Verify and potentially improve Python-related code, #316231; removed old patches

Package-Manager: portage-2.2.0_alpha6/cvs/Linux x86_64

6 files changed, 99 insertions, 523 deletions

diff --git a/sci-mathematics/fann/ChangeLog b/sci-mathematics/fann/ChangeLog
index f7d9c74cc1a3..aa6b725bdc4c 100644
--- a/sci-mathematics/fann/ChangeLog
+++ b/sci-mathematics/fann/ChangeLog
@@ -1,6 +1,11 @@
 # ChangeLog for sci-mathematics/fann
 # Copyright 1999-2010 Gentoo Foundation; Distributed under the GPL v2
-# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/ChangeLog,v 1.14 2010/06/04 15:32:47 arfrever Exp $
+# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/ChangeLog,v 1.15 2010/12/23 08:26:55 jlec Exp $
+
+  23 Dec 2010; Justin Lecher <jlec@gentoo.org> -files/fann-1.2.0-r1.patch,
+  -files/fann-1.2.0-setup.py, fann-2.0.0.ebuild, fann-2.1.0_beta.ebuild:
+  Verify and potentially improve Python-related code, #316231; removed old
+  patches
 
   04 Jun 2010; Arfrever Frehtes Taifersar Arahesis <arfrever@gentoo.org>
   fann-2.1.0_beta.ebuild:
diff --git a/sci-mathematics/fann/Manifest b/sci-mathematics/fann/Manifest
index 5c886e8cbf8e..535d9c93e851 100644
--- a/sci-mathematics/fann/Manifest
+++ b/sci-mathematics/fann/Manifest
@@ -1,5 +1,6 @@
-AUX fann-1.2.0-r1.patch 14130 RMD160 b6cf23f60464efb330af374cbce21825f79f051c SHA1 bfbee4b483b22db3487c9751c4bdf0a48aa86aef SHA256 e3c902ae4d1bf6c1f007319406742285f762def454be590c2e8774cfc1263892
-AUX fann-1.2.0-setup.py 1503 RMD160 5577f9ca2845e09454ced87df38eabe8e164bfc0 SHA1 e70764a15c23b8b958b309b029586ba9ea129a87 SHA256 2b77107528c369fbf557b5c502bea17fdea2144d9a8caa906a1c531bc348adba
+-----BEGIN PGP SIGNED MESSAGE-----
+Hash: SHA1
+
 AUX fann-2.0.0-benchmark.patch 1986 RMD160 9660044ab4fadc476cda8653ad171ef7b0d5e1e5 SHA1 43645f9e1a198040d7c63d2da7755696087f07bc SHA256 ba4dd808fc66dd7fadb61e82ff12fdb6841c56e70c3d17a6a5e8d316e4d79b66
 AUX fann-2.0.0-shared-libs-gentoo.patch 1193 RMD160 b7e70b62187fe81363406fad1cabffbd9c98349c SHA1 c2d27d013e11d7bf0098dccf6ad619a32d25a1c8 SHA256 788faf6fde0ee954581b95e2630b265aeb3e88c3bb2fd696bc98e470b87b30f3
 AUX fann-2.1.0_beta-asneeded.patch 280 RMD160 495614dcab634ada103a1be9755f5e54d32ef2b8 SHA1 a9dc32d477a30a2682fdf301922da3dc73778dc6 SHA256 a9ff761ccaf54136795f4491945c486a23560db15f8839991ce8c2a8cee73187
@@ -8,7 +9,14 @@ AUX fann-2.1.0_beta-examples.patch 923 RMD160 7379369370db10635234f7245f4636969e
 AUX fann-2.1.0_beta-python.patch 750 RMD160 1609d02da5096c2fc3404f2747f55261faba58bd SHA1 9cf261f3733be27a49e8bcebf0879347fb7b1d6a SHA256 94490da5c5b6216c97e987965b92347e3d5125ea32a9aaa62cd8b584036f9a01
 DIST fann-2.0.0.tar.bz2 2310853 RMD160 9d7268eaf06ab177eafb72359a1cf73a70e5a886 SHA1 af4d4efe2362e68929bee73cde85bca10c48df43 SHA256 762a1313a9b935300cb66ebf052d469d04823ca721fe6dd2a49c01e13e8ab30a
