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Merge pull request #15 from ubigu/vooka-pohjois-savo
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remove old compareKTJindicestokunta
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@smassine
smassine authored Feb 2, 2024
2 parents fc6c221 + 9b68288 commit 0306280
Showing 1 changed file with 0 additions and 190 deletions.
190 changes: 0 additions & 190 deletions lib/kunta_ktj_kaavavertailu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -146,193 +146,3 @@ def calculate_iou(geom1, geom2):
print(sorted(set(puuttuvat)))

return(kunta_pala)

def compareKTJindicesToKunta(base_kaavadata, refe_kaavadata, kuntanimi, kaavalajit, dissolve_refe=False, **kwargs):

"""
Mandatory parameters
--------------------
base_kaavadata: <gpd.GeoDataFrame>
Input kaavadata as a Geopandas Geodataframe, KTJ from MML in this case. To be used as a base for comparisons.
refe_kaavadata: <gpd.GeoDataFrame>
Input reference data from municipalities as a Geopandas Geodataframe.
kuntanimi: <str>
Name of the wanted municipality.
kaavalajit <list>, list item <str>
A list including kaavalaji numbers to be examined. E.g. asemakaavat ['31', '33']
Check all numbers from: https://koodistot.suomi.fi/codescheme;registryCode=rytj;schemeCode=RY_Kaavalaji
Optional parameters
-------------------
dissolve_refe <boolean>
True/False (default False).
True if there is a need to group kaavaindex rows to form a kaava.
False if input data already has an individual kaava as a row.
dissolve_column
When dissolve_kunta=True
Name of the column to be used when dissolving the data.
Output
------
<gpd.GeoDataFrame>
KTJ's kaavadata with comparison information included.
"""

import sys
import geopandas as gpd
from shapely.geometry import Polygon, LineString, Point, MultiPolygon , MultiLineString, MultiPoint

import warnings
warnings.filterwarnings("ignore")

def get_DE9IM_pattern(geom1, geom2):
pattern = geom1.relate(geom2)
return(pattern)

def topologically_equal_DE9IM(geom1, geom2):
# Two geometries are topologically equal if their interiors intersect and no part of the interior or boundary of one geometry intersects the exterior of the other.
# DE-9IM pattern: "T*F**FFF*"
equals = geom1.relate_pattern(geom2, 'T*F**FFF*')
return(equals)

def calculate_iou(geom1, geom2):
iou = round((geom1.intersection(geom2).area / geom1.union(geom2).area)*100, 2)
return(iou)

dissolve_column = kwargs.get('dissolve_column', None)

base_pala = base_kaavadata.loc[base_kaavadata['kuntanimi'] == kuntanimi]
base_pala = base_pala.loc[base_pala['kaavalaji'].isin(kaavalajit)]
refe_pala = refe_kaavadata.loc[refe_kaavadata['kuntanimi'] == kuntanimi]
refe_pala = refe_pala.loc[refe_pala['kaavalaji'].isin(kaavalajit)]

# Check to see if datasets have the same CRS system
if base_pala.crs['init'] != refe_pala.crs['init']:
# If not, comparison cannot be made. Sys exit.
sys.exit("Your data must have the same coordinate reference system!")

base_pala['area_ha'] = None
base_pala['refe_area_ha'] = None
base_pala['de9im_pattern'] = None
base_pala['topo_equal'] = None
base_pala['iou'] = None
base_pala['refe_kaavatunnus'] = None
base_pala['a_delta_%'] = None
base_pala['kl_equal'] = None
base_pala['hyv_equal'] = None
base_pala['voim_equal'] = None

if dissolve_refe == True:
refe_pala = refe_pala.dissolve(by=dissolve_column)
refe_pala.reset_index(inplace=True)

base_pala = base_pala.dissolve(by="kaavatunnus_1")
base_pala.reset_index(inplace=True)

for index, row in base_pala.iterrows():

