-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathsearchindex.js
More file actions
1 lines (1 loc) · 14.4 KB
/
Copy pathsearchindex.js
File metadata and controls
1 lines (1 loc) · 14.4 KB
1
Search.setIndex({docnames:["2D and 3D visualisation of Sunspotter dataset","ATLAS variable star Classification","Astronomical Image Reconstruction using Autoencoder","HTRU1 Batched Dataset Classification","OGLE variable star classification","README","XRay Binary Classification","index","mirapy","mirapy.autoencoder","mirapy.classifiers","mirapy.fitting","mirapy.utils","mirapy.visualization","tutorials"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.cpp":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,sphinx:56},filenames:["2D and 3D visualisation of Sunspotter dataset.rst","ATLAS variable star Classification.rst","Astronomical Image Reconstruction using Autoencoder.rst","HTRU1 Batched Dataset Classification.rst","OGLE variable star classification.rst","README.rst","XRay Binary Classification.rst","index.rst","mirapy.rst","mirapy.autoencoder.rst","mirapy.classifiers.rst","mirapy.fitting.rst","mirapy.utils.rst","mirapy.visualization.rst","tutorials.rst"],objects:{"mirapy.autoencoder":{models:[9,0,0,"-"]},"mirapy.autoencoder.models":{Autoencoder:[9,1,1,""],DeNoisingAutoencoder:[9,1,1,""]},"mirapy.autoencoder.models.Autoencoder":{compile:[9,2,1,""],load_model:[9,2,1,""],plot_history:[9,2,1,""],predict:[9,2,1,""],save_model:[9,2,1,""],summary:[9,2,1,""],train:[9,2,1,""]},"mirapy.autoencoder.models.DeNoisingAutoencoder":{compile:[9,2,1,""],predict:[9,2,1,""],show_image_pairs:[9,2,1,""],train:[9,2,1,""]},"mirapy.classifiers":{models:[10,0,0,"-"]},"mirapy.classifiers.models":{AtlasVarStarClassifier:[10,1,1,""],Classifier:[10,1,1,""],HTRU1Classifier:[10,1,1,""],OGLEClassifier:[10,1,1,""],XRayBinaryClassifier:[10,1,1,""]},"mirapy.classifiers.models.AtlasVarStarClassifier":{compile:[10,2,1,""],predict:[10,2,1,""],train:[10,2,1,""]},"mirapy.classifiers.models.Classifier":{compile:[10,2,1,""],load_model:[10,2,1,""],plot_history:[10,2,1,""],predict:[10,2,1,""],reset:[10,2,1,""],save_model:[10,2,1,""],train:[10,2,1,""]},"mirapy.classifiers.models.HTRU1Classifier":{compile:[10,2,1,""],predict:[10,2,1,""],train:[10,2,1,""]},"mirapy.classifiers.models.OGLEClassifier":{compile:[10,2,1,""],predict:[10,2,1,""],train:[10,2,1,""]},"mirapy.classifiers.models.XRayBinaryClassifier":{compile:[10,2,1,""],predict:[10,2,1,""],train:[10,2,1,""]},"mirapy.fitting":{losses:[11,0,0,"-"],models:[11,0,0,"-"],optimizers:[11,0,0,"-"]},"mirapy.fitting.losses":{mean_squared_error:[11,3,1,""],negative_log_likelihood:[11,3,1,""]},"mirapy.fitting.models":{Gaussian1D:[11,1,1,""],Model1D:[11,1,1,""]},"mirapy.fitting.models.Gaussian1D":{evaluate:[11,2,1,""],get_params_as_array:[11,2,1,""],set_params_from_array:[11,2,1,""]},"mirapy.fitting.models.Model1D":{evaluate:[11,2,1,""],get_params_as_array:[11,2,1,""],set_params_from_array:[11,2,1,""]},"mirapy.fitting.optimizers":{ParameterEstimation:[11,1,1,""]},"mirapy.fitting.optimizers.ParameterEstimation":{fit:[11,2,1,""],get_model:[11,2,1,""],regression_function:[11,2,1,""]},"mirapy.utils":{utils:[12,0,0,"-"]},"mirapy.utils.utils":{accuracy_per_class:[12,3,1,""],append_one_to_shape:[12,3,1,""],get_psf_airy:[12,3,1,""],image_augmentation:[12,3,1,""],psnr:[12,3,1,""],to_numeric:[12,3,1,""],unpickle:[12,3,1,""]},"mirapy.visualization":{visualize:[13,0,0,"-"]},"mirapy.visualization.visualize":{visualize_2d:[13,3,1,""],visualize_3d:[13,3,1,""]},mirapy:{autoencoder:[9,0,0,"-"],classifiers:[10,0,0,"-"],fitting:[11,0,0,"-"],utils:[12,0,0,"-"],visualization:[13,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"],"3":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method","3":"py:function"},terms:{"050000e":0,"060000e":0,"0x1179c7748":0,"0x16b0d728cf8":6,"0x17a952b1400":4,"0x1c568a10898":1,"10s":1,"134s":4,"135s":4,"136s":4,"137s":4,"139s":4,"140s":4,"16s":2,"178s":4,"17s":[2,3],"19s":3,"20000424_1251_mdib_1_8955":0,"20001004_1251_mdib_1_9180":0,"20010824_1251_mdib_1_9593":0,"20030310_1247_mdib_1_0309":0,"20030516_1246_mdib_1_0360":0,"222s":4,"256x256":2,"270000e":0,"280000e":0,"290000e":0,"296500e":0,"30s":2,"32x32px":3,"331u":3,"333u":3,"334u":3,"335u":3,"336u":3,"372u":3,"45it":2,"530be1223ae74079c30007d9":0,"530be1303ae74079c3001315":0,"530be1493ae74079c3002735":0,"530be1763ae74079c3004a0d":0,"530be17a3ae74079c3004cf1":0,"580000e":0,"733569e":0,"770000e":0,"810000e":0,"910000e":0,"928112e":0,"940000e":0,"95it":2,"boolean":[9,10],"class":[0,1,2,4,6,9,10,11,12,14],"default":2,"final":5,"float":[11,12],"function":[2,3,9,10,11,12,13],"import":[0,1,2,3,4,6],"new":[5,7,11],"return":[2,10,11,12],"true":[0,2,3,6,9,10,11,12],"try":3,"while":3,One:3,The:[3,5,7],There:[3,5,7],Using:[1,2,6,14],_________________________________________________________________:[3,4],_subplot:0,abl:[5,7],about:7,abov:3,acc:[1,4,6],accordingli:3,accuraci:[1,3,4,6,12],accuracy_per_class:[3,12],accuracy_scor:[1,3,6],achiev:3,activ:[3,9,10],activation_1:3,activation_2:3,activation_3:3,activation_4:3,activation_5:3,activation_6:3,adam:[1,2,3,4,6,10],add:[5,7],adding:2,aim:[5,7],akhil:5,all:10,all_clear_dataset:0,alpha:0,also:[2,3,5],amplitud:11,amsgrad:2,anaconda3:2,analysi:[5,7,13],angl:0,anna:3,api:7,append:2,append_one_to_shap:[2,12],appli:[2,5,7],area:0,areafrac:0,areathesh:0,arnav:5,arrai:[2,3,9,10,11,12,13],arxiv:3,ascaif:3,assign:3,astronom:[3,5,7,14],astronomi:7,astyp:3,asz00001g3:0,asz00001pz:0,asz00006u:0,asz00008tj:0,asz00009la:0,atla:[1,5,7],atlasvarstarclassifi:[1,10],augment:[2,12],autoencod:[5,7,8,14],autograd:[5,7],averag:3,avg:[1,3,6],axes:0,axessubplot:0,axx:0,backend:[1,2,3,6],bail:3,bar:12,barr:3,base:[9,10,11],basic:[5,7],batch:14,batch_siz:[1,3,4,6,9,10],becom:3,been:3,befor:9,begin:3,belong:3,below:3,beta:0,beta_1:[2,3],beta_2:2,better:[5,7],bhavsar:5,binari:[5,7,14],bipolesep:0,bool:12,build:[2,5],built:[5,7],bxo:0,c1flr24hr:0,calcul:12,call:2,callback:[1,4,6,11],can:[2,3,5,7,14],candid:3,cantain:3,catalog:[2,5,7],categor:[3,6],categori:3,categorical_crossentropi:[3,4,10],cep:4,channel:[2,3],choos:0,cifar:3,citat:14,class_weight:[3,10],classif:[0,5,7,14],classifi:[1,3,4,6,8],classification_report:[