示例#1
0
    def reset_utils(self):
        self.utility = resize(0.0, (self.num_squares_x, self.num_squares_y))

        for e in self.pits:
            self.utility[e] = -1.0
        e = self.goal
        self.utility[e] = 1.0
示例#2
0
def corrcoef(*args):
    """
    
    corrcoef(X) where X is a matrix returns a matrix of correlation
    coefficients for each row of X.
    
    corrcoef(x,y) where x and y are vectors returns the matrix or
    correlation coefficients for x and y.

    Numeric arrays can be real or complex

    The correlation matrix is defined from the covariance matrix C as

    r(i,j) = C[i,j] / (C[i,i]*C[j,j])
    """

    if len(args) == 2:
        X = transpose(array([args[0]] + [args[1]]))
    elif len(args == 1):
        X = args[0]
    else:
        raise RuntimeError, 'Only expecting 1 or 2 arguments'

    C = cov(X)
    d = resize(diagonal(C), (2, 1))
    r = divide(C, sqrt(matrixmultiply(d, transpose(d))))[0, 1]
    try:
        return r.real
    except AttributeError:
        return r
示例#3
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 def makeTreeArray(self, dec_list=None):
     """Makes an array with nodes in rows and descendants in columns.
     
     A value of 1 indicates that the decendant is a descendant of that node/
     A value of 0 indicates that it is not
     
     also returns a list of nodes in the same order as they are listed
     in the array"""
     #get a list of internal nodes
     node_list = [node for node in self.traverse() if node.Children]
     node_list.sort()
     
     #get a list of TerminalDescendants Data if one is not supplied
     if not dec_list:
         dec_list = [dec.Data for dec in self.TerminalDescendants]
         dec_list.sort()
     #make a blank array of the right dimensions to alter
     result = resize(array([0]), (len(node_list), len(dec_list)))
     #put 1 in the column for each child of each node
     for i, node in enumerate(node_list):
         children = [dec.Data for dec in node.TerminalDescendants]
         for j, dec in enumerate(dec_list):
             if dec in children:
                 result[i,j] = 1
     return result, node_list
示例#4
0
文件: td.py 项目: agigom2233/pyrobot
    def reset_utils(self):
        self.utility = resize(0.0, (self.num_squares_x, self.num_squares_y))

        for e in self.pits:
            self.utility[e] = -1.0
        e = self.goal
        self.utility[e] = 1.0
示例#5
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文件: misc.py 项目: ayosec/pyslide
def RenderGradient(surf, topcolor, bottomcolor):
    '''Creates a new 3d vertical gradient array.

    This code was copied from the vgrade example'''

    import pygame
    from Numeric import array, repeat, resize, arange, \
        Float, NewAxis, Int, UnsignedInt8

    topcolor = array(topcolor, copy=0)
    bottomcolor = array(bottomcolor, copy=0)
    diff = bottomcolor - topcolor
    width, height = surf.get_size()
    # create array from 0.0 to 1.0 triplets
    column = arange(height, typecode=Float)/height
    column = repeat(column[:, NewAxis], [3], 1)
    # create a single column of gradient
    column = topcolor + (diff * column).astype(Int)
    # make the column a 3d image column by adding X
    column = column.astype(UnsignedInt8)[NewAxis,:,:]
    #3d array into 2d array
    column = pygame.surfarray.map_array(surf, column)
    # stretch the column into a full image
    return resize(column, (width, height))
示例#6
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 def reset_frequencies(self):
     self.frequencies = resize(0, (self.num_squares_x, self.num_squares_y))
示例#7
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    def reset_reward(self):
        self.reward = resize(0.0, (self.num_squares_x, self.num_squares_y))

        self.reward[self.goal] = 100
        for e in self.pits:
            self.reward[e] = -50
示例#8
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def iagaussian(s,mu,sigma):
    """  o Purpose
      Generate a 2D Gaussian image.

