def convert_coordinates(df,
x_col="Easting",
y_col="Northing",
from_epsg="32631",
to_epsg="3857"):
"""Transform coordinates from one system to another
Parameters
----------
df : pandas DataFrame
Points or artifacts DataFrame with coordinate columns
x_col, y_col : str
Columns with x- and y-coordinates
from_epsg, to_epsg : str
EPSG coordinate system codes for the input and output coordinates
Returns
-------
df : pandas DataFrame
Original DataFrame with new columns 'x2' and 'y2'
Notes
-----
Default behavior is to convert UTMs from Zone 31N to Web Mercator
"""
from functools import partial
from shapely.ops import transform
import pyproj
df["new_coords"] = df.apply(
lambda row: transform(
partial(
pyproj.transform,
pyproj.Proj(init=f"EPSG:{from_epsg}"),
pyproj.Proj(init=f"EPSG:{to_epsg}"),
),
_Point(row.loc[x_col], row.loc[y_col]),
),
axis=1,
)
df["x2"] = df["new_coords"].apply(lambda pt: pt.x)
df["y2"] = df["new_coords"].apply(lambda pt: pt.y)
df.drop(columns=["new_coords"], inplace=True)
return df
def __contains__(self, point, validate=True):
"""
"""
point = space3.Point(*point, validate=validate)
ulc, urc, llc, lrc = self.corners
_polygon = _Polygon((
(ulc.x, ulc.y),
(urc.x, urc.y),
(lrc.x, lrc.y),
(llc.x, llc.y),
))
_point = _Point(point.x, point.y)
if (self.plane.get_distance(point) == 0 and
(_polygon.contains(_point) or _polygon.intersects(_point))):
return T
else:
return F
def find_geo_field(df, fields_shp_path):
"""Find the identifier for the field where the point or artifact lies geographically.
Parameters
----------
df : pandas DataFrame
Points or Artifacts DataFrame; must contain 'Easting' and 'Northing' columns
fields_shp_path : str
Path to the shapefile (.shp) containing the fields
Returns
-------
joined_df : pandas DataFrame
Identical to the input points DataFrame with an added 'geo_field' column
Notes
-----
"""
fields = _gpd.read_file(fields_shp_path) # load all fields
fields["fid"] = (fields["MASA"].str[-2:] + fields["PARCELA"].str[-3:] +
fields["SUBPARCE"].str[0:])
fields = fields[["fid", "geometry"]] # get only columns we need
geometry = [
_Point(xy) for xy in zip(
df["Easting"].fillna(0), # make coords into shapely Points
df["Northing"].fillna(0),
)
]
pts_gdf = _gpd.GeoDataFrame(
df, geometry=geometry) # make Points into GeoDataFrame
pts_gdf.crs = fields.crs # make coordinate systems equivalent
joined_df = _gpd.sjoin(
pts_gdf, fields, how="inner", op="intersects"
) # do a spatial join to find the ACTUAL fields that intersect locations
joined_df = joined_df.rename(
columns={"fid": "geo_field"}) # returns the geo_field for every record
return joined_df