1,3,6],clone:5,cnn:3,code:[0,5],color:2,com:5,come:3,command:3,commun:5,compar:14,compil:[1,2,3,4,6,9,10],compon:[5,7,13],compress:3,comput:[2,12],config:2,configur:[9,10],confusion_matrix:3,connect:3,consist:3,contain:3,content:[7,8],continu:[5,7],contribut:7,conv2d:3,conv2d_1:3,conv2d_2:3,conv2d_3:3,conv2d_4:3,convert:[1,3,12],convolut:[2,3,5,7],copi:11,copyright:5,count:0,cpu:[5,7],cso:0,csv:[0,1],csv_file:1,curv:[5,7],custom:[9,10],d_rl:2,d_tv:2,d_w:2,dask:2,data:[0,1,2,3,4,5,6,7,9,10,11,12,13],data_dir:[2,3,6],databas:0,datagen:2,dataset:[1,2,5,7,14],date:14,decai:2,decod:9,decoded_imag:9,decoded_img:2,decoded_rl:2,decoded_tv:2,decoded_w:2,deconvolut:2,decreas:3,deep:7,def:2,demonstr:2,denois:2,denoise_tv_chambol:2,denoisingautoencod:[2,9],dens:[3,4],dense_1:3,dense_25:4,dense_26:4,dense_27:4,dense_2:3,deprec:2,describ:0,detail:[0,2,3],develop:[5,7],df1:0,dictionari:10,differ:[5,7],directori:10,disabl:12,displai:[0,9],distribut:2,done:[2,3],dowload:3,download:5,dropout:[3,4,10],dropout_1:3,dropout_2:3,dropout_3:3,dropout_9:4,dsct:4,dso:0,dure:[3,9,10],dynam:3,each:[3,12],easi:[5,7],empti:4,enabl:12,encod:1,engin:[5,7],epoch:[1,2,3,4,6,9,10],eps:2,epsilon:2,error:[2,11],estim:11,evalu:[3,11],exampl:[0,2],experi:[5,7],extract:[5,7],fals:[2,3,12],far:5,featur:[0,1,5,7,13],file:[9,10,12],filename_i:0,filename_x:0,find:[5,7,14],first:[3,5,7,12],firstli:[2,3],fit:[0,1,5,7,8],fit_transform:[0,1],fitsfil:14,five:3,flatten:3,flatten_1:3,float32:3,flux:0,fluxfrac:0,flynn:3,follow:[0,2,3,5,7,14],foremost:3,form:[9,12],four:2,fraction:3,free:3,from:[0,1,2,3,4,5,6,7,9,10,11,12],full:2,fulli:3,futur:[5,7],galaxi:2,gaussian1d:11,gaussian:11,gener:12,get_model:11,get_params_as_arrai:11,get_psf_airi:[2,12],get_xaxi:3,get_yaxi:3,git:5,github:5,given:[9,10,11],gpu:[5,7],gradient:[9,10],graph:[9,10],grayscal:2,grid:9,grow:[5,7],grs1905:[5,7],guidanc:5,h5py:[9,10],hale:0,handl:14,hang:5,has:3,have:[2,5],hcpos_i:0,hcpos_x:0,head:0,height_shift_rang:2,here:[2,3],histori:[1,4,6],home:2,horizontal_flip:2,how:[0,2],howev:3,hspace:3,htru1:[5,7,14],htru1classifi:[3,10],http:[2,3,5],hunt:2,id_filenam:0,id_i:0,id_x:0,idx:3,ignor:1,imag:[3,5,7,9,12,14],image_augment:[2,12],image_data_gener:12,image_id:0,imagedatagener:2,imbalanc:14,img1:12,img2:12,img_dim:[2,9],imit:0,implement:[3,5,7],improv:3,imshow:3,increas:2,index:7,indian:5,inequ:4,inlin:[0,3],inner:0,inplac:0,input:[2,9,10,11,12],input_dim:[3,10],input_s:[1,4,10],inspir:3,instal:7,instanc:[9,10,11],institut:5,integ:[1,9,10],integer_encod:1,interest:3,invers:3,its:[5,7],join:[1,14],jpg:0,jupyt:14,k_valu:0,kean:3,kera:[1,2,3,4,5,6,7,10,12],label:3,label_encod:1,labelencod:1,layer:[3,4],learn:[3,7],left_on:0,length:4,lib:2,licens:7,like:[3,5,7],likelihood:11,link:3,linspac:2,list:1,load:[2,3,9,10,12],load_atlas_star_data:1,load_dataset:[1,2,3,4,6],load_htru1_data:3,load_messier_catalog_imag:2,load_model:[9,10],load_ogle_dataset:4,load_xray_binary_data:6,loader:[2,3],log:11,look:3,lookup_properti:0,lookup_timesfit:0,loss:[1,2,3,4,6,8,9,10],loss_funct:11,love:5,lpv:4,lstm:4,lstm_9:4,luci:2,m1flr12hr:0,m5flr12hr:0,machin:[