Package: python-kwant-doc Source: kwant Version: 1.3.3-1~bpo9+1 Architecture: all Maintainer: Christoph Groth Installed-Size: 6691 Depends: libjs-sphinxdoc (>= 1.0), libjs-mathjax Homepage: http://kwant-project.org/ Priority: optional Section: doc Filename: pool/main/k/kwant/python-kwant-doc_1.3.3-1~bpo9+1_all.deb Size: 4293366 SHA256: 1b5ca4c52a7a94d2c05b428dfcc8705b34163618ae30e0079342620ed5d29dfd SHA1: 095d2bd68ddcf9421a8c92cef33846d649c92f87 MD5sum: c48ac697f312c6842f89bd9774416068 Description: Kwant documentation Kwant is a Python package for numerical quantum transport calculations. It exposes the natural concepts of the theory of quantum transport (lattices, symmetries, electrodes, orbital/spin/electron-hole degrees of freedom) in a simple and transparent way. Kwant offers direct support for calculations of transport properties (conductance, noise, scattering matrix), dispersion relations, modes, wave functions, various Green’s functions, and out-of-equilibrium local quantities. Other computations involving tight-binding Hamiltonians can be implemented easily. . This package contains the documentation for Kwant in HTML format. Package: python-tinyarray Source: tinyarray Version: 1.2.1-1~bpo9+1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 145 Depends: python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7~), libc6 (>= 2.4), libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://kwant-project.org/tinyarray/ Priority: optional Section: python Filename: pool/main/t/tinyarray/python-tinyarray_1.2.1-1~bpo9+1_i386.deb Size: 44614 SHA256: ee1e4a31842a46d5bbcf9497e2865fc5d636c4cdf3947d428ec4c76bf514da47 SHA1: 2c7432497ef3344f38d014a7ff0a135ca0e11dd0 MD5sum: 0c2a7d6516dc339c2398ba3e2b27db54 Description: Arrays of numbers, optimized for small sizes (Python 2) Tinyarray is a numerical array module for Python. The multi-dimensional arrays it provides are best thought of as (possibly nested) tuples of numbers that, unlike Python's built-in tuples, support mathematical operations. Like tuples, tinyarrays are hashable and immutable and thus can be used as dictionary keys. The module's interface is a subset of that of NumPy and hence should be familiar to many Python programmers. Tinyarray has been heavily optimized for small arrays: For example, common operations on 1-d arrays of length 3 run 3-7 times faster than with NumPy. When storing many small arrays, memory consumption is reduced by a factor of 3. In summary, Tinyarray is a more efficient alternative to NumPy when many separate small numerical arrays are to be used. . This package installs the library for Python 2. Package: python-tinyarray-dbgsym Source: tinyarray Version: 1.2.1-1~bpo9+1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 196 Depends: python-tinyarray (= 1.2.1-1~bpo9+1) Homepage: http://kwant-project.org/tinyarray/ Priority: extra Section: debug Filename: pool/main/t/tinyarray/python-tinyarray-dbgsym_1.2.1-1~bpo9+1_i386.deb Size: 168888 SHA256: 70b6441d6e0c54d61468aae3348afa5e3a0940ec5ae77efcb6e66b0c9fa69c1a SHA1: abec2408e016440cb94504bd42a70ae0360d61bc MD5sum: 2929b4cd96c870f5d28b857ec1b4f323 Description: Debug symbols for python-tinyarray Build-Ids: ec4ea82383bc45ff2a338c76a116e9b66679ae73 Package: python3-kwant Source: kwant Version: 1.4.1-1~bpo9+1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 3676 Depends: python3 (<< 3.6), python3 (>= 3.5~), python3-numpy (>= 1.11), python3-scipy (>= 0.17), python3-tinyarray (>= 1.2), python3:any (>= 3.5~), libc6 (>= 2.4), libgfortran3 (>= 4.3), libmumps-4.10.0, libmumps-scotch-4.10.0 Recommends: python3-matplotlib (>= 1.5.1), python3-sympy (>= 0.7.6) Suggests: python-kwant-doc, python3-pytest (>= 2.8) Homepage: http://kwant-project.org/ Priority: optional Section: python Filename: pool/main/k/kwant/python3-kwant_1.4.1-1~bpo9+1_i386.deb Size: 713336 SHA256: e63904db5eec50e32c875a07d43a66f2cefe6961823093a7e2c8e08fc962e0cc SHA1: 460648c4b00c3ea5512796f6c170b8eeee2621c2 MD5sum: 21b7a8ca46c1bdf6a75dfbe00bf68278 Description: Python package for numerical quantum transport calculations Kwant is a Python package for numerical quantum transport calculations. It exposes the natural concepts of the theory of quantum transport (lattices, symmetries, electrodes, orbital/spin/electron-hole degrees of freedom) in a simple and transparent way. Kwant offers direct support for calculations of transport properties (conductance, noise, scattering matrix), dispersion relations, modes, wave functions, various Green’s functions, and out-of-equilibrium local quantities. Other computations involving tight-binding Hamiltonians can be implemented easily. . This package contains Kwant for Python 3. Package: python3-kwant-dbgsym Source: kwant Version: 1.4.1-1~bpo9+1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 2604 Depends: python3-kwant (= 1.4.1-1~bpo9+1) Homepage: http://kwant-project.org/ Priority: extra Section: debug Filename: pool/main/k/kwant/python3-kwant-dbgsym_1.4.1-1~bpo9+1_i386.deb Size: 2370286 SHA256: b6876731bf2f83e175805d5e958d1834e7a23c7bf2e89d90adc03d47b27bb75c SHA1: f3162fcb1a8a604bc93b5042fee60b0c877b671f MD5sum: f107661b8eee9713fe03b913956af4c8 Description: Debug symbols for python3-kwant Build-Ids: 095998d782675ac5a342ec3c36f21c6ae8279a61 52dd4978c015cae686233e157b97b9d21df6ac22 c46d85d55dd5f1685deb82484dc7697d0ebc0b5a d42c312f4e788ff5999afa5555651495afec4356 ecf522af42e2bc6671c8d37cdd278cb6e3519a83 ee718d702d0e448c0b1b99e21722d0da46f33c38 Package: python3-tinyarray Source: tinyarray Version: 1.2.1-1~bpo9+1 Architecture: i386 Maintainer: Christoph Groth Installed-Size: 141 Depends: python3 (<< 3.6), python3 (>= 3.5~), python3:any (>= 3.4~), libc6 (>= 2.4), libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://kwant-project.org/tinyarray/ Priority: optional Section: python Filename: pool/main/t/tinyarray/python3-tinyarray_1.2.1-1~bpo9+1_i386.deb Size: 41328 SHA256: be7c1b056d2cf6f866c99a13b8e27529c98faf0f572e8c1141e7bcad4a343c6d SHA1: 030ee0f0836f394086c74687e5b2b5b8ef201c10 MD5sum: c7461ba92b4ab54ae18656fe08bde608 Description: Arrays of numbers, optimized for small sizes (Python 3) Tinyarray is a numerical array module for Python. The multi-dimensional arrays it provides are best thought of as (possibly nested) tuples of numbers that, unlike Python's built-in tuples, support mathematical operations. Like tuples, tinyarrays are hashable and immutable and thus can be used as dictionary keys. The module's interface is a subset of that of NumPy and hence should be familiar to many Python programmers. Tinyarray has been heavily optimized for small arrays: For example, common operations on 1-d arrays of length 3 run 3-7 times faster than with NumPy. When storing many small arrays, memory consumption is reduced by a factor of 3. In summary, Tinyarray is a more efficient alternative to NumPy when many separate small numerical arrays are to be used. . This package installs the library for Python 3. Package: python3-tinyarray-dbgsym Source: tinyarray Version: 1.2.1-1~bpo9+1 Auto-Built-Package: debug-symbols Architecture: i386 Maintainer: Christoph Groth Installed-Size: 197 Depends: python3-tinyarray (= 1.2.1-1~bpo9+1) Homepage: http://kwant-project.org/tinyarray/ Priority: extra Section: debug Filename: pool/main/t/tinyarray/python3-tinyarray-dbgsym_1.2.1-1~bpo9+1_i386.deb Size: 170702 SHA256: 914bdd31d2631eca5ceb469f679deac49867b6716c7db07ddaa2716d7fb58a4f SHA1: 8f83001c5ed6bfac76031e598d817b96eb5d7fb7 MD5sum: 70310c47496397cdbc28fbf00d5b226c Description: Debug symbols for python3-tinyarray Build-Ids: df2cb8efc5bacc6f7dcd0d692eb548e14525dc2a