  o Synopsis
      g = iagaussian(s,mu,sigma)

  o Input
      s: [rows columns]
    mu: Mean vector. 2D point (x;y). Point of maximum value.
    sigma: covariance matrix (square).  [ Sx^2 Sxy; Syx Sy^2]

  o Output
      g: 

  o Description
      A 2D Gaussian image is an image with a Gaussian distribution. It can be used to generate test patterns or Gaussian filters both for spatial and frequency domain. The integral of the gaussian function is 1.0.

  o Examples
      import Numeric
      f = iagaussian([8,4], [3,1], [[1,0],[0,1]])
      print Numeric.array2string(f, precision=4, suppress_small=1)
      g = ianormalize(f, [0,255]).astype(Numeric.UnsignedInt8)
      print g
    f = iagaussian(100, 50, 10*10)
      g = ianormalize(f, [0,1])
      g,d = iaplot(g)
      showfig(g)
    f = iagaussian([50,50], [25,10], [[10*10,0],[0,20*20]])
      g = ianormalize(f, [0,255]).astype(Numeric.UnsignedInt8)
      iashow(g)
"""
    from Numeric import asarray,product,arange,NewAxis,transpose,matrixmultiply,reshape,concatenate,resize,sum,zeros,Float,ravel,pi,sqrt,exp 
    from LinearAlgebra import inverse,determinant 
    
    if type(sigma).__name__ in ['int', 'float', 'complex']: sigma = [sigma]
    s, mu, sigma = asarray(s), asarray(mu), asarray(sigma)
    
    if (product(s) == max(s)):
        x = arange(product(s))
        d = x - mu
        if len(d.shape) == 1:
            tmp1 = d[:,NewAxis]
            tmp3 = d
        else:
            tmp1 = transpose(d)
            tmp3 = tmp1
        if len(sigma) == 1:
            tmp2 = 1./sigma
        else:
            tmp2 = inverse(sigma)
        k = matrixmultiply(tmp1, tmp2) * tmp3
    else:
        aux = arange(product(s))
        x, y = iaind2sub(s, aux)
        xx = reshape(concatenate((x,y)), (2, product(x.shape)))
    
        d = transpose(xx) - resize(reshape(mu,(len(mu),1)), (s[0]*s[1],len(mu)))
    
        if len(sigma) == 1:
            tmp = 1./sigma
        else:
            tmp = inverse(sigma)
        k = matrixmultiply(d, tmp) * d
        k = sum(transpose(k))
    
    g = zeros(s, Float)
    aux = ravel(g)
    if len(sigma) == 1:
        tmp = sigma
    else:
        tmp = determinant(sigma)
    aux[:] = 1./(2*pi*sqrt(tmp)) * exp(-1./2 * k)
    
    return g
示例#9
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def psd(x,
        NFFT=256,
        Fs=2,
        detrend=detrend_none,
        window=window_hamming,
        noverlap=0):
    """
    The power spectral density by Welches average periodogram method.
    The vector x is divided into NFFT length segments.  Each segment
    is detrended by function detrend and windowed by function window.
    noperlap gives the length of the overlap between segments.  The
    absolute(fft(segment))**2 of each segment are averaged to compute Pxx,
    with a scaling to correct for power loss due to windowing.  Fs is
    the sampling frequency.

    -- NFFT must be a power of 2
    -- detrend and window are functions, unlike in matlab where they are
       vectors.
    -- if length x < NFFT, it will be zero padded to NFFT
    

    Refs:
      Bendat & Piersol -- Random Data: Analysis and Measurement
        Procedures, John Wiley & Sons (1986)

    """

    if NFFT % 2:
        raise ValueError, 'NFFT must be a power of 2'

    # zero pad x up to NFFT if it is shorter than NFFT
    if len(x) < NFFT:
        n = len(x)
        x = resize(x, (NFFT, ))
        x[n:] = 0

    # for real x, ignore the negative frequencies


#    if x.typecode()==Complex: numFreqs = NFFT
    if any(numpy.iscomplex(x)): numFreqs = NFFT
    else: numFreqs = NFFT // 2 + 1

