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Commit 7083c1b7 authored by hm-schuhba1's avatar hm-schuhba1
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add python script for seed test to gitlab pipeline

parent a4b9ca4b
Pipeline #76137 failed with stages
      in 2 minutes and 53 seconds
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      Showing with 735113 additions and 140531 deletions
      .gitignore
      View file @ 7083c1b7
      ......@@ -11,8 +11,9 @@ __pycache__/
      *$py.class
      **/venv/
      Tools/VadereAnalysisTool/dist/
      Tools/VadereAnalysisTool/build/
      Tools/VadereAnalysisTool/VadereAnalysisTool.egg-info/
      Tools/ContinuousIntegration/**/output
      # C extensions
      *.so
      vadere_analysis_tool/build
      ......
      .gitlab-ci.yml
      View file @ 7083c1b7
      ......@@ -65,3 +65,12 @@ run_origin_test:
      - python3 Tools/ContinuousIntegration/install_vadere_analysis_tool.py
      - python3 Tools/ContinuousIntegration/run_orign_translation_test.py
      run_seed_test:
      stage: deploy
      script:
      - Documentation/version-control/git-hook-vadere-software
      - mvn clean
      - mvn -Dmaven.test.skip=true package
      - python3 Tools/ContinuousIntegration/install_vadere_analysis_tool.py
      - python3 Tools/ContinuousIntegration/run_seed_comparison_test.py
      Tools/ContinuousIntegration/install_vadere_analysis_tool.py
      View file @ 7083c1b7
      ......@@ -21,9 +21,12 @@ def install_package_if_needed(package_name='VadereAnalysisTool', search_path='To
      check=True,
      stdout=subprocess.PIPE,
      stderr=subprocess.PIPE)
      print("ReturnCode: {}\nStdOut: {} \nStdErr: {}".format(p_make_package.returncode,
      p_make_package.stdout.decode('utf8'),
      p_make_package.stderr.decode('utf8')))
      if p_make_package.stdout:
      print("StdOut: {}".format(p_make_package.stdout.decode('utf8')))
      if p_make_package.stderr:
      print("StdErr: {}".format(p_make_package.stderr.decode('utf8')))
      print("ReturnCode: {}".format(p_make_package.returncode))
      if p_make_package.returncode == 0:
      stdout = p_make_package.stdout.decode('utf8')
      dist_dir = os.path.join(search_path, "dist")
      ......@@ -41,9 +44,12 @@ def install_package_if_needed(package_name='VadereAnalysisTool', search_path='To
      stdout=subprocess.PIPE,
      stderr=subprocess.PIPE)
      print("ReturnCode: {}\nStdOut: {} \nStdErr: {}".format(p_install_package.returncode,
      p_install_package.stdout.decode('utf8'),
      p_install_package.stderr.decode('utf8')))
      if p_install_package.stdout:
      print("StdOut: {}".format(p_install_package.stdout.decode('utf8')))
      if p_install_package.stderr:
      print("StdErr: {}".format(p_install_package.stderr.decode('utf8')))
      print("ReturnCode: {}".format(p_install_package.returncode))
      else:
      exit(1)
      else:
      ......
