<thead id="xthz1"></thead>
            <form id="xthz1"></form>

                <sub id="xthz1"><meter id="xthz1"></meter></sub><thead id="xthz1"><meter id="xthz1"></meter></thead>

                <thead id="xthz1"><meter id="xthz1"></meter></thead>

                <th id="xthz1"></th>

                  <font id="xthz1"><meter id="xthz1"><i id="xthz1"></i></meter></font>

                          <nobr id="xthz1"><meter id="xthz1"></meter></nobr>

                          <th id="xthz1"><meter id="xthz1"></meter></th>

                          <nobr id="xthz1"></nobr>

                                  <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                  <th id="xthz1"></th>
                                  <thead id="xthz1"><meter id="xthz1"><b id="xthz1"></b></meter></thead>
                                  
                                  

                                      <pre id="xthz1"><noframes id="xthz1"><track id="xthz1"></track>

                                          <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                          <th id="xthz1"></th>

                                            <address id="xthz1"></address>

                                            <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                <video id="xthz1"><span id="xthz1"><nobr id="xthz1"></nobr></span></video>

                                                  <th id="xthz1"><meter id="xthz1"></meter></th>

                                                  <th id="xthz1"></th>

                                                    <th id="xthz1"></th><track id="xthz1"><meter id="xthz1"></meter></track>

                                                      <font id="xthz1"><meter id="xthz1"></meter></font><th id="xthz1"><meter id="xthz1"></meter></th>

                                                          <sub id="xthz1"><progress id="xthz1"></progress></sub>

                                                              <sub id="xthz1"></sub>

                                                                          <track id="xthz1"><meter id="xthz1"></meter></track>
                                                                              當前位置 > 首頁 > 技術文檔 > Numpy學習(2)

                                                                              Numpy學習(2)

                                                                              來源:CPDA數據分析師學習網 | 時間:2018-02-09 | 作者:數據分析學習網

                                                                              我們接著《Python數據分析之numpy學習(一)》繼續講解有關numpy方面的知識!

                                                                              統計函數與線性代數運算

                                                                              統計運算中常見的聚合函數有:最小值、最大值、中位數、均值、方差、標準差等。首先來看看數組元素級別的計算

                                                                              In [94]: arr11 = 5-np.arange(1,13).reshape(4,3)

                                                                              In [95]: arr12 = np.random.randint(1,10,size = 12).reshape(4,3)

                                                                              In [96]: arr11

                                                                              Out[96]:

                                                                              array([[ 4, ?3, ?2],

                                                                              [ 1, ?0, -1],

                                                                              [-2, -3, -4],

                                                                              [-5, -6, -7]])

                                                                              In [97]: arr12

                                                                              Out[97]:

                                                                              array([[1, 3, 7],

                                                                              [7, 3, 7],

                                                                              [3, 7, 4],

                                                                              [6, 1, 2]])

                                                                              In [98]: arr11 ** 2 ? ?#計算每個元素的平方

                                                                              Out[98]:

                                                                              array([[16, ?9, ?4],

                                                                              [ 1, ?0, ?1],

                                                                              [ 4, ?9, 16],

                                                                              [25, 36, 49]])

                                                                              In [99]: np.sqrt(arr11) ?#計算每個元素的平方根

                                                                              Out[99]:

                                                                              array([[ 2. ? ? ? ?, ?1.73205081, ?1.41421356],

                                                                              [ 1. ? ? ? ?, ?0. ? ? ? ?, ? ? ? ? nan],

                                                                              [ ? ? ? ?nan, ? ? ? ? nan, ? ? ? ? nan],

                                                                              [ ? ? ? ?nan, ? ? ? ? nan, ? ? ? ? nan]])

                                                                              由于負值的平方根沒有意義,故返回nan

                                                                              In [100]: np.exp(arr11) ? #計算每個元素的指數值

                                                                              Out[100]:

                                                                              array([[ ?5.45981500e+01, ? 2.00855369e+01, ? 7.38905610e+00],

                                                                              [ ?2.71828183e+00, ? 1.00000000e+00, ? 3.67879441e-01],

                                                                              [ ?1.35335283e-01, ? 4.97870684e-02, ? 1.83156389e-02],

                                                                              [ ?6.73794700e-03, ? 2.47875218e-03, ? 9.11881966e-04]])

                                                                              In [101]: np.log(arr12) ? #計算每個元素的自然對數值

                                                                              Out[101]:

