code: def get_pca_incorrect_data():
      """Generate wide table with number of features twice more than number of objects"""
      features = np.array(
          [
              [1.0, 1.5, 2.0, 2.5, 3.0, 3.5],
              [2.0, 2.5, 3.0, 3.5, 4.0, 4.5],
              [1.0, 5.0, 4.5, 0.5, 1.0, 1.5],
          ]
      )
      target = np.array([[1], [2], [3]])
  
      task = Task(TaskTypesEnum.regression)
      input_data = InputData(
          idx=[0, 1, 2],
          features=features,
          target=target,
          task=task,
          data_type=DataTypesEnum.table,
      )
      return input_data
  
imports: import pickle
  from copy import deepcopy
  from time import perf_counter
  from typing import Tuple, Optional
  import numpy
  import pytest
  from golem.core.log import default_log
  from sklearn.datasets import make_classification
  from sklearn.metrics import mean_absolute_error, mean_squared_error, roc_auc_score
  from sklearn.preprocessing import MinMaxScaler
  from fedot.core.constants import FAST_TRAIN_PRESET_NAME
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import PCAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.discriminant_analysis import LDAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.naive import NaiveAverageForecastImplementation, RepeatLastValueImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.statsmodels import GLMImplementation
  from fedot.core.operations.model import Model
  from fedot.core.operations.operation_parameters import get_default_params, OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationMetaInfo, OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from test.unit.common_tests import is_predict_ignores_target
  from test.unit.data_operations.test_time_series_operations import synthetic_univariate_ts
  from test.unit.tasks.test_forecasting import get_ts_data, get_ts_data_with_dt_idx
  from test.unit.tasks.test_regression import get_synthetic_regression_data
label_desc: Use image node_id 5 for calling a global function with example usage: get_pca_incorrect_data() and returns: input_data