Cada equipo tiene su estilo único. Aquí te presentamos algunas estrategias clave que podrían definir los próximos partidos:
Estrategias Ofensivas
yuanliliang/Meituan<|file_sep|>/js/portal.js
$(function(){
//头部导航栏
$(".header .header-nav").hover(function(){
$(".header-nav-list").show();
},function(){
$(".header-nav-list").hide();
})
$(".header-nav-item").hover(function(){
$(this).find(".header-nav-list").show();
},function(){
$(this).find(".header-nav-list").hide();
})
})<|file_sep|># Meituan
美团网页制作
<|repo_name|>neurodata/guacamole<|file_sep|>/docs/source/guacamole.rst
guacamole package
==================
Submodules
----------
guacamole.analyze module
------------------------
.. automodule:: guacamole.analyze
:members:
:undoc-members:
:show-inheritance:
guacamole.cluster module
------------------------
.. automodule:: guacamole.cluster
:members:
:undoc-members:
:show-inheritance:
guacamole.compare module
------------------------
.. automodule:: guacamole.compare
:members:
:undoc-members:
:show-inheritance:
guacamole.data module
---------------------
.. automodule:: guacamole.data
:members:
:undoc-members:
:show-inheritance:
guacamole.plot module
---------------------
.. automodule:: guacamole.plot
:members:
:undoc-members:
:show-inheritance:
guacamole.utils module
----------------------
.. automodule:: guacamole.utils
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: guacamole
:members:
:undoc-members:
:show-inheritance:
<|file_sep|># -*- coding: utf-8 -*-
"""
Created on Mon Sep 14
@author: [email protected]
Description: This module contains functions for generating and manipulating
networks from the adjacency matrix of the network.
"""
import numpy as np
def degree(ADJ):
""" Returns the degree of each node in the network.
Parameters
----------
ADJ: ndarray (n,n)
Adjacency matrix of the network.
Returns
-------
deg: ndarray (n,)
Degree of each node in the network.
"""
deg = np.sum(ADJ,axis=0)
return deg
def avg_degree(ADJ):
deg = degree(ADJ)
avg_deg = np.mean(deg)
return avg_deg
def betweenness_centrality(ADJ):
#TODO
pass
def closeness_centrality(ADJ):
#TODO
pass
def eigenvector_centrality(ADJ):
#TODO
pass
def coreness(ADJ):
#TODO
pass
def clustering_coefficient(ADJ):
#TODO
pass
def diameter(ADJ):
#TODO
pass
def diameter_bin(ADJ):
#TODO
pass
def generate_random_graph(n,p):
G = np.random.rand(n,n)
G[G=p]=1
return G
def generate_scale_free_graph(n,mu):
G = np.zeros((n,n))
for i in range(n-1):
new_node = np.ones((1,n))
new_node[0,i+1:] =0
G = np.vstack((G,new_node))
row_sum = np.sum(G,axis=1)
probs = row_sum/np.sum(row_sum)
probs[probs==0] =np.finfo(float).eps
probs[-1]=0
new_conn = np.random.choice(range(i+1),mu,p=probs[:-1])
G[i+1,new_conn]=1
G[new_conn,i+1]=1
return G
def generate_regular_graph(n,k):
if k > n-1 or k%2 != n%2 :
raise ValueError("Graph not possible with these parameters.")
if n<=k/2 :
raise ValueError("Graph not possible with these parameters.")
if n==k:
return np.ones((n,n))-np.eye(n)
ADJ=np.zeros((n,n))
<|file_sep|># -*- coding: utf-8 -*-
"""
Created on Mon Sep 14
@author: [email protected]
Description: This module contains functions for generating and manipulating
networks from the adjacency matrix of the network.
"""
import numpy as np
from . import utils
from scipy.stats import entropy as KL_divergence
def mutual_information(gene_exp, ADJ):
"""Returns the mutual information for each pair of genes in gene_exp.
The genes are ordered by their indices in gene_exp.
Parameters
----------
gene_exp: ndarray (m,n)
Expression values for m genes over n samples.
ADJ: ndarray (m,m)
Adjacency matrix of the network.
Returns
-------
MI: ndarray (m,m)
Mutual information for each pair of genes in gene_exp.
"""
def joint_entropy(gene_exp):
"""Returns the joint entropy for each pair of genes in gene_exp.
The genes are ordered by their indices in gene_exp.
Parameters
----------
gene_exp: ndarray (m,n)
Expression values for m genes over n samples.
