How to use n_value_list method in avocado

Best Python code snippet using avocado_python

sympy_transfer_matrix.py

Source:sympy_transfer_matrix.py

1# -*- coding: utf-8 -*-2"""3Created on Tue May 18 16:32:48 20214@author: jo28dohe5this package is strongly influenced by the python tmm package. 6for better performance repeatedly evaluated functions can be created with a lot of math already solved. 7"""8### testing around with sp and transfer matrices9import numpy as np10import matplotlib.pyplot as plt11from matplotlib import cm 12import sympy as sp13from sympy.utilities.lambdify import lambdify14sp.init_printing()15try:16    import refractive_index as ri17except:18    from LAP_eval import refractive_index as ri19n=sp.Symbol('n')20l=sp.Symbol('l')21lamb=sp.Symbol('lamb')22n1=sp.Symbol('n1')23n2=sp.Symbol('n2')24n3=sp.Symbol('n3')25n_SiC=2.6   ### bei 800nm https://refractiveindex.info/?shelf=main&book=SiC&page=Wang-4H-o26n_SiO2=1.45   ##https://refractiveindex.info/?shelf=main&book=SiO2&page=Malitson27#n_SiC=ri.n_from_string('SiC')28n_Au=ri.n_from_string('Au') 29n_Al=ri.n_from_string('Al') 30n_MoS2_ML=ri.n_from_string('MoS2').get_n(600e-9)31n_graphene=ri.n_from_string('graphene')32d_Al=3.5e-933d_MoS2=0.615e-934d_graphene=0.35e-935d_SiO2=135e-936d_vac=2300e-937d_Au=50e-938def ref_E(n_1,n_2):39    return((n_1-n_2)/(n_1+n_2))40    41def trans_E(n_1,n_2):42        return(2*n_1/(n_1+n_2))43def P__(n,l,lamb):    44    return sp.simplify(sp.Matrix([[sp.exp(-1j*2*sp.pi*l*n/lamb),0],[0,sp.exp(+1j*2*sp.pi*l*n/lamb)]]))45def D__(n_1,n_2):46    return sp.simplify(1/trans_E(n_1,n_2)*sp.Matrix([[1,ref_E(n_1,n_2)],[ref_E(n_1,n_2),1]]))47def t_from_M__(M): 48    t=1/M[0,0]49    return(t)50    51def r_from_M__(M):52    r=M[1,0]/M[0,0]53    return(r)54def find_in_structure(d_list, distance):55    """56    d_list is list of thicknesses of layers, all of which are finite.57    distance is the distance from the front of the whole multilayer structure58    (i.e., from the start of layer 0.)59    Function returns [layer,z], where:60    * layer is what number layer you're at.61    * z is the distance into that layer.62    For large distance, layer = len(d_list), even though d_list[layer] doesn't63    exist in this case. For negative distance, return [-1, distance]64    """65    if sum(d_list) == np.inf:66        raise ValueError('This function expects finite arguments')67    if distance < 0:68        return [-1, distance]69    layer = 070    while (layer < len(d_list)) and (distance >= d_list[layer]):71        distance -= d_list[layer]72        layer += 173    return [layer, distance]74def find_in_structure_with_inf(d_list, distance):75    """76    d_list is list of thicknesses of layers [inf, blah, blah, ..., blah, inf]77    distance is the distance from the front of the whole multilayer structure78    (i.e., from the start of layer 1.)79    Function returns [layer,z], where:80    * layer is what number layer you're at,81    * z is the distance into that layer.82    For distance < 0, returns [0, distance]. So the first interface can be described as83    either [0,0] or [1,0].84    """85    86    print(d_list)87    print(distance)88    if distance < 0:89        return [0, distance]90    [layer, distance_in_layer] = find_in_structure(d_list[1:-1], distance)91    return [layer+1, distance_in_layer]92class sympy_tmm():93    94    """95    an object which corresponds to a layered structure and contains functions for optical parameters96    like Reflectance, Transmission and depth-dependant E-Field97    """98    def __init__(self,n_value_list=[n_SiC,n_graphene,1,n_Au,n_SiC],99                d_value_list=[np.inf,d_graphene,d_vac,d_Au, np.inf],100                d_parameter_list=[2],101                n_parameter_list=[1,3],102                lamb_list=np.linspace(530e-9,1000e-9,200)):103        104        assert len(n_value_list)== len(d_value_list), 'n_value_list and d_value_list must have same lenght!'105        assert len(n_value_list)>1, 'n_value_list