def parseFile(self, filename, name="database", augment=False):
"""Construct the database of tuples from an existing midi database.
:param path: The path to the folder to load (must contain midi files).
:param name: The name to give to the database object, optional.
:type path: str
:type name: str
"""
if not os.path.isdir(".TEMP"):
os.makedirs(".TEMP")
# Number of skiped files
skipedFiles = 0
# Total number of files
N = 0
self.data = []
self.files = []
if filename[filename.rfind("."):] in [".mid", ".midi"]:
if os.path.isfile(filename):
try:
self.data.append(score.score(filename))
self.files.append(filename)
except RuntimeError:
skipedFiles += 1
N += 1
self.getViewpointRepresentation()
if augment is True:
self.augmentData()
def addFile(self, file):
"""
Parse a midi file
:param file: file to parse
:type file: string
"""
self.data.append(score.score(file))
self.getViewpointRepresentation()
def generate(self, length):
"""
Implement a very easy random walk in order to generate a sequence
:param length: length of the generated sequence (in elements, not beat so it depends on the quantization)
:type length: int
:return: sequence (score object)
"""
S = []
# We uniformly choose the first element
S.extend(ast.literal_eval(np.random.choice(self.stateAlphabet)))
while len(S) < length and str(S[-self.order:]) in self.stateAlphabet:
S.append(self.sample(S))
return score.score(S)
def addFiles(self, files, augmentation=True):
"""
Parse a list of midi file
:param files: files to parse
:type file: list of string
"""
for file in files:
print("__", file)
self.data.append(score.score(file))
print("___ Constructing viewPoint representation")
self.getViewpointRepresentation()
if augmentation:
print("_____ Augmenting database ...")
print()
self.augmentData()
def generate(self, length):
"""
Return a piece of music generated using the model; works only with pitch and length.
:param length: length of the output
:type length: int
:return: class piece
"""
S = [{"pitch": 74, "length": 24}]
while len(S) < length and S[-1] is not None:
S.append(self.sample(S))
if S[-1] is None:
S = S[:-1]
ret = []
for note in S:
ret.extend([note["pitch"]] * note["length"])
return score.score(ret)
import sys
sys.path.append('../')
from idyom import score
import matplotlib.pyplot as plt
import numpy as np
import copy
# Import one of my masterpieces ...
#s = score.score("velocity.mid")
s = score.score("../stimuli/Chinese/test1/chinese-001.mid")
s.plot()
print(s.getData())
quit()
s = score.score("dataBaseTest/easy.mid")
s = score.score("../stimuli/giovanni/audio1.mid")
print(list(s.getData()))
tmp = list(s.getData())
for i in range(1, len(tmp)):
if tmp[i] == -1:
tmp[i] = tmp[i - 1]
print(tmp)
import sys
sys.path.append('../')
from idyom import score
import matplotlib.pyplot as plt
import numpy as np
import copy
# Import one of my masterpieces ...
#s = score.score("velocity.mid")
s = score.score("../shanx185.mid")
#s = score.score("../dataset/shanxi_train_enculturation/shanx188.mid")
s.plot()
with np.printoptions(threshold=np.inf):
print(s.getData())
quit()
s = score.score("dataBaseTest/easy.mid")
s = score.score("../stimuli/giovanni/audio1.mid")
print(list(s.getData()))
tmp = list(s.getData())
for i in range(1, len(tmp)):
import sys
sys.path.append('../')
from idyom import score
import matplotlib.pyplot as plt
import numpy as np
import copy
# Import one of my masterpieces ...
#s = score.score("velocity.mid")
s = score.score("dataBaseTest/002606b_.mid")
plt.plot(s.getData())
plt.show()
s.fromData(s.getData())
s.plot()
s.writeToMidi("dataBaseTest/out.mid")
quit()
'''
Part for the midi
'''
# Return the length in time beat
print("length:", s.getLength())
# Plot the piano roll representation of the score
s.plot()
import sys
sys.path.append('../')
from idyom import longTermModel
from idyom import data
from idyom import score
import numpy as np
import matplotlib.pyplot as plt
L = longTermModel.longTermModel("pitch", maxOrder=None)
M = data.data()
#M.parse("../dataset/")
M.parse("dataBaseTest/")
L.train(M.getData("pitch"))
G = L.generate(500)
print(G)
s = score.score(G)
s.plot()
s.writeToMidi("exGen.mid")
L.save("longTermModel.save")
def parse(self, path, name=None):
"""Construct the database of tuples from an existing midi database.
:param path: The path to the folder to load (must contain midi files).
:param name: The name to give to the database object, optional.
:type path: str
:type name: str
"""
if os.path.isdir(path):
self.path = path
if name:
self.name = name
else:
self.name = str(path)
print()
print("________ We are working on '" + path + "'")
print()
else:
print(
"The path you gave is not a directory, please provide a correct directory."
)
raise RuntimeError("Invalid database directory")
if not os.path.isdir(".TEMP"):
os.makedirs(".TEMP")
print("_____ Filling the database ...")
print()
# Number of skiped files
skipedFiles = 0
# Total number of files
N = 0
self.data = []
self.files = []
for filename in glob(self.path + '/**', recursive=True):
if filename[filename.rfind("."):] in [".mid", ".midi"]:
if os.path.isfile(filename):
print(" -", filename)
try:
self.data.append(score.score(filename))
self.files.append(filename)
except RuntimeError:
skipedFiles += 1
N += 1
print()
print("We passed a total of ", N, "files.")
print(skipedFiles, "of them have been skiped.")
print()
print("_____ Computing multiple viewpoints representation")
self.getViewpointRepresentation()
print("_____ Augmenting database ...")
print()
self.augmentData()
#random.shuffle(self.data)
print("Data processing done.")