      Tools/ContinuousIntegration/run_seed_comparison_test.d/scenarios/2_bridge_coordinates_kai_unit_with_offset.scenario 0 → 100644
      View file @ 7083c1b7
      {
      "name" : "2_bridge_coordinates_kai_unit_with_offset",
      "description" : "",
      "release" : "0.6",
      "commithash" : "628b018374f404d2aca1afa3483e308428b6ae20",
      "processWriters" : {
      "files" : [ {
      "type" : "org.vadere.simulator.projects.dataprocessing.outputfile.TimestepPedestrianIdOutputFile",
      "filename" : "postvis.trajectories",
      "processors" : [ 1, 2 ]
      }, {
      "type" : "org.vadere.simulator.projects.dataprocessing.outputfile.TimestepPedestrianIdOverlapOutputFile",
      "filename" : "overlaps.csv",
      "processors" : [ 3 ]
      }, {
      "type" : "org.vadere.simulator.projects.dataprocessing.outputfile.NoDataKeyOutputFile",
      "filename" : "overlapCount.txt",
      "processors" : [ 4 ]
      } ],
      "processors" : [ {
      "type" : "org.vadere.simulator.projects.dataprocessing.processor.PedestrianPositionProcessor",
      "id" : 1
      }, {
      "type" : "org.vadere.simulator.projects.dataprocessing.processor.PedestrianTargetIdProcessor",
      "id" : 2
      }, {
      "type" : "org.vadere.simulator.projects.dataprocessing.processor.PedestrianOverlapProcessor",
      "id" : 3
      }, {
      "type" : "org.vadere.simulator.projects.dataprocessing.processor.NumberOverlapsProcessor",
      "id" : 4,
      "attributesType" : "org.vadere.state.attributes.processor.AttributesNumberOverlapsProcessor",
      "attributes" : {
      "pedestrianOverlapProcessorId" : 3
      }
      } ],
      "isTimestamped" : true
      },
      "scenario" : {
      "mainModel" : "org.vadere.simulator.models.osm.OptimalStepsModel",
      "attributesModel" : {
      "org.vadere.state.attributes.models.AttributesOSM" : {
      "stepCircleResolution" : 18,
      "numberOfCircles" : 1,
      "varyStepDirection" : false,
      "stepLengthIntercept" : 0.4625,
      "stepLengthSlopeSpeed" : 0.2345,
      "stepLengthSD" : 0.036,
      "movementThreshold" : 0.0,
      "optimizationType" : "NELDER_MEAD",
      "movementType" : "ARBITRARY",
      "dynamicStepLength" : false,
      "updateType" : "EVENT_DRIVEN",
      "seeSmallWalls" : false,
      "minimumStepLength" : false,
      "targetPotentialModel" : "org.vadere.simulator.models.potential.fields.PotentialFieldTargetGrid",
      "pedestrianPotentialModel" : "org.vadere.simulator.models.potential.PotentialFieldPedestrianCompactSoftshell",
      "obstaclePotentialModel" : "org.vadere.simulator.models.potential.PotentialFieldObstacleCompactSoftshell",
      "submodels" : [ ]
      },
      "org.vadere.state.attributes.models.AttributesPotentialCompactSoftshell" : {
      "pedPotentialIntimateSpaceWidth" : 0.45,
      "pedPotentialPersonalSpaceWidth" : 1.2,
      "pedPotentialHeight" : 50.0,
      "obstPotentialWidth" : 0.8,
      "obstPotentialHeight" : 6.0,
      "intimateSpaceFactor" : 1.2,
      "personalSpacePower" : 1,
      "intimateSpacePower" : 1
      },
      "org.vadere.state.attributes.models.AttributesFloorField" : {
      "createMethod" : "HIGH_ACCURACY_FAST_MARCHING",
      "potentialFieldResolution" : 0.1,
      "obstacleGridPenalty" : 0.1,
      "targetAttractionStrength" : 1.0,
      "timeCostAttributes" : {
      "standardDeviation" : 0.7,
      "type" : "UNIT",
      "obstacleDensityWeight" : 3.5,
      "pedestrianSameTargetDensityWeight" : 3.5,
      "pedestrianOtherTargetDensityWeight" : 3.5,
      "pedestrianWeight" : 3.5,
      "queueWidthLoading" : 1.0,
      "pedestrianDynamicWeight" : 6.0,
      "loadingType" : "CONSTANT"
      }
      }
      },
      "attributesSimulation" : {
      "finishTime" : 200.0,
      "simTimeStepLength" : 0.4,
      "realTimeSimTimeRatio" : 0.0,
      "writeSimulationData" : true,
      "visualizationEnabled" : true,
      "printFPS" : false,
      "digitsPerCoordinate" : 2,
      "useFixedSeed" : true,
      "fixedSeed" : -5104110572817619091,
      "simulationSeed" : 0
      },
      "topography" : {
      "attributes" : {
      "bounds" : {
      "x" : 564280.0,
      "y" : 5933391.0,
      "width" : 50.0,
      "height" : 50.0
      },
      "boundingBoxWidth" : 0.5,
      "bounded" : true
      },
      "obstacles" : [ {
      "shape" : {
      "type" : "POLYGON",