 DIST fann-2.1.0beta.zip 4033198 RMD160 f0d5366547a1f3998246b9ffec9c9a65ec70fa9e SHA1 ee86afbb9787cd41a42e07db2a9bc10699b555f6 SHA256 c24171b5b9c87946bd2f50045cc8dbd0121629fe426615501db14e6043e4a141
-EBUILD fann-2.0.0.ebuild 1838 RMD160 2dd97d2396b1937461060a7b832ca7cfb536b6a5 SHA1 30252e4366a99e7b57950a98681e0d222b8d7b01 SHA256 7cdf98b489d3ffda3e2c19c0b98cf64191640c2b281b8f72bb2b11e0c4000577
-EBUILD fann-2.1.0_beta.ebuild 1929 RMD160 4c672f9d35b9bb3c1928bca84c1587ffc4e0d6ea SHA1 e65db98ad57ced0a007e1406b35c9f1664a316a9 SHA256 101301ba463c67161ebde6bc77e51e1d6aaec956660b9450a4b630a489536a95
-MISC ChangeLog 2633 RMD160 89f313d8d464bd0f5f04601c2732cfcebc9ee3e6 SHA1 0cdc45bbb33af29a93026a78d2597859ca449c00 SHA256 fd560fe83043acfbe103c02c239ccf1a2146cdc8411dd1f5cef8e744f63d9e5e
+EBUILD fann-2.0.0.ebuild 1855 RMD160 e266c54e5e9d1c59349bd7dcdb372251bc3fabe5 SHA1 360f872831c5a3df84807ab7c63850a71161dadb SHA256 8daee06d19d14f7c39a35d090b5e797baa7e9f0ff88c764a7315c792f77a425f
+EBUILD fann-2.1.0_beta.ebuild 2262 RMD160 a6bfd0bcfbeb33b6efaabf2a1ec006fd4ef07624 SHA1 35f7f965ce3be59cdebdb0c8c8308d433da07ed2 SHA256 25e542c1d638094c60f368c7671811793f899ea4f2bc0761ff8fc0906987bbdf
+MISC ChangeLog 2863 RMD160 5f5344cb06a94fafc7178c301611e189feb579f6 SHA1 10be359f10cc563337bad9b785f33fc0ab24165a SHA256 69e803881cd2080c94ff0b74445f14fada1599824cd9b3e9d7743f0dbe149f4b
 MISC metadata.xml 658 RMD160 25e209eb45899500179b5f893cc72ca41ab2370a SHA1 0c05318426869d997f382e37c9a9a5371123b052 SHA256 003060bd03fae3d61eeffbe23a4b181b905761a9e21bb1482fdec962e099641b
+-----BEGIN PGP SIGNATURE-----
+Version: GnuPG v2.0.16 (GNU/Linux)
+
+iEYEARECAAYFAk0TB9oACgkQgAnW8HDreRaYzwCdH6DnK/YoFHOK6RhQzHJBdXnA
+vPMAoMo2h9bYa3HZImldRypkqLnRPupP
+=3dLG
+-----END PGP SIGNATURE-----
diff --git a/sci-mathematics/fann/fann-2.0.0.ebuild b/sci-mathematics/fann/fann-2.0.0.ebuild
index beaa6df68635..61a71e4ed63c 100644
--- a/sci-mathematics/fann/fann-2.0.0.ebuild
+++ b/sci-mathematics/fann/fann-2.0.0.ebuild
@@ -1,68 +1,77 @@
-# Copyright 1999-2008 Gentoo Foundation
+# Copyright 1999-2010 Gentoo Foundation
 # Distributed under the terms of the GNU General Public License v2
-# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/fann-2.0.0.ebuild,v 1.6 2008/05/12 13:10:17 markusle Exp $
+# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/fann-2.0.0.ebuild,v 1.7 2010/12/23 08:26:55 jlec Exp $
 
-inherit eutils
+EAPI=2
 
-DESCRIPTION="Fast Artificial Neural Network Library implements multilayer artificial neural networks in C"
+PYTHON_DEPEND="python? 2"
+SUPPORT_PYTHON_ABIS="1"
+RESTRICT_PYTHON_ABIS="3.*"
+
+inherit eutils python
+
+MY_P=${P/_/}
+
+DESCRIPTION="Fast Artificial Neural Network Library"
 HOMEPAGE="http://leenissen.dk/fann/"
-SRC_URI="mirror://sourceforge/fann/${P}.tar.bz2"
+SRC_URI="mirror://sourceforge/${PN}/${P}.tar.bz2"
 
 LICENSE="LGPL-2.1"
 SLOT="0"
 KEYWORDS="~amd64 ~ppc ~x86"
 IUSE="doc python"
 
