How to use compare_iterables method in Sure

Best Python code snippet using sure_python

test_libshape.py

Source:test_libshape.py

...210            #    expjaco[2] +=1e-6211            #    # breakpoint()212213            msg = f'Consistency for 1d Jacobian determinant fails for {ipoint=} '214            self.compare_iterables(actjdet,expjdet,msg=msg,rtol=closertol,atol=closeatol,desc='integration point')215216            msg = f'Consistency for 1d Jacobian jacobian fails for {ipoint=} '217            self.compare_iterables(actjaco,expjaco,msg=msg,rtol=closertol,atol=closeatol,desc='integration point')218            219            msg = f'Consistency for 1d Jacobian global derivatives fails for {ipoint=} '220            self.compare_iterables(actgder,expgder,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')221            222            # AssertionError must be raised when length of element is very small ( <1e-12 )223            self.assertRaises(AssertionError,jaco1d,[p1,p1],der)224225    def test_consistency_shift_jaco2d(self):226        for ipoint in range(1,maxinteg):227            # for this test we map an arbitrary rectangle to parent domain and compare global derivatives228            # the sides of the element defining  x and y axis must be parallel to the parent x any y axes229            # this is equivalent to saying the lower left point of the global domain should be 1,230            # lower right 2, upper right 3 and upper left 4231            232            # get location of lower left corner233            px = 1024*np.random.rand()234            py = 1024*np.random.rand()235            236            while True:237                # generate random values of length and breadth, both non-zero238                length  = abs(1024*np.random.rand())239                breadth = abs(1024*np.random.rand())240                if ( length != 0 and breadth != 0):241                    break242243            p1 = np.asarray((px,py,0));244            p2 = np.asarray((px+breadth,py,0));245            p3 = np.asarray((px+breadth,py+length,0));246            p4 = np.asarray((px,py+length,0))247248            plist = [p1,p2,p3,p4]249250            # get global derivatives using jaco2d251            gg     = gauss2d(ipoint);252            *ss,   = map(shape2d,gg.pts)253            der    = [ s.der for s in ss ]254            *jj,   = map(jaco2d,itertools.repeat(plist),der)255            actder = [j.gder for j in jj]256257            # interpolate nodal coords to get x,y,z at all integration points258            pp = interp_parent(plist,ss)259260            x1 = p1[0]; y1=p1[1]261            x2 = p2[0]; y2=p2[1]262            x3 = p3[0]; y3=p3[1]263            x4 = p4[0]; y4=p4[1]264265            expder = []266            for i,p in enumerate(pp):267                x = p[0]; y = p[1]; z=p[2]268269                N1x = (    -1.0/(x2-x1) ) * ( (y4-y)/(y4-y1) )270                N1y = (  (x2-x)/(x2-x1) ) * (   -1.0/(y4-y1) )271                N2x = (    -1.0/(x1-x2) ) * ( (y3-y)/(y3-y2) )272                N2y = (  (x1-x)/(x1-x2) ) * (   -1.0/(y3-y2) )273                N3x = (    -1.0/(x4-x3) ) * ( (y2-y)/(y2-y3) )274                N3y = (  (x4-x)/(x4-x3) ) * (   -1.0/(y2-y3) ) 275                N4x = (    -1.0/(x3-x4) ) * ( (y1-y)/(y1-y4) )276                N4y = (  (x3-x)/(x3-x4) ) * (   -1.0/(y1-y4) )277278                # sanity check, must fail279                # if ( ipoint == 3  and i ==2 ):280                #    N3x +=1e-6281282                tmp = np.asarray(( (N1x,N1y), (N2x,N2y), (N3x,N3y), (N4x,N4y)  ))283                expder.append(tmp)284285            msg = f'Checking global derivatives for jaco2d in test_consistency_shift_jaco2d {ipoint=} '286            self.compare_iterables(actder,expder,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')287288    def test_consistency_rotation_shift_jaco2d(self):289        # similar to test_consistency_shift_jaco2d but a rotation is added290        # for this test we map an arbitrary rectangle to parent domain and compare global derivatives291        # the sides of the element x and y axis  can be inclined to the global/parent x any y axes292293        # we generate a rectangle with sides parallel to global x and y axis. Rotate it by a random angle.294        # compute global derivatives, and jdet using jaco2d295        # compute derivatives analytically in a rotated frame of reference296        # map these derivatives from the rotated frame of reference to the global frame of reference297298        for ipoint in range(1,maxinteg):299            # lower left corner300            px = 16*np.random.rand(); py = 16*np.random.rand()301            302            while True:303                # generate random values of length and breadth, both non-zero304                length  = abs(16*np.random.rand())305                breadth = abs(16*np.random.rand())306                if ( length != 0 and breadth != 0):307                    break308309            # theta = 45.0*math.pi/180.0310            theta = 90*np.random.rand()*math.pi/180.0311            312            # these are coordinates in the standard global frame of reference313            p1 = np.asarray((px,py));314            p2 = np.asarray((px+breadth,py));315            p3 = np.asarray((px+breadth,py+length));316            p4 = np.asarray((px,py+length))317318            ct = math.cos(theta); st = math.sin(theta)319            Q  = np.asarray(( (ct,-st),(st,ct) ))320            Qt = Q.T321322            # rotate the points323            p1r = Q@p1 ; p2r = Q@p2 ; p3r = Q@p3 ; p4r = Q@p4324325            plist    = [p1,p2,p3,p4]326            plistrot = [p1r,p2r,p3r,p4r]327328            # compute global derivatives via jaco2d329            gg      = gauss2d(ipoint);330            *ss,    = map(shape2d,gg.pts)331            der     = [ s.der for s in ss ]332            *jj,    = map(jaco2d,itertools.repeat(plistrot),der)333            actder  = [j.gder for j in jj]334            actjdet = [j.jdet for j in jj]335336            # to create expected output, we are going to work in the rotated frame of reference337            # and then rotate back to global. Note that in the rotated frame of reference,338            # the coordinates are the original unrotated coordinates.339            340            pp = interp_parent(plist,ss)341342            x1 = p1[0]; y1=p1[1]343            x2 = p2[0]; y2=p2[1]344            x3 = p3[0]; y3=p3[1]345            x4 = p4[0]; y4=p4[1]346347            expder = [] ; expjdet = []348            349            for p in pp:350                x = p[0]; y = p[1]; 351352                N1x = (    -1.0/(x2-x1) ) * ( (y4-y)/(y4-y1) )353                N1y = (  (x2-x)/(x2-x1) ) * (   -1.0/(y4-y1) )354                N2x = (    -1.0/(x1-x2) ) * ( (y3-y)/(y3-y2) )355                N2y = (  (x1-x)/(x1-x2) ) * (   -1.0/(y3-y2) )356                N3x = (    -1.0/(x4-x3) ) * ( (y2-y)/(y2-y3) )357                N3y = (  (x4-x)/(x4-x3) ) * (   -1.0/(y2-y3) ) 358                N4x = (    -1.0/(x3-x4) ) * ( (y1-y)/(y1-y4) )359                N4y = (  (x3-x)/(x3-x4) ) * (   -1.0/(y1-y4) )360361                N1x,N1y = Q@(N1x,N1y)362                N2x,N2y = Q@(N2x,N2y)363                N3x,N3y = Q@(N3x,N3y)364                N4x,N4y = Q@(N4x,N4y)       365                366                tmp = np.asarray(( (N1x,N1y), (N2x,N2y), (N3x,N3y), (N4x,N4y)  ))367                expder.append(tmp)368                expjdet.append(length*breadth/4.0)369370            msg = f'Checking global derivatives for jaco2d in test_consistency_rotation_shift_jaco2d {ipoint=} '371            self.compare_iterables(actder,expder,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')372373            # sanity test, must fail374            #if ( ipoint == 4 ):375            #    expjdet[2] += 1e-6376                377            msg = f'Checking jacodets for jaco2d in test_consistency_rotation_shift_jaco2d {ipoint=} '378            self.compare_iterables(actjdet,expjdet,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')379380381                382    def test_jaco1d_general_element(self):383        # consider two points p1 = (1,2,7) and p2 = (5,3,11) and 3 integration points384        # check that jdet,gder,jaco are correct385        p1 = np.asarray((1,2,7));         p2 = np.asarray((5,3,11));386387        # distance between p1 and p2388        dd = 5.744562646538029389390        # hand calculated values391        gder1 =  (1.0 - 0.0)/(0 - dd)  # derivative of the first shape function392        gder2 =  (0.0 - 1.0)/(0 - dd)  # derivative of the second shape function393        jdet  =  dd/2.0          394        jaco  =  dd/2.0395396        gg   = gauss1d(3)397        *ss, = map(shape1d,gg.pts)398        der  = [s.der for s in ss]399        *jj, = map(jaco1d,itertools.repeat([p1,p2]),der)400401        actgder = [ j.gder for j in jj]402        actjdet = [ j.jdet for j in jj]403        actjaco = [ j.jaco for j in jj]404405        self.assertAlmostEqual(gder1,actgder[0][0],      places=closeplaces,msg='gder1 failure in test_jaco1d')406        self.assertAlmostEqual(gder2,actgder[0][1],      places=closeplaces,msg='gder2 failure in test_jaco1d')407        self.assertAlmostEqual(jdet, actjdet[0],         places=closeplaces,msg='jdet  failure in test_jaco1d')408        self.assertAlmostEqual(jaco, actjaco[0][0][0],   places=closeplaces,msg='jdet  failure in test_jaco1d')409410411    def test_jaco2d_general_element(self):412        413        # this is the element414        p1 = np.asarray((1,2,0));415        p2 = np.asarray((6,4,0));416        p3 = np.asarray((3,7,0));417        p4 = np.asarray((-3,4,0));418419        gg   = gauss2d(3);420        *ss, = map(shape2d,gg.pts)421        der  = [s.der for s in ss]422        *jj, = map(jaco2d,itertools.repeat([p1,p2,p3,p4]),der)423424        # check at first integration point: jdet,jaco,gder425        j00 =  2.5563508326896285426        j01 = -1.9436491673103709427        j10 =  1.0563508326896291428        j11 =  1.0563508326896291429430        expjaco    = np.asarray(( (j00,j01 )  , (j10,j11 ) ))431        expjdet    = np.linalg.det(expjaco)432        tmp        = np.asarray(( ( j11, -j01)  ,(-j10 , j00) ))433        expjacoinv = (1.0/expjdet)*tmp434        expgder    = ss[0].der@expjacoinv435        436        msg = f'Compare general element jaco2d: jdet '437        self.compare_iterables([jj[0].jdet],[expjdet],msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')438439        msg = f'Compare general element jaco2d: jaco '440        self.compare_iterables([jj[0].jaco],[expjaco],msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')441442        msg = f'Compare general element jaco2d: gder '443        self.compare_iterables([jj[0].gder],[expgder],msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')444445446    def test_jaco2d_with_parent_domain(self):447        for ipoint in range(1,maxinteg):448            p1 = np.asarray((-1,-1,0));449            p2 = np.asarray(( 1,-1,0));450            p3 = np.asarray(( 1, 1,0));451            p4 = np.asarray((-1, 1,0));452453            gg   = gauss2d(ipoint);454            *ss, = map(shape2d,gg.pts)455            der  = [s.der for s in ss]456            # the following is a map. der yields shape function derivatives at the particular integration point457            # der is 'iterable', exhausting der terminates the map458            *jj, = map(jaco2d,itertools.repeat([p1,p2,p3,p4]),der)459460            actjdet = [j.jdet for j in jj]461            actjaco = [j.jaco for j in jj]462            actgder = [j.gder for j in jj]463464            # i'm using deepcopy because I want to perturb values while not modifying other values in the list or linked values465            expjdet = [1]*ipoint*ipoint466            expjaco = np.asarray([ [1.0, 0.0],[0.0, 1.0] ])467            expjaco = [ copy.deepcopy(expjaco) for i in range(ipoint*ipoint)]# deep copy468            expgder = copy.deepcopy(der)469470            #if ( ipoint == 4):471            #    breakpoint()472473            msg = f'Consistency of jaco2d for jdet with input parent domain fails for {ipoint=} '474            self.compare_iterables(actjdet,expjdet,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')475476            msg = f'Consistency of jaco2d for jaco with input parent domain fails for {ipoint=} '477            self.compare_iterables(actjaco,expjaco,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')478479            msg = f'Consistency of jaco2d for gder with input parent domain fails for {ipoint=} '480            self.compare_iterables(actgder,expgder,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')481            482            483            484    def test_parent_interp_consistency(self):485        # test 1d interpolation with scalars, vectors and matrices486        # set the nodes to a constant value (scalar/vector/matrix), and see487        # that the constant is reproduced by interpolation at all integration points488        489        # Sanity testing - if the data at each node is a constant,490        # then after interpolation data at integration point should be the same constant491492        for ipoint,idim,ddim in itertools.product(range(1,maxinteg),range(1,3),range(-1,3)):493            494            # ipoint: number of integration points to use495            # idim  : dimension we're testing i.e. calling (gauss1d,shape1d) or (gauss2d,shape2d)496            # ddim  : dimension dimension of data we're interpolating scalars,vectors or matrices497            #         ddim = -1 corresponds to pure python scalar,498            #              =  0 corresponds to zero dim np array499            #              =  1             to 1    dim np array (vector)500            #              =  2             to 2    dim np array (matrix)501502            fgauss = eval(f'gauss{idim}d')503            fshape = eval(f'shape{idim}d')504            gg     = fgauss(ipoint)505            *ss,   = map(fshape,gg.pts)506507            # get random data at the two nodes of the linear element, or four nodes of a quad508            mult   = np.random.randint(1,2**16)509            rowdim = np.random.randint(1,10)510            coldim = np.random.randint(1,16)511            512            if ( ddim == -1 ): dd = mult*np.random.rand()                # pure scalar513            if ( ddim ==  0 ): dd = np.asarray(mult*np.random.rand())    # zero dim np array514            if ( ddim ==  1 ): dd = mult*np.random.rand(rowdim)          # 1 dim numpy array515            if ( ddim ==  2 ): dd = mult*np.random.rand(rowdim,coldim)   # 2 dim