moggs2

def restructure(newlist, lookback):
   total = np.shape(newlist)[0]
   totalcolumns=np.shape(newlist)[1]
   newarray=np.empty([total-(lookback-1), lookback, totalcolumns])
   i=0
   q=0
   while i < total:
     if i>=(lookback-1):
       j=i-(lookback-1)
       k=0

moggs2

using DelimitedFiles
#using OrderedCollections
using Glob

function generateseries(length=140,readseries="dataseries.csv")

   #newseries = rand(Int, (length, 1))
   newseries=range(1,1,140)
   newseries2=[1:1:length;]
   #print(newseries)

moggs2

import pandas as pd
import numpy as np

df =pd.DataFrame(np.random.randint(1,4,size=(1000, 6)), columns=list('ABCDEF'))
df.columns=['Date', 'Open', 'High', 'Low', 'Close', 'Volume']

import gym
from gym import spaces
import random

moggs2

import tensorflow as tf
import glob
import numpy as np
from PIL import Image, ImageDraw
import matplotlib.pyplot as plt


filenames = glob.glob('sketchesdata/training.tfrecord-*')
raw_dataset = tf.data.TFRecordDataset(filenames)
raw_dataset

moggs2

import pandas as pd
import numpy as np
import tensorflow as tf
import glob

def preparedataset(thepath):

 totalchorales=len(glob.glob(thepath))
 newarray=np.zeros([totalchorales,3000])
 i=0

moggs2

import tensorflow as tf
import glob
import numpy as np
from PIL import Image, ImageDraw
import matplotlib.pyplot as plt

def parse_function(tfrecorddata):
    tf.io.parse_single_example(tfrecorddata,
      {"ink": tf.io.VarLenFeature(dtype=tf.float32),
       "shape": tf.io.FixedLenFeature([2], dtype=tf.int64),

moggs2

import pandas as pd
import numpy as np
from random import random
import plotext as plt
import tensorflow as tf


newlist1=[]
newlist2=[]
newlisty=[]

moggs2

import pandas as pd
import numpy as np
from random import random
import plotext as plt
import tensorflow as tf


newlist1=[]
newlist2=[]
newlisty=[]

moggs2

import pandas as pd
import numpy as np
from random import random
import plotext as plt
import tensorflow as tf


newlist1=[]
newlisty=[]

moggs2

import tensorflow as tf
from pathlib import Path
import numpy as np
import pandas as pd
import tensorflow_datasets as tfds
import gc

#folderlist=[]
#
#photodir = Path('/root/flower_photos')