Wheelodex » Projects » pyinterpolate » pyinterpolate-0.5.2-py3-none-any.whl

pyinterpolate

View on PyPI — Reverse Dependencies (0)

0.5.2 pyinterpolate-0.5.2-py3-none-any.whl

Wheel Details

Project: pyinterpolate
Version: 0.5.2
Filename: pyinterpolate-0.5.2-py3-none-any.whl
Download: [link]
Size: 138187
MD5: 7fe6b496c31ceeaa346eb1395fdb06fd
SHA256: b9cd8447be2f56c92190024e9ad878c004de867c4706a16b94fc75341bdf3470
Uploaded: 2024-06-26 18:37:24 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: pyinterpolate
Version: 0.5.2
Summary: Spatial Interpolation in Python
Author: Szymon Moliński
Author-Email: simon[at]dataverselabs.com
Home-Page: https://github.com/DataverseLabs/pyinterpolate
Download-Url: https://github.com/DataverseLabs/pyinterpolate/archive/
Project-Url: Documentation, https://readthedocs.org/projects/pyinterpolate/
Project-Url: Source, https://github.com/DataverseLabs/pyinterpolate
Project-Url: Tracker, https://github.com/DataverseLabs/pyinterpolate/issues
License: BSD 3-clause
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Requires-Dist: descartes
Requires-Dist: scikit-learn (==1.2.2)
Requires-Dist: matplotlib (>=3.6)
Requires-Dist: prettytable (>=3.3.0)
Requires-Dist: pyogrio
Requires-Dist: rtree (>=1.0.0)
Requires-Dist: shapely (>=2.0.1)
Requires-Dist: pyarrow
Requires-Dist: pylibtiff (>=0.6.1)
Requires-Dist: deprecation (==2.1.0)
Requires-Dist: numpy (==1.21.2); python_version <= "3.9"
Requires-Dist: tqdm (==4.64.0); python_version <= "3.9"
Requires-Dist: geopandas (<1); python_version == "3.8"
Requires-Dist: pandas (==1.4.3); python_version == "3.8"
Requires-Dist: dask (==2022.2.1); python_version == "3.8" and sys_platform == "darwin"
Requires-Dist: tqdm (>=4.64); python_version > "3.9"
Requires-Dist: numpy (<2); python_version >= "3.10"
Requires-Dist: scipy (>=1.9.0); python_version >= "3.8"
Requires-Dist: dask (==2023.3.2); python_version >= "3.8" and sys_platform == "linux"
Requires-Dist: dask (>=2023.3.2); python_version >= "3.8" and sys_platform == "windows"
Requires-Dist: geopandas; python_version >= "3.9"
Requires-Dist: pandas (>=1.4.3); python_version >= "3.9"
Requires-Dist: dask (==2023.3.2); python_version >= "3.9" and sys_platform == "darwin"
Description-Content-Type: text/markdown; charset=UTF-8
[Description omitted; length: 8589 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (70.1.1)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
pyinterpolate/__init__.py sha256=49DOBrLq--WT-dlka41HgMDnWiN2cLtF2api9m14RXQ 1599
pyinterpolate/distance/__init__.py sha256=KtJDKJDDqXJEA2IfYAudTgHND6V8CwixFfQoD491c30 251
pyinterpolate/distance/clusters.py sha256=Ecat27Gu9kKK_XYsyryE1kjYIWnnMgpQSRu7-ssc5a8 8276
pyinterpolate/distance/distance.py sha256=QA2z8PT1oHI20giLxNU9Gi3AVUQ6Sg7Nfr7kDlOqA8E 11221
pyinterpolate/distance/gridding.py sha256=4b--9_lPv_nkDV-tjodXRqTCz6zUhakQvtr-3twtXrE 6243
pyinterpolate/distance/point.py sha256=q36Hk3dA2olYgL8QYsg933qI7NdP1I4wfY__CkR95yo 2239
pyinterpolate/idw/__init__.py sha256=myAgSf9soymTzNsTAmncpZjPCeRWoRyyjzzvUamTc1w 60
pyinterpolate/idw/idw.py sha256=S5nGAJUoLWIJJETqX2D-y96XpRLOpd1TRcxXb8wkvAo 3476
pyinterpolate/io/__init__.py sha256=CQyGGYsSi4Sqe_NYhMEyapdP5rYqpTxxdtpbj5QhTZQ 70