-RDEPEND="python? ( dev-lang/python )"
-DEPEND="${RDEPEND}
-		python? ( dev-lang/swig )"
+RDEPEND=""
+DEPEND="
+	${RDEPEND}
+	python? ( dev-lang/swig )"
 
-src_unpack() {
-	unpack ${A}
-	cd "${S}"
-	epatch "${FILESDIR}"/${P}-shared-libs-gentoo.patch
-	epatch "${FILESDIR}"/${P}-benchmark.patch
+src_prepare() {
+	epatch \
+		"${FILESDIR}"/${P}-shared-libs-gentoo.patch \
+		"${FILESDIR}"/${P}-benchmark.patch
+	use python && python_copy_sources python
 }
 
 src_compile() {
-	econf ${myconf} || die "configure failed"
 	emake || die "failed to build src"
-	if use python; then
-		cd "${S}"/python || \
-			die "failed to step into python subdirectory"
-		emake || die "failed to build python wrappers"
-		cd "${S}"
-	fi
+	compilation() {
+		emake PYTHON_VERSION="$(python_get_version)" || die "emake python failed"
+	}
+	use python && python_execute_function -s --source-dir python compilation
 }
 
 src_install() {
-	make install DESTDIR="${D}" || die "install failed"
-	dodoc AUTHORS ChangeLog NEWS README TODO
+	emake install DESTDIR="${D}" || die "install failed"
+	dodoc AUTHORS ChangeLog NEWS README TODO || die
 
 	if use doc; then
 		dodoc doc/*.txt || \
 			die "failed to install docs"
-		insinto /usr/share/doc/${P}
+		insinto /usr/share/doc/${PF}
 		doins doc/fann_en.pdf || \
 			die "failed to install reference manual"
-		insinto /usr/share/${PN}/benchmarks
-		doins -r benchmarks/* || \
+		insinto /usr/share/${PN}
+		doins -r benchmarks || \
 			die "failed to install benchmarks"
-		insinto /usr/share/${PN}/examples
-		doins examples/* || \
+		doins -r examples || \
 			die "failed to install examples"
 	fi
 
-	if use python; then
-		cd "${S}"/python || \
-			die "Faild to step into python subdirectory"
-		make install ROOT="${D}" || \
-			die "failed to install python wrappers"
+	installation() {
+		emake install ROOT="${D}" || die "failed to install python wrappers"
 		if use doc; then
-			local python_doc_dir="/usr/share/${PN}/examples/python"
-			insinto ${python_doc_dir}
-			doins examples/* || \
-				die "failed to install python examples"
+			insinto /usr/share/doc/${PF}/examples/python
+			doins -r examples || die "failed to install python examples"
 		fi
-	fi
+	}
+	use python && python_execute_function -s --source-dir python installation
+}
+
+pkg_postinst() {
+	python_mod_optimize py${PN}
+}
+
+pkg_postrm() {
+	python_mod_cleanup py${PN}
 }
diff --git a/sci-mathematics/fann/fann-2.1.0_beta.ebuild b/sci-mathematics/fann/fann-2.1.0_beta.ebuild
index 1534700a45c8..61b5d5b79d01 100644
--- a/sci-mathematics/fann/fann-2.1.0_beta.ebuild
+++ b/sci-mathematics/fann/fann-2.1.0_beta.ebuild
@@ -1,11 +1,17 @@
 # Copyright 1999-2010 Gentoo Foundation
 # Distributed under the terms of the GNU General Public License v2
-# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/fann-2.1.0_beta.ebuild,v 1.4 2010/06/04 15:32:47 arfrever Exp $
+# $Header: /var/cvsroot/gentoo-x86/sci-mathematics/fann/fann-2.1.0_beta.ebuild,v 1.5 2010/12/23 08:26:55 jlec Exp $
 
 EAPI=2
+
+PYTHON_DEPEND="python? 2"
+SUPPORT_PYTHON_ABIS="1"
+RESTRICT_PYTHON_ABIS="3.*"
+
 inherit eutils python autotools
 
 MY_P=${P/_/}
+
 DESCRIPTION="Fast Artificial Neural Network Library"
 HOMEPAGE="http://leenissen.dk/fann/"
 SRC_URI="mirror://sourceforge/${PN}/${MY_P}.zip"
@@ -15,27 +21,30 @@ SLOT="0"
 KEYWORDS="~amd64 ~ppc ~x86"
 IUSE="doc python"
 
