# Path: s2p/estimation.py
# def fundamental_matrix_cameras(P1, P2):
# def get_angle_from_cos_and_sin(c, s):
# def rectifying_similarities_from_affine_fundamental_matrix(F, debug=False):
# def affine_fundamental_matrix(matches):
# def affine_transformation(x, xx):
# def translation(x, xx):
#     X0 = P1[[1, 2], :]
#     X1 = P1[[2, 0], :]
#     X2 = P1[[0, 1], :]
#     Y0 = P2[[1, 2], :]
#     Y1 = P2[[2, 0], :]
#     Y2 = P2[[0, 1], :]
#     F = np.zeros((3, 3))
#     F[0, 0] = np.linalg.det(np.vstack([X0, Y0]))
#     F[0, 1] = np.linalg.det(np.vstack([X1, Y0]))
#     F[0, 2] = np.linalg.det(np.vstack([X2, Y0]))
#     F[1, 0] = np.linalg.det(np.vstack([X0, Y1]))
#     F[1, 1] = np.linalg.det(np.vstack([X1, Y1]))
#     F[1, 2] = np.linalg.det(np.vstack([X2, Y1]))
#     F[2, 0] = np.linalg.det(np.vstack([X0, Y2]))
#     F[2, 1] = np.linalg.det(np.vstack([X1, Y2]))
#     F[2, 2] = np.linalg.det(np.vstack([X2, Y2]))
#     R1 = (1.0 / r) * np.array([[b, -a], [a, b]])
#     R2 = (1.0 / s) * np.array([[-d, c], [-c, -d]])
#     S1 = np.zeros((3, 3))
#     S1[0:2, 0:2] = z * R1
#     S1[1, 2] = t
#     S1[2, 2] = 1
#     S2 = np.zeros((3, 3))
#     S2[0:2, 0:2] = (1.0 / z) * R2
#     S2[1, 2] = -t
#     S2[2, 2] = 1
#     X = matches[:, [2, 3, 0, 1]]
#     N = len(X)
#     XX = np.sum(X, axis=0) / N
#     A = X - np.tile(XX, (N, 1))
#     U, S, V = np.linalg.svd(A)
#     N = V[-1, :]
#     F = np.zeros((3, 3))
#     F[0, 2] = N[0]
#     F[1, 2] = N[1]
#     F[2, 0] = N[2]
#     F[2, 1] = N[3]
#     F[2, 2] = -np.dot(N, XX)
#     A = np.hstack((x, xx))
#     U, S, V = np.linalg.svd(A)
#     B = tmp[0:2, :]
#     C = tmp[2:4, :]
#     H = np.dot(C, np.linalg.inv(B))
#     A = np.eye(3)
#     A[0:2, 0:2] = H
#     A[0:2, 2] = np.dot(H, t) - tt
#     A = np.eye(3)
#     A[0, 2] = t[0]
#     A[1, 2] = t[1]
# 
# Path: s2p/common.py
# def remove(target):
# def garbage_cleanup():
# def tmpfile(ext=''):
# def run(cmd, env=os.environ):
# def mkdir_p(path):
# def shellquote(s):
# def matrix_translation(x, y):
# def image_size_gdal(im):
# def gdal_read_as_array_with_nans(im):
# def image_zoom_out_morpho(im, f):
# def rasterio_write(path, array, profile={}, tags={}):
# def image_apply_homography(out, im, H, w, h):
# def image_qauto(im, out=None):
# def points_apply_homography(H, pts):
# def bounding_box2D(pts):
# def image_crop_gdal(im, x, y, w, h, out=None):
# def run_binary_on_list_of_points(points, binary, option=None, env_var=None):
# def get_rectangle_coordinates(im):
# def get_roi_coordinates(img, preview):
# def cargarse_basura(inputf, outputf):
# def print_elapsed_time(since_first_call=False):
# class RunFailure(Exception):


import numpy as np
from numpy.testing import assert_array_almost_equal
from s2p import estimation
from s2p import common
    return R


def test_affine_transformation():
    x =  np.array([[0, 0], [0, 1], [1, 0], [1, 1]])

    # list of transformations to be tested
    T = np.eye(3)
    I = np.eye(3)
    S = np.eye(3)
    A = np.eye(3)
    translations = []
    isometries = []
    similarities = []
    affinities = []

    for i in range(100):
        translations.append(T)
        isometries.append(I)
        similarities.append(S)
        affinities.append(A)
        T[0:2, 2] = np.random.random(2)
        I = rotation_matrix(2*np.pi * np.random.random_sample())
        I[0:2, 2] = np.random.random(2)
        S = similarity_matrix(2*np.pi * np.random.random_sample(),
                np.random.random_sample())
        S[0:2, 2] = 100 * np.random.random(2)
        A[0:2, :] = np.random.random((2, 3))

    for B in translations + isometries + similarities + affinities:

# Path: s2p/estimation.py
# def fundamental_matrix_cameras(P1, P2):
# def get_angle_from_cos_and_sin(c, s):
# def rectifying_similarities_from_affine_fundamental_matrix(F, debug=False):
# def affine_fundamental_matrix(matches):
# def affine_transformation(x, xx):
# def translation(x, xx):
#     X0 = P1[[1, 2], :]
#     X1 = P1[[2, 0], :]
#     X2 = P1[[0, 1], :]
#     Y0 = P2[[1, 2], :]
#     Y1 = P2[[2, 0], :]
#     Y2 = P2[[0, 1], :]
#     F = np.zeros((3, 3))
#     F[0, 0] = np.linalg.det(np.vstack([X0, Y0]))
#     F[0, 1] = np.linalg.det(np.vstack([X1, Y0]))
#     F[0, 2] = np.linalg.det(np.vstack([X2, Y0]))
#     F[1, 0] = np.linalg.det(np.vstack([X0, Y1]))
#     F[1, 1] = np.linalg.det(np.vstack([X1, Y1]))
#     F[1, 2] = np.linalg.det(np.vstack([X2, Y1]))
#     F[2, 0] = np.linalg.det(np.vstack([X0, Y2]))
#     F[2, 1] = np.linalg.det(np.vstack([X1, Y2]))
#     F[2, 2] = np.linalg.det(np.vstack([X2, Y2]))
#     R1 = (1.0 / r) * np.array([[b, -a], [a, b]])
#     R2 = (1.0 / s) * np.array([[-d, c], [-c, -d]])
#     S1 = np.zeros((3, 3))
#     S1[0:2, 0:2] = z * R1
#     S1[1, 2] = t
#     S1[2, 2] = 1
#     S2 = np.zeros((3, 3))
#     S2[0:2, 0:2] = (1.0 / z) * R2
#     S2[1, 2] = -t
#     S2[2, 2] = 1
#     X = matches[:, [2, 3, 0, 1]]
#     N = len(X)
#     XX = np.sum(X, axis=0) / N
#     A = X - np.tile(XX, (N, 1))
#     U, S, V = np.linalg.svd(A)
#     N = V[-1, :]
#     F = np.zeros((3, 3))
#     F[0, 2] = N[0]
#     F[1, 2] = N[1]
#     F[2, 0] = N[2]
#     F[2, 1] = N[3]
#     F[2, 2] = -np.dot(N, XX)
#     A = np.hstack((x, xx))
#     U, S, V = np.linalg.svd(A)
#     B = tmp[0:2, :]
#     C = tmp[2:4, :]
#     H = np.dot(C, np.linalg.inv(B))
#     A = np.eye(3)
#     A[0:2, 0:2] = H
#     A[0:2, 2] = np.dot(H, t) - tt
#     A = np.eye(3)
#     A[0, 2] = t[0]
#     A[1, 2] = t[1]
# 
# Path: s2p/common.py
# def remove(target):
# def garbage_cleanup():
# def tmpfile(ext=''):
# def run(cmd, env=os.environ):
# def mkdir_p(path):
# def shellquote(s):
# def matrix_translation(x, y):
# def image_size_gdal(im):
# def gdal_read_as_array_with_nans(im):
# def image_zoom_out_morpho(im, f):
# def rasterio_write(path, array, profile={}, tags={}):
# def image_apply_homography(out, im, H, w, h):
# def image_qauto(im, out=None):
# def points_apply_homography(H, pts):
# def bounding_box2D(pts):
# def image_crop_gdal(im, x, y, w, h, out=None):
# def run_binary_on_list_of_points(points, binary, option=None, env_var=None):
# def get_rectangle_coordinates(im):
# def get_roi_coordinates(img, preview):
# def cargarse_basura(inputf, outputf):
# def print_elapsed_time(since_first_call=False):
# class RunFailure(Exception):


# Path: s2p/test_estimation.py
import numpy as np
from numpy.testing import assert_array_almost_equal
from s2p import estimation
from s2p import common

    return R


def test_affine_transformation():
    x =  np.array([[0, 0], [0, 1], [1, 0], [1, 1]])

    # list of transformations to be tested
    T = np.eye(3)
    I = np.eye(3)
    S = np.eye(3)
    A = np.eye(3)
    translations = []
    isometries = []
    similarities = []
    affinities = []

    for i in range(100):
        translations.append(T)
        isometries.append(I)
        similarities.append(S)
        affinities.append(A)
        T[0:2, 2] = np.random.random(2)
        I = rotation_matrix(2*np.pi * np.random.random_sample())
        I[0:2, 2] = np.random.random(2)
        S = similarity_matrix(2*np.pi * np.random.random_sample(),
                np.random.random_sample())
        S[0:2, 2] = 100 * np.random.random(2)
        A[0:2, :] = np.random.random((2, 3))

    for B in translations + isometries + similarities + affinities:

        xx = common.points_apply_homography(B, x)