      "points" : [ {
      "x" : 564330.2959240791,
      "y" : 5933433.506680049
      }, {
      "x" : 564311.2959240791,
      "y" : 5933433.506680049
      }, {
      "x" : 564300.9318720899,
      "y" : 5933401.544835466
      }, {
      "x" : 564312.1291207125,
      "y" : 5933396.936819093
      }, {
      "x" : 564330.1291207125,
      "y" : 5933396.936819093
      } ]
      },
      "id" : 1
      }, {
      "shape" : {
      "type" : "POLYGON",
      "points" : [ {
      "x" : 564309.9431192318,
      "y" : 5933389.478288522
      }, {
      "x" : 564309.9431192318,
      "y" : 5933391.478288522
      }, {
      "x" : 564287.7114777192,
      "y" : 5933401.030658626
      }, {
      "x" : 564280.3263510215,
      "y" : 5933402.349890053
      }, {
      "x" : 564280.3263510215,
      "y" : 5933390.349890053
      } ]
      },
      "id" : 2
      }, {
      "shape" : {
      "type" : "POLYGON",
      "points" : [ {
      "x" : 564283.8886836024,
      "y" : 5933411.251412248
      }, {
      "x" : 564290.0683166787,
      "y" : 5933406.240937642
      }, {
      "x" : 564295.4593781466,
      "y" : 5933403.808810473
      }, {
      "x" : 564303.4638894079,
      "y" : 5933436.907734532
      }, {
      "x" : 564280.4638894079,
      "y" : 5933436.907734532
      } ]
      },
      "id" : -1
      } ],
      "stairs" : [ ],
      "targets" : [ {
      "id" : 1,
      "absorbing" : true,
      "shape" : {
      "type" : "POLYGON",
      "points" : [ {
      "x" : 564280.3,
      "y" : 5933402.3
      }, {
      "x" : 564280.1,
      "y" : 5933403.7
      }, {
      "x" : 564280.5,
      "y" : 5933414.2
      }, {
      "x" : 564283.9,
      "y" : 5933411.2
      } ]
      },
      "waitingTime" : 0.0,
      "waitingTimeYellowPhase" : 0.0,
      "parallelWaiters" : 0,
      "individualWaiting" : true,
      "deletionDistance" : 0.1,
      "startingWithRedLight" : false,
      "nextSpeed" : -1.0
      }, {
      "id" : 1,
      "absorbing" : true,
      "shape" : {
      "type" : "POLYGON",
      "points" : [ {
      "x" : 564313.9,
      "y" : 5933391.2
      }, {
      "x" : 564309.9,
      "y" : 5933391.5
      }, {
      "x" : 564312.3,
      "y" : 5933397.0
      }, {
      "x" : 564316.4,
      "y" : 5933395.9
      } ]
      },
      "waitingTime" : 0.0,
      "waitingTimeYellowPhase" : 0.0,
      "parallelWaiters" : 0,
      "individualWaiting" : true,
      "deletionDistance" : 0.1,
      "startingWithRedLight" : false,
      "nextSpeed" : -1.0
      } ],
      "sources" : [ {
      "id" : -1,
      "shape" : {
      "x" : 564304.3,
      "y" : 5933435.5,
      "width" : 8.0,
      "height" : 4.4,
      "type" : "RECTANGLE"
      },
      "interSpawnTimeDistribution" : "org.vadere.state.scenario.ConstantDistribution",
      "distributionParameters" : [ 1.0 ],
      "spawnNumber" : 4,
      "maxSpawnNumberTotal" : -1,
      "startTime" : 0.0,
      "endTime" : 100.0,
      "spawnAtRandomPositions" : false,
      "useFreeSpaceOnly" : true,
      "targetIds" : [ 1 ],
      "groupSizeDistribution" : [ 1.0 ],
      "dynamicElementType" : "PEDESTRIAN"
      } ],
      "dynamicElements" : [ ],
      "attributesPedestrian" : {
      "radius" : 0.195,
      "densityDependentSpeed" : false,
      "speedDistributionMean" : 1.34,
      "speedDistributionStandardDeviation" : 0.26,
      "minimumSpeed" : 0.5,
      "maximumSpeed" : 2.2,
      "acceleration" : 2.0
      },
      "attributesCar" : {
      "id" : -1,
      "radius" : 0.195,
      "densityDependentSpeed" : false,
      "speedDistributionMean" : 1.34,
      "speedDistributionStandardDeviation" : 0.26,
      "minimumSpeed" : 0.5,
      "maximumSpeed" : 2.2,
      "acceleration" : 2.0,
      "length" : 4.5,
      "width" : 1.7,
      "direction" : {
      "x" : 1.0,
      "y" : 0.0
      }
      }
      }
      }
      }
      \ No newline at end of file
      Tools/VadereAnalysisTool/vadere_analysis_tool/tests/testData/s2ucre/output/bridge_coordinates_kai_2018-10-15_10-34-43.80/bridge_coordinates_kai.scenario → Tools/ContinuousIntegration/run_seed_comparison_test.d/scenarios/bridge_coordinates_kai.scenario
      View file @ 7083c1b7
      ......@@ -2,7 +2,6 @@
      "name" : "bridge_coordinates_kai",
      "description" : "",
      "release" : "0.6",
      "commithash" : "topographyWarning: no commit hash",
