|
| 1 | +"""Validation of PEtab visualization files""" |
| 2 | +import logging |
| 3 | + |
| 4 | +import pandas as pd |
| 5 | + |
| 6 | +from .. import C, Problem |
| 7 | +from ..C import VISUALIZATION_DF_REQUIRED_COLS |
| 8 | + |
| 9 | + |
| 10 | +logger = logging.getLogger(__name__) |
| 11 | + |
| 12 | + |
| 13 | +def validate_visualization_df( |
| 14 | + problem: Problem |
| 15 | +) -> bool: |
| 16 | + """Validate visualization table |
| 17 | +
|
| 18 | + Arguments: |
| 19 | + problem: The PEtab problem containing a visualization table |
| 20 | +
|
| 21 | + Returns: |
| 22 | + ``True`` if errors occurred, ``False`` otherwise |
| 23 | + """ |
| 24 | + vis_df = problem.visualization_df |
| 25 | + if vis_df is None or vis_df.empty: |
| 26 | + return False |
| 27 | + |
| 28 | + errors = False |
| 29 | + |
| 30 | + if missing_req_cols := (set(VISUALIZATION_DF_REQUIRED_COLS) |
| 31 | + - set(vis_df.columns)): |
| 32 | + logger.error(f"Missing required columns {missing_req_cols} " |
| 33 | + "in visualization table.") |
| 34 | + errors = True |
| 35 | + |
| 36 | + # Set all unspecified optional values to their defaults to simplify |
| 37 | + # validation |
| 38 | + vis_df = vis_df.copy() |
| 39 | + _apply_defaults(vis_df) |
| 40 | + |
| 41 | + if unknown_types := (set(vis_df[C.PLOT_TYPE_SIMULATION].unique()) |
| 42 | + - set(C.PLOT_TYPES_SIMULATION)): |
| 43 | + logger.error(f"Unknown {C.PLOT_TYPE_SIMULATION}: {unknown_types}. " |
| 44 | + f"Must be one of {C.PLOT_TYPES_SIMULATION}") |
| 45 | + errors = True |
| 46 | + |
| 47 | + if unknown_types := (set(vis_df[C.PLOT_TYPE_DATA].unique()) |
| 48 | + - set(C.PLOT_TYPES_DATA)): |
| 49 | + logger.error(f"Unknown {C.PLOT_TYPE_DATA}: {unknown_types}. " |
| 50 | + f"Must be one of {C.PLOT_TYPES_DATA}") |
| 51 | + errors = True |
| 52 | + |
| 53 | + if unknown_scale := (set(vis_df[C.X_SCALE].unique()) |
| 54 | + - set(C.X_SCALES)): |
| 55 | + logger.error(f"Unknown {C.X_SCALE}: {unknown_scale}. " |
| 56 | + f"Must be one of {C.X_SCALES}") |
| 57 | + errors = True |
| 58 | + |
| 59 | + if any( |
| 60 | + (vis_df[C.X_SCALE] == 'order') |
| 61 | + & (vis_df[C.PLOT_TYPE_SIMULATION] != C.LINE_PLOT) |
| 62 | + ): |
| 63 | + logger.error(f"{C.X_SCALE}=order is only allowed with " |
| 64 | + f"{C.PLOT_TYPE_SIMULATION}={C.LINE_PLOT}.") |
| 65 | + errors = True |
| 66 | + |
| 67 | + if unknown_scale := (set(vis_df[C.Y_SCALE].unique()) |
| 68 | + - set(C.Y_SCALES)): |
| 69 | + logger.error(f"Unknown {C.Y_SCALE}: {unknown_scale}. " |
| 70 | + f"Must be one of {C.Y_SCALES}") |
| 71 | + errors = True |
| 72 | + |
| 73 | + if problem.condition_df is not None: |
| 74 | + # check for ambiguous values |
| 75 | + reserved_names = {C.TIME, "condition"} |
| 76 | + for reserved_name in reserved_names: |
| 77 | + if reserved_name in problem.condition_df \ |
| 78 | + and reserved_name in vis_df[C.X_VALUES]: |
| 79 | + logger.error(f"Ambiguous value for `{C.X_VALUES}`: " |
| 80 | + f"`{reserved_name}` has a special meaning as " |
| 81 | + f"`{C.X_VALUES}`, but there exists also a model " |
| 82 | + "entity with that name.") |
| 83 | + errors = True |
| 84 | + |
| 85 | + # check xValues exist in condition table |
| 86 | + for xvalue in set(vis_df[C.X_VALUES].unique()) - reserved_names: |
| 87 | + if xvalue not in problem.condition_df: |
| 88 | + logger.error(f"{C.X_VALUES} was set to `{xvalue}`, but no " |
| 89 | + "such column exists in the conditions table.") |
| 90 | + errors = True |
| 91 | + |
| 92 | + if problem.observable_df is not None: |
| 93 | + # yValues must be an observable |
| 94 | + for yvalue in vis_df[C.Y_VALUES].unique(): |
| 95 | + if yvalue not in problem.observable_df.index: |
| 96 | + logger.error( |
| 97 | + f"{C.Y_VALUES} was set to `{yvalue}`, but no such " |
| 98 | + "observable exists in the observables table." |
| 99 | + ) |
| 100 | + errors = True |
| 101 | + |
| 102 | + return errors |
| 103 | + |
| 104 | + |
| 105 | +def _apply_defaults(vis_df: pd.DataFrame): |
| 106 | + """ |
| 107 | + Set default values. |
| 108 | +
|
| 109 | + Adds default values to the given visualization table where no value was |
| 110 | + specified. |
| 111 | + """ |
| 112 | + def set_default(column: str, value): |
| 113 | + if column not in vis_df: |
| 114 | + vis_df[column] = value |
| 115 | + elif value is not None: |
| 116 | + vis_df[column].fillna(value) |
| 117 | + |
| 118 | + set_default(C.PLOT_NAME, "") |
| 119 | + set_default(C.PLOT_TYPE_SIMULATION, C.LINE_PLOT) |
| 120 | + set_default(C.PLOT_TYPE_DATA, C.MEAN_AND_SD) |
| 121 | + set_default(C.DATASET_ID, None) |
| 122 | + set_default(C.X_VALUES, C.TIME) |
| 123 | + set_default(C.X_OFFSET, 0) |
| 124 | + set_default(C.X_LABEL, vis_df[C.X_VALUES]) |
| 125 | + set_default(C.X_SCALE, C.LIN) |
| 126 | + set_default(C.Y_VALUES, None) |
| 127 | + set_default(C.Y_OFFSET, 0) |
| 128 | + set_default(C.Y_LABEL, vis_df[C.Y_VALUES]) |
| 129 | + set_default(C.Y_SCALE, C.LIN) |
| 130 | + set_default(C.LEGEND_ENTRY, vis_df[C.DATASET_ID]) |
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