w2w_delta.py

import pandas as pd
import numpy as np
from arcgis.gis import GIS
from arcgis import features
from IPython.display import display
from copy import deepcopy

try:
    gis = GIS("", "", "")
    print('Success!')
except:
    print('Failed to login. Check credentials and network connection and try again.')

def sort_descending(layerlist):
    lyrnames = []
    for lyr in layerlist:
        lyrnames.append(lyr.properties.name)

    sorted_names = np.argsort(lyrnames)[::-1]
    return list(np.array(layerlist)[sorted_names])

# function to output the index of a field
def find_field(layer, fieldname):
    fields = layer.manager.properties.fields
    for indx, field_props in enumerate(fields):
        if field_props.get('name') == fieldname:
            fieldname_indx = indx
            return fieldname_indx
            break
    return 'Unable to find field'

# create function to create fc_w2w_delta or FID_copy field
def add_fields(layer, field='fc_w2w_delta'):
    newfields = ['fc_w2w_delta', 'FID_copy']
    if field not in newfields:
        raise ValueError(f'Invalid field name. Expected one of {newfields}.')

    currentfields = layer.manager.properties.fields
    fc_field = currentfields[find_field(layer, 'fc')]
    field_to_copy = fc_field # copying twice bc copying the FID field yielded an error
    
    fields_to_be_added = []

    new_field = dict(deepcopy(field_to_copy))
    new_field["name"] = field.lower()
    new_field["alias"] = field
    if field == 'FID_copy':
        new_field["type"] = 'esriFieldTypeInteger'
        # new_field["isUnique"] = True # not needed, but IDK why...

    fields_to_be_added.append(new_field)

    try:
        layer.manager.add_to_definition({'fields':fields_to_be_added})
    except:
        raise

# retrieve CERES_Canopy_WFL1 feature class
canopy = gis.content.get('')

# receive input from user what field to calculate vine growth deltas for
error_counter = 0
while error_counter == 0:
    field = input("What field are you calculating vine growth delta? Enter 58cd, 137CC, or 137CS")
    if field == '58cd':
        error_counter = 1
    elif field == '137CC':
        error_counter = 1
    elif field == '137CS':
        error_counter = 1
    else:
        print('Invalid field number. Try again.')
    print(f'field # is {field}.')

layernames = []
for lyr in canopy.layers:
    layernames.append(lyr.properties.name)

# add layers corresponding to field #
layers_in_field = [layer for layer in canopy.layers if field in layer.properties.name]

# sorts layers from most to least recent
sort_descending(layers_in_field)

# getting vine growth measurements from same plot, diff times
current_week = layers_in_field[0]
prev_week = layers_in_field[1]

current_database = current_week.query().sdf
prev_database = prev_week.query().sdf

# add fc_w2w_delta and FID_copy fields
add_fields(current_week, 'fc_w2w_delta')
add_fields(current_week, 'FID_copy')

#  reload layer in the notebook to see the new fields
canopy = gis.content.get('')

layers_in_field = [layer for layer in canopy.layers if field in layer.properties.name]
sort_descending(layers_in_field)

current_week = layers_in_field[0]
prev_week = layers_in_field[1]

current_database = current_week.query().sdf
prev_database = prev_week.query().sdf

for i in current_week.properties.fields:
    print(i.name)

# to delete fields
# current_week.manager.delete_from_definition({'fields': [dict(current_week.manager.properties.fields[find_field(current_week, 'fid_copy')]), dict(current_week.manager.properties.fields[find_field(current_week, 'fc_w2w_delta')])]})

# copy FID values to FID_copy
current_week.calculate(where="FID >= 0", calc_expression={"field": "fid_copy", "sqlExpression": "FID"})

# delete the spatial join layer. Only use if need to re-rerun.
# sj_temp.delete()

# join current and prev weeks' layers
sj_temp = features.analysis.join_features(current_week, prev_week, spatial_relationship='identicalto', output_name="sj_temp")

# display the spatially-joined db
sj_temp.layers[0].query().sdf

# calculate fc_w2w_delta on sj layer
sj_temp.layers[0].calculate(where="fid_copy >= 0", calc_expression={"field": "fc_w2w_delta", "sqlExpression": "fc - fc_1"})
sj_temp.layers[0].query().sdf

# sort features by FID, ascending
sj_features = sj_temp.layers[0].query(order_by_fields = 'fid_copy ASC').features

# copy fc_w2w_delta values from sj_temp to current_week
for value in sj_features:
    delta_by_fid = value.attributes['fc_w2w_delta']
    current_week.calculate(where=f'FID = {value.attributes["fid_copy"]}', calc_expression={'field': 'fc_w2w_delta', 'sqlExpression': f'{delta_by_fid}'})
# current_week.query().sdf

# confirm fc_w2w_delta from current_week matches with the sj layer
# if so, safe to delete the sj layer
# if not, delete sj_temp layer and redo

diff_counter = 0
for oid, item in enumerate(current_week.query().features):
    if item.attributes['fc_w2w_delta'] == sj_features[oid].attributes['fc_w2w_delta']:
        continue
    else:
        diff_counter += 1
        print('fc_w2w_delta mismatch. Redo calculation.')
        break

if diff_counter == 0:
    print('All fc_w2w_delta\' s match!')

# delete the spatial join layer. Only use if diff_counter != 0.
# sj_temp.delete()

# find and delete the fid_copy field
fid_copy_indx = find_field(current_week, 'fid_copy')
current_week.manager.delete_from_definition({'fields': [dict(current_week.manager.properties.fields[fid_copy_indx])]})

# delete spatial join layer
sj_temp.delete()

del sj_temp, sj_features