Showing 6 open source projects for "xlrd module python"

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    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization

    Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms.
    Downloads: 0 This Week
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  • 2
    CAMPARI

    CAMPARI

    Software for molecular simulations and trajectory analysis

    We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model.
    Downloads: 3 This Week
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  • 3

    wmtsa-python

    Discrete wavelet methods for time series analysis using python

    Several python libraries implement discrete wavelet transforms. However, none of them, or at least none that I know, is aimed at scientific use. This library aims at filling this gap, in particular considering discrete wavelet transform as described by Percival and Walden. This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices.
    Downloads: 0 This Week
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  • 4

    XNDiff

    X-ray and Neutron powder pattern simulation analysis

    Keywords (XNDiff): -SAXS -SANS -absolute units -core (double)shell crystalline nanoparticles -with a parallelepidal shape -particle assemblies -powder and ensemble average -C/C++ -Unix -OpenMP -HPC Cluster Keywords (BatchMultiFit): -simultaneous fits for several SAXS and SANS curves with simulation data from XNDiff -SANS data can be smeared with dq values from experimental data sets or analytical functions -Mathematica console -local and global optimizers (simulated annealing, differential evolution, Nelder-Mead, ...) can be used -range for fit parameters and further constraints between fit parameters -parallelized (typ. 4-8 threads) TODO (BatchMultiFit): -read and use errorbars from experimental data sets -allow different q-ranges for different data sets in the fits -rewrite and test in Python using e.g. the lmfit module: https://pypi.python.org/pypi/lmfit/ to get rid of Mathematica and to run it on HPC clusters
    Downloads: 0 This Week
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  • 5
    NTuple is a Python module used by high-energy physicists and astrophysicists to easily and efficiently access ntuple data stored in large ROOT data stores. Specifically, NTuple provides a friendly Pythonic interface to TNtuples and TTrees stored in TFiles
    Downloads: 0 This Week
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  • 6
    We are trying to create a very complete physics teaching program. So, we would be pleased if you could suggest any improvement or create any module for us. To use any of these sources you need python 2.2, pygame and scipy.
    Downloads: 0 This Week
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