must have more than 1 entry'106        self.lamb_list=lamb_list107        self.n_value_list=n_value_list108        self.d_value_list=d_value_list109        self.d_parameter_list=d_parameter_list110        self.n_parameter_list=n_parameter_list111        112        113        self.n_list=[]114        self.d_list=[]115        self.lamb=sp.Symbol('lamb')116        self.all_parameter_list=[self.lamb]117       118        119        for i in range(len(n_value_list)):120            if i in n_parameter_list:121                self.n_list.append(sp.Symbol('n'+str(i)))122                self.all_parameter_list.append(self.n_list[-1])123            else:124                self.n_list.append(n_value_list[i])125            if i in d_parameter_list:126                self.d_list.append(sp.Symbol('d'+str(i)))127                self.all_parameter_list.append(self.d_list[-1])128            else:129                self.d_list.append(d_value_list[i])130        131        132        133        ## initialize Transfer Matrix at last boundary:134        self.M__=D__(self.n_list[-2],self.n_list[-1])135        ## save list that contains Transfer matrices of all boundaries from last to first (for E-field calculation)136        self.M__list=[self.M__]137        138        for i in range(len(self.n_value_list)-2):139           self.M__=D__(self.n_list[-3-i],self.n_list[-2-i])*P__(self.n_list[-2-i],self.d_list[-2-i],lamb)*self.M__140           self.M__list.append(self.M__)141        print('Matrix_Multiplication_done')142        143        144          145        self.r=r_from_M__(self.M__)146        self.t=t_from_M__(self.M__)147        self.R=sp.Abs(self.r)**2148        self.T=sp.Abs(self.t)**2*self.n_value_list[-1].real/self.n_value_list[0].real149        150        ## make list of arguments which should be plugged in later151        self.lambdify_args=[self.lamb]152        for index in self.n_parameter_list:153            self.lambdify_args.append(self.n_list[index])154        for index in self.d_parameter_list:155            self.lambdify_args.append(self.d_list[index])156        157        ## lambdify functions for numpy-like evaluation158        self.lam_R=lambdify(self.lambdify_args,self.R)    159        self.lam_T=lambdify(self.lambdify_args,self.T)160        161        162    def plot_R_T(self,lamb_list,d_vac=d_vac,n_lists=()):163        params=*n_lists,d_vac164        print(params)165        plt.plot(lamb_list,self.lam_R(lamb_list,*params),label='R')166        plt.plot(lamb_list,self.lam_T(lamb_list,*params),label='T')167        plt.plot(lamb_list,self.lam_R(lamb_list,*params)+self.lam_T(lamb_list,*params),label='Sum')168        plt.grid(True)169        plt.legend()170        plt.show()171        172    def plot_R_d(self,lamb_list,d_min,d_max,n_lists,n_d=200):173        d_list=np.linspace(d_min,d_max,n_d)174        plt.figure()175        for i in range(len(d_list)):176            plt.scatter(lamb_list,np.ones(len(lamb_list))*d_list[i],c=self.lam_R(lamb_list,*n_lists,d_list[i]),177                        vmin=0,vmax=1,cmap=cm.nipy_spectral)178        plt.xlim(min(lamb_list),max(lamb_list))179        plt.ylim(min(d_list),max(d_list))180        plt.show()181        182        183    def R_fit_func(self,d,lamb_list,n_lists):184        R=self.lam_R(lamb_list,*n_lists,d)185        return (R)186        187    def make_lam_E(self,d_E=0):188       189        i_layer,d_extra=find_in_structure_with_inf(self.d_value_list, d_E)190        self.E_r_l_boundary_list=[sp.Matrix([self.t,0])]191        for i in range(len(self.M__list)):192            self.E_r_l_boundary_list.append(self.M__list[i]*self.E_r_l_boundary_list[0])193        194        if self.d_list[i_layer]==np.inf:195            d_prop=-d_extra196        else:197            d_prop=self.d_list[i_layer]-d_extra198        E_r_l_pos=P__(self.n_list[i_layer],d_prop,self.lamb)*self.E_r_l_boundary_list[-1-i_layer]  ## propagation from right side of i_layer_th material to position199        200        