                                                                              array([[ 0. ? ? ? ?, ?1.09861229, ?1.94591015],

                                                                              [ 1.94591015, ?1.09861229, ?1.94591015],

                                                                              [ 1.09861229, ?1.94591015, ?1.38629436],

                                                                              [ 1.79175947, ?0. ? ? ? ?, ?0.69314718]])

                                                                              In [102]: np.abs(arr11) ? #計算每個元素的絕對值

                                                                              Out[102]:

                                                                              array([[4, 3, 2],

                                                                              [1, 0, 1],

                                                                              [2, 3, 4],

                                                                              [5, 6, 7]])

                                                                              相同形狀數組間元素的操作:

                                                                              In [103]: arr11 + arr12 ? #加

                                                                              Out[103]:

                                                                              array([[ 5, ?6, ?9],

                                                                              [ 8, ?3, ?6],

                                                                              [ 1, ?4, ?0],

                                                                              [ 1, -5, -5]])

                                                                              In [104]: arr11 - arr12 ? #減

                                                                              Out[104]:

                                                                              array([[ ?3, ? 0, ?-5],

                                                                              [ -6, ?-3, ?-8],

                                                                              [ -5, -10, ?-8],

                                                                              [-11, ?-7, ?-9]])

                                                                              In [105]: arr11 * arr12 ? #乘

                                                                              Out[105]:

                                                                              array([[ ?4, ? 9, ?14],

                                                                              [ ?7, ? 0, ?-7],

                                                                              [ -6, -21, -16],

                                                                              [-30, ?-6, -14]])

                                                                              In [106]: arr11 / arr12 ? #除

                                                                              Out[106]:

                                                                              array([[ 4. ? ? ? ?, ?1. ? ? ? ?, ?0.28571429],

                                                                              [ 0.14285714, ?0. ? ? ? ?, -0.14285714],

                                                                              [-0.66666667, -0.42857143, -1. ? ? ? ?],

                                                                              [-0.83333333, -6. ? ? ? ?, -3.5 ? ? ? ]])

                                                                              In [107]: arr11 // arr12 ?#整除

                                                                              Out[107]:

                                                                              array([[ 4, ?1, ?0],

                                                                              [ 0, ?0, -1],

                                                                              [-1, -1, -1],

                                                                              [-1, -6, -4]], dtype=int32)

                                                                              In [108]: arr11 % arr12 ? #取余

                                                                              Out[108]:

                                                                              array([[0, 0, 2],

                                                                              [1, 0, 6],

                                                                              [1, 4, 0],

                                                                              [1, 0, 1]], dtype=int32)

                                                                              接下來我們看看統計運算函數:

                                                                              In [109]: np.sum(arr11) ? #計算所有元素的和

                                                                              Out[109]: -18

                                                                              In [110]: np.sum(arr11,axis = 0) ? ?#對每一列求和

                                                                              Out[110]: array([ -2, ?-6, -10])

                                                                              In [111]: np.sum(arr11, axis = 1) #對每一行求和

                                                                              Out[111]: array([ ?9, ? 0, ?-9, -18])

                                                                              In [112]: np.cumsum(arr11) #對每一個元素求累積和(從上到下,從左到右的元素順序)

                                                                              Out[112]: array([ ?4, ? 7, ? 9, ?10, ?10, ? 9, ? 7, ? 4, ? 0, ?-5, -11, -18], dtype=int32)

                                                                              In [113]: np.cumsum(arr11, axis = 0) #計算每一列的累積和,并返回二維數組

                                                                              Out[113]:

                                                                              array([[ ?4, ? 3, ? 2],

                                                                              [ ?5, ? 3, ? 1],

                                                                              [ ?3, ? 0, ?-3],

                                                                              [ -2, ?-6, -10]], dtype=int32)

                                                                              In [114]: np.cumprod(arr11, axis = 1) #計算每一行的累計積,并返回二維數組

                                                                              Out[114]:

                                                                              array([[ ? 4, ? 12, ? 24],

                                                                              [ ? 1, ? ?0, ? ?0],

                                                                              [ ?-2, ? ?6, ?-24],

                                                                              [ ?-5, ? 30, -210]], dtype=int32)

                                                                              In [115]: np.min(arr11) ? #計算所有元素的最小值

                                                                              Out[115]: -7

                                                                              In [116]: np.max(arr11, axis = 0) #計算每一列的最大值

                                                                              Out[116]: array([4, 3, 2])

                                                                              In [117]: np.mean(arr11) ?#計算所有元素的均值

                                                                              Out[117]: -1.5

                                                                              In [118]: np.mean(arr11, axis = 1) #計算每一行的均值

                                                                              Out[118]: array([ 3., ?0., -3., -6.])

