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untitled0.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Sep 26 12:26:32 2020
@author: tommasobassignana
"""
import numpy as np
X = np.array([[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4]])
# y = np.array([1, 2, 3, 4, 5, 6])
# tscv = expanding_window()
# for train_index, test_index in tscv.split(X):
# print(train_index)
# print(test_index)
initial= 1
horizon = 1
period = 1
gap = 1
data = X
counter = 0 # for us to iterate and track later, like i?
data
data_length = data.shape[0] # rows
print(data_length)
data_index = list(np.arange(data_length))
print(data_index)
output_train = []
output_test = []
# append initial index
output_train.append(list(np.arange(initial)))
print(output_train)
progress = [x for x in data_index if x not in list(np.arange(initial))] #indexes left to append to train
print(progress)
output_train[counter]
output_test.append([x for x in data_index if x not in output_train[counter]][:horizon])
print(output_test)
# clip initial indexes from progress since that is what we are left
while len(progress) != 0:
print(" len progress is")
print(len(progress))
print("progress is")
print(progress)
temp = progress[:period]
print("period is")
print(period)
print("temp is")
print(temp)
print("counter is")
print(counter)
print("output_train[counter]")
print(output_train[counter])
to_add = output_train[counter] + temp
print("to add is")
print(to_add)
# update the train index
print("train_index before adding")
print(output_train)
output_train.append(to_add)
print("train_index after adding")
print(output_train)
# increment counter
counter +=1
# then we update the test index
print("test_index before adding")
print(output_test)
print("what to add to test")
#to_add_test = [x for x in data_index if x not in output_train[counter] ][:(horizon + gap)]
to_add_test = [x for x in data_index if x not in output_train[counter] ][:horizon]
if len(to_add_test) == 0:
break
to_add_test = int(to_add_test[-1])+gap
print(to_add_test)
output_test.append(to_add_test)
print("test_index after adding")
print(output_test)
# update progress
progress = [x for x in data_index if x not in output_train[counter]]
# clip the last element of output_train and output_test
#output_train = output_train[:-1]
#output_test = output_test[:-1]
output_train = output_train[:-gap]
output_test = output_test[:-gap]
print("final")
print(output_train)
print(output_test)
# mimic sklearn output
#index_output = [(train,test) for train,test in zip(output_train,output_test)]
X = np.array([[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4],[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4]])
# y = np.array([1, 2, 3, 4, 5, 6])
# tscv = expanding_window()
# for train_index, test_index in tscv.split(X):
# print(train_index)
# print(test_index)
initial= 1
horizon = 1
period = 1
gap = 0
#è problematico per gap = 0 e gap = 1??
data = X
counter = 0 # for us to iterate and track later, like i?
data
data_length = data.shape[0] # rows
print(data_length)
data_index = list(np.arange(data_length))
print(data_index)
output_train = []
output_test = []
# append initial index
output_train.append(list(np.arange(initial)))
print(output_train)
progress = [x for x in data_index if x not in list(np.arange(initial))] #indexes left to append to train
print(progress)
output_train[counter]
output_test.append([x for x in data_index if x not in output_train[counter]][:horizon])
print(output_test)
# clip initial indexes from progress since that is what we are left
while len(progress) != 0:
print(" len progress is")
print(len(progress))
print("progress is")
print(progress)
temp = progress[:period]
print("period is")
print(period)
print("temp is")
print(temp)
print("counter is")
print(counter)
print("output_train[counter]")
print(output_train[counter])
to_add = output_train[counter] + temp
print("to add is")
print(to_add)
# update the train index
print("train_index before adding")
print(output_train)
output_train.append(to_add)
print("train_index after adding")
print(output_train)
# increment counter
counter +=1
# then we update the test index
print("test_index before adding")
print(output_test)
print("what to add to test")
#to_add_test = [x for x in data_index if x not in output_train[counter] ][:(horizon + gap)]
to_add_test = [x for x in data_index if x not in output_train[counter] ][:horizon]
if len(to_add_test) == 0:
break
to_add_test = int(to_add_test[-1])+gap
print(to_add_test)
output_test.append(to_add_test)
print("test_index after adding")
print(output_test)
# update progress
progress = [x for x in data_index if x not in output_train[counter]]
# clip the last element of output_train and output_test
#output_train = output_train[:-1]
#output_test = output_test[:-1]
if gap != 0:
output_train = output_train[:-gap]
output_test = output_test[:-gap]
output_train = output_train[:len(output_test)]
print("final")
print(output_train)
print(output_test)
############
# X = np.array([[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4],[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4]])
# initial= 1
# horizon = 1
# period = 1
# gap = 0
# #è problematico per gap = 0 e gap = 1??
# data = X
# counter = 0 # for us to iterate and track later, like i?
# data
# data_length = data.shape[0] # rows
# print(data_length)
# data_index = list(np.arange(data_length))
# print(data_index)
# output_train = []
# output_test = []
# real_output_train = []
# # append initial index
# output_train.append(list(np.arange(initial)))
# print(output_train)
# progress = [x for x in data_index if x not in list(np.arange(initial))] #indexes left to append to train
# print(progress)
# output_train[counter]
# output_test.append([x for x in data_index if x not in output_train[counter]][:horizon])
# print(output_test)
# # clip initial indexes from progress since that is what we are left
# cut = period
# while len(progress) != 0:
# print(" len progress is")
# print(len(progress))
# print("progress is")
# print(progress)
# temp = progress[:period]#period è quanti indici aggiungo ogni volta
# print("period is")
# print(period)
# print("temp is")
# print(temp)
# print("counter is")
# print(counter)
# print("output_train[counter]")
# print(output_train[counter])
# to_add = output_train[counter] + temp
# print("QUELLO CHE VORREI")
# print("cut is")
# print(cut)
# print(to_add[cut:])
# cut += 1
# print("to add is")
# print(to_add)
# # update the train index
# print("train_index before adding")
# print(output_train)
# output_train.append(to_add)
# print("train_index after adding")
# print(output_train)
# # increment counter
# counter +=1
# # then we update the test index
# print("test_index before adding")
# print(output_test)
# print("what to add to test")
# #to_add_test = [x for x in data_index if x not in output_train[counter] ][:(horizon + gap)]
# to_add_test = [x for x in data_index if x not in output_train[counter] ][:horizon]
# if len(to_add_test) == 0:
# break
# to_add_test = int(to_add_test[-1])+gap
# print(to_add_test)
# output_test.append(to_add_test)
# print("test_index after adding")
# print(output_test)
# # update progress
# progress = [x for x in data_index if x not in output_train[counter]]
# # clip the last element of output_train and output_test
# #output_train = output_train[:-1]
# #output_test = output_test[:-1]
# if gap != 0:
# output_train = output_train[:-gap]
# output_test = output_test[:-gap]
# output_train = output_train[:len(output_test)]
# print("final")
# print(output_train)
# print(output_test)