import re
import xml.etree.ElementTree as ET
from enum import Enum
from typing import Optional
import pandas as pd
[docs]
class TempoGroup2(Enum):
"""
Contains constants refering to grouped tempo on the second level that will be used by the tempo module.
"""
NA = "NA"
SLOW = "Slow"
MODERATE = "Moderate"
FAST = "Fast"
[docs]
def get_time_signature_type(time_signature: str) -> str:
"""
Given a time signature, it returns the correspondent type.
Parameters
----------
time_signature: str
Time signature in the form of string separated by '/' to obtain the time signature type.
"""
if time_signature in [
"1/2",
"1/4",
"1/8",
"1/16",
"2/2",
"2/4",
"2/8",
"2/16",
"4/4",
"C",
"4/2",
"4/8",
"4/16",
"8/2",
"8/4",
"8/8",
"8/16",
]:
return "simple duple"
elif time_signature in ["6/8", "3/8", "12/2", "12/4", "12/8", "12/16"]:
return "compound duple"
elif time_signature in ["3/2", "3/4", "3/16", "6/2", "6/4", "6/16"]:
return "simple triple"
elif time_signature in ["9/2", "9/4", "9/8", "9/16"]:
return "compound triple"
else:
return "other"
[docs]
def get_tempo_grouped_1(tempo: str) -> str:
"""
Returns a 1st level of grouping for the tempo markings, removing secondary labels
and diminutive endings.
Parameters
----------
tempo: str
Tempo string in italian to be extract the group from.
"""
tempo = re.sub("\\W+", " ", tempo) # removes eventual special characters
replacements = [
(w, "")
for w in [
"molto",
"poco",
"un poco",
"tanto",
"un tanto",
"assai",
"meno",
"più",
"piuttosto",
]
]
if not tempo:
return "NA"
for r in replacements:
tempo = tempo.replace(*r)
tempo = (
tempo.replace("Con brio", "brio")
.replace("con brio", "brio")
.replace("Con spirito", "spiritoso")
.replace("con spirito", "spiritoso")
)
base_important_words = [
"adagio",
"allegro",
"andante",
"andantino",
"largo",
"lento",
"presto",
"vivace",
"minueto",
]
# if the tempo marking ends in -ietto and or -issimo, it retuns the marking without that ending
important_words = (
base_important_words
+ [w[0:-1] + "etto" for w in base_important_words]
+ [w[0:-1] + "ietto" for w in base_important_words]
+ [w[0:-1] + "issimo" for w in base_important_words]
+ [w[0:-1] + "ssimo" for w in base_important_words]
+ [w[0:-1] + "hetto" for w in base_important_words]
)
last_words = ""
for word in tempo.split(" "):
if word.lower() in important_words and (
"ma non" not in last_words
or " ma " not in last_words
or "Tempo di" in last_words
):
return word.capitalize()
last_words += " " + word
################ SECOND IMPORTANT WORDS ################
relevant_words = [
"amoroso",
"affettuoso",
"agitato",
"arioso",
"cantabile",
"comodo",
"brio",
"spiritoso",
"espressivo",
"fiero",
"giusto",
"grave",
"grazioso",
"gustoso",
"maestoso",
"moderato",
"risoluto",
"sostenuto",
"spiritoso",
"tempo",
]
words_contained = []
for word in tempo.split(" "):
if word.lower() in relevant_words:
words_contained.append(word)
## FINAL DECISION (Two exceptions: tempo and con brio) ##
if len(words_contained) == 1:
if words_contained[0].lower() not in ["tempo", "brio"]:
return words_contained[0].capitalize()
elif words_contained[0].lower() == "tempo":
return "A tempo"
else:
return "Con brio"
elif len(words_contained) > 1:
for w in words_contained:
if w[0].isupper():
if w.lower() != "tempo":
return w # returns the capitalized term
elif w.lower() == "tempo":
return "A tempo"
else:
return "Con brio"
if words_contained[0] != "tempo":
return words_contained[0].capitalize()
elif words_contained[0] == "tempo":
return "A tempo" # or the first one
else:
return "Con brio"
return "NA"
[docs]
def get_tempo_grouped_2(tempo_grouped_1: str) -> str:
"""
Returns a 2nd level of grouping for the tempo markings.
Parameters
----------
tempo_grouped_1: str
Tempo string got from get_tempo_grouped_1
"""
if tempo_grouped_1 is None or tempo_grouped_1.lower() == TempoGroup2.NA.value:
return TempoGroup2.NA.value
possible_terminations = ["ino", "etto", "ietto", "ssimo", "issimo", "hetto"]
slow_basis = [
"Adagio",
"Affettuoso",
"Grave",
"Sostenuto",
"Largo",
"Lento",
"Sostenuto",
]
slow = slow_basis + [w[:-1] + t for w in slow_basis for t in possible_terminations]
moderate_basis = [
"Andante",
"Arioso",
"Comodo",
"Cantabile",
"Comodo",
"Espressivo",
"Grazioso",
"Gustoso",
"Maestoso",
"Minueto",
"Moderato",
"Marcía",
"Amoroso",
]
moderate = moderate_basis + [
w[:-1] + t for w in moderate_basis for t in possible_terminations
]
fast_basis = [
"Agitato",
"Allegro",
"Con brio",
"Spiritoso",
"Fiero",
"Presto",
"Risoluto",
"Vivace",
]
fast = fast_basis + [w[:-1] + t for w in fast_basis for t in possible_terminations]
if tempo_grouped_1 in ["A tempo", "Giusto"]:
return TempoGroup2.NA.value
elif tempo_grouped_1 in slow:
return TempoGroup2.SLOW.value
elif tempo_grouped_1 in moderate:
return TempoGroup2.MODERATE.value
elif tempo_grouped_1 in fast:
return TempoGroup2.FAST.value
[docs]
def get_number_of_beats(time_signature: str) -> int:
"""
Returns the number of beats corresponding to a time signature.
By default, this returns the numerator, with the exceptions when the numerator is
6, 9, or 12 and when the time signature is C or 3/8. If it is empty, it returns 1.
If it is `"NA"`, it returns `pd.NA`.
Parameters
----------
time_signature: str
Time signature in the form of string separated by '/' to obtain the time
signature type.
"""
# we only take the first time signature in case we receive more than one
time_signature = time_signature.split(",")[0]
if time_signature == "C":
return 4
elif time_signature == "":
return 1
elif time_signature == "NA":
return pd.NA
num, den = time_signature.split("/")
if num == "3" and den == "8":
return 1
elif num == "6":
return 2
elif num == "9":
return 3
elif num == "12":
return 4
else:
return int(num)
# raise ValueError(f"The {time_signature} is not a known time signature")
