Package: fail2ban Version: 0.8.6-3~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 612 Depends: neurodebian-popularity-contest, python (>= 2.4), python-central (>= 0.6.11), lsb-base (>= 2.0-7) Recommends: iptables, whois, python-gamin Suggests: mailx Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.8.6-3~nd11.04+1_all.deb Size: 103468 SHA256: d3327c84e7ab3f07be88f6a4e6942b129518be2cb722866360b24df0e4d01ba3 SHA1: 5050c018f615ff82fbda3d048fffbfd56cd1dd33 MD5sum: 771a9dcf792f6851068d12e917cf49e8 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Python-Version: current, >= 2.4 Package: python-pandas Source: pandas Version: 0.7.1+git1-ga2e86c2-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2080 Depends: neurodebian-popularity-contest, python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-dateutil, python-pandas-lib (>= 0.7.1+git1-ga2e86c2-1~nd11.04+1) Recommends: python-scipy, python-matplotlib, python-tables, python-tz, python-xlrd, python-scikits.statsmodels Suggests: python-pandas-doc Provides: python2.6-pandas, python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.7.1+git1-ga2e86c2-1~nd11.04+1_all.deb Size: 399444 SHA256: 5934c2f30b23e8a2406a359d6aa60b2880ef8d99d58ba0cff85191454b72e819 SHA1: ef8f2a2f67641871fa25514eed3e79cf6298876c MD5sum: 39a635aea1973dca858d21bfa1d85120 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure Package: spm8-common Source: spm8 Version: 8.4667~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 22352 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4667~dfsg.1-1~nd11.04+1_all.deb Size: 10573730 SHA256: 1ed89a6bdc612f421a81d873339a371d525db78787353ef924ff9c84959ba3c0 SHA1: 3f9ca30b40af16c9789bce60d5f248a7b3dfe446 MD5sum: d640a888ad262e3cdf83dcf52c835f16 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4667~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 73084 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4667~dfsg.1-1~nd11.04+1_all.deb Size: 52167688 SHA256: ce55009bec2f76b96ce90263f625630697db37418b8a3252f4c26ad1dbccca70 SHA1: 483782bd568d9f95d9062bf168dcfb1a766742f2 MD5sum: 99c20008937ad48f7e8163d887be2af4 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4667~dfsg.1-1~nd11.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9380 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4667~dfsg.1-1~nd11.04+1_all.deb Size: 8648920 SHA256: 735926447772fa98fadc948f4b83de1a4be1cb628df1d508c178185e575bc57f SHA1: 8b47dfda11247dc24e77c835e83129ccf8c379f5 MD5sum: baba74d55f63322228a92cd8ecb4901d Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format.