples

>>> works = analyzer.extract_artist_works('pablo-picasso')
>>> styles = analyzer.analyze_styles(works)
>>> for style, count in styles[:3]:
...     print(f"{style}: {count} works")

analyze_temporal_distribution(works)

Analyze the temporal distribution of works by decade.

Parameters:

works (List[Dict[str, Any]]) – List of artwork dictionaries

Return type:

Dict[str, int]

Returns:

Dictionary mapping decades to work counts

Examples

>>> works = analyzer.extract_artist_works('vincent-van-gogh')
>>> decades = analyzer.analyze_temporal_distribution(works)
>>> for decade, count in sorted(decades.items()):
...     print(f"{decade}s: {count} works")

get_work_summary(works)

Generate a comprehensive summary of a collection of works.

Parameters:

works (List[Dict[str, Any]]) – List of artwork dictionaries

Return type:

Dict[str, Any]

Returns:

Dictionary with summary statistics

Examples

>>> works = analyzer.extract_artist_works('edvard-munch')
>>> summary = analyzer.get_work_summary(works)
>>> print(f"Total works: {summary['total_works']}")
>>> print(f"Main style: {summary['primary_style']}")

plot_genre_distribution(artist_name, limit=None, save_path=None, figsize=(10, 6))

Plot genre distribution for a specific artist as a bar chart.

Parameters:

• artist_name (str) – Artist name as it appears in WikiArt

• limit (Optional[int]) – Optional limit on number of works to analyze

• save_path (Optional[str]) – Optional path to save the figure

• figsize (tuple) – Figure size as (width, height)

Return type:

None

Example

>>> analyzer = ArtistAnalyzer()
>>> analyzer.plot_genre_distribution('pierre-auguste-renoir')

plot_style_distribution(artist_name, limit=None, save_path=None, figsize=(10, 6))

Plot style distribution for a specific artist as a bar chart.

Parameters:

• artist_name (str) – Artist name as it appears in WikiArt

• limit (Optional[int]) – Optional limit on number of works to analyze

• save_path (Optional[str]) – Optional path to save the figure

• figsize (tuple) – Figure size as (width, height)

Return type:

None

Example

>>> analyzer = ArtistAnalyzer()
>>> analyzer.plot_style_distribution('pablo-picasso')

compare_artists_genres(artist_names, limit=None, save_path=None, figsize=(12, 8))

Compare genre distributions across multiple artists.

Parameters:

• artist_names (List[str]) – List of artist names to compare

• limit (Optional[int]) – Optional limit on number of works per artist

• save_path (Optional[str]) – Optional path to save the figure

• figsize (tuple) – Figure size as (width, height)

Return type:

None

Example

>>> analyzer = ArtistAnalyzer()
>>> analyzer.compare_artists_genres(['claude-monet', 'pierre-auguste-renoir', 'edgar-degas'])

create_artist_overview(artist_name, limit=None, save_path=None, figsize=(14, 10))

Create a comprehensive overview visualization for an artist.

Includes genre distribution, style distribution, and temporal analysis in a multi-panel figure.

Parameters:

• artist_name (str) – Artist name as it appears in WikiArt

• limit (Optional[int]) – Optional limit on number of works to analyze

• save_path (Optional[str]) – Optional path to save the figure

• figsize (tuple) – Figure size as (width, height)

Return type:

None

Example

>>> analyzer = ArtistAnalyzer()
>>> analyzer.create_artist_overview('vincent-van-gogh')

renoir.analyzer.quick_analysis(artist_name, limit=None, show_summary=True, show_plots=False)

Quick function to analyze an artist’s works with minimal setup.

This is a convenience function for beginners, combining extraction and analysis in a single call.

Parameters:

• artist_name (str) – Artist name as it appears in WikiArt

• limit (Optional[int]) – Optional maximum number of works to retrieve

• show_summary (bool) – If True, print a summary of the results

• show_plots (bool) – If True, display visualization plots (requires matplotlib)

Return type:

List[Dict[str, Any]]

Returns:

List of artwork dictionaries

Examples

>>> works = quick_analysis('claude-monet', limit=20)
Loading WikiArt dataset...
✓ Loaded 103250 artworks
✓ Found 20 works by claude-monet

Artist Summary: - Total works: 20 - Primary style: Impressionism - Primary genre: landscape - Date range: 1865-1926

>>> works = quick_analysis('claude-monet', limit=20, show_plots=True)
# Displays visualization plots