    #    windowVals = window(ones((NFFT,),x.typecode()))
    windowVals = window(numpy.ones(NFFT))
    step = NFFT - noverlap
    ind = range(0, len(x) - NFFT + 1, step)
    n = len(ind)
    #    Pxx = zeros((numFreqs,n), Float)
    Pxx = numpy.zeros([numFreqs, n])

    # do the ffts of the slices
    for i in range(n):
        thisX = x[ind[i]:ind[i] + NFFT]
        thisX = windowVals * detrend(thisX)
        fx = absolute(fft(thisX))**2
        #print("numFreqs={0:f}".format(numFreqs))
        #print("len of fx slice={0:d}".format(len(fx[:int(numFreqs)])))
        #print("len of destination in Pxx={0:d}")
        Pxx[:, i] = fx[:int(numFreqs)]

    # Scale the spectrum by the norm of the window to compensate for
    # windowing loss; see Bendat & Piersol Sec 11.5.2
    if n > 1: Pxx = mean(Pxx, 1)
    Pxx = divide(Pxx, norm(windowVals)**2)
    freqs = Fs / NFFT * arange(0, numFreqs)
    return Pxx, freqs
示例#10
0
def csd(x,
        y,
        NFFT=256,
        Fs=2,
        detrend=detrend_none,
        window=window_hamming,
        noverlap=0):
    """
    The cross spectral density Pxy by Welches average periodogram
    method.  The vectors x and y are divided into NFFT length
    segments.  Each segment is detrended by function detrend and
    windowed by function window.  noverlap gives the length of the
    overlap between segments.  The product of the direct FFTs of x and
    y are averaged over each segment to compute Pxy, with a scaling to
    correct for power loss due to windowing.  Fs is the sampling
    frequency.

    NFFT must be a power of 2

    Refs:
      Bendat & Piersol -- Random Data: Analysis and Measurement
        Procedures, John Wiley & Sons (1986)

    """

    if NFFT % 2:
        raise ValueError, 'NFFT must be a power of 2'

    # zero pad x and y up to NFFT if they are shorter than NFFT
    if len(x) < NFFT:
        n = len(x)
        x = resize(x, (NFFT, ))
        x[n:] = 0
    if len(y) < NFFT:
        n = len(y)
        y = resize(y, (NFFT, ))
        y[n:] = 0

    # for real x, ignore the negative frequencies


#    if x.typecode()==Complex: numFreqs = NFFT
    if any(numpy.iscomplex(x)): numFreqs = NFFT
    else: numFreqs = NFFT // 2 + 1

    #    windowVals = window(ones((NFFT,),x.typecode()))
    windowVals = window(numpy.ones(NFFT))
    step = NFFT - noverlap
    ind = range(0, len(x) - NFFT + 1, step)
    n = len(ind)
    #    Pxy = zeros((numFreqs,n), Complex)
    Pxy = numpy.zeros([numFreqs, n])

    # do the ffts of the slices
    for i in range(n):
        thisX = x[ind[i]:ind[i] + NFFT]
        thisX = windowVals * detrend(thisX)
        thisY = y[ind[i]:ind[i] + NFFT]
        thisY = windowVals * detrend(thisY)
        fx = fft(thisX)
        fy = fft(thisY)
        Pxy[:, i] = fy[:numFreqs] * conjugate(fx[:numFreqs])

    # Scale the spectrum by the norm of the window to compensate for
    # windowing loss; see Bendat & Piersol Sec 11.5.2
    if n > 1: Pxy = mean(Pxy, 1)
    Pxy = divide(Pxy, norm(windowVals)**2)
    freqs = Fs / NFFT * arange(0, numFreqs)
    return Pxy, freqs
示例#11
0
    def __init__(self, root, width, height):
        Tkinter.Toplevel.__init__(self, root)

