src package

Subpackages

• src.combined_metrics package
  • Submodules
  • src.combined_metrics.combined_metrics module
    • configure_plot()
    • main()
    • plot_duration()
    • plot_duration_volume_1rm()
    • plot_frequency()
    • save_plot()
  • src.combined_metrics.get_frequency_data module
    • get_frequency_data()
  • Module contents
• src.model package
  • Submodules
  • src.model.model module
    • calc_volume()
    • get_data()
    • get_df()
    • get_weight()
    • main()
    • one_rep_max_estimator()
  • src.model.plot_model module
    • create_1rm_plots()
    • create_volume_plots()
    • get_split()
    • main()
    • make_plots()
  • Module contents
• src.simulations package
  • Submodules
  • src.simulations.simulate_data module
    • get_dates()
    • simulate_data()
  • src.simulations.simulate_people module
  • src.simulations.workout_simulator module
    • DataFormatter
      • DataFormatter.format_data()
      • DataFormatter.write_data()
    • ExerciseRepository
      • ExerciseRepository.get_exercises()
    • ExerciseSelector
      • ExerciseSelector.exercises
      • ExerciseSelector.repository
      • ExerciseSelector.select_random_exercises()
      • ExerciseSelector.split
    • JSONWorkoutFormatter
      • JSONWorkoutFormatter.format_data()
      • JSONWorkoutFormatter.write_data()
    • WorkoutSimulator
      • WorkoutSimulator.generate_exercise_mapping()
      • WorkoutSimulator.simulate_workout_data()
    • main()
  • Module contents
• src.utils package
  • Submodules
  • src.utils.cleanup module
    • main()
  • src.utils.config_loader module
  • src.utils.custom_storage module
    • YAMLStorage
      • YAMLStorage.close()
      • YAMLStorage.read()
      • YAMLStorage.write()
    • main()
  • src.utils.get_bodyweight module
    • get_bw()
    • main()
  • src.utils.get_breath_holding module
    • get_breath_holding()
    • get_sheet_title()
    • main()
    • make_figure()
  • src.utils.get_exercises module
    • get_available_exercises()
    • main()
  • src.utils.get_program module
    • get_pgm_from_date()
    • main()
    • parse_date()
  • src.utils.get_split module
    • Split
      • Split.BACK
      • Split.CHEST
      • Split.LEGS
  • src.utils.get_volume module
    • get_total_volume()
    • get_weight()
    • main()
  • src.utils.get_workout_duration module
    • get_all_durations()
    • main()
  • src.utils.google_sheet module
    • get_sheet()
    • main()
    • update_sheet()
  • src.utils.logger_config module
    • log_running_file()
    • setup_logger()
  • src.utils.set_db_and_table module
    • TinyDBSingleton
      • TinyDBSingleton.close()
      • TinyDBSingleton.get_db()
    • main()
    • set_db_and_table()
  • src.utils.validate module
    • ExercisesFormatError
    • Workout
      • Workout.cooldown
      • Workout.date
      • Workout.end_time
      • Workout.exercise_valid()
      • Workout.exercises
      • Workout.gym
      • Workout.model_config
      • Workout.notes
      • Workout.split
      • Workout.start_time
      • Workout.warmup
    • WorkoutFactory
      • WorkoutFactory.create_workout()
      • WorkoutFactory.create_workouts_from_json()
      • WorkoutFactory.create_workouts_from_yaml()
    • WorkoutValidator
      • WorkoutValidator.validate_exercises()
    • main()
  • Module contents

Submodules

src.main module

src.one_rep_max module

acsm_1rm, epley or brzycki formulas are used to implement the 1RM estimation.

ACSM 1RM formula

\[\frac{w}{\frac{100 - r \cdot 2.5}{100}}\]

Epley 1RM formula

\[w \cdot \frac{1 + r}{30}\]

Brzycki 1RM formula

\[w \cdot \frac{36}{37 - r}\]

class src.one_rep_max.ACSMStrategy

Bases: OneRepMaxStrategy

ACSM formula for one-repetition-maximum estimation.

estimate(weight, reps)

class src.one_rep_max.BrzyckiStrategy

Bases: OneRepMaxStrategy

Brzycki formula for one-repetition-maximum estimation.

estimate(weight, reps)

class src.one_rep_max.EpleyStrategy

Bases: OneRepMaxStrategy

Epley formula for one-repetition-maximum estimation.

estimate(weight, reps)

class src.one_rep_max.OneRepMaxStrategy

Bases: ABC

Abstract class for one-repetition-maximum estimation strategies.

abstractmethod estimate(weight, reps)

src.one_rep_max_calc module

Definition of popular 1-repetition-maximum formulas.

class src.one_rep_max_calc.BrzyckiInvertedStrategy

Bases: OneRepMaxStrategy

estimate(one_rm, reps, progression)

class src.one_rep_max_calc.EpleyInvertedStrategy

Bases: OneRepMaxStrategy

estimate(one_rm, reps, progression)

class src.one_rep_max_calc.InvertedCalculator(strategy)

Bases: object

calculate(one_rm, reps, progression)

static validate_inputs(one_rm, reps, progression)

Ensure that inputs are either scalars or Pandas Series.

class src.one_rep_max_calc.OneRepMaxCalculator(strategy)

Bases: object

calculate(weight, reps)

static validate_inputs(weight, reps)

src.one_rep_max_calc.main() → None

src.one_rep_max_plot module

Plots of popular 1-repetition-maximum formulas.

src.one_rep_max_plot.get_data() → tuple

Get data for plotting 1-repetition-maximum formulas.

Returns:

tuple of dataframes

Return type:

tuple

src.one_rep_max_plot.make_plots(df1: DataFrame, df2: DataFrame, df3: DataFrame, df4: DataFrame) → None

Make plots of 1-repetition-maximum formulas.

Parameters:

• df1 (pd.DataFrame) – dataframe with weight, one_rep_max, and variable columns

• df2 (pd.DataFrame) – dataframe with reps, one_rep_max, and variable columns

• df3 (pd.DataFrame) – dataframe with weight, inverse_one_rep_max, and variable columns

• df4 (pd.DataFrame) – dataframe with reps, inverse_one_rep_max, and variable columns

src.plot module

Plot weight-training data.

src.plot.compare_workouts(dfs_1: dict, dfs_2: dict) → tuple[dict[Any, Any], dict[Any, Any]]

Compare two workouts and return common exercises.

Parameters:

• dfs_1 (dict) – Dataframes with training data

• dfs_2 (dict) – Dataframes with training data

Returns:

Dataframes with common exercises

Return type:

tuple[dict[Any, Any], dict[Any, Any]]

src.plot.create_barplots(dfs: dict, date: str) → None

Plot training data for specific date.

Parameters:

• dfs (dict) – Dataframes with training data

• date (str) – Date of the workout

src.plot.get_data(date: str, split: str) → dict[str, DataFrame] | dict

Prepare pandas dataframes with training data for plotting.

Parameters:

• date (str) – Date of the workout

• split (str) – Split of the workout

Returns:

Dataframes with training data

Return type:

dict[str, pd.DataFrame] | dict

src.plot.main() → None

Get data and create figure.

src.plot.validate_date_format(date: str) → str

Validate date format and return year.

Parameters:

date (str) – Date of the workout

src.user_settings module

User Settings. TODO: Implement/integrate this module

Module contents