      "processWriters" : {
      "files" : [ {
      "type" : "org.vadere.simulator.projects.dataprocessing.outputfile.TimestepPedestrianIdOutputFile",
      ......@@ -96,7 +95,7 @@
      "digitsPerCoordinate" : 2,
      "useFixedSeed" : true,
      "fixedSeed" : -3213925745664992646,
      "simulationSeed" : -3213925745664992646
      "simulationSeed" : 0
      },
      "topography" : {
      "attributes" : {
      ......@@ -276,4 +275,4 @@
      }
      }
      }
      }
      }
      \ No newline at end of file
      Tools/ContinuousIntegration/run_seed_comparison_test.py 0 → 100644
      View file @ 7083c1b7
      import os
      import shutil
      import subprocess
      import time
      from vadere_analysis_tool import VadereProject
      from vadere_analysis_tool import SameSeedTrajectory
      def run_scenario_files_with_vadere_console(project, number_of_runs=3, vadere_console="VadereSimulator/target/vadere-console.jar",
      scenario_timeout_in_sec=60*5):
      scenario_files = project.scenario_files
      total_scenario_files = len(scenario_files)
      output_dir = project.output_path
      passed_scenarios = []
      failed_scenarios_with_exception = []
      for run in range(number_of_runs):
      for i, scenario_file in enumerate(scenario_files):
      try:
      scenario_name = os.path.basename(scenario_file)
      print("Running scenario file ({}/{}) of run {}/{}: {}".format(i + 1, total_scenario_files, run + 1, number_of_runs, scenario_name))
      # Measure wall time and not CPU time simply because it is the simplest method.
      wall_time_start = time.time()
      # Use timout feature, check return value and capture stdout/stderr to a PIPE (use
      # completed_process.stdout to get it).
      # print("subprocess call: {}".format(' '.join(
      # ["java", "-enableassertions", "-jar", vadere_console, "scenario-run", "-f", scenario_file, "-o", output_dir])))
      completed_process = subprocess.run(
      args=["java", "-enableassertions", "-jar", vadere_console, "scenario-run", "-f", scenario_file, "-o",
      output_dir],
      timeout=scenario_timeout_in_sec,
      check=True,
      stdout=subprocess.PIPE,
      stderr=subprocess.PIPE)
      wall_time_end = time.time()
      wall_time_delta = wall_time_end - wall_time_start
      print("Finished scenario file ({:.1f} s): {}".format(wall_time_delta, scenario_file))
      passed_scenarios.append(scenario_file)
      except subprocess.TimeoutExpired as exception:
      print("Scenario file failed: {}".format(scenario_file))
      print("-> Reason: timeout after {} s".format(exception.timeout))
      failed_scenarios_with_exception.append((scenario_file, exception))
      except subprocess.CalledProcessError as exception:
      print("Scenario file failed: {}".format(scenario_file))
      print("-> Reason: non-zero return value {}".format(exception.returncode))
      failed_scenarios_with_exception.append((scenario_file, exception))
      return {"passed": passed_scenarios, "failed": failed_scenarios_with_exception}
      if __name__ == '__main__':
      project = VadereProject('Tools/ContinuousIntegration/run_seed_comparison_test.d')
      project.clear_output_dir()
      run_scenario_files_with_vadere_console(project)
      # this will reload project
      seed_test = SameSeedTrajectory('Tools/ContinuousIntegration/run_seed_comparison_test.d')
      seed_results = seed_test.get_trajectory_comparison_result()
      seed_err = [res for res in seed_results if not res['hash_is_equal']]
      seed_ok = [res for res in seed_results if res['hash_is_equal']]
      if seed_err:
      for res in seed_err:
      print("Scenario {} with scenario-hash {} - ERROR".format(res['scenario_name'], res['scenario_hash']))
      for res_out in res['scenario_outputs']:
      print(" {}--{}".format(res_out[1], res_out[0]))
      if seed_ok:
      for res in seed_ok:
      print("Scenario {} with scenario-hash {} - OK".format(res['scenario_name'], res['scenario_hash']))
      Tools/VadereAnalysisTool/build/lib/vadere_analysis_tool/__init__.py deleted 100644 → 0
      View file @ a4b9ca4b
      from vadere_analysis_tool.scenario_output import ScenarioOutput
      from vadere_analysis_tool.scenario_output import NamedFiles
      from vadere_analysis_tool.vadere_project import VadereProject