        self.inaccessible = [(-1,-1),\
                             ( 4, 2),( 5, 2),( 6, 2),( 4, 3),( 5, 3),( 6, 3),\
                             ( 9, 2),(10, 2),(11, 2),( 9, 3),(10, 3),(11, 3),( 9, 4),(10, 4),(11, 4),\
                             (13, 1),(14, 1),(13, 2),(14, 2),(13, 3),(14, 3),(13, 4),(14, 4),\
                             (3,6),(4,6),(5,6),(3,7),(4,7),(5,7),(3,8),(4,8),(5,8),(3,9),(4,9),(5,9),\
                             (7,6),(8,6),     (7,7),(8,7),     (7,8),(8,8),    \
                             (6,9),(7,9),(8,9),     (6,10),(7,10),(8,10),(9,10),(10,10),(6,11),(7,11),\
                             (8,11),(9,11),(10,11),(6,12),(7,12),(8,12),(9,12),(6,13),(7,13),(8,13),\
                             (11,6),(12,6),(13,6),(11,7),(12,7),(13,7),(11,8),(12,8),(13,8),\
                             (0,11),(1,11),(2,11),(0,12),(1,12),(2,12),(0,13),(1,13),(2,13),(0,14),(1,14),(2,14)];
    
	self.path_color        = "#5ee563"
	self.visited_color     = "#c5c5c5"
        self.current_pos_color = "#00AF32"
	self.inaccessible_color= "black"
	self.gridline_color    = "black"
	self.background_color  = "white"

        self.path    = []
        self.visited = []
	self.pits    = []
	self.goal    = []

	self.goal_id = -1
	self.pit_ids = []

        # how many states ?
        self.num_squares_x = 15
        self.num_squares_y = 15

        self.squares     = resize(   0,(self.num_squares_x,self.num_squares_y)); 

        # various object members
        self.done    = 0
        self.quit    = 0
        self.root    = root
        self.width   = width
        self.height  = height
        self.complete = 0

        # various tk objects
        self.title("SymbolicSimulator: RLWorld")
        self.canvas = Tkinter.Canvas(self,width=self.width,height=self.height,bg="black")
        self.canvas.pack()
        self.winfo_toplevel().protocol('WM_DELETE_WINDOW',self.destroy)

        # set height and width of images
        self.square_height = self.width  / self.num_squares_x;
        self.square_width  = self.height / self.num_squares_y;

        # goal image
        goldFilename = pyrobotdir() + "/images/rlgoal.gif" 
        goldImage = Image.open(goldFilename)
        goldImage = goldImage.resize( [self.square_height-2, self.square_width-2] )
        self.goldImageTk = ImageTk.PhotoImage(goldImage)

        # pit image
        pitFilename = pyrobotdir() + "/images/rlpit.gif" 
        pitImage = Image.open(pitFilename)
        pitImage = pitImage.resize( [self.square_height-2, self.square_width-2] )
        self.pitImageTk = ImageTk.PhotoImage(pitImage, height=self.square_height, width=self.square_width)

	for i in range(0, self.num_squares_x):
	  for j in range(0, self.num_squares_y):
            self.squares[i][j] = self.canvas.create_rectangle( i*self.square_width, j*self.square_height,
                            	        (i+1)*self.square_width - 1, (j+1)*self.square_height - 1,
                                	fill= self.background_color, tag = "square-%d-%d" % (i,j));

        # initialize the world
        self.initWorld()
        self.resetStates()
        
        # used by simulator
        self.properties = ["location", "obstacles", "goal", "home", \
                           "final", "visited", "complete", \
                           "pits", "path"]

        self.movements = ["up", "right", "down", "left"]
        self.ports = [60000]

