automatic import of python-pollination-adaptive-comfort-map

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+/pollination-adaptive-comfort-map-0.9.0.tar.gz
diff --git a/python-pollination-adaptive-comfort-map.spec b/python-pollination-adaptive-comfort-map.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pollination-adaptive-comfort-map
+Version:	0.9.0
+Release:	1
+Summary:	Adaptive thermal comfort map for Pollination.
+License:	PolyForm Shield License 1.0.0, https://polyformproject.org/wp-content/uploads/2020/06/PolyForm-Shield-1.0.0.txt
+URL:		https://github.com/pollination/adaptive-comfort-map
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/27/9b/ed07085bf900c3765d21638bbf9cb2db71ca178e93478970faa6114f71a0/pollination-adaptive-comfort-map-0.9.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pollination-ladybug
+Requires:	python3-pollination-ladybug-comfort
+Requires:	python3-pollination-honeybee-radiance
+Requires:	python3-pollination-honeybee-energy
+Requires:	python3-pollination-lbt-honeybee
+Requires:	python3-pollination-alias
+Requires:	python3-pollination-path
+Requires:	python3-pollination-honeybee-display
+
+%description
+# Adaptive Comfort Map
+
+Adaptive thermal comfort map recipe for Pollination.
+
+Compute spatially-resolved operative temperature and adaptive thermal comfort from
+a Honeybee model and EPW. Raw results are written into a `results/` folder and
+include CSV matrices of hourly operative temperatures and thermal conditions. Processed
+metrics of Thermal Comfort Percent (TCP) can be found in the `metrics/` folder.
+
+## Methods
+
+This recipe uses EnergyPlus to obtain longwave radiant temperatures and indoor air
+temperatures. The outdoor air temperature and air speed are taken directly from
+the EPW. All outdoor points are assumed to be at one half of the EPW meteorological
+wind speed (effectively representing wind speed at ground/human height).
+
+Longwave radiant temperatures are achieved by computing spherical view factors
+from each sensor to the surfaces of the model using Radiance. These view factors
+are then multiplied by the surface temperatures output by EnergyPlus to yield
+longwave MRT at each sensor. All indoor shades (eg. those representing furniture)
+are assumed to be at the room-average MRT. For outdoor sensors, the EnergyPlus
+outdoor surface temperatures are used and each sensor's sky view is multiplied by
+the EPW sky temperature to account for longwave radiant exchange with the sky.
+All outdoor context shades and the ground are assumed to be at the EPW air
+temperature unless they have been modeled as Honeybee rooms.
+
+A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations,
+which precisely represents direct sun by tracing a ray from each sensor to the
+solar position. The energy properties of the model geometry are what determine
+the reflectance and transmittance of the Radiance materials in this shortwave
+calculation.
+
+To determine Thermal Comfort Percent (TCP), the occupancy schedules of the energy
+model are used. Any hour of the occupancy schedule that is 0.1 or greater will be
+considered occupied. For outdoor sensors, all hours are considered occupied.
+
+
+
+
+%package -n python3-pollination-adaptive-comfort-map
+Summary:	Adaptive thermal comfort map for Pollination.
+Provides:	python-pollination-adaptive-comfort-map
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pollination-adaptive-comfort-map
+# Adaptive Comfort Map
+
+Adaptive thermal comfort map recipe for Pollination.
+
+Compute spatially-resolved operative temperature and adaptive thermal comfort from
+a Honeybee model and EPW. Raw results are written into a `results/` folder and
+include CSV matrices of hourly operative temperatures and thermal conditions. Processed
+metrics of Thermal Comfort Percent (TCP) can be found in the `metrics/` folder.
+
+## Methods
+
+This recipe uses EnergyPlus to obtain longwave radiant temperatures and indoor air
+temperatures. The outdoor air temperature and air speed are taken directly from
+the EPW. All outdoor points are assumed to be at one half of the EPW meteorological
+wind speed (effectively representing wind speed at ground/human height).
+
+Longwave radiant temperatures are achieved by computing spherical view factors
+from each sensor to the surfaces of the model using Radiance. These view factors
+are then multiplied by the surface temperatures output by EnergyPlus to yield
+longwave MRT at each sensor. All indoor shades (eg. those representing furniture)
+are assumed to be at the room-average MRT. For outdoor sensors, the EnergyPlus
+outdoor surface temperatures are used and each sensor's sky view is multiplied by
+the EPW sky temperature to account for longwave radiant exchange with the sky.
+All outdoor context shades and the ground are assumed to be at the EPW air
+temperature unless they have been modeled as Honeybee rooms.
+
+A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations,
+which precisely represents direct sun by tracing a ray from each sensor to the
+solar position. The energy properties of the model geometry are what determine
+the reflectance and transmittance of the Radiance materials in this shortwave
+calculation.
+
+To determine Thermal Comfort Percent (TCP), the occupancy schedules of the energy
+model are used. Any hour of the occupancy schedule that is 0.1 or greater will be
+considered occupied. For outdoor sensors, all hours are considered occupied.
+
+
+
+
+%package help
+Summary:	Development documents and examples for pollination-adaptive-comfort-map
+Provides:	python3-pollination-adaptive-comfort-map-doc
+%description help
+# Adaptive Comfort Map
+
+Adaptive thermal comfort map recipe for Pollination.
+
+Compute spatially-resolved operative temperature and adaptive thermal comfort from
+a Honeybee model and EPW. Raw results are written into a `results/` folder and
+include CSV matrices of hourly operative temperatures and thermal conditions. Processed
+metrics of Thermal Comfort Percent (TCP) can be found in the `metrics/` folder.
+
+## Methods
+
+This recipe uses EnergyPlus to obtain longwave radiant temperatures and indoor air
+temperatures. The outdoor air temperature and air speed are taken directly from
+the EPW. All outdoor points are assumed to be at one half of the EPW meteorological
+wind speed (effectively representing wind speed at ground/human height).
+
+Longwave radiant temperatures are achieved by computing spherical view factors
+from each sensor to the surfaces of the model using Radiance. These view factors
+are then multiplied by the surface temperatures output by EnergyPlus to yield
+longwave MRT at each sensor. All indoor shades (eg. those representing furniture)
+are assumed to be at the room-average MRT. For outdoor sensors, the EnergyPlus
+outdoor surface temperatures are used and each sensor's sky view is multiplied by
+the EPW sky temperature to account for longwave radiant exchange with the sky.
+All outdoor context shades and the ground are assumed to be at the EPW air
+temperature unless they have been modeled as Honeybee rooms.
+
+A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations,
+which precisely represents direct sun by tracing a ray from each sensor to the
+solar position. The energy properties of the model geometry are what determine
+the reflectance and transmittance of the Radiance materials in this shortwave
+calculation.
+
+To determine Thermal Comfort Percent (TCP), the occupancy schedules of the energy
+model are used. Any hour of the occupancy schedule that is 0.1 or greater will be
+considered occupied. For outdoor sensors, all hours are considered occupied.
+
+
+
+
+%prep
+%autosetup -n pollination-adaptive-comfort-map-0.9.0
+
+%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-pollination-adaptive-comfort-map -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..8cfee0b
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+3f6dcc4ea8792695108808627071d8bc  pollination-adaptive-comfort-map-0.9.0.tar.gz