      from vadere_analysis_tool.vadere_project import NamedOutput
      from vadere_analysis_tool.analysis.origin_deviation import OriginDeviation
      name = 'vadere_analysis_tool'
      Tools/VadereAnalysisTool/build/lib/vadere_analysis_tool/analysis/__init__.py deleted 100644 → 0
      View file @ a4b9ca4b
      from vadere_analysis_tool.analysis.origin_deviation import OriginDeviation
      \ No newline at end of file
      Tools/VadereAnalysisTool/build/lib/vadere_analysis_tool/analysis/origin_deviation.py deleted 100644 → 0
      View file @ a4b9ca4b
      import matplotlib.pyplot as plt
      import numpy as np
      import pandas as pd
      from vadere_analysis_tool import ScenarioOutput
      class OriginDeviation:
      """ Calculate deviation of origin after transforming it form 0 to X.
      In output_pair a array like structure with output_pair[0] (no translation)
      and output_pair[1] (with translation) is expected.
      """
      def __init__(self, output_pair, name='', max_diff_ok=1e-7, max_diff_warn=1e-4):
      self.output_pair = output_pair
      self.max_diff_ok= max_diff_ok
      self.max_diff_warn = max_diff_warn
      self.df = pd.DataFrame()
      self.name = name
      self.get_origin_deviation_data()
      def get_origin_deviation_data(self):
      # Create ScenarioOutput object
      out_0_origin = ScenarioOutput(self.output_pair[0])
      out_offset_origin = ScenarioOutput(self.output_pair[1])
      if self.name == '':
      self.name = out_0_origin.output_dir_name + "---" + out_offset_origin.output_dir_name
      # Load trajectories and offset
      trajectory_0_orign = out_0_origin.files['postvis.trajectories']()
      trajectory_offset_orign = out_offset_origin.files['postvis.trajectories']()
      offset = out_offset_origin.get_bound_offset()
      # Merge data frames and calculate differences after reverting offset transformation
      df = pd.merge(trajectory_0_orign, trajectory_offset_orign, on=['timeStep', 'pedestrianId'],
      suffixes=['_0', '_offset'])
      df['x_trans'] = np.abs(df['x_offset'] - offset[0])
      df['y_trans'] = np.abs(df['y_offset'] - offset[1])
      df['x_diff'] = np.abs(df['x_0'] - (df['x_offset'] - offset[0]))
      df['y_diff'] = np.abs(df['y_0'] - (df['y_offset'] - offset[1]))
      df['diff'] = np.abs(np.sqrt(df.x_0 ** 2 + df.y_0 ** 2) - (np.sqrt(df.x_trans ** 2 + df.y_trans ** 2)))
      # find maximal difference for each pedestrian in postvis.trajectories.
      # df_max_diff_per_pedId contains one row per pedestrian
      df_max_diff = df.loc[df.groupby('pedestrianId')['diff'].idxmax(),]
      df_start_diff = df.loc[df.groupby('pedestrianId')['timeStep'].idxmin(),]
      return df, df_max_diff, df_start_diff
      def get_origin_deviation_result(self):
      _, df_max_diff, df_start_diff = self.get_origin_deviation_data()
      ped_id_warn = df_max_diff[(df_max_diff['diff'] > self.max_diff_ok) & (df_max_diff['diff'] <= self.max_diff_warn)].index.values
      ped_id_err = df_max_diff[(df_max_diff['diff'] > self.max_diff_warn)].index.values
      ped_id_ok_ = df_max_diff[(df_max_diff['diff'] <= self.max_diff_ok)].index.values
      ret = {'err_count': len(ped_id_err), 'warn_count': len(ped_id_warn), 'ok_count': len(ped_id_ok_),
      'err_dict': df_max_diff.loc[ped_id_err].to_dict('index'),
      'warn_dict': df_max_diff.loc[ped_id_warn].to_dict('index'),
      'stats_at_max_diff': df_max_diff['diff'].describe(), 'stats_at_start': df_start_diff['diff'].describe(),
      'output_name': self.name, 'df_max_diff': df_max_diff, 'df_start_diff': df_start_diff
      }
      return ret
      def get_figure(self, results):
      width = 15
      height = 4 * len(results)
      fig, axes = plt.subplots(ncols=2, nrows=len(results), figsize=[width, height])
      i = 0
      for result in results:
      self._add_axis(axes[i, 0], result['df_max_diff'], 'pedestrianId', 'diff',
      title="MaxDiff " + result['output_name'],
      yscale='log')
      self._add_axis(axes[i, 1], result['df_start_diff'], 'pedestrianId', 'diff',
      title="StartDiff " + result['output_name'],
      yscale='log')
      i += 1
      return fig
      @staticmethod
      def _add_axis(ax, data, x_data_label, y_data_label, yscale='linear', title='', x_text_label='', y_text_label=''):
      ax.plot(x_data_label, y_data_label, data=data, linestyle='', marker='.')