-RDEPEND="python? ( virtual/python )"
-DEPEND="${RDEPEND}
+RDEPEND=""
+DEPEND="
+	${RDEPEND}
 	python? ( dev-lang/swig )
 	app-arch/unzip"
 
 S="${WORKDIR}/${P/_beta/}"
 
 src_prepare() {
-	epatch "${FILESDIR}"/${P}-python.patch
-	epatch "${FILESDIR}"/${P}-benchmark.patch
-	epatch "${FILESDIR}"/${P}-examples.patch
-	epatch "${FILESDIR}"/${P}-asneeded.patch
+	epatch \
+		"${FILESDIR}"/${P}-python.patch \
+		"${FILESDIR}"/${P}-benchmark.patch \
+		"${FILESDIR}"/${P}-examples.patch \
+		"${FILESDIR}"/${P}-asneeded.patch
 	eautoreconf
+	use python && python_copy_sources python
 }
 
 src_compile() {
 	emake || die "emake failed"
-	if use python; then
-		cd "${S}"/python
+	compilation() {
 		emake PYTHON_VERSION="$(python_get_version)" || die "emake python failed"
-	fi
+	}
+	use python && python_execute_function -s --source-dir python compilation
 }
 
 src_test() {
@@ -44,15 +53,15 @@ src_test() {
 		|| die "emake examples failed"
 	LD_LIBRARY_PATH="../src/.libs" emake runtest || die "tests failed"
 	emake clean
-	if use python; then
-		cd "${S}"/python
+	testing() {
 		emake test || die "failed tests for python wrappers"
-	fi
+	}
+	 use python && python_execute_function -s --source-dir python testing
 }
 
 src_install() {
 	emake install DESTDIR="${D}" || die "emake install failed"
-	dodoc AUTHORS ChangeLog NEWS README TODO
+	dodoc AUTHORS ChangeLog NEWS README TODO || die
 
 	if use doc; then
 		dodoc doc/*.txt
@@ -62,12 +71,20 @@ src_install() {
 		doins -r benchmarks || die "failed to install benchmarks"
 	fi
 
-	if use python; then
-		cd "${S}"/python
+	installation() {
 		emake install ROOT="${D}" || die "failed to install python wrappers"
 		if use doc; then
 			insinto /usr/share/doc/${PF}/examples/python
 			doins -r examples || die "failed to install python examples"
 		fi
-	fi
+	}
+	use python && python_execute_function -s --source-dir python installation
+}
+
+pkg_postinst() {
+	python_mod_optimize py${PN}
+}
+
+pkg_postrm() {
+	python_mod_cleanup py${PN}
 }
diff --git a/sci-mathematics/fann/files/fann-1.2.0-r1.patch b/sci-mathematics/fann/files/fann-1.2.0-r1.patch
deleted file mode 100644
index 12aae86dad7e..000000000000
--- a/sci-mathematics/fann/files/fann-1.2.0-r1.patch
+++ /dev/null
@@ -1,417 +0,0 @@
-diff -N -u -r fann-1.2.0.orig/python/examples/mushroom.py fann-1.2.0.my/python/examples/mushroom.py
---- fann-1.2.0.orig/python/examples/mushroom.py	2004-07-24 01:36:04.000000000 +0200
-+++ fann-1.2.0.my/python/examples/mushroom.py	2005-01-03 20:48:21.000000000 +0100
-@@ -20,9 +20,9 @@
- 
- # start training the network
- print "Training network"
--ann.set_activation_function_hidden(fann.FANN_SIGMOID_SYMMETRIC_STEPWISE)
--ann.set_activation_function_output(fann.FANN_SIGMOID_STEPWISE)
--ann.set_training_algorithm(fann.FANN_TRAIN_INCREMENTAL)
-+ann.set_activation_function_hidden(fann.SIGMOID_SYMMETRIC_STEPWISE)
-+ann.set_activation_function_output(fann.SIGMOID_STEPWISE)
-+ann.set_training_algorithm(fann.TRAIN_INCREMENTAL)
- 	
- ann.train_on_data(train_data, max_iterations, iterations_between_reports, desired_error)
- 	
-@@ -40,9 +40,3 @@
- print "Saving network"
- ann.save("mushroom_float.net")
- 
--# blow it all up
--print "Cleaning up."
--ann.destroy()
--test_data.destroy()
--train_data.destroy()
--
-diff -N -u -r fann-1.2.0.orig/python/examples/simple_train.py fann-1.2.0.my/python/examples/simple_train.py
---- fann-1.2.0.orig/python/examples/simple_train.py	2004-07-24 01:35:58.000000000 +0200
-+++ fann-1.2.0.my/python/examples/simple_train.py	2005-01-03 20:48:01.000000000 +0100
-@@ -12,9 +12,9 @@
- iterations_between_reports = 1000
- 
- ann = fann.create(connection_rate, learning_rate, (num_input, num_neurons_hidden, num_output))
-+ann.set_activation_function_output(fann.SIGMOID_SYMMETRIC_STEPWISE)
- 
- ann.train_on_file("datasets/xor.data", max_iterations, iterations_between_reports, desired_error)
- 
- ann.save("xor_float.net")
- 
--ann.destroy()
-diff -N -u -r fann-1.2.0.orig/python/fann_helper.c fann-1.2.0.my/python/fann_helper.c
---- fann-1.2.0.orig/python/fann_helper.c	2004-07-26 09:52:30.000000000 +0200
-+++ fann-1.2.0.my/python/fann_helper.c	2005-01-03 22:13:09.000000000 +0100
-@@ -68,3 +68,8 @@
- 	return get_row_from_double_array(t->output, row, t->num_output);

