Почему индекс кортежа выходит за пределы допустимого диапазона при создании таймсерий с помощью библиотеки тиграмитов? ⇐ Python

[Гость]

I have installed the

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tigramite

package for causal inference and imported the following libraries:

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# Imports import numpy as np import matplotlib from matplotlib import pyplot as plt %matplotlib inline      import sklearn import tigramite from tigramite import data_processing as pp from tigramite.toymodels import structural_causal_processes as toys from tigramite import plotting as tp from tigramite.pcmci import PCMCI from tigramite.lpcmci import LPCMCI from tigramite.independence_tests.parcorr import ParCorr from tigramite.independence_tests.robust_parcorr import RobustParCorr from tigramite.independence_tests.parcorr_wls import ParCorrWLS  from tigramite.independence_tests.gpdc import GPDC from tigramite.independence_tests.cmiknn import CMIknn from tigramite.independence_tests.cmisymb import CMIsymb from tigramite.independence_tests.gsquared import Gsquared from tigramite.independence_tests.regressionCI import RegressionCI 

Now I have found the following code to generate and simulate time series:

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np.random.seed(42)     # Fix random seed to make results reproducible links_coeffs = {0: [((0, -1), 0.7), ((1, -1), -0.8)],             1: [((1, -1), 0.8), ((3, -1), 0.8)],             2: [((2, -1), 0.5), ((1, -2), 0.5), ((3, -3), 0.6)],             3: [((3, -1), 0.4)],             } #stores the coefficients of the SCM  T = 1000     # time series length  #generate the timeseries  data, true_parents_neighbors = toys.structural_causal_process(links_coeffs, T=T)   T, N = data.shape  # Initialize dataframe object, specify time axis and variable names  var_names = [r'$X^0$', r'$X^1$', r'$X^2$', r'$X^3$']  dataframe = pp.DataFrame(data,                       datatime = {0:np.arange(len(data))},                       var_names=var_names) 

However I got

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IndexError: tuple index out of range

coming, probably from the line to generate the time series

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data, true_parents_neighbors = toys.structural_causal_process(links_coeffs, T=T)

How can I solve it?


Источник: https://stackoverflow.com/questions/781 ... th-tigrami