source: inundation/utilities/numerical_tools.py @ 2920

#!/usr/bin/env python
"""Auxiliary numerical tools

"""


#Establish which Numeric package to use
#(this should move to somewhere central)
try:
    from scipy import ArrayType, array, sum, innerproduct, ravel, sqrt, searchsorted, sort, concatenate, Float    
except:
    #print 'Could not find scipy - using Numeric'
    from Numeric import ArrayType, array, sum, innerproduct, ravel, sqrt, searchsorted, sort, concatenate, Float    

# Getting an infinite number to use when using Numeric
INF = (array([1])/0.)[0]



def angle(v1, v2=None):
    """Compute angle between 2D vectors v1 and v2.
    
    If v2 is not specified it will default 
    to e1 (the unit vector in the x-direction)

    The angle is measured as a number in [0, 2pi] from v2 to v1.
    """
    from math import acos, pi, sqrt
  
    # Prepare two Numeric vectors
    if v2 is None:
        v2 = [1.0, 0.0] # Unit vector along the x-axis
        
    v1 = ensure_numeric(v1, Float)
    v2 = ensure_numeric(v2, Float)    
    
    # Normalise
    v1 = v1/sqrt(sum(v1**2))
    v2 = v2/sqrt(sum(v2**2))
   
    # Compute angle
    p = innerproduct(v1, v2)
    c = innerproduct(v1, normal_vector(v2)) # Projection onto normal
                                            # (negative cross product)
    
    theta = acos(p)
    
    # Correct if v1 is in quadrant 3 or 4 with respect to v2 (as the x-axis) 
    # If v2 was the unit vector [1,0] this would correspond to the test
    # if v1[1] < 0: theta = 2*pi-theta    
    # In general we use the sign of the projection onto the normal.
    if c < 0: 
       #Quadrant 3 or 4
       theta = 2*pi-theta        
       
    return theta

    
def anglediff(v0, v1):
    """Compute difference between angle of vector v0 (x0, y0) and v1 (x1, y1).
    This is used for determining the ordering of vertices,
    e.g. for checking if they are counter clockwise.

    Always return a positive value
    """

    from math import pi

    a0 = angle(v0)
    a1 = angle(v1)

    #Ensure that difference will be positive
    if a0 < a1:
        a0 += 2*pi

    return a0-a1

def normal_vector(v):
    """Normal vector to v
    """
    
    return array([-v[1], v[0]], Float)

    
#def crossproduct_length(v1, v2):
#    return v1[0]*v2[1]-v2[0]*v1[1]
   
       
def mean(x):
    """Mean value of a vector
    """
    return(float(sum(x))/len(x))


def cov(x, y=None):
    """Covariance of vectors x and y.

    If y is None: return cov(x, x) 
    """
    
    if y is None:
        y = x 

    assert(len(x)==len(y))
    N = len(x)
 
    cx = x - mean(x)  
    cy = y - mean(y)  

    p = innerproduct(cx,cy)/N
    return(p)


def err(x, y=0, n=2, relative=True):
    """Relative error of ||x-y|| to ||y||
       n = 2:    Two norm
       n = None: Max norm

       If denominator evaluates to zero or if y is omitted,
       absolute error is returned
    """

    x = ensure_numeric(x)
    if y:
        y = ensure_numeric(y)        

    if n == 2:
        err = norm(x-y)
        if relative is True:
            try:
                err = err/norm(y)
            except:
                pass

    else:
        err = max(abs(x-y))
        if relative is True:
            try:
                err = err/max(abs(y))    
            except:
                pass
          
    return err
  

def norm(x):
    """2-norm of x
    """
  
    y = ravel(x)
    p = sqrt(innerproduct(y,y))
    return p
    
  
def corr(x, y=None):
    """Correlation of x and y
    If y is None return autocorrelation of x
    """

    from math import sqrt
    if y is None:
        y = x 

    varx = cov(x)
    vary = cov(y)

    if varx == 0 or vary == 0:
        C = 0
    else:  
        C = cov(x,y)/sqrt(varx * vary)   

    return(C)


        
def ensure_numeric(A, typecode = None):
    """Ensure that sequence is a Numeric array.
    Inputs:
        A: Sequence. If A is already a Numeric array it will be returned
                     unaltered
                     If not, an attempt is made to convert it to a Numeric
                     array
        typecode: Numeric type. If specified, use this in the conversion.
                                If not, let Numeric decide

    This function is necessary as array(A) can cause memory overflow.
    """

    if typecode is None:
        if type(A) == ArrayType:
            return A
        else:
            return array(A)
    else:
        if type(A) == ArrayType:
            if A.typecode == typecode:
                return array(A)  #FIXME: Shouldn't this just return A?
            else:
                return array(A,typecode)
        else:
            return array(A,typecode)




def histogram(a, bins):
    """Standard histogram straight from the Numeric manual
    """

    n = searchsorted(sort(a), bins)
    n = concatenate( [n, [len(a)]] )
    return n[1:]-n[:-1]



####################################################################
#Python versions of function that are also implemented in numerical_tools_ext.c
#

def gradient_python(x0, y0, x1, y1, x2, y2, q0, q1, q2):
    """
    """

    det = (y2-y0)*(x1-x0) - (y1-y0)*(x2-x0)
    a = (y2-y0)*(q1-q0) - (y1-y0)*(q2-q0)
    a /= det

    b = (x1-x0)*(q2-q0) - (x2-x0)*(q1-q0)
    b /= det

    return a, b


def gradient2_python(x0, y0, x1, y1, q0, q1):
    """Compute radient based on two points and enforce zero gradient
    in the direction orthogonal to (x1-x0), (y1-y0) 
    """

    #Old code
    #det = x0*y1 - x1*y0
    #if det != 0.0:
    #    a = (y1*q0 - y0*q1)/det
    #    b = (x0*q1 - x1*q0)/det

    #Correct code (ON)
    det = (x1-x0)**2 + (y1-y0)**2
    if det != 0.0:
        a = (x1-x0)*(q1-q0)/det
        b = (y1-y0)*(q1-q0)/det
        
    return a, b        


##############################################
#Initialise module

from utilities import compile
if compile.can_use_C_extension('util_ext.c'):
    from util_ext import gradient, gradient2
else:
    gradient = gradient_python
    gradient2 = gradient2_python    


if __name__ == "__main__":
    pass


    
def angle_obsolete(v):
    """Compute angle between e1 (the unit vector in the x-direction)
    and the specified vector v.
    
    Return a number in [0, 2pi]
    """
    from math import acos, pi, sqrt
  
    # Normalise v
    v = ensure_numeric(v, Float)
    v = v/sqrt(sum(v**2))
   
    # Compute angle
    theta = acos(v[0])
     
    if v[1] < 0: 
       #Quadrant 3 or 4
        theta = 2*pi-theta
    
    return theta