- }

- 

-+

-+int fann_is_NULL(struct fann *ann)

-+{

-+	return ann == NULL ? 1 : 0;

-+}

-diff -N -u -r fann-1.2.0.orig/python/fann.py fann-1.2.0.my/python/fann.py
---- fann-1.2.0.orig/python/fann.py	2004-07-26 09:46:04.000000000 +0200
-+++ fann-1.2.0.my/python/fann.py	2005-01-03 22:32:49.000000000 +0100
-@@ -21,30 +21,23 @@
- 
- import libfann
- 
--# Activation function
--FANN_LINEAR = 0
--FANN_THRESHOLD = 1
--FANN_THRESHOLD_SYMMETRIC = 2
--FANN_SIGMOID = 3
--FANN_SIGMOID_STEPWISE = 4                # default
--FANN_SIGMOID_SYMMETRIC = 5
--FANN_SIGMOID_SYMMETRIC_STEPWISE = 6
--FANN_GAUSSIAN = 7
--FANN_GAUSSIAN_STEPWISE = 8
--FANN_ELLIOT = 9                          # not implemented yet
--FANN_ELLIOT_SYMMETRIC = 10               # not implemented yet
--
--# Training algorithm
--FANN_TRAIN_INCREMENTAL = 0
--FANN_TRAIN_BATCH = 1
--FANN_TRAIN_RPROP = 2
--FANN_TRAIN_QUICKPROP = 3
-+# import all FANN_ constants without FANN_ prefix
-+for name, value in libfann.__dict__.iteritems():
-+    if name.startswith('FANN_') and not name.endswith('_NAMES'):
-+        globals()[name[5:]] = value
-+del name, value
- 
- class fann_class:
- 
-     def __init__(self, ann):
-+        """
-+        Never call this directly.
-+        """
-         self.__ann = ann
--    
-+
-+    def __del__(self):
-+        libfann.fann_destroy(self.__ann)
-+
-     def get_native_object(self):
-         return self.__train_data
- 
-@@ -54,13 +47,6 @@
-         """
-         return libfann.fann_run(self.__ann, input)
- 
--    def destroy(self):
--        """ 
--        Destructs the entire network.
--        Be sure to call this function after finished using the network.
--        """
--        libfann.fann_destroy(self.__ann)
--
-     def randomize_weights(self, min_weight, max_weight):
-         """
-         Randomize weights (from the beginning the weights are random between -0.1 and 0.1)
-@@ -198,31 +184,31 @@
-         """
-         libfann.fann_set_activation_function_output(self.__ann, activation_function)
- 
--    def get_activation_hidden_steepness(self):
-+    def get_activation_steepness_hidden(self):
-         """
-         Get the steepness parameter for the sigmoid function used in the hidden layers.
-         """
--        return libfann.get_activation_hidden_steepness(self.__ann)
-+        return libfann.get_activation_steepness_hidden(self.__ann)
- 
--    def set_activation_hidden_steepness(self, steepness):
-+    def set_activation_steepness_hidden(self, steepness):
-         """
-         Set the steepness of the sigmoid function used in the hidden layers.
-         Only usefull if sigmoid function is used in the hidden layers (default 0.5).
-         """
--        libfann.fann_set_activation_hidden_steepness(self.__ann, steepness)
-+        libfann.fann_set_activation_steepness_hidden(self.__ann, steepness)
- 
--    def get_activation_output_steepness(self):
-+    def get_activation_steepness_output(self):
-         """
-         Get the steepness parameter for the sigmoid function used in the output layer.
-         """
--        return libfann.fann_get_activation_output_steepness(self.__ann)
-+        return libfann.fann_get_activation_steepness_output(self.__ann)
- 
--    def set_activation_output_steepness(self, steepness):
-+    def set_activation_steepness_output(self, steepness):
-         """
-         Set the steepness of the sigmoid function used in the output layer.
-         Only usefull if sigmoid function is used in the output layer (default 0.5).