numpy array516            517            nodedata = [dd]*(2**idim) 518            519            # output at all integration points520            actout = interp_parent(nodedata,ss)521            # expout = expected output at each integration point522            expout  = [dd]*(ipoint**idim)523524            # sanity testing of the test - should fail525            # if ( ( ipoint == 4 ) and ( idim  == 2 ) and ( ddim == 2 ) ):526            #    actout[2] += 1e-5527528            #if (( ipoint == 2 ) and (idim == 1) and ( ddim == 2)):529            #    breakpoint()530531            msg = f'Consistency for {idim}d parent interpolation with constant data fails for {ipoint=} {idim=} {ddim=} '532            self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')533534    def test_parent_interp_1d(self):535        # integration points536        npoint = 3537        gg     = gauss1d(npoint)538        *ss,   = map(shape1d,gg.pts)539        540        # scalar data541        nodedata  = [11.2,-13.7]542        actout    = interp_parent(nodedata,ss)543        expout    = [8.393728532056468, -1.25,-10.893728532056468]544        msg = 'test_parent_interp_1d fails for scalar data '545        self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')546        547        # vector data548549        d1 = np.asarray([1.23, -0.5]); d2 = np.asarray([7.12, 0.25])550        nodedata = [d1,d2]551        actout   = interp_parent(nodedata,ss)552        out1     = np.asarray([ 1.8938128090838315, -0.4154737509655563 ])553        out2     = np.asarray([ 4.175, -0.125 ])554        out3     = np.asarray([ 6.456187190916169 , 0.1654737509655563])555        expout   = [out1,out2,out3]556        msg = 'test_parent_interp_1d fails for vector data '557        self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')558559        # matrix data560561        d1 = np.asarray(( (12.0,-6.0),  (11.125, 2.5) ))562        d2 = np.asarray(( (1.0, 3.0),   (0.175, 1.5) ))563        nodedata = [d1,d2]564        actout   = interp_parent(nodedata,ss)565        out1     = np.asarray([[10.76028168082816  , -4.985685011586675 ],[ 9.890916764097122 ,  2.3872983346207413]])566        out2     = np.asarray([[ 6.5 , -1.5 ],[ 5.65,  2.  ]])567        out3     = np.asarray([[2.2397183191718413, 1.9856850115866753],[1.4090832359028784, 1.6127016653792583]])568        expout   = [out1,out2,out3]569        msg = 'test_parent_interp_1d fails for matrix data '570        self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')571572    def test_parent_interp_2d(self):573        npoint = 2574        gg     = gauss2d(npoint)575        *ss,   = map(shape2d,gg.pts)576        577        # scalar interpolation578        d1 = 0.5; d2 = 1.245; d3 = 11.2; d4 = -5.1579        nodedata = [d1,d2,d3,d4]580        actout   = interp_parent(nodedata,ss)581        out1     = 0.16867605983550216; out2=-1.1666437290040874; out3=2.496643729004088;out4=6.346323940164497582        expout   = [out1,out2,out3,out4]583        msg = 'test_parent_interp_2d fails for scalar data '584        self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')585        586        # vector interpolation587        d1 = np.asarray((1.23,0.259)); d2 = np.asarray((2.3,0.91));588        d3 = np.asarray((3.1,-0.765)); d4 = np.asarray((-11.2,-1.3));589        nodedata = [d1,d2,d3,d4]590        actout   = interp_parent(nodedata,ss)591        592        out1 = np.asarray([-0.5798225016923   ,  0.0619366711584217])593        out2 = np.asarray([-6.142114317029974 , -0.8523053807878699])594        out3 = np.asarray([1.652114317029974  ,  0.4236387141212032])595        out4 = np.asarray([ 0.4998225016923001, -0.5292700044917551])596        expout  = [out1,out2,out3,out4]597        msg = 'test_parent_interp_2d fails for vector data '598        self.compare_iterables(actout,expout,msg=msg,rtol=closertol,atol=closeatol,desc='integration point ')599        600        # matrix interpolation601        d1 = np.asarray(( (121.0,-26.0),  (1.15, 0.5) ))602        d2 = np.asarray(( (1.0, 32.0),   (0.333, 133.5) ))603        d3 = np.asarray(( (11.0,-61.0),  (12.5, 0.15) ))604        d4 = np.asarray(( (199.0, 39.0),   (-0.42, 0.5) ))605606        nodedata = [d1,d2,d3,d4]607        actout   = interp_parent(nodedata,ss)608        609        out1 = np.asarray([[109.08759813876276  ,  -7.063036955848214 ],[  1.2590372223488737,  22.651036297108188 ]])610        out2 = np.asarray([[145.82434331643964  ,  11.187392608830354 ],[  2.0286276236501064,   6.381207098889888 ]])611        out3 = np.asarray([[31.50899001689372 ,  7.145940724502975],[ 2.463372376349894, 83.16879290111011 ]])612        out4 = np.asarray([[ 45.57906852790392 , -27.270296377485117],[  7.811962777651126,  22.448963702891817]])613614        expout  = [out1,out2,out3,out4]615        msg     = 'test_parent_interp_2d fails for matrix data '616        
...

