10884071777

Committed 16 Sep 2024 12:41PM UTC coverage: 92.844% (+6.4%) from 86.4%

Build # 10884071777

Build Type

Pull #10

github

Committed by

uvchik

Commit Message

Add get_layer function for all layers

Pull Request Pull Request #10: Add basic functions

Run Details

65 of 71 branches covered (91.55%)

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93.55

/src/dave_data/geometry/polygon.py

from geopandas import read_file

from dave_data.geometry.layers import get_federal_state_layer
from dave_data.geometry.layers import get_nuts_layer
from dave_data.geometry.layers import get_postcode_layer

dave_data_settings = {"crs_main": "EPSG:4326"}


def postalcode_to_polygon(postalcode):
    """
    Creating a polygon based on postalcodes

    Parameters
    ----------
    postalcode : int, str, list of str, list of int
          Postalcodes areas which define the polygon. Use ['ALL'] for all
          postalcode areas in germany

    Returns
    -------
    polygon : Shapely Polygon / MultiPolygon

    Examples
    --------
    >>> from dave_data.geometry.polygon import postalcode_to_polygon
    >>> from shapely.geometry import MultiPolygon, Polygon
    >>> polygon_postal = postalcode_to_polygon(postalcode=['34225', '34117'])
    >>> isinstance(polygon_postal, MultiPolygon)
    True
    >>> polygon_postal = postalcode_to_polygon(postalcode=[34225])
    >>> isinstance(polygon_postal, Polygon)
    True
    """
    # convert single values to list
    if isinstance(postalcode, (int, str)):
        postalcode = [str(postalcode).zfill(5)]

    # convert all values to str and check if string values are valid numbers
    postalcode = [str(int(p)).zfill(5) for p in postalcode]

    # get postcode map
    postal, meta_data = get_postcode_layer()

    # return one polygon containing all postcode polygons
    return postal.loc[postalcode].union_all()


def ags2polygon(ags):
    """
    Returns the polygon of the given region.

    Find the ags-code of any town in Germany:
    https://www.statistikportal.de/de/gemeindeverzeichnis

    Parameters
    ----------
    ags : str or int

    Returns
    -------
    shapely.polygon : Outline of the given region

    """
    raise NotImplementedError("ags2polygon is not implemented so far.")


def town_to_polygon(town):
    """
    Create a polygon based on town names

    Parameters
    ----------
    town : str
        Town areas which define the polygon. Use ['ALL'] for all town areas
        in germany

    Returns
    -------
    polygon : Shapely Polygon / MultiPolygon

    Examples
    --------
    >>> from shapely.geometry import MultiPolygon
    >>> from dave_data.geometry.polygon import town_to_polygon
    >>> polygon_town = town_to_polygon(town='Kassel')
    >>> isinstance(polygon_town, MultiPolygon)
    True
    """
    postal, meta_data = get_postcode_layer()

    town = postal.loc[postal["note"].str.lower().str.find(town.lower()) >= 0]

    return town.union_all()


def federal_state_to_polygon(federal_state):
    """
    Create a polygon based on federal states

    Parameters
    ----------
    federal_state : str
        Federal state areas which define the polygon. Use ['ALL'] for all
        Federal state areas in germany

    Returns
    -------
    polygon : Shapely Polygon / MultiPolygon

    Examples
    --------
    >>> from dave_data.geometry.polygon import federal_state_to_polygon
    >>> from shapely.geometry import MultiPolygon, Polygon
    >>> polygon_fed = federal_state_to_polygon(federal_state='Hessen')
    >>> isinstance(polygon_fed, (MultiPolygon, Polygon))
    True
    """
    states, meta_data = get_federal_state_layer()

    state = states.loc[
        states["name"].str.lower().str.find(federal_state.lower()) >= 0
    ]
    return state.union_all()


def nuts_to_polygon(nuts, year=2016):
    """
    Create a polygon based on nuts regions

    Parameters
    ----------
    nuts : List(Str)
          Nuts areas which define the polygon. Diffrent nuts levels can
          be combined. Use ['ALL'] for all Nuts 3 areas in germany

    year : scalar(INT), optional(default=2016)
          The year which forms the basis of the data set

    Returns
    -------
    polygon : Shapely Polygon / MultiPolygon

    Examples
    --------
    >>> from dave_data.geometry.polygon import nuts_to_polygon
    >>> from shapely.geometry import Polygon
    >>> polygon_nuts = nuts_to_polygon(nuts="DE11B", year=2013)
    >>> isinstance(polygon_nuts, Polygon)
    True
    """
    # read nuts-3 areas
    nuts_all, meta_data = get_nuts_layer(year=year)
    nuts_3 = nuts_all[nuts_all.LEVL_CODE == 3]

    nuts_region = nuts_3.loc[nuts_3["NUTS_ID"].str.lower() == nuts.lower()]

    return nuts_region.union_all()


def file_to_polygon(filepath, layer=None):
    """
    Create a polygon based on a file including geographical data

    Parameters
    ----------
    filepath : scalar(Str)
        Absolut Path to a file including geographical data. Possible datatypes
        are .shp, .gpkg and .geojson

    layer : scalar(Str), optional(default=None)
          The layer name of the data to be considered. Necessary for datatype
          .gpkg

    Returns
    -------
    polygon : Shapely Polygon / MultiPolygon

    """
    file_data = read_file(filepath, layer=layer)
    return file_data.union_all()