-         """
--        libfann.fann_set_activation_output_steepness(self.__ann, steepness)
-+        libfann.fann_set_activation_steepness_output(self.__ann, steepness)
- 
-     def train_on_data(self, data, max_epochs, epochs_between_reports, desired_error):
-         """
-@@ -269,7 +255,12 @@
- class train_class:
- 
-     def __init__(self, train_data):
-+        """
-+        Never call this directly.
-+        """
-         self.__train_data = train_data
-+    def __del__(self):
-+        libfann.fann_destroy_train(self.__train_data)
- 
-     def get_native_object(self):
-         return self.__train_data
-@@ -289,13 +280,6 @@
-     def get_output(self, index):
- 	return libfann.get_train_data_output(self.__train_data, index);
- 
--    def destroy(self):
--        """
--        Destructs the training data
--        Be sure to call this function after finished using the training data.
--        """
--        libfann.fann_destroy_train(self.__train_data)
--
-     def shuffle(self):
-         """
-         Shuffles training data, randomizing the order
-@@ -317,12 +301,10 @@
- 
-     def merge(self, other):
-         """
--        Merges training data into a single struct
-+        Merges training data into a new struct
-         """
-         outcome = libfann.fann_merge_train_data(self.__train_data, other.get_native_object())
--        self.destroy()
--        self.__train_data = outcome
--        return self
-+        return train_class(outcome)
- 
-     def duplicate(self):
-         """
-@@ -345,6 +327,8 @@
-     When running the network, the bias nodes always emits 1
-     """
-     ann = libfann.fann_create_array(connection_rate, learning_rate, len(layers), layers)
-+    if libfann.fann_is_NULL(ann):
-+        return None # probably won't happen
-     return fann_class(ann)
- 
- def create_from_file(filename):
-@@ -352,6 +336,8 @@
-     Constructs a backpropagation neural network from a configuration file.
-     """
-     ann = libfann.fann_create_from_file(filename)
-+    if libfann.fann_is_NULL(ann):
-+        raise IOError, "Could not load ann from file '%s'" + filename
-     return fann_class(ann)
- 
- def read_train_from_file(filename):
-diff -N -u -r fann-1.2.0.orig/python/libfann.i fann-1.2.0.my/python/libfann.i
---- fann-1.2.0.orig/python/libfann.i	2004-07-20 00:21:20.000000000 +0200
-+++ fann-1.2.0.my/python/libfann.i	2005-01-03 22:58:56.000000000 +0100
-@@ -7,15 +7,16 @@
- #include "../src/include/fann.h"

- %}

- 

--%typemap(in) fann_type[ANY] {

-+%define CHECKED_FLOAT_ARRAY(typemap_name, expected_length)

-+%typemap(in) typemap_name {

-   int i;

-   if (!PySequence_Check($input)) {

-     PyErr_SetString(PyExc_ValueError,"Expected a sequence");

--    return NULL;

-+    SWIG_fail;

-   }

--  if (PySequence_Length($input) == 0) {

--    PyErr_SetString(PyExc_ValueError,"Size mismatch. Expected some elements");

--    return NULL;

-+  if (PySequence_Length($input) != expected_length) {

-+    PyErr_SetString(PyExc_ValueError,"Sequence has wrong length");

-+    SWIG_fail;

-   }

-   $1 = (float *) malloc(PySequence_Length($input)*sizeof(float));

-   for (i = 0; i < PySequence_Length($input); i++) {

-@@ -24,20 +25,29 @@
-       $1[i] = (float) PyFloat_AsDouble(o);

-     } else {

-       PyErr_SetString(PyExc_ValueError,"Sequence elements must be numbers");      

--      return NULL;

-+      Py_DECREF(o);

-+      SWIG_fail;

-     }

-+    Py_DECREF(o);

-   }

- }

-+%typemap(freearg) typemap_name {

-+   if ($1) free($1);

