Source code for ptrail.visualization.statViz

    This File contains static visualizations i.e the ones that do not require the use of

        The visualizations in this module are currently developed with a focus around the
        starkey.csv data as it has been developed as a side project by the developers. It
        will further be integrated into the library as a general class of visualizers in
        the time to come. Some of the visualization types may or may not work with other

    | Authors: Yaksh J Haranwala
import pandas as pd

from ptrail.core.TrajectoryDF import PTRAILDataFrame
from ptrail.features.kinematic_features import KinematicFeatures as kin
from ptrail.features.temporal_features import TemporalFeatures as temp

import as px

[docs]class StatViz:
[docs] @staticmethod def trajectory_distance_treemap(dataset: PTRAILDataFrame, path: list): """ Plot a treemap of distance travelled by the moving object on a particular date. Parameters ---------- dataset: PTRAILDataFrame The dataframe containing all the trajectory data. map_date: str The date for which the TreeMap is to be plotted. path: list The hierarchy of the treemap. This is passed directly into plotly's Treemap API. Returns ------- plotly.graph_objects.Figure: Treemap depicting the distance travelled. """ # First obtain all the unique trajectory IDs of the dataset. traj_ids = dataset.reset_index()['traj_id'].unique() # Now, for each of the traj_id in the list above, calculate the distance # travelled by the moving object on that day and store it in a dictionary. dist_df = pd.DataFrame(columns=['traj_id', 'distance']) for val in traj_ids: try: distance = kin.get_distance_travelled_by_traj_id(dataframe=dataset, traj_id=val) duration = temp.get_traj_duration(dataframe=dataset, traj_id=val) dist_df.loc[val] = distance / int(duration.dt.days) except KeyError: # If the animal's trajectory is not recorded on the date given in, just skip it. continue # Drop the extra column that is acting as the traj ID and reset the index # and rename the index column to be traj_id. dist_df = dist_df.drop(columns=['traj_id']).reset_index().rename(columns={'index': 'traj_id'}) species = [] for i in range(len(dist_df)): if 'D' in dist_df.iloc[i]['traj_id']: species.append('Deer') elif 'E' in dist_df.iloc[i]['traj_id']: species.append('Elk') else: species.append('Cattle') dist_df['Species'] = species palette = ['#B42F32', '#DF6747', '#E3E3CD', '#878D92', '#49494D'] # Draw the treemap using plotly. tree_map = px.treemap(data_frame=dist_df, values='distance', path=path, color_discrete_sequence=palette, title="Average Distance Travelled Per Day") # Arrange the margins. tree_map.update_layout(margin=dict(t=50, l=25, r=25, b=25)) # Set the color of the root of the treemap. tree_map.update_traces(root_color=palette[3]) return tree_map