                                                                              In [119]: np.median(arr11) ? #計算所有元素的中位數

                                                                              Out[119]: -1.5

                                                                              In [120]: np.median(arr11, axis = 0) ? #計算每一列的中位數

                                                                              Out[120]: array([-0.5, -1.5, -2.5])

                                                                              In [121]: np.var(arr12) ? #計算所有元素的方差

                                                                              Out[121]: 5.354166666666667

                                                                              In [122]: np.std(arr12, axis = 1) ? #計算每一行的標準差

                                                                              Out[122]: array([ 2.49443826, ?1.88561808, ?1.69967317, ?2.1602469 ])

                                                                              numpy中的統計函數運算是非常靈活的,既可以計算所有元素的統計值,也可以計算指定行或列的統計指標。還有其他常用的函數,如符號函數sign,ceil(>=x的最小整數),floor(<=x的最大整數),modf(將浮點數的整數部分與小數部分分別存入兩個獨立的數組),cos,arccos,sin,arcsin,tan,arctan等。

                                                                              讓我很興奮的一個函數是where(),它類似于Excel中的if函數,可以進行靈活的變換:

                                                                              In [123]: arr11

                                                                              Out[123]:

                                                                              array([[ 4, ?3, ?2],

                                                                              [ 1, ?0, -1],

                                                                              [-2, -3, -4],

                                                                              [-5, -6, -7]])

                                                                              In [124]: np.where(arr11 < 0, 'negtive','positive')

                                                                              Out[124]:

                                                                              array([['positive', 'positive', 'positive'],

                                                                              ['positive', 'positive', 'negtive'],

                                                                              ['negtive', 'negtive', 'negtive'],

                                                                              ['negtive', 'negtive', 'negtive']],

                                                                              dtype='<U8')

                                                                              當然,np.where還可以嵌套使用,完成復雜的運算。

                                                                              其它函數

                                                                              unique(x):計算x的唯一元素,并返回有序結果

                                                                              intersect(x,y):計算x和y的公共元素,即交集

                                                                              union1d(x,y):計算x和y的并集

                                                                              setdiff1d(x,y):計算x和y的差集,即元素在x中,不在y中

                                                                              setxor1d(x,y):計算集合的對稱差,即存在于一個數組中,但不同時存在于兩個數組中

                                                                              in1d(x,y):判斷x的元素是否包含于y中

                                                                              線性代數運算

                                                                              同樣numpu也跟R語言一樣,可以非常方便的進行線性代數方面的計算,如行列式、逆、跡、特征根、特征向量等。但需要注意的是,有關線性代數的函數并不在numpy中,而是numpy的子例linalg中。

                                                                              In [125]: arr13 = np.array([[1,2,3,5],[2,4,1,6],[1,1,4,3],[2,5,4,1]])

                                                                              In [126]: arr13

                                                                              Out[126]:

                                                                              array([[1, 2, 3, 5],

                                                                              [2, 4, 1, 6],

                                                                              [1, 1, 4, 3],

                                                                              [2, 5, 4, 1]])

                                                                              In [127]: np.linalg.det(arr13) ? ?#返回方陣的行列式

                                                                              Out[127]: 51.000000000000021

                                                                              In [128]: np.linalg.inv(arr13) ? ?#返回方陣的逆

                                                                              Out[128]:

                                                                              array([[-2.23529412, ?1.05882353, ?1.70588235, -0.29411765],

                                                                              [ 0.68627451, -0.25490196, -0.7254902 , ?0.2745098 ],

                                                                              [ 0.19607843, -0.21568627, ?0.07843137, ?0.07843137],

                                                                              [ 0.25490196, ?0.01960784, -0.09803922, -0.09803922]])

                                                                              In [129]: np.trace(arr13) #返回方陣的跡(對角線元素之和),注意跡的求解不在linalg子例程中

                                                                              Out[129]: 10

                                                                              In [130]: np.linalg.eig(arr13) ? ?#返回由特征根和特征向量組成的元組

                                                                              Out[130]:

