pi_action_export_cluster.py

'''
    Like pi_action_export BUT uses a list of selected images to determine
    groupings of pictures based on location.

    Export folder names are based one the parent directory of the selected
    image appended with "c_{n}" where n = the cluster number. Those images
    without a location are copied to "c_0". If all images contained a location
    the "c_0" folder is not created.

    Listens for event names generated when this action was created.

    Like all actions, this class has a 'handle_event(self,event,values)' method.

    When a new instance of this class is created:
        text   - menu item text to display
        rowget - method to call to get list of rows to export
        selectget - method to call to get list of node locations

    To use, simply create a new instance with the name of the event
    and the key of the list within event values. For example:

        # set up action for Export Event and Gallery Element 
        PiActionExport(rowget=self.get_row,selectget=self.get_selected_rows).item(),

    User may want to generate a map before calling this function. The map will
    then show which clusters will be exported to.

    TODO: create a "map clusters" function which would look for "c_{n}" folders
    in the "_export" subdirectory generated by this action. It would then
    generate a map with one point for each cluster and a link pointing to 
    the exported cluster directory. Use that function in the tree list for 
    selected folders?

'''
import os
from pathlib import Path
import shutil

import pi_config as c
from pi_action import PiAction
from pi_action_export import PiActionExport

class PiActionExport(PiActionExport):
    '''
        Export selected files and folders.
        Parms:
        text     - menu item text to display
        rowget   - method to call to get list of rows to export
        clusters - method to call to get rows which define
                    the cluster centroids
    '''
    @staticmethod
    def get_cluster(clusters,test_row):
        ''' Given a list of cluster represented by rows in parm clusters, 
            calculate the index of the cluster row which is closest to test_row. 
            Return -1 if no GPS co-ordinates in row or none in any clusters '''
        c_node = -1
        min_d  = -1
        c_idx  = -1
        for c in clusters:
            c_idx += 1
            d = c.get_hyp_sq(test_row)
            if d != -1:
                if  d < min_d or min_d == -1:
                    c_node = c_idx
                    min_d  = d

        return c_node
    
    def __init__(self,text="Cluster",rowget=None,clusters=None):
        self._clusters = clusters
        super().__init__(text,rowget)

    def handle_event(self,event,values):
        ''' Handle Cluster Event - copy each image into a cluster
            subdirectory based on which cluster it is closest to.
            Cluster 0 is for images without gps location. '''
        
        # callback row getter
        rows = self._rowget(values)
        cnt = 0

        # callback cluster getter
        clusters = self._clusters(values)

        for row in rows:
            cnt += 1
            subdir = row['file_location']
            fn     = row['file_name']
            dst_dir = f'{c.directory}/_export{subdir}'


            self.copy_file(subdir,dst_dir,fn,f'export {cnt} {subdir}/{fn}')

        c.update_status(f'exported {cnt} images to {c.directory}/_export')