geom1 = row['geometry']
base_pala.at[index, 'area_ha'] = geom1.area / 10000
item_dict = {"knro":[], "iou":[], "pattern": [], "topo_equal": [], "refe_area": [], "a_delta": [], "kl_equal": [], "hyv_equal": [], "voim_equal": []}
print("---------")

for idx, rivi in refe_pala.iterrows():

geom2 = rivi['geometry']

if geom1.intersects(geom2) == True:

iou = calculate_iou(geom1, geom2)
print(iou)

pattern = get_DE9IM_pattern(geom1, geom2)

topo_equal = topologically_equal_DE9IM(geom1, geom2)
if topo_equal == False:
if iou >= 98:
topo_equal = True

refe_area = geom2.area / 10000

try:
delta = round(((refe_area - (geom1.area / 10000)) / (geom1.area / 10000)) * 100, 2)
except TypeError:
delta = None

# Kaavalaji
if row['kaavalaji'] == rivi['kaavalaji']:
kl_equal = True
else:
kl_equal = False

# Hyvaksymispvm
if row['hyvaksymispvm'] == None:
if rivi['hyvaksymispvm'] == None:
hyv_equal = 'Hyvpvm puuttuu molemmista'
else:
hyv_equal = 'Hyvpvm puuttuu KTJ'
else:
if rivi['hyvaksymispvm'] != None:
if row['hyvaksymispvm'] == rivi['hyvaksymispvm']:
hyv_equal = '1'
else:
hyv_equal = '0'
else:
hyv_equal = 'Hyvpvm puuttuu kunta'

# Voimaantulopvm
if row['voimaantulopvm'] == None:
if rivi['voimaantulopvm'] == None:
voim_equal = 'Voimpvm puuttuu molemmista'
else:
voim_equal = 'Voimpvm puuttuu KTJ'
else:
if rivi['voimaantulopvm'] != None:
if row['voimaantulopvm'] == rivi['voimaantulopvm']:
voim_equal = '1'
else:
voim_equal = '0'
else:
voim_equal = 'Voimpvm puuttuu kunta'

item_dict['knro'].append(rivi['kaavatunnus'])
item_dict['iou'].append(iou)
item_dict['pattern'].append(pattern)
item_dict['topo_equal'].append(topo_equal)
item_dict['refe_area'].append(refe_area)
item_dict['a_delta'].append(delta)
item_dict['kl_equal'].append(kl_equal)
item_dict['hyv_equal'].append(hyv_equal)
item_dict['voim_equal'].append(voim_equal)

if len(item_dict['iou']) >= 1:
base_pala.at[index, 'iou'] = max(item_dict['iou'])
indeksimme = item_dict['iou'].index(max(item_dict['iou']))
base_pala.at[index, 'refe_kaavatunnus'] = item_dict['knro'][indeksimme]
base_pala.at[index, 'topo_equal'] = item_dict['topo_equal'][indeksimme]
base_pala.at[index, 'de9im_pattern'] = item_dict['pattern'][indeksimme]
base_pala.at[index, 'refe_area_ha'] = item_dict['refe_area'][indeksimme]
base_pala.at[index, 'a_delta_%'] = item_dict['a_delta'][indeksimme]
base_pala.at[index, 'kl_equal'] = item_dict['kl_equal'][indeksimme]
base_pala.at[index, 'hyv_equal'] = item_dict['hyv_equal'][indeksimme]
base_pala.at[index, 'voim_equal'] = item_dict['voim_equal'][indeksimme]
else:
None

#List missing reference indices
lista = base_pala['refe_kaavatunnus'].tolist()
puuttuvat = []

for index, row in refe_pala.iterrows():

if row['kaavatunnus'] not in lista:
puuttuvat.append(row['kaavatunnus'])

print("")
print("Missing reference indices:")
print(sorted(set(puuttuvat)))

base_exp = base_pala.explode()
base_exp = base_exp.reset_index(drop=True)

return(base_exp)

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