pyinterpolate/io/read_data.py sha256=a-STLXTXw04zoWnFCvfEQvbEnqfLFhhprj86hOp2QhM 6650
pyinterpolate/kriging/__init__.py sha256=0jljHe5ra2xYanmgfJy7RZOROsoKcC0C53_YFhGBh1E 595
pyinterpolate/kriging/point_kriging.py sha256=yySlUaiXMmvV0eSoiMO3SgOKNYEXzIOeIW-ZXJ1AnNo 7666
pyinterpolate/kriging/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/kriging/models/block/__init__.py sha256=yo2sBquYye3DVHgKuz2W7ufDfmfYKksGYbi7pDeICqA 187
pyinterpolate/kriging/models/block/area_to_area_poisson_kriging.py sha256=MqSIsAPzyCXV66aZjMFkvvAdFmFp6TG28vkP3y3ri6U 7705
pyinterpolate/kriging/models/block/area_to_point_poisson_kriging.py sha256=UJf_jZVrCbpyYuopaPmImm3zgKn1WlmJe7KtIsIF9z0 9800
pyinterpolate/kriging/models/block/centroid_based_poisson_kriging.py sha256=IlHsz95SHTGglQlgSpcccVze0FJueMUabCFGpXHukUg 7387
pyinterpolate/kriging/models/block/weight.py sha256=NOjXEi_Ybowty9JhUNnSLIWSpxqW_FJfWebvqDOnP1I 10644
pyinterpolate/kriging/models/indicator/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/kriging/models/indicator/indicator_point_kriging.py sha256=V3zPsau1mG1yqryGUMqPt0-i87YNTaVWjCnLXyaQY3Q 13128
pyinterpolate/kriging/models/point/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/kriging/models/point/ordinary_kriging.py sha256=4V5Qzh2xU_rs6sUafWLeQFyZvQSCa3SVpDRUVwckABE 6965
pyinterpolate/kriging/models/point/simple_kriging.py sha256=4YdqLecBqXr3v5e3iWqEkof0_KIzfcVJyHBeIQbIsjE 3766
pyinterpolate/kriging/models/structures/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/kriging/models/structures/point_kriging.py sha256=X13BpSGstG664lSIEEYWQKiJcQK2bEYwpC-nbUI-q1Y 687
pyinterpolate/kriging/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/kriging/utils/kwarnings.py sha256=e-19Xn-LTD5bFEouwQMnmnHy3Wd6R3wWMo4BIf7_QcQ 1078
pyinterpolate/kriging/utils/process.py sha256=MCpZxptd8vjCt4lnjeJlYMT695X1BId2Qm9tGS6vfyk 4861
pyinterpolate/pipelines/__init__.py sha256=r78lrKnl6cXOSP3H_Pm1NtjWDo6KTk1YPDoBFDGUo7U 246
pyinterpolate/pipelines/block_filtering.py sha256=JqUtPHHbwimiT4NP-vWipFlDIUArliDGoV-_IZT3BaM 13437
pyinterpolate/pipelines/deconvolution.py sha256=iJbXDdf-xVHhW7hfTa5afJkaYTQPGvYLnI30HpCrJOY 5227
pyinterpolate/pipelines/multi_kriging.py sha256=xYoWdLbUVao7kY-yOqPB1V_v8ZfalvjSui3DGb-chVI 12890
pyinterpolate/processing/__init__.py sha256=5IUx89PXDurOhsMuH8i7tnIg6bEXCr1G9bY7BhruUME 79
pyinterpolate/processing/checks.py sha256=1XqByOZMZ6M3_mSFgXKIC_QUJjLt27SWqk656GzmP3s 2543
pyinterpolate/processing/select_values.py sha256=52hqfCTTvxGiiDg3VR9w__9jxf_cjkzzt3hmFVRxhmQ 36358
pyinterpolate/processing/preprocessing/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/processing/preprocessing/blocks.py sha256=pdDhBe1TCn3XB9hXVuivrNxuOyCoqegAHF4U5am21yQ 18278
pyinterpolate/processing/transform/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/processing/transform/statistics.py sha256=Yy3sYJy6ZoQNgkhH0fQHgk04lNh0moofxi2qwdI16aY 5490
pyinterpolate/processing/transform/transform.py sha256=Z7wW8UzJnPMjU2d2NyP4dIHzKK1J9IqwSPUXA6Q9tEs 11202
pyinterpolate/processing/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/processing/utils/exceptions.py sha256=IdRnu_ESYSrdOhFb5drxQ1CDhLAXZxr6KyJj7wZ09EE 1802
pyinterpolate/validation/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/validation/cross_validation.py sha256=Eu6iya9KmOAIUlOexEFP1ZhLlLJlN0w_Ez3L1epgXIc 4079