                                                                              (array([ 11.35035004, ?-3.99231852, ?-0.3732631 , ? 3.01523159]),

                                                                              array([[-0.4754174 , -0.48095078, -0.95004728, ?0.19967185],

                                                                              [-0.60676806, -0.42159999, ?0.28426325, -0.67482638],

                                                                              [-0.36135292, -0.16859677, ?0.08708826, ?0.70663129],

                                                                              [-0.52462832, ?0.75000995, ?0.09497472, -0.07357122]]))

                                                                              In [131]: np.linalg.qr(arr13) #返回方陣的QR分解

                                                                              Out[131]:

                                                                              (array([[-0.31622777, -0.07254763, -0.35574573, -0.87645982],

                                                                              [-0.63245553, -0.14509525, ?0.75789308, -0.06741999],

                                                                              [-0.31622777, -0.79802388, -0.38668014, ?0.33709993],

                                                                              [-0.63245553, ?0.580381 ?, -0.38668014, ?0.33709993]]),

                                                                              array([[-3.16227766, -6.64078309, -5.37587202, -6.95701085],

                                                                              [ 0. ? ? ? ?, ?1.37840488, -1.23330963, -3.04700025],

                                                                              [ 0. ? ? ? ?, ?0. ? ? ? ?, -3.40278524, ?1.22190924],

                                                                              [ 0. ? ? ? ?, ?0. ? ? ? ?, ?0. ? ? ? ?, -3.4384193 ]]))

                                                                              In [132]:np.linalg.svd(arr13) ? ?#返回方陣的奇異值分解

                                                                              Out[132]:

                                                                              (array([[-0.50908395, ?0.27580803, ?0.35260559, -0.73514132],

                                                                              [-0.59475561, ?0.4936665 , -0.53555663, ?0.34020325],

                                                                              [-0.39377551, -0.10084917, ?0.70979004, ?0.57529852],

                                                                              [-0.48170545, -0.81856751, -0.29162732, -0.11340459]]),

                                                                              array([ 11.82715609, ? 4.35052602, ? 3.17710166, ? 0.31197297]),

                                                                              array([[-0.25836994, -0.52417446, -0.47551003, -0.65755329],

                                                                              [-0.10914615, -0.38326507, -0.54167613, ?0.74012294],

                                                                              [-0.18632462, -0.68784764, ?0.69085326, ?0.12194478],

                                                                              [ 0.94160248, -0.32436807, -0.05655931, -0.07050652]]))

                                                                              In [133]: np.dot(arr13,arr13) ? ? #方陣的正真乘積運算

                                                                              Out[133]:

                                                                              array([[18, 38, 37, 31],

                                                                              [23, 51, 38, 43],

                                                                              [13, 25, 32, 26],

                                                                              [18, 33, 31, 53]])

                                                                              In [134]:arr14 = np.array([[1,-2,1],[0,2,-8],[-4,5,9]])

                                                                              In [135]: vector = np.array([0,8,-9])

                                                                              In [136]: np.linalg.solve(arr14,vector)

                                                                              Out[136]: array([ 29., ?16., ? 3.])

                                                                              隨機數生成

                                                                              統計學中經常會講到數據的分布特征,如正態分布、指數分布、卡方分布、二項分布、泊松分布等,下面就講講有關分布的隨機數生成。

                                                                              正態分布直方圖

                                                                              In [137]: import matplotlib #用于繪圖的模塊

                                                                              In [138]: np.random.seed(1234) ? ?#設置隨機種子

                                                                              In [139]: N = 10000 ? #隨機產生的樣本量

                                                                              In [140]: randnorm = np.random.normal(size = N) ? #生成正態隨機數

                                                                              In [141]: counts, bins, path = matplotlib.pylab.hist(randnorm, bins = np.sqrt(N), normed = True, color = 'blue') ?#繪制直方圖

                                                                              以上將直方圖的頻數和組距存放在counts和bins內。

                                                                              In [142]: sigma = 1; mu = 0

                                                                              In [143]: norm_dist = (1/np.sqrt(2*sigma*np.pi))*np.exp(-((bins-mu)**2)/2) ? ?#正態分布密度函數

                                                                              In [144]: matplotlib.pylab.plot(bins,norm_dist,color = 'red') #繪制正態分布密度函數圖

                                                                              1

                                                                              使用二項分布進行賭博

                                                                              同時拋棄9枚硬幣,如果正面朝上少于5枚,則輸掉8元,否則就贏8元。如果手中有1000元作為賭資,請問賭博10000次后可能會是什么情況呢?