      ax.set_yscale(yscale)
      ax.set_title(title)
      ax.set_xlabel(x_text_label)
      ax.set_ylabel(y_text_label)
      return ax
      Tools/VadereAnalysisTool/build/lib/vadere_analysis_tool/helper.py deleted 100644 → 0
      View file @ a4b9ca4b
      import os
      import json
      def read_lines(path):
      if os.path.exists(path):
      with open(path, 'r') as f:
      return f.readlines()
      else:
      raise FileNotFoundError("File not found {}".format(path))
      def read_json_to_dict(path):
      if os.path.exists(path):
      with open(path, 'r') as f:
      return json.load(f)
      else:
      raise FileNotFoundError("File not found {}".format(path))
      def clean_dir_name(dir_name):
      ret = dir_name.replace('.', '_')
      ret = ret.replace('-','_')
      return ret
      \ No newline at end of file
      Tools/VadereAnalysisTool/build/lib/vadere_analysis_tool/origin_deviation.py deleted 100644 → 0
      View file @ a4b9ca4b
      import matplotlib.pyplot as plt
      import numpy as np
      import pandas as pd
      from vadere_analysis_tool import ScenarioOutput
      class OriginDeviation:
      """ Calculate deviation of origin after transforming it form 0 to X.
      In output_pair a array like structure with output_pair[0] (no translation)
      and output_pair[1] (with translation) is expected.
      """
      def __init__(self, output_pair, name='', max_diff_ok=1e-7, max_diff_warn=1e-4):
      self.output_pair = output_pair
      self.max_diff_ok= max_diff_ok
      self.max_diff_warn = max_diff_warn
      self.get_origin_deviation_data()
      self.df = pd.DataFrame()
      self.name = name
      def get_origin_deviation_data(self):
      # Create ScenarioOutput object
      out_0_origin = ScenarioOutput(self.output_pair[0])
      out_offset_origin = ScenarioOutput(self.output_pair[1])
      if self.name == '':
      self.name = out_0_origin.output_dir_name + "---" + out_offset_origin.output_dir_name
      # Load trajectories and offset
      trajectory_0_orign = out_0_origin.files['postvis.trajectories']()
      trajectory_offset_orign = out_offset_origin.files['postvis.trajectories']()
      offset = out_offset_origin.get_bound_offset()
      # Merge data frames and calculate differences after reverting offset transformation
      df = pd.merge(trajectory_0_orign, trajectory_offset_orign, on=['timeStep', 'pedestrianId'],
      suffixes=['_0', '_offset'])
      df['x_trans'] = np.abs(df['x_offset'] - offset[0])
      df['y_trans'] = np.abs(df['y_offset'] - offset[1])
      df['x_diff'] = np.abs(df['x_0'] - (df['x_offset'] - offset[0]))
      df['y_diff'] = np.abs(df['y_0'] - (df['y_offset'] - offset[1]))
      df['diff'] = np.abs(np.sqrt(df.x_0 ** 2 + df.y_0 ** 2) - (np.sqrt(df.x_trans ** 2 + df.y_trans ** 2)))
      # find maximal difference for each pedestrian in postvis.trajectories.
      # df_max_diff_per_pedId contains one row per pedestrian
      df_max_diff = df.loc[df.groupby('pedestrianId')['diff'].idxmax(),]