pyinterpolate/variogram/__init__.py sha256=MG64ftB9XlYiEzrEeZccdPpfq0VcJojCjTjrMRk2mpI 682
pyinterpolate/variogram/empirical/__init__.py sha256=blwOUE4mLPH0_bOS72F6GFu1Kl--pC1MJuySY05RWhE 1857
pyinterpolate/variogram/empirical/cloud.py sha256=EN03u8_H2uUFaV89aGRQgtnjdQW9VzkEAR8y44wc_Vk 23312
pyinterpolate/variogram/empirical/covariance.py sha256=vKBEdno6H5JNZLw70jcDm7_QduUMlOf7UDPLjPI6nig 10469
pyinterpolate/variogram/empirical/experimental_variogram.py sha256=8iPdMH8HYG2_1FFrlwS8ChDSsW55eWGDwLHg6q_6rcQ 24223
pyinterpolate/variogram/empirical/semivariance.py sha256=66bcUhLHpTYfqmi3AExE1i8S7RHFbwW-QMMdkKOCEzs 23443
pyinterpolate/variogram/indicator/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/variogram/indicator/indicator_variogram.py sha256=-a_v594yKTKL6oAQit1tDmROkDfnQ_3IL1ziCLj1WcE 16103
pyinterpolate/variogram/regularization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/variogram/regularization/aggregated.py sha256=Z9RmljNo5bMgIp0ABFaXlQiRPcWKDIrbJLvcU6FESRo 24597
pyinterpolate/variogram/regularization/deconvolution.py sha256=1W3lWdv81kUXfS4CduOhpJ6RHsmqiqJq2ycD2HCu0Ic 32871
pyinterpolate/variogram/regularization/block/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/variogram/regularization/block/avg_block_to_block_semivariances.py sha256=r9qxQOQb6uAkF1DxW8wGLbAlvwWcgVrCFIWcYwXIzVM 1489
pyinterpolate/variogram/regularization/block/avg_inblock_semivariances.py sha256=k17a5uykuaQiqGroA_-US2C12AFXd_bQD9JcgzWy7hQ 4047
pyinterpolate/variogram/regularization/block/block_to_block_semivariance.py sha256=jtmPfMLvHwq7z9djSglvXDczjqb8LwJAVUIhypNLLLQ 5223
pyinterpolate/variogram/regularization/block/inblock_semivariance.py sha256=e89_-5zkcaqGSJbIxtan7vbi129BqNfcpgcYmNYHHo0 8887
pyinterpolate/variogram/theoretical/__init__.py sha256=pJIfrK5FGt8KDtxpndIz2DKPCwieA3g1hpFS5cLir3E 5340
pyinterpolate/variogram/theoretical/semivariogram.py sha256=Elqg2GsBRJOamomgu3X3MV4wP5bbywT6uMDuD4i3Pqs 36986
pyinterpolate/variogram/theoretical/spatial_dependency_index.py sha256=7S4si7DRiAWCHgC1QZck66-XYsbGpYT9Ww764WOxYeQ 1140
pyinterpolate/variogram/theoretical/models/__init__.py sha256=6BgcGlEBkPEuZAsQgbyIQrlvZaMBr0TL4v27ioa874I 31
pyinterpolate/variogram/theoretical/models/variogram_models.py sha256=HWApj8MbcnD3o8fxPmTEnRthkJbAhPym2DQwe3c-P4Q 8319
pyinterpolate/variogram/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyinterpolate/variogram/utils/exceptions.py sha256=SwbjxXmjKP4pRdjGymmSGn-AAvPpPNN5xGeWtcR3Vmw 6851
pyinterpolate/variogram/utils/metrics.py sha256=GuN12aiJcz5tpzidnSvL16_YhzmmBRxchIBVSS765Jc 9500
pyinterpolate/variogram/utils/plots.py sha256=c6ve3KQr2UtSz7V-OddnfNwaLyXB8eTrXWQ7atMAAGs 2046
pyinterpolate/viz/__init__.py sha256=ZWsE2T6kh1KdtJCUqOPG1Rj4IueBQZREcyCE-kniMBg 55
pyinterpolate/viz/raster.py sha256=5Rc1n6oAP3D3mp5h6SvvVEjyWNCh5NxIZrjXHzZpyW8 12908
pyinterpolate-0.5.2.dist-info/METADATA sha256=gNc3Y9nHjXVyykYXzi5Y6IiXj_N5rBFgxEVN4bfFCRM 10782
pyinterpolate-0.5.2.dist-info/WHEEL sha256=mguMlWGMX-VHnMpKOjjQidIo1ssRlCFu4a4mBpz1s2M 91
pyinterpolate-0.5.2.dist-info/top_level.txt sha256=bRpcBIDbBLgPsQ3B8GZQIfC8NFAQ1dbJJHcdKIMdYOM 14
pyinterpolate-0.5.2.dist-info/RECORD — —

top_level.txt

pyinterpolate