                                                                              In [146]: np.random.seed(1234)

                                                                              In [147]: binomial = np.random.binomial(9,0.5,10000) ?#生成二項分布隨機數

                                                                              In [148]: money = np.zeros(10000) #生成10000次賭資的列表

                                                                              In [149]: money[0] = 1000 #首次賭資為1000元

                                                                              In [150]: for i in range(1,10000):

                                                                              ...: ? ? if binomial[i] < 5:

                                                                              ...: ? ? ? ? money[i] = money[i-1] - 8

                                                                              #如果少于5枚正面,則在上一次賭資的基礎上輸掉8元

                                                                              ...: ? ? else:

                                                                              ...: ? ? ? ? money[i] = money[i-1] + 8

                                                                              #如果至少5枚正面,則在上一次賭資的基礎上贏取8元

                                                                              In [151]: matplotlib.pylab.plot(np.arange(10000), money)

                                                                              2

                                                                              使用隨機整數實現隨機游走

                                                                              一個醉漢在原始位置上行走10000步后將會在什么地方呢?如果他每走一步是隨機的,即下一步可能是1也可能是-1。

                                                                              In [152]: np.random.seed(1234) ? ?#設定隨機種子

                                                                              In [153]: position = 0 ? ?#設置初始位置

                                                                              In [154]: walk = [] ? #創建空列表

                                                                              In [155]: steps = 10000 ? #假設接下來行走10000步

                                                                              In [156]: for i in np.arange(steps):

                                                                              ...: ? ? step = 1 if np.random.randint(0,2) else -1 ?#每一步都是隨機的

                                                                              ...: ? ? position = position + step ?#對每一步進行累計求和

                                                                              ...: ? ? walk.append(position) ? #確定每一步所在的位置

                                                                              In [157]: matplotlib.pylab.plot(np.arange(10000), walk) ? #繪制隨機游走圖

                                                                              1

                                                                              上面的代碼還可以寫成(結合前面所講的where函數,cumsum函數):

                                                                              In [158]: np.random.seed(1234)

                                                                              In [159]: step = np.where(np.random.randint(0,2,10000)>0,1,-1)

                                                                              In [160]: position = np.cumsum(step)

                                                                              In [161]: matplotlib.pylab.plot(np.arange(10000), position)

                                                                              1
                                                                              避免for循環,可以達到同樣的效果。

                                                                              使用Python進行數據分析,一般都會使用到numpy,pandas,scipy和matplotlib等模塊,而numpy是最為基礎的模塊,其他模塊的使用都是以numpy為核心,所以這里講解了有關numpy的方方面面,這部分的學習非常重要,希望感興趣的朋友多看看這方面的文檔和動手操作。在接下來Python一期中將會講到pandas模塊的學習。

                                                                               

                                                                              作者:劉順祥

                                                                              上一篇 :
                                                                              下一篇 :

                                                                                      <thead id="xthz1"></thead>
                                                                                        <form id="xthz1"></form>

                                                                                            <sub id="xthz1"><meter id="xthz1"></meter></sub><thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                            <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                            <th id="xthz1"></th>

                                                                                              <font id="xthz1"><meter id="xthz1"><i id="xthz1"></i></meter></font>

                                                                                                      <nobr id="xthz1"><meter id="xthz1"></meter></nobr>

                                                                                                      <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                      <nobr id="xthz1"></nobr>

                                                                                                              <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                              <th id="xthz1"></th>
                                                                                                              <thead id="xthz1"><meter id="xthz1"><b id="xthz1"></b></meter></thead>
                                                                                                              
                                                                                                              

                                                                                                                  <pre id="xthz1"><noframes id="xthz1"><track id="xthz1"></track>

                                                                                                                      <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                                      <th id="xthz1"></th>

                                                                                                                        <address id="xthz1"></address>

                                                                                                                        <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                            <video id="xthz1"><span id="xthz1"><nobr id="xthz1"></nobr></span></video>

                                                                                                                              <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                              <th id="xthz1"></th>

                                                                                                                                <th id="xthz1"></th><track id="xthz1"><meter id="xthz1"></meter></track>

                                                                                                                                  <font id="xthz1"><meter id="xthz1"></meter></font><th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                      <sub id="xthz1"><progress id="xthz1"></progress></sub>

