markov_fingerpicking.py

import itertools as it
import numpy as np
import midiutil
from midiutil.MidiFile import MIDIFile

#generates about half an h of modal fingerpicking tunes using a simple markov model
#change the seed with increments of about 100K to get a new one.
#lots of parameters to play around with but you can figure it out yourself.


startseed=234567

def get_tm(seed):
    #think of some better way to populate this matrix in the future lol
    transition_matrix = np.tile(probs,(len(states),1))
    for i in range(10000):
        np.random.seed(i+seed)
        x=np.random.randint(len(states))
        np.random.seed(i+123456+seed)
        y=np.random.randint(len(states))
        transition_matrix[x,y]*=0.5
        transition_matrix[y,x]*=0.5
    transition_matrix[transition_matrix < np.sort(transition_matrix.flatten())[-150]]= 0
    for i in range(len(states)):
        transition_matrix[i,i]=0
    row_sums = transition_matrix.sum(axis=1)
    for i in range(len(row_sums)):
        transition_matrix[i,i]=0
        if row_sums[i]==0 or list(transition_matrix[i]).count(0)==1:
            identity=np.zeros(len(row_sums))
            identity[i]=0.25
            identity[(i+1)%len(row_sums)]=0.25
            identity[(i+2)%len(row_sums)]=0.25
            identity[(i+3)%len(row_sums)]=0.25
            transition_matrix[i]=identity
            row_sums[i]=1
    transition_matrix = transition_matrix / row_sums[:, np.newaxis]
    return transition_matrix

def allowednotes(scale,root=60,maxnote=84,minnote=36):
    start=root%12-12
    allnotes =[]
    beginscale=[note+start for note in scale]
    for i in range(12): #max 12 octaves bc midi max is 127
        for note in beginscale:
            allnotes.append(note+12*i)
    notes_list = [note for note in allnotes if note >= minnote and note <= maxnote]
    return notes_list

scales= [[0,3,5,7,8,10],[0,2,3,5,7,8,10],[0,2,3,5,7,10],[0,2,3,5,7,9,10],[0,3,5,7,9,10],[0,1,3,5,7,9,10],[0,1,3,5,7,10],[0,1,3,5,7,8,10],[0,3,5,7,8,10]]
nls=[allowednotes(x,minnote=40,maxnote=82) for x in scales]
pitch_delta = [0,1,2,3,-1,-2,-3]
pitch_proba = [10.,0.1,0.1,0.1,0.1,0.1,0.1]
time_delta = [1,0.5,0.25,-64,.75,4,8]
time_proba = [10.,10.04,20.03,20.02,15.01,0.5,0.5]
states = list(it.product(pitch_delta,time_delta))
probs = list(tup[0]*tup[1] for tup in it.product(pitch_proba,time_proba))
curr_state=0
states_list=[]
for i in range(40):
    notes=500
    transition_matrix=get_tm(startseed+250*i)
    for i in range(notes):
        np.random.seed(i+startseed)
        curr_state = np.random.choice(np.arange(len(states)),replace=True,p=transition_matrix[curr_state])
        states_list.append(states[curr_state])
# parse states list into midi
mf = MIDIFile(1, adjust_origin = True)
mf.addTrackName(0, 0, "test")
mf.addTempo(0, 0, 140)
curr_pitch = 60
curr_time = 0
curr_time_delta = 1
t1=0.25
times=set([])
curr_scale=0
scene_len=1000
min_time=-500
for i,state in enumerate(states_list):
    if i%2000==0:
        nl=nls[curr_scale]
        curr_scale=(curr_scale+1)%len(nls)
        min_time+=500
        times=set([])
    try:
        curr_pitch=nl[(nl.index(curr_pitch)+state[0])%len(nl)]
    except:
        curr_pitch=nl[0]
    curr_time_delta=state[1]
    curr_time=(curr_time+curr_time_delta)%scene_len
    if curr_time not in times:
        if 0>curr_time_delta>4:
            t1=curr_time_delta
        else:
            t1=4
        mf.addNote(0, 0, curr_pitch, min_time+curr_time, t1, 50+(i%10)*5)
    times.add(curr_time)

with open("output_{}.mid".format(startseed), 'wb') as outf:
    mf.writeFile(outf)