-+}

-+%enddef

-+

-+CHECKED_FLOAT_ARRAY(fann_type *input, arg1->num_input)

-+CHECKED_FLOAT_ARRAY(fann_type *desired_output, arg1->num_output)

- 

- %typemap(in) int[ANY] {

-   int i;

-   if (!PySequence_Check($input)) {

-     PyErr_SetString(PyExc_ValueError,"Expected a sequence");

--    return NULL;

-+    SWIG_fail;

-   }

-   if (PySequence_Length($input) == 0) {

-     PyErr_SetString(PyExc_ValueError,"Size mismatch. Expected some elements");

--    return NULL;

-+    SWIG_fail;

-   }

-   $1 = (unsigned int *) malloc(PySequence_Length($input)*sizeof(unsigned int));

-   for (i = 0; i < PySequence_Length($input); i++) {

-@@ -46,37 +56,41 @@
-       $1[i] = (int) PyInt_AsLong(o);

-     } else {

-       PyErr_SetString(PyExc_ValueError,"Sequence elements must be numbers");      

--      return NULL;

-+      Py_DECREF(o);

-+      SWIG_fail;

-     }

-+    Py_DECREF(o);

-   }

- }

--

--%typemap(freearg) fann_type* {

-+%typemap(freearg) int[ANY] {

-    if ($1) free($1);

- }

-+%apply int[ANY] {int *, unsigned int*};

-+

-+typedef double fann_type; 

- 

- %typemap(out) PyObject* {

-   $result = $1;

- }

- 

--%apply fann_type[ANY] {fann_type *};

--%apply int[ANY] {int *, unsigned int*};

-+// create_array is used instead

-+%ignore fann_create;

-+%ignore fann_create_shortcut;

- 

--#define FANN_INCLUDE

--%varargs(10,int n = 0) fann_create;

- %rename(fann_run_old) fann_run;

- %rename(fann_run) fann_run2;

- 

- %rename(fann_test_old) fann_test;

- %rename(fann_test) fann_test2;

- 

-+#define FANN_INCLUDE

- %include "../src/include/fann.h"

- %include "../src/include/fann_data.h"

-+%include "../src/include/fann_activation.h"

- 

- // Helper functions

- PyObject* fann_run2(struct fann *ann, fann_type *input);

- PyObject* fann_test2(struct fann *ann, fann_type *input, fann_type *desired_output);

- PyObject* get_train_data_input(struct fann_train_data *ann, int row);

- PyObject* get_train_data_output(struct fann_train_data *ann, int row);

--

--

-+int fann_is_NULL(struct fann *ann);

-diff -N -u -r fann-1.2.0.orig/python/makefile.gnu fann-1.2.0.my/python/makefile.gnu
---- fann-1.2.0.orig/python/makefile.gnu	2004-10-09 13:56:57.000000000 +0200
-+++ fann-1.2.0.my/python/makefile.gnu	2005-01-02 16:52:23.000000000 +0100
-@@ -1,5 +1,7 @@
- # This makefile was written to compile a distribution of pyfann for
- # GNU platforms (cygwin included.)
-+#
-+# This is NOT needed for Linux/Unix, use setup_unix.py instead.
- 
- TARGETS = _libfann.dll
- 
-diff -N -u -r fann-1.2.0.orig/python/README fann-1.2.0.my/python/README
---- fann-1.2.0.orig/python/README	2004-08-06 10:54:13.000000000 +0200
-+++ fann-1.2.0.my/python/README	2005-01-02 17:00:28.000000000 +0100
-@@ -1,6 +1,9 @@
- This python binding is provided by Vincenzo Di Massa <hawk.it@tiscalinet.it>
- and Gil Megidish <gil@megidish.net>
- 
-+Instructions for Windows:
-+^^^^^^^^^^^^^^^^^^^^^^^^^
-+
- MAKE
- Make sure to make the fann library first. You are required to have
- swig and python development files installed. After you compiled the
-@@ -24,3 +27,17 @@
- 
- USAGE
- Just import fann.
-+
-+Instructions for Unix/Linux:
-+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-+
-+First build and install the fann library. Then run:
-+
-+./setup_unix.py build
-+./setup_unix.py install
-+
-+Install alone will work too, if you run it twice (a small bug).
-+The examples/ (not installed) should work now after you copy the datasets:
-+
-+mkdir examples/datasets
-+cp ../examples/xor.data ../benchmarks/datasets/mushroom.* examples/datasets/
-diff -N -u -r fann-1.2.0.orig/python/setup.py fann-1.2.0.my/python/setup.py
---- fann-1.2.0.orig/python/setup.py	2004-07-26 09:56:59.000000000 +0200
-+++ fann-1.2.0.my/python/setup.py	2005-01-02 16:49:45.000000000 +0100
-@@ -22,7 +22,7 @@
-     """

-     override default distutils install_data, so we can copy

-     files directly, without splitting into modules, scripts,

--    packages, and extensions."