                                                                                                                                          <sub id="xthz1"></sub>

                                                                                                                                                      <track id="xthz1"><meter id="xthz1"></meter></track>
                                                                                                                                                          快3赚钱方法如下

                                                                                                                                                                  <thead id="xthz1"></thead>
                                                                                                                                                                    <form id="xthz1"></form>

                                                                                                                                                                        <sub id="xthz1"><meter id="xthz1"></meter></sub><thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                        <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                        <th id="xthz1"></th>

                                                                                                                                                                          <font id="xthz1"><meter id="xthz1"><i id="xthz1"></i></meter></font>

                                                                                                                                                                                  <nobr id="xthz1"><meter id="xthz1"></meter></nobr>

                                                                                                                                                                                  <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                  <nobr id="xthz1"></nobr>

                                                                                                                                                                                          <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                                                                                                          <th id="xthz1"></th>
                                                                                                                                                                                          <thead id="xthz1"><meter id="xthz1"><b id="xthz1"></b></meter></thead>
                                                                                                                                                                                          
                                                                                                                                                                                          

                                                                                                                                                                                              <pre id="xthz1"><noframes id="xthz1"><track id="xthz1"></track>

                                                                                                                                                                                                  <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                                                                                                                  <th id="xthz1"></th>

                                                                                                                                                                                                    <address id="xthz1"></address>

                                                                                                                                                                                                    <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                                                        <video id="xthz1"><span id="xthz1"><nobr id="xthz1"></nobr></span></video>

                                                                                                                                                                                                          <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                                          <th id="xthz1"></th>

                                                                                                                                                                                                            <th id="xthz1"></th><track id="xthz1"><meter id="xthz1"></meter></track>

                                                                                                                                                                                                              <font id="xthz1"><meter id="xthz1"></meter></font><th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                                                  <sub id="xthz1"><progress id="xthz1"></progress></sub>

                                                                                                                                                                                                                      <sub id="xthz1"></sub>

                                                                                                                                                                                                                                  <track id="xthz1"><meter id="xthz1"></meter></track>

                                                                                                                                                                                                                                              <thead id="xthz1"></thead>
                                                                                                                                                                                                                                                <form id="xthz1"></form>

                                                                                                                                                                                                                                                    <sub id="xthz1"><meter id="xthz1"></meter></sub><thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                                                                                                    <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                                                                                                    <th id="xthz1"></th>

                                                                                                                                                                                                                                                      <font id="xthz1"><meter id="xthz1"><i id="xthz1"></i></meter></font>

                                                                                                                                                                                                                                                              <nobr id="xthz1"><meter id="xthz1"></meter></nobr>

                                                                                                                                                                                                                                                              <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                                                                                              <nobr id="xthz1"></nobr>

                                                                                                                                                                                                                                                                      <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                                                                                                                                                                                      <th id="xthz1"></th>
                                                                                                                                                                                                                                                                      <thead id="xthz1"><meter id="xthz1"><b id="xthz1"></b></meter></thead>
                                                                                                                                                                                                                                                                      
                                                                                                                                                                                                                                                                      

                                                                                                                                                                                                                                                                          <pre id="xthz1"><noframes id="xthz1"><track id="xthz1"></track>

                                                                                                                                                                                                                                                                              <nobr id="xthz1"><meter id="xthz1"><var id="xthz1"></var></meter></nobr>

                                                                                                                                                                                                                                                                              <th id="xthz1"></th>

                                                                                                                                                                                                                                                                                <address id="xthz1"></address>

                                                                                                                                                                                                                                                                                <thead id="xthz1"><meter id="xthz1"></meter></thead>

                                                                                                                                                                                                                                                                                    <video id="xthz1"><span id="xthz1"><nobr id="xthz1"></nobr></span></video>

                                                                                                                                                                                                                                                                                      <th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                                                                                                                      <th id="xthz1"></th>

                                                                                                                                                                                                                                                                                        <th id="xthz1"></th><track id="xthz1"><meter id="xthz1"></meter></track>

                                                                                                                                                                                                                                                                                          <font id="xthz1"><meter id="xthz1"></meter></font><th id="xthz1"><meter id="xthz1"></meter></th>

                                                                                                                                                                                                                                                                                              <sub id="xthz1"><progress id="xthz1"></progress></sub>

                                                                                                                                                                                                                                                                                                  <sub id="xthz1"></sub>

                                                                                                                                                                                                                                                                                                              <track id="xthz1"><meter id="xthz1"></meter></track>