3,5,7],macro:[1,3,6],major:5,make:[5,7],man:3,mandi:5,matplotlib:[0,3,9],max:[0,3],max_column:0,max_imag:9,max_pooling2d_1:3,max_pooling2d_2:3,maxpooling2:3,mean:[0,2,11],mean_squared_error:[1,2,6,10,11],merg:0,meshgrid:2,messier:2,messier_catalog_galaxi:2,metric:[1,3,4,6],micro:[1,3,6],min:0,min_max_scal:0,minim:4,minmaxscal:0,minor:3,mirapi:[1,2,3,4,6,14],mit:5,model1d:11,model:[1,2,3,4,5,6,7,8],model_nam:[9,10],model_select:[1,2,6],modul:[2,3,7,8],monthli:3,more:[5,7],morello:3,msg:2,mtp:[1,4,6],multichannel:2,n_iter_max:2,n_nar:0,name:[9,10],need:[0,3,5,7],neg:11,negative_log_likelihood:11,network:[2,3,5,7],neural:[3,5,7],nimg:2,noaa:0,nois:[2,12],noisi:2,non:[3,4],non_dub:1,none:[0,2,3,4,9,10,11],nonpulsar:3,normal:[0,3],notebook:14,notic:3,now:[2,5,7],np_util:4,npsf:2,num_class:[1,3,4,10],num_of_augument:12,num_plot:3,number:[3,9,10,12],numer:[3,6,12],numpi:[0,2,3,9,10,12],obersv:3,object:[9,10,11,12],obs_dat:0,observ:3,often:3,ogl:4,ogleclassifi:[4,10],onehotencod:1,open:5,optim:[1,2,3,4,6,8,9,10],option:0,order:3,org:[2,5],origin:[2,9],original_imag:9,other:3,our:[2,3,5,7,14],out:5,outperform:[2,3],output:[2,3,4,9,10,11],overal:3,oversampl:3,packag:[2,7,8],pad:[3,9,10],page:7,pair:9,panda:[0,1],param:[3,4,11],paramet:[2,9,10,11,12,13],parameterestim:11,part:[5,7],path:[1,4,9,10],pca:[5,7,13],peak:[2,12],per:[3,9,10,12],perfect:5,perform:[2,5,7],pickl:12,pip:5,plai:14,pleas:2,plot:[0,3,9,10],plot_histori:[9,10],plt:[0,3],point:[3,12],poisson:2,pool:3,pre:2,precis:[1,3,6],predict:[0,2,3,9,10,11,12],prepar:2,prepare_messier_catalog_imag:2,preprocess:[0,1,2],princip:[5,7,13],print:[1,3,4,6],probabl:12,problem:[3,5,7],process:2,prof:3,progress:12,project:[5,7],propos:[2,3],propot:3,provid:3,psf:2,psnr:[2,12],pulsar:[3,5,7],pxpos_i:0,pxpos_x:0,pyplot:[0,3],python3:2,python:7,pytorch:3,pyyaml:2,rai:[5,7],randint:3,random:3,random_st:2,rang:3,rank:14,ratio:[2,12],read:[0,2,3,12],read_csv:0,recal:[1,3,6],reconstruct:[5,7,14],recurr:[5,7],recurs:5,reduct:[5,7],regress:11,regression_funct:11,regular:3,releas:3,relu:[1,2,3,4,6,9,10],remov:2,repositori:[0,5,7,14],repres:2,requir:[3,5],research:[3,5,7],reset:10,reset_weight:10,reshap:[0,2,12],restor:2,result:[11,14],retrain:3,richardson:2,richardson_luci:2,right:[5,7],right_on:0,rmsprop:3,rnn:[5,7],rotation_rang:2,round:[1,3,6],row:9,royal:3,rrlyr:4,run:[3,5,7],same:[2,3,9,10],sampl:[2,3,4,9,10],save:[9,10],save_model:[9,10],scaif:3,scipi:2,score:[0,1,3,6],seamlessli:[5,7],search:7,second:12,see:[2,5,7],seed:3,select:[1,3,5,7],sep:0,set:[0,2,3,5,7,9,10,11],set_index:0,set_params_from_arrai:11,set_vis:3,setup:[3,5],shape:[1,3,4],sharma:5,show:[2,3],show_image_pair:[2,9],shuffl:9,sigma:2,signal:[2,12],similar:3,singhal:5,site:2,size:[2,3],skimag:2,sklearn:[0,1,2,3,6],slack:[5,7],slightli:3,small:3,societi:3,solut:3,solv:[5,7],some:[5,7],soon:[5,7],sourc:5,special:2,spinn:3,spread:12,sqrt:2,squar:[2,11],sszn:0,standard:2,standardscal:1,star:[5,7],state:[5,7],std:0,std_dev:0,stddev:11,step:3,straightforward:3,straten:3,string:[1,9,10],student:[5,7],submodul:8,subpackag:[],subplot:3,subplots_adjust:3,suggest:