Returns
-------
JE: ndarray (m,m)
Joint entropy for each pair of genes in gene_exp.
"""
def KL_divergence(gene_exp):
def conditional_entropy(gene_exp, ADJ):
<|file_sep|># -*- coding: utf-8 -*-
"""
Created on Mon Sep 14
@author: [email protected]
Description: This module contains functions for analyzing networks.
"""
import numpy as np
from . import utils
def detect_communities(ADJ):
def shortest_path_length(ADJ):
def hop_plot(ADJ):
def random_walks(ADJ):
<|repo_name|>neurodata/guacamole<|file_sep|>/README.md
# Guacamole
Guacamole is an open source python package for analyzing biological networks and expression data.
## Installation
To install the latest release from PyPI:
pip install guacamole-network-analysis
To install the latest version from source:
git clone https://github.com/neurodata/guacamole.git && cd guacamole && python setup.py install
## Documentation
The documentation can be found at https://neurodata.github.io/guacamole/
<|repo_name|>neurodata/guacamole<|file_sep|>/docs/source/index.rst
Welcome to Guacamoel's documentation!
======================================
Contents:
.. toctree::
:maxdepth: 4
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
.. image:: https://github.com/neurodata/guacamole/workflows/Build/badge.svg?branch=master&event=push
.. image:: https://codecov.io/gh/neurodata/guacamole/branch/master/graph/badge.svg?token=8g32ULB9Zi
.. image:: https://img.shields.io/pypi/v/guacamole-network-analysis?color=brightgreen&label=PyPI%20version&logo=pypi&logoColor=brightgreen&style=for-the-badge
.. image:: https://img.shields.io/github/license/neurodata/guacamole?color=blue&label=License&logoColor=blue&style=for-the-badge
.. image:: https://img.shields.io/pypi/pyversions/guacamole-network-analysis?color=blueviolet&label=Supported%20Python%20Versions&logoColor=blueviolet&style=for-the-badge
Guacamoel is an open source python package for analyzing biological networks and expression data.
Installation
-------------
To install the latest release from PyPI:
::
pip install guacamole-network-analysis
To install the latest version from source:
::
git clone https://github.com/neurodata/guacamole.git && cd guacamole && python setup.py install
Documentation
-------------
The documentation can be found at https://neurodata.github.io/guacamole/
Indices and tables
------------------
* genindex
* modindex
* search
Guacamoel is an open source python package for analyzing biological networks and expression data.
Installation
-------------
To install the latest release from PyPI:
::
pip install guacamole-network-analysis
To install the latest version from source:
::
git clone https://github.com/neurodata/guacamole.git && cd guacamole && python setup.py install
Documentation
-------------
The documentation can be found at https://neurodata.github.io/guacamole/
Indices and tables
------------------
* genindex
* modindex
* search
<|repo_name|>wrmackey/ruby-metasploit-framework<|file_sep|>/lib/metasploit/framework/sessions/meterpreter/command_shell.rb
##
# $Id$
##
##
# Copyright (c) Metasploit Corporation. All rights reserved.
# See LICENSE.txt for complete licensing information.
##
require 'msf/core/sessions/command_shell'
module Metasploit3
###
#
# Meterpreter Command Shell Session Object - The Meterpreter Command Shell session object provides methods that allow you to interact with a Meterpreter session via command shell output.
#
###
class Sessions::MeterpreterCommandShellModule
include Msf::Sessions::CommandShellMixin
attr_reader :session_id
def initialize(client_connection)
super(client_connection)
session_id = client_connection.session_id
end
def post_inject_command(cmd, opts={})
opts[:session_id] ||= @session_id
post_module("core/inject/command_shell", opts.merge({:cmd => cmd}))
end
def post_process_inject_command(cmd, opts={})
opts[:session_id] ||= @session_id
post_module("core/inject/process_injector", opts.merge({:cmd => cmd}))
end
def get_file(filename, local_path=nil, opts={})
opts[:session_id] ||= @session_id
post_module("auxiliary/server/capture/capture_file", opts.merge({:filename => filename,
:local_path => local_path}))
end
def put_file(filename, local_path=nil, opts={})
opts[:session_id] ||= @session_id
post_module("auxiliary/server/capture/capture_file", opts.merge({:filename => filename,
:local_path => local_path}))
end
def shell_execute(cmd, args=nil, dir=nil, env={}, codepage=nil, show=true)
opts[:session_id] ||= @session_id
post_module("post