o si@sdZddlZddlmZidddddddd d d d d d dddddddddddddddddddddd diZd!d"Zd#d$Zd%d&Zd'd(Zd)d*Z dS)+a Key Detection involves determining the underlying key (distribution of notes and note transitions) in a piece of music. Key detection algorithms are evaluated by comparing their estimated key to a ground-truth reference key and reporting a score according to the relationship of the keys. Conventions ----------- Keys are represented as strings of the form ``'(key) (mode)'``, e.g. ``'C# major'`` or ``'Fb minor'``. The case of the key is ignored. Note that certain key strings are equivalent, e.g. ``'C# major'`` and ``'Db major'``. The mode may only be specified as either ``'major'`` or ``'minor'``, no other mode strings will be accepted. Metrics ------- * :func:`mir_eval.key.weighted_score`: Heuristic scoring of the relation of two keys. N)utilczc#dbdzd#ebefzf#gbgzg#aba za# bbb xcCst|dkrt|r|dkstd||dkrM|\}}|dkr4td||tvrAtd||dvrOtd|dd Sd S) aCheck that a key is well-formatted, e.g. in the form ``'C# major'``. The Key can be 'X' if it is not possible to categorize the Key and mode can be 'other' if it can't be categorized as major or minor. Parameters ---------- key : str Key to verify rrz-'{}' is not in the form '(key) (mode)' or 'X'z9Mode {} is invalid; 'X' (Uncategorized) doesn't have modezDKey {} is invalid; should be e.g. D or C# or Eb or X (Uncategorized))majorminorotherzMode 'z1' is invalid; must be 'major', 'minor' or 'other'N)lensplitlower ValueErrorformatKEY_TO_SEMITONEkeymoder'@/home/ubuntu/.local/lib/python3.10/site-packages/mir_eval/key.py validate_key.s((       r)cCs||fD]}t|qdS)zCheck that the input annotations to a metric are valid key strings and throws helpful errors if not. Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. N)r)) reference_key estimated_keyr%r'r'r(validateMs r,cCs.|dkr |\}}nd}t||fS)a~Split a key string (of the form, e.g. ``'C# major'``), into a tuple of ``(key, mode)`` where ``key`` is is an integer representing the semitone distance from C. Parameters ---------- key : str String representing a key. Returns ------- key : int Number of semitones above C. mode : str String representing the mode. rN)r rr#r$r'r'r(split_key_string\s r-cCst||t|\}}t|\}}||kr||krdS|dus#|dur%dS||kr3||ddkr3dS||kr=dkrInn ||ddkrId S||krSd kr_nn ||dd kr_d S||kri||krid SdS) aCompute a heuristic score which is weighted according to the relationship of the reference and estimated key, as follows: +------------------------------------------------------+-------+ | Relationship | Score | +------------------------------------------------------+-------+ | Same key and mode | 1.0 | +------------------------------------------------------+-------+ | Estimated key is a perfect fifth above reference key | 0.5 | +------------------------------------------------------+-------+ | Relative major/minor (same key signature) | 0.3 | +------------------------------------------------------+-------+ | Parallel major/minor (same key) | 0.2 | +------------------------------------------------------+-------+ | Other | 0.0 | +------------------------------------------------------+-------+ Examples -------- >>> ref_key = mir_eval.io.load_key('ref.txt') >>> est_key = mir_eval.io.load_key('est.txt') >>> score = mir_eval.key.weighted_score(ref_key, est_key) Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. Returns ------- score : float Score representing how closely related the keys are. g?Ng rg?rrg333333?rrg?)r,r-)r*r+reference_modeestimated_moder'r'r(weighted_scorets$ $  r1cKst}tt|||d<|S)aCompute all metrics for the given reference and estimated annotations. Examples -------- >>> ref_key = mir_eval.io.load_key('reference.txt') >>> est_key = mir_eval.io.load_key('estimated.txt') >>> scores = mir_eval.key.evaluate(ref_key, est_key) Parameters ---------- reference_key : str Reference key string. estimated_key : str Estimated key string. **kwargs Additional keyword arguments which will be passed to the appropriate metric or preprocessing functions. Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. zWeighted Score) collections OrderedDictr filter_kwargsr1)r*r+kwargsscoresr'r'r(evaluates r7) __doc__r2rr#r)r,r-r1r7r'r'r'r(sZ       D