How to use the vector.dot function in vector

To help you get started, we’ve selected a few vector examples, based on popular ways it is used in public projects.

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github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
def PointFit(points):
    avg = AvgPoint(points)
    dev = 0
    max_dev = 0
    for p in points:
        v = vector.sub(p[:3], avg)
        d = vector.dot(v, v)
        max_dev = max(d, max_dev)
        dev += d
    dev /= len(points)
    return avg, dev**.5, max_dev**.5
github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
            r1 = lmap(lambda y, z : beta[6] - vector.dot(y, z), m, g)
github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
            r0 = lmap(lambda y : efit[3]**2 - vector.dot(y, y), m)
            #return r0
github christiangoltz / shaape / shaape / graphalgorithms.py View on Github external
def right_angle(v1, v2):
    x = vector.Vector(v1[0], v1[1])
    y = vector.Vector(v2[0], v2[1])
    dot = vector.dot(x, y)
    _angle = math.acos(dot / x.length() / y.length())
    if x[0] * y[1] < y[0] * x[1]:
        _angle = 2 * math.pi - _angle
    return _angle
github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
line_fit = [datamean, vv[0]]
    plane_fit = [datamean, vv[2]]

    line_dev = 0
    max_line_dev = 0
    plane_dev = 0
    max_plane_dev = 0
    for p in data:
        t = vector.dot(p, line_fit[1]) - vector.dot(line_fit[0], line_fit[1])
        q = lmap(lambda o, n : o + t*n, line_fit[0], line_fit[1])
        v = vector.sub(p, q)
        d = vector.dot(v, v)
        max_line_dev = max(d, max_line_dev)
        line_dev += d

        t = vector.dot(p, plane_fit[1]) - vector.dot(plane_fit[0], plane_fit[1])
        v = lmap(lambda b : t*b, plane_fit[1])
        d = vector.dot(v, v)
        max_plane_dev = max(d, max_plane_dev)
        plane_dev += d
        
    line_dev /= len(points)
    plane_dev /= len(points)

    line = [line_fit, line_dev**.5, max_line_dev**.5]
    plane = [plane_fit, plane_dev**.5, max_plane_dev**.5]
    return line, plane
github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
line_dev = 0
    max_line_dev = 0
    plane_dev = 0
    max_plane_dev = 0
    for p in data:
        t = vector.dot(p, line_fit[1]) - vector.dot(line_fit[0], line_fit[1])
        q = lmap(lambda o, n : o + t*n, line_fit[0], line_fit[1])
        v = vector.sub(p, q)
        d = vector.dot(v, v)
        max_line_dev = max(d, max_line_dev)
        line_dev += d

        t = vector.dot(p, plane_fit[1]) - vector.dot(plane_fit[0], plane_fit[1])
        v = lmap(lambda b : t*b, plane_fit[1])
        d = vector.dot(v, v)
        max_plane_dev = max(d, max_plane_dev)
        plane_dev += d
        
    line_dev /= len(points)
    plane_dev /= len(points)

    line = [line_fit, line_dev**.5, max_line_dev**.5]
    plane = [plane_fit, plane_dev**.5, max_plane_dev**.5]
    return line, plane
github snake-biscuits / QtPyHammer / hammer.py View on Github external
##        glEnd()

        # SOLIDS
##        glColor(1, 1, 1)
##        glBegin(GL_TRIANGLES)
##        for vertex in brush_triangles:
##            glVertex(*vertex)
##        glEnd()

        glBegin(GL_TRIANGLES)
        for solid in render_solids:
            if not solid.is_displacement:
                glColor(*solid.colour) # Flat Colour Unshaded
                for side_index, index_range in enumerate(solid.face_tri_map):
                    normal = solid.planes[side_index][0]
                    Kd = (vector.dot(normal, (1, 1, 1)) / 16) + .75
                    glColor(*[Kd * x for x in solid.colour])
                    start, end = index_range
                    for vertex in solid.triangles[start:end]:
                        glVertex(*vertex)
        glEnd()

        # DISPLACEMENTS
        glBegin(GL_TRIANGLES)
        glColor(.5, .5, .5)
        for solid in render_solids:
            if solid.is_displacement:
                glColor(1, 1, 1) # Hammer Default
                for i, points in solid.displacement_triangles.items():
                    for point, alpha, normal in points:
                        Kd = (vector.dot(normal, (1, 1, 1)) / 16) + .75
                        # clamped from 0.75 to 0.75 + 1/32
github pypilot / pypilot / pypilot / calibration_fit.py View on Github external
def ComputeDeviation(points, fit):
    m, d  = 0, 0
    for p in points:
        v = vector.sub(p[:3], fit[:3])
        m += (1 - vector.dot(v, v) / fit[3]**2)**2

        if len(fit) > 4:
            n = vector.dot(v, p[3:]) / vector.norm(v)
            if abs(n) <= 1:
                ang = math.degrees(math.asin(n))
                d += (fit[4] - ang)**2
            else:
                d += 1e111
    m /= len(points)
    d /= len(points)
    return [m**.5, d**.5]