-+    packages, and extensions.

-     """

-     def run(self):

-         # need to change self.install_dir to the actual library dir

-diff -N -u -r fann-1.2.0.orig/python/setup_unix.py fann-1.2.0.my/python/setup_unix.py
---- fann-1.2.0.orig/python/setup_unix.py	1970-01-01 01:00:00.000000000 +0100
-+++ fann-1.2.0.my/python/setup_unix.py	2005-01-02 16:27:17.000000000 +0100
-@@ -0,0 +1,38 @@
-+#!/usr/bin/env python
-+from distutils.core import setup, Extension
-+#from glob import glob
-+
-+VERSION='1.2.0'
-+
-+LONG_DESCRIPTION="""\
-+Fast Artificial Neural Network Library implements multilayer
-+artificial neural networks with support for both fully connected
-+and sparsely connected networks. It includes a framework for easy 
-+handling of training data sets. It is easy to use, versatile, well 
-+documented, and fast. 
-+"""
-+
-+module1 = Extension(
-+    '_libfann', 
-+    sources = ['libfann.i', 'fann_helper.c'], 
-+    libraries = ['fann'],
-+    #extra_objects = glob('../src/fann*.o'),
-+    )
-+
-+setup(
-+    name='pyfann',
-+    version=VERSION,
-+    description='Fast Artificial Neural Network Library (fann)',
-+    long_description=LONG_DESCRIPTION,
-+    author='Steffen Nissen',
-+    author_email='lukesky@diku.dk',
-+    maintainer='Gil Megidish',
-+    maintainer_email='gil@megidish.net',
-+    url='http://sourceforge.net/projects/fann/',
-+    license='GNU LESSER GENERAL PUBLIC LICENSE (LGPL)',
-+    platforms='UNIX',
-+
-+    ext_modules = [module1],
-+    py_modules = ['libfann', 'fann']
-+    )
-+
diff --git a/sci-mathematics/fann/files/fann-1.2.0-setup.py b/sci-mathematics/fann/files/fann-1.2.0-setup.py
deleted file mode 100644
index 82e8e10f46ca..000000000000
--- a/sci-mathematics/fann/files/fann-1.2.0-setup.py
+++ /dev/null
@@ -1,46 +0,0 @@
-from distutils.core import setup, Extension

-from distutils.command.install_data import install_data

-from compiler.pycodegen import compileFile

-import glob

-import distutils

-import distutils.sysconfig

-import distutils.core

-import os

-

-DISTUTILS_DEBUG="True"

-

-VERSION='1.2.0'

-

-LONG_DESCRIPTION="""\

-Fast Artificial Neural Network Library implements multilayer

-artificial neural networks with support for both fully connected

-and sparsely connected networks. It includes a framework for easy 

-handling of training data sets. It is easy to use, versatile, well 

-documented, and fast. 

-"""

-

-setup(

-	name='pyfann',

-	description='Fast Artificial Neural Network Library (fann)',

-	long_description=LONG_DESCRIPTION,

-	version=VERSION,

-	author='Steffen Nissen',

-	author_email='lukesky@diku.dk',

-	maintainer='Gil Megidish',

-	maintainer_email='gil@megidish.net',

-	url='http://sourceforge.net/projects/fann/',

-	license='GNU LESSER GENERAL PUBLIC LICENSE (LGPL)',

-	# Description of the package in the distribution

-	packages=['fann'],

-	ext_package="fann",

-	ext_modules=[

-		Extension("_libfann", ["fann_helper.c","libfann.i"],

-			include_dirs=["../src/include"],

-			extra_link_args=['-L/usr/local/bin','-L/usr/bin','-L../src/include','-lpython2.3','-dll'],

-				extra_objects=['/var/tmp/portage/fann-1.2.0/work/fann-1.2.0/src/fann_error.o',

-					'../src/fann_io.o','../src/fann.o','../src/fann_options.o',

-					'../src/fann_train_data.o','../src/fann_train.o'],

-			 )

-		],

-	)

-