1	from geopandas import read_file	5✔
2
3	from dave_data.geometry.layers import get_federal_state_layer	5✔
4	from dave_data.geometry.layers import get_nuts_layer	5✔
5	from dave_data.geometry.layers import get_postcode_layer	5✔
6
7	dave_data_settings = {"crs_main": "EPSG:4326"}	5✔
8
9
10	def postalcode_to_polygon(postalcode):	5✔
11	"""
12	Creating a polygon based on postalcodes
13
14	Parameters
15	----------
16	postalcode : int, str, list of str, list of int
17	Postalcodes areas which define the polygon. Use ['ALL'] for all
18	postalcode areas in germany
19
20	Returns
21	-------
22	polygon : Shapely Polygon / MultiPolygon
23
24	Examples
25	--------
26	>>> from dave_data.geometry.polygon import postalcode_to_polygon
27	>>> from shapely.geometry import MultiPolygon, Polygon
28	>>> polygon_postal = postalcode_to_polygon(postalcode=['34225', '34117'])
29	>>> isinstance(polygon_postal, MultiPolygon)
30	True
31	>>> polygon_postal = postalcode_to_polygon(postalcode=[34225])
32	>>> isinstance(polygon_postal, Polygon)
33	True
34	"""
35	# convert single values to list
36	if isinstance(postalcode, (int, str)):	5✔
NEW 37	postalcode = [str(postalcode).zfill(5)]	×
38
39	# convert all values to str and check if string values are valid numbers
40	postalcode = [str(int(p)).zfill(5) for p in postalcode]	5✔
41
42	# get postcode map
43	postal, meta_data = get_postcode_layer()	5✔
44
45	# return one polygon containing all postcode polygons
46	return postal.loc[postalcode].union_all()	5✔
47
48
49	def ags2polygon(ags):	5✔
50	"""
51	Returns the polygon of the given region.
52
53	Find the ags-code of any town in Germany:
54	https://www.statistikportal.de/de/gemeindeverzeichnis
55
56	Parameters
57	----------
58	ags : str or int
59
60	Returns
61	-------
62	shapely.polygon : Outline of the given region
63
64	"""
NEW 65	raise NotImplementedError("ags2polygon is not implemented so far.")	×
66
67
68	def town_to_polygon(town):	5✔
69	"""
70	Create a polygon based on town names
71
72	Parameters
73	----------
74	town : str
75	Town areas which define the polygon. Use ['ALL'] for all town areas
76	in germany
77
78	Returns
79	-------
80	polygon : Shapely Polygon / MultiPolygon
81
82	Examples
83	--------
84	>>> from shapely.geometry import MultiPolygon
85	>>> from dave_data.geometry.polygon import town_to_polygon
86	>>> polygon_town = town_to_polygon(town='Kassel')
87	>>> isinstance(polygon_town, MultiPolygon)
88	True
89	"""
90	postal, meta_data = get_postcode_layer()	5✔
91
92	town = postal.loc[postal["note"].str.lower().str.find(town.lower()) >= 0]	5✔
93
94	return town.union_all()	5✔
95
96
97	def federal_state_to_polygon(federal_state):	5✔
98	"""
99	Create a polygon based on federal states
100
101	Parameters
102	----------
103	federal_state : str
104	Federal state areas which define the polygon. Use ['ALL'] for all
105	Federal state areas in germany
106
107	Returns
108	-------
109	polygon : Shapely Polygon / MultiPolygon
110
111	Examples
112	--------
113	>>> from dave_data.geometry.polygon import federal_state_to_polygon
114	>>> from shapely.geometry import MultiPolygon, Polygon
115	>>> polygon_fed = federal_state_to_polygon(federal_state='Hessen')
116	>>> isinstance(polygon_fed, (MultiPolygon, Polygon))
117	True
118	"""
119	states, meta_data = get_federal_state_layer()	5✔
120
121	state = states.loc[	5✔
122	states["name"].str.lower().str.find(federal_state.lower()) >= 0
123	]
124	return state.union_all()	5✔
125
126
127	def nuts_to_polygon(nuts, year=2016):	5✔
128	"""
129	Create a polygon based on nuts regions
130
131	Parameters
132	----------
133	nuts : List(Str)
134	Nuts areas which define the polygon. Diffrent nuts levels can
135	be combined. Use ['ALL'] for all Nuts 3 areas in germany
136
137	year : scalar(INT), optional(default=2016)
138	The year which forms the basis of the data set
139
140	Returns
141	-------
142	polygon : Shapely Polygon / MultiPolygon
143
144	Examples
145	--------
146	>>> from dave_data.geometry.polygon import nuts_to_polygon
147	>>> from shapely.geometry import Polygon
148	>>> polygon_nuts = nuts_to_polygon(nuts="DE11B", year=2013)
149	>>> isinstance(polygon_nuts, Polygon)
150	True
151	"""
152	# read nuts-3 areas
153	nuts_all, meta_data = get_nuts_layer(year=year)	5✔
154	nuts_3 = nuts_all[nuts_all.LEVL_CODE == 3]	5✔
155
156	nuts_region = nuts_3.loc[nuts_3["NUTS_ID"].str.lower() == nuts.lower()]	5✔
157
158	return nuts_region.union_all()	5✔
159
160
161	def file_to_polygon(filepath, layer=None):	5✔
162	"""
163	Create a polygon based on a file including geographical data
164
165	Parameters
166	----------
167	filepath : scalar(Str)
168	Absolut Path to a file including geographical data. Possible datatypes
169	are .shp, .gpkg and .geojson
170
171	layer : scalar(Str), optional(default=None)
172	The layer name of the data to be considered. Necessary for datatype
173	.gpkg
174
175	Returns
176	-------
177	polygon : Shapely Polygon / MultiPolygon
178
179	"""
180	file_data = read_file(filepath, layer=layer)	5✔
181	return file_data.union_all()	5✔

DaveFoss / DAVE_data / 10884071777

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