diff --git a/enpt/io/reader.py b/enpt/io/reader.py
index de0432d5d4703ab3f9aa5619f907e780e880e445..732bd8bbb6c67e090640543192aa4615af506f62 100644
--- a/enpt/io/reader.py
+++ b/enpt/io/reader.py
@@ -33,7 +33,6 @@ import logging
import os
from fnmatch import filter
import numpy as np
-from scipy.interpolate import interp1d
from ..model.images import EnMAPL1Product_SensorGeo
from ..options.config import EnPTConfig
@@ -162,14 +161,14 @@ class L1B_Reader(object):
pass
-def Solar_Irradiance_reader(path_solar_irr_model: str, resol_nm: float = None, wvl_min_nm: float = None,
- wvl_max_nm: float = None) -> np.ndarray:
+def read_solar_irradiance(path_solar_irr_model: str, resol_nm: float = None, wvl_min_nm: float = None,
+ wvl_max_nm: float = None) -> np.ndarray:
"""Read the given solar irradiance file and return an array of irradiances.
:param path_solar_irr_model: file path to solar irradiance model
-> must be arranged like that:
- col0 = Wavelength[nm]; col1 = Solar Irradiance [W/m2/µm])
+ col0 = Wavelength[nm]; col1 = Solar Irradiance [W/m2/µm]
:param resol_nm: spectral resolution for returned irradiances [nanometers]
:param wvl_min_nm: minimum wavelength of returned irradiances [nanometers]
:param wvl_max_nm: maximum wavelength of returned irradiances [nanometers]
@@ -180,5 +179,5 @@ def Solar_Irradiance_reader(path_solar_irr_model: str, resol_nm: float = None, w
wvl_min = (np.min(sol_irr[:, 0]) if wvl_min_nm is None else wvl_min_nm)
wvl_max = (np.max(sol_irr[:, 0]) if wvl_max_nm is None else wvl_max_nm)
wvl_rsp = np.arange(wvl_min, wvl_max, resol_nm)
- sol_irr = interp1d(sol_irr[:, 0], sol_irr[:, 1], kind='linear')(wvl_rsp)
+ sol_irr = np.interp(wvl_rsp, sol_irr[:, 0], sol_irr[:, 1])
return sol_irr
diff --git a/enpt/model/metadata/metadata_sensorgeo.py b/enpt/model/metadata/metadata_sensorgeo.py
index a95da215ed2ac49fc320095a490ba4317cd56c79..d51ddaf450b182d8cdf07998823eab5535a5a39b 100644
--- a/enpt/model/metadata/metadata_sensorgeo.py
+++ b/enpt/model/metadata/metadata_sensorgeo.py
@@ -384,11 +384,10 @@ class EnMAP_Metadata_L1B_Detector_SensorGeo(object):
return gA
else:
- from scipy.interpolate import interp1d
- coeffs_interp = \
- interp1d(gA.meta.band_meta['wavelength'], gA[:],
- axis=2, kind='linear', fill_value="extrapolate", bounds_error=False)(self.wvl_center)
-
+ from scipy.interpolate import make_interp_spline
+ # equivalent to legacy scipy.interpolate.interp1d
+ # interp1d(wvl, gA[:], axis=2, kind='linear', fill_value="extrapolate", bounds_error=False)(self.wvl_center)
+ coeffs_interp = make_interp_spline(gA.meta.band_meta['wavelength'], gA[:], k=1, axis=2)(self.wvl_center)
gA_ = GeoArray(coeffs_interp)
gA_.meta.band_meta['wavelength'] = self.wvl_center
@@ -444,11 +443,11 @@ class EnMAP_Metadata_L1B_Detector_SensorGeo(object):
return lons, lats
def calc_solar_irradiance_CWL_FWHM_per_band(self) -> np.array:
- from ...io.reader import Solar_Irradiance_reader
+ from ...io.reader import read_solar_irradiance
self.logger.debug('Calculating solar irradiance...')
- sol_irr = Solar_Irradiance_reader(path_solar_irr_model=self.cfg.path_solar_irr, wvl_min_nm=350, wvl_max_nm=2500)
+ sol_irr = read_solar_irradiance(path_solar_irr_model=self.cfg.path_solar_irr, wvl_min_nm=350, wvl_max_nm=2500)
irr_bands = []
for band in self.srf.bands:
diff --git a/enpt/processors/spatial_transform/spatial_transform.py b/enpt/processors/spatial_transform/spatial_transform.py
index 17dcbf0581b2e446d37d92032c912075c663bd99..3ec62842f664df633d80aa4b527527e4139be72b 100644
--- a/enpt/processors/spatial_transform/spatial_transform.py
+++ b/enpt/processors/spatial_transform/spatial_transform.py
@@ -32,7 +32,7 @@ from typing import Union, Tuple, List, Optional, Sequence # noqa: F401
from multiprocessing import Pool, cpu_count
from collections import OrderedDict
import numpy as np
-from scipy.interpolate import interp1d, LinearNDInterpolator
+from scipy.interpolate import LinearNDInterpolator, make_interp_spline
from scipy.spatial import Delaunay
from geoarray import GeoArray
from natsort import natsorted
@@ -405,26 +405,27 @@ class RPC_Geolayer_Generator(object):
raise ValueError(arr.ndim, '2D numpy array expected.')
if along_axis not in [0, 1]:
raise ValueError(along_axis, "The 'axis' parameter must be set to 0 or 1")
-
- kw = dict(kind='linear', fill_value='extrapolate')
+ arr[0, 0] = np.nan
+ arr[0, 1] = np.nan
+ arr[1, 1] = np.nan
nans = np.isnan(arr)
if along_axis == 0:
- # extrapolate in top/bottom direction
+ # extrapolate linearly in top/bottom direction
cols_with_nan = np.arange(arr.shape[1])[np.any(nans, axis=0)]
for col in cols_with_nan:
data = arr[:, col]
idx_goodvals = np.argwhere(~nans[:, col]).flatten()
- arr[:, col] = interp1d(idx_goodvals, data[idx_goodvals], **kw)(range(data.size))
+ arr[:, col] = make_interp_spline(idx_goodvals, data[idx_goodvals], k=1)(range(data.size))
else:
- # extrapolate in left/right direction
+ # extrapolate linearly in left/right direction
rows_with_nan = np.arange(arr.shape[0])[np.any(nans, axis=1)]
for row in rows_with_nan:
data = arr[row, :]
idx_goodvals = np.argwhere(~nans[row, :]).flatten()
- arr[row, :] = interp1d(idx_goodvals, data[idx_goodvals], **kw)(range(data.size))
+ arr[row, :] = make_interp_spline(idx_goodvals, data[idx_goodvals], k=1)(range(data.size))
return arr