utils.py

Source:utils.py

...123    elif isinstance(number, Decimal):124        return cast_number(str(number))125    elif isinstance(number, (float, int)):126        return number127def compare_iterables(keys, this):128    """129    Compare two iterables.130    Check that all the elements of the (list, tuple or dict) passed as keys exist in131    the (list, tuple or dict) passed as "this"132    Parameters133    ----------134    keys : list, tuple or dict135    this : list, tuple or dict136    Returns137    -------138    bool: True if all the elements of the (list, tuple or dict) passed as keys exist in139    the (list, tuple or dict) passed as "this"140    Examples141    --------142    >>> from core_utils.utils import compare_iterables143    >>> compare_iterables(["a", "b"], ["a", "b", "c"])144    """145    return (146        all([key in this for key in keys])147        if isinstance(keys, (list, dict)) and isinstance(this, (list, dict))148        else False149    )150def dict_strip_nulls(d):151    """152    Remove null values from a dictionary.153    Parameters154    ----------155    d : dict156    Returns157    -------...

conftest.py

Source:conftest.py

...19def dicts_with_null_path():20    return os.path.join('tests', 'data', 'with-null.json')21@pytest.fixture(scope='function')22def compare_iter():23    def compare_iterables(collection1, collection2):24        for i1, i2 in zip(collection1, collection2):25            assert i1 == i2, "%s != %s" % (i1, i2)26    return compare_iterables27def test_compare_iterables(compare_iter):28    compare_iter('abc', 'abc')29    with pytest.raises(AssertionError):...

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