1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
|
%global _empty_manifest_terminate_build 0
Name: python-satflow
Version: 0.3.36
Release: 1
Summary: Satellite Optical Flow
License: MIT License
URL: https://github.com/openclimatefix/satflow
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ee/e0/cc6d95438ff7c0fcfc71a722913a9bd38f60b0d0fe863f393a08777d01f6/satflow-0.3.36.tar.gz
BuildArch: noarch
Requires: python3-albumentations
Requires: python3-antialiased-cnns
Requires: python3-hydra-core
Requires: python3-hydra-optuna-sweeper
Requires: python3-hydra-colorlog
Requires: python3-lightning-bolts
Requires: python3-neptune-client
Requires: python3-neptune-pytorch-lightning
Requires: python3-pytest
Requires: python3-dotenv
Requires: python3-pytorch-msssim
Requires: python3-rich
Requires: python3-torchvision
Requires: python3-affine
Requires: python3-torch-optimizer
Requires: python3-huggingface-hub
Requires: python3-einops
Requires: python3-metnet
Requires: python3-skillful-nowcasting
Requires: python3-perceiver-model
Requires: python3-nowcasting-dataset
Requires: python3-nowcasting-utils
Requires: python3-transformers
Requires: python3-torch
%description
# SatFlow
***Sat***ellite Optical ***Flow*** with machine learning models.
The goal of this repo is to improve upon optical flow models for predicting
future satellite images from current and past ones, focused primarily on EUMETSAT data.
## Installation
Clone the repository, then run
```shell
conda env create -f environment.yml
conda activate satflow
pip install -e .
````
Alternatively, you can also install a usually older version through ```pip install satflow```
## Data
The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG
satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and
numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded
from the tagged release, as well as included under ```datasets/```.
%package -n python3-satflow
Summary: Satellite Optical Flow
Provides: python-satflow
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-satflow
# SatFlow
***Sat***ellite Optical ***Flow*** with machine learning models.
The goal of this repo is to improve upon optical flow models for predicting
future satellite images from current and past ones, focused primarily on EUMETSAT data.
## Installation
Clone the repository, then run
```shell
conda env create -f environment.yml
conda activate satflow
pip install -e .
````
Alternatively, you can also install a usually older version through ```pip install satflow```
## Data
The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG
satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and
numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded
from the tagged release, as well as included under ```datasets/```.
%package help
Summary: Development documents and examples for satflow
Provides: python3-satflow-doc
%description help
# SatFlow
***Sat***ellite Optical ***Flow*** with machine learning models.
The goal of this repo is to improve upon optical flow models for predicting
future satellite images from current and past ones, focused primarily on EUMETSAT data.
## Installation
Clone the repository, then run
```shell
conda env create -f environment.yml
conda activate satflow
pip install -e .
````
Alternatively, you can also install a usually older version through ```pip install satflow```
## Data
The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG
satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and
numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded
from the tagged release, as well as included under ```datasets/```.
%prep
%autosetup -n satflow-0.3.36
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-satflow -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.36-1
- Package Spec generated
|