self.lam_E_r=lambdify(self.lambdify_args,E_r_l_pos[0])201        self.lam_E_l=lambdify(self.lambdify_args,E_r_l_pos[1])202        self.lam_E_ges=lambdify(self.lambdify_args,E_r_l_pos[0]+E_r_l_pos[1])203        print('object now has E_r,E_l,E_ges functions')204        return(self.lam_E_ges)205        206        207    def plot_spectrum_modification(self,lamb_list,d_E=0,n_lists=(),d_vac_min=0,d_vac_max=2300e-9):208            209        self.make_lam_E(d_E=d_E)210        plt.figure()211        d_list=np.linspace(d_vac_min,d_vac_max,200)212        for i in range(len(d_list)):213            I_laser=np.abs(self.lam_E_ges(532e-9,*n_lists,d_list[i]))**2*np.ones(len(lamb_list))214            I_emission=np.abs(self.lam_E_ges(lamb_list,*n_lists,d_list[i]))**2            215            plt.scatter(1e9*lamb_list,1e9*d_list[i]*np.ones(len(lamb_list)),216                        c=I_laser*I_emission,217                        vmin=-0.5,vmax=4,cmap=cm.nipy_spectral)218            219        plt.xlim(1e9*min(lamb_list),1e9*max(lamb_list))220        plt.ylim(1e9*min(d_list),1e9*max(d_list))221        plt.xlabel('wavelength in nm ')222        plt.ylabel('d in nm')223        plt.title('optical enhancement factor (Photoluminescence)')224        plt.show()225        226    def plot_spectrum_modification_to_ax(self,ax,d=0,lamb_list=[],n_lists=(),d_vac_min=0,d_vac_max=2300e-9):227            228        self.make_lam_E(d=d)229        230        d_list=np.linspace(d_vac_min,d_vac_max,200)231        for i in range(len(d_list)):232            I_laser=np.abs(self.lam_E_ges(532e-9,*n_lists,d_list[i]))**2*np.ones(len(lamb_list))233            I_emission=np.abs(self.lam_E_ges(lamb_list,*n_lists,d_list[i]))**2            234            ax.scatter(1e9*lamb_list,1e9*d_list[i]*np.ones(len(lamb_list)),235                        c=I_laser*I_emission,236                        vmin=0,vmax=5,cmap=cm.nipy_spectral)237            238        ax.set_xlim(1e9*min(lamb_list),1e9*max(lamb_list))239        ax.set_ylim(1e9*min(d_list),1e9*max(d_list))240        ax.set_xlabel(r'$\lambda$ in nm')241        ax.set_ylabel(r'$d$ in nm')242        ax.set_title('simulated optical enhancement factor')243        244    def plot_E_of_lamb(self,d_E=0,lamb_list=[],n_lists=(),d_vac=d_vac):245            246        247        self.make_lam_E(d_E=d_E)248        print('d_value_list: ',self.d_value_list)249        I_emission=np.abs(self.lam_E_ges(lamb_list,*n_lists,d_vac))**2250        plt.plot(1e9*lamb_list,I_emission)251        plt.xlim(1e9*min(lamb_list),1e9*max(lamb_list))252        plt.show()253    254    def plot_d_dep_E(self,d_vac=d_vac,lamb=600e-9):255        E_list=[]256        d_list=np.linspace(-100e-9,100e-9+np.sum(self.d_value_list[1:-1]))257        for d in d_list:258            self.make_lam_E(d=d)259            E_list.append(np.abs(self.lam_E_ges(lamb,n_Al.get_n(lamb),n_Au.get_n(lamb),d_vac)))260        plt.plot(d_list,E_list)261        plt.show()262        263    def E_of_d_vac(self,d_vac,lamb=532e-9):264        return(self.lam_E_ges(lamb,n_graphene.get_n(lamb),n_Au.get_n(lamb),d_vac))265        266        267    def plot_E_of_d_vac(self,lamb=532e-9):268        plt.figure()269        d_list=np.linspace(0,2300e-9,300)270        plt.plot(np.abs(self.E_of_d_vac(d_list))**2,d_list)271        plt.show()272if __name__=='__main__':273    example_tmm=sympy_tmm()274    lamb_list=np.linspace(530e-9,950e-9,200)275    n_Au_list=n_Au.get_n(lamb_list)276    n_graphene_list=n_graphene.get_n(lamb_list)277    example_tmm.plot_R_T(lamb_list,d_vac=1000e-9,n_lists=(n_graphene_list,n_Au_list))278    example_tmm.plot_E_of_lamb(lamb_list=lamb_list,d_vac=900e-9,n_lists=(n_graphene_list,n_Au_list))279    example_tmm.make_lam_E()280    example_tmm.plot_E_of_d_vac()281    example_tmm.plot_spectrum_modification(lamb_list,n_lists=(n_graphene_list,n_Au_list))282    #example_tmm.plot_E(d=d_SiO2+d_Al)283    #example_tmm.plot_R_T(600e-9,900e-9)...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.