code: def partial_plot_test_with_user_splits():
      data = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate_cat_NA.csv")
      )
      x = data.names
      y = "CAPSULE"
      x.remove(y)
  
      # Build a GBM model predicting for response CAPSULE
      gbm_model = H2OGradientBoostingEstimator(
          ntrees=50, learn_rate=0.05, seed=12345
      )
      gbm_model.train(x=x, y=y, training_frame=data)
  
      file, filename = tempfile.mkstemp(suffix=".png")
      user_splits = dict()
      user_splits["AGE"] = [
          43.0,
          44.89473684210526,
          46.78947368421053,
          48.68421052631579,
          50.578947368421055,
          52.473684210526315,
          54.368421052631575,
          56.26315789473684,
          58.1578947368421,
          60.05263157894737,
          61.94736842105263,
          63.84210526315789,
          65.73684210526315,
          67.63157894736842,
          69.52631578947368,
          71.42105263157895,
          73.3157894736842,
          75.21052631578948,
          77.10526315789474,
      ]
      user_splits["RACE"] = ["Black", "White"]
      pdpUserSplit2D = gbm_model.partial_plot(
          frame=data,
          server=True,
          plot=True,
          user_splits=user_splits,
          col_pairs_2dpdp=[["AGE", "PSA"], ["AGE", "RACE"]],
          save_to_file=filename,
      )
      pdpUserSplit1D2D = gbm_model.partial_plot(
          frame=data,
          cols=["AGE", "RACE", "DCAPS"],
          server=True,
          plot=True,
          user_splits=user_splits,
          col_pairs_2dpdp=[["AGE", "PSA"], ["AGE", "RACE"]],
          save_to_file=filename,
      )
      pdpUserSplit1D = gbm_model.partial_plot(
          frame=data,
          cols=["AGE", "RACE", "DCAPS"],
          server=True,
          plot=True,
          user_splits=user_splits,
          save_to_file=filename,
      )
      if os.path.isfile(filename):
          os.remove(filename)
          # compare results 1D pdp
      for i in range(3):
          pyunit_utils.assert_H2OTwoDimTable_equal_upto(
              pdpUserSplit1D[i],
              pdpUserSplit1D2D[i],
              pdpUserSplit1D[i].col_header,
              tolerance=1e-10,
          )
      # compare results 2D pdp
      pyunit_utils.assert_H2OTwoDimTable_equal_upto(
          pdpUserSplit2D[0],
          pdpUserSplit1D2D[3],
          pdpUserSplit2D[0].col_header,
          tolerance=1e-10,
      )
      pyunit_utils.assert_H2OTwoDimTable_equal_upto(
          pdpUserSplit2D[1],
          pdpUserSplit1D2D[4],
          pdpUserSplit2D[1].col_header,
          tolerance=1e-10,
      )
  
imports: import sys
  import os
  import h2o
  import tempfile
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: partial_plot_test_with_user_splits() without return types