code: def stan_estimator_lgt_model_input():
      stan_model_name = "lgt"
      model_param_names = [
          "l",
          "b",
          "lev_sm",
          "slp_sm",
          "obs_sigma",
          "nu",
          "lgt_sum",
          "gt_pow",
          "lt_coef",
          "gt_coef",
          "s",
          "sea_sm",
      ]
      data_input = {
          "WITH_MCMC": 1,
          "NUM_OF_OBS": 157,
          "RESPONSE": np.array(
              [
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                  7.58771258,
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                  7.99874461,
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                  7.92529138,
                  7.81512862,
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                  7.8801177,
                  8.21061382,
                  8.13363296,
                  8.10531478,
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                  8.11712744,
                  8.06752991,
                  8.14161123,
                  8.09942204,
                  8.12278759,
                  8.30482629,
                  8.16593318,
                  7.86516153,
                  8.14815287,
                  8.10534245,
                  8.12602089,
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                  7.94651151,
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              ]
          ),
          "IS_VALID_RES": np.array(
              [
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              ]
          ),
          "SEASONALITY": 52,
          "SEASONALITY_SD": 0.33,
          "SEA_SM_INPUT": -1,
          "LEV_SM_INPUT": -1,
          "SLP_SM_INPUT": -1,
          "MIN_NU": 5.0,
          "MAX_NU": 40.0,
          "CAUCHY_SD": 0.2955647529713108,
          "NUM_OF_PR": 0,
          "PR_MAT": np.empty((157, 0), dtype=np.float64),
          "PR_BETA_PRIOR": [],
          "PR_SIGMA_PRIOR": [],
          "NUM_OF_NR": 0,
          "NR_MAT": np.empty((157, 0), dtype=np.float64),
          "NR_BETA_PRIOR": [],
          "NR_SIGMA_PRIOR": [],
          "NUM_OF_RR": 0,
          "RR_MAT": np.empty((157, 0), dtype=np.float64),
          "RR_BETA_PRIOR": [],
          "RR_SIGMA_PRIOR": [],
          "REG_PENALTY_TYPE": 0,
          "AUTO_RIDGE_SCALE": 0.5,
          "LASSO_SCALE": 0.0,
      }
      return stan_model_name, model_param_names, data_input
  
file_path: orbit/tests/conftest.py
imports: import pytest
  import pandas
  import numpy
  import importlib_resources
  from copy import deepcopy
  from orbit.utils.simulation import make_trend, make_seasonality, make_regression
label_desc: Use image node_id 7 for calling a global function with example usage: stan_estimator_lgt_model_input() and returns: stan_model_name,  model_param_names,  data_input