        # start things off
        self.redraw()
        self.drawInaccessible()
示例#12
0
文件: td.py 项目: agigom2233/pyrobot
 def reset_frequencies(self):
     self.frequencies = resize(0, (self.num_squares_x, self.num_squares_y))
示例#13
0
文件: td.py 项目: agigom2233/pyrobot
    def reset_reward(self):
        self.reward = resize(0.0, (self.num_squares_x, self.num_squares_y))

        self.reward[self.goal] = 100
        for e in self.pits:
            self.reward[e] = -50
示例#14
0
    def __init__(self, root, width, height):
        Tkinter.Toplevel.__init__(self, root)

        self.inaccessible = [(-1,-1),\
                             ( 4, 2),( 5, 2),( 6, 2),( 4, 3),( 5, 3),( 6, 3),\
                             ( 9, 2),(10, 2),(11, 2),( 9, 3),(10, 3),(11, 3),( 9, 4),(10, 4),(11, 4),\
                             (13, 1),(14, 1),(13, 2),(14, 2),(13, 3),(14, 3),(13, 4),(14, 4),\
                             (3,6),(4,6),(5,6),(3,7),(4,7),(5,7),(3,8),(4,8),(5,8),(3,9),(4,9),(5,9),\
                             (7,6),(8,6),     (7,7),(8,7),     (7,8),(8,8),    \
                             (6,9),(7,9),(8,9),     (6,10),(7,10),(8,10),(9,10),(10,10),(6,11),(7,11),\
                             (8,11),(9,11),(10,11),(6,12),(7,12),(8,12),(9,12),(6,13),(7,13),(8,13),\
                             (11,6),(12,6),(13,6),(11,7),(12,7),(13,7),(11,8),(12,8),(13,8),\
                             (0,11),(1,11),(2,11),(0,12),(1,12),(2,12),(0,13),(1,13),(2,13),(0,14),(1,14),(2,14)]

        self.path_color = "#5ee563"
        self.visited_color = "#c5c5c5"
        self.current_pos_color = "#00AF32"
        self.inaccessible_color = "black"
        self.gridline_color = "black"
        self.background_color = "white"

        self.path = []
        self.visited = []
        self.pits = []
        self.goal = []

        self.goal_id = -1
        self.pit_ids = []

        # how many states ?
        self.num_squares_x = 15
        self.num_squares_y = 15

        self.squares = resize(0, (self.num_squares_x, self.num_squares_y))

        # various object members
        self.done = 0
        self.quit = 0
        self.root = root
        self.width = width
        self.height = height
        self.complete = 0

        # various tk objects
        self.title("SymbolicSimulator: RLWorld")
        self.canvas = Tkinter.Canvas(self,
                                     width=self.width,
                                     height=self.height,
                                     bg="black")
        self.canvas.pack()
        self.winfo_toplevel().protocol('WM_DELETE_WINDOW', self.destroy)

        # set height and width of images
        self.square_height = self.width / self.num_squares_x
        self.square_width = self.height / self.num_squares_y

        # goal image
        goldFilename = os.environ["PYROBOT"] + "/images/rlgoal.gif"
        goldImage = Image.open(goldFilename)
        goldImage = goldImage.resize(
            [self.square_height - 2, self.square_width - 2])
        self.goldImageTk = ImageTk.PhotoImage(goldImage)

        # pit image
        pitFilename = os.environ["PYROBOT"] + "/images/rlpit.gif"
        pitImage = Image.open(pitFilename)
        pitImage = pitImage.resize(
            [self.square_height - 2, self.square_width - 2])
        self.pitImageTk = ImageTk.PhotoImage(pitImage,
                                             height=self.square_height,
                                             width=self.square_width)

        for i in range(0, self.num_squares_x):
            for j in range(0, self.num_squares_y):
                self.squares[i][j] = self.canvas.create_rectangle(
                    i * self.square_width,
                    j * self.square_height, (i + 1) * self.square_width - 1,
                    (j + 1) * self.square_height - 1,
                    fill=self.background_color,
                    tag="square-%d-%d" % (i, j))

        # initialize the world
        self.initWorld()
        self.resetStates()

        # used by simulator
        self.properties = ["location", "obstacles", "goal", "home", \
                           "final", "visited", "complete", \
                           "pits", "path"]

        self.movements = ["up", "right", "down", "left"]
        self.ports = [60000]

        # start things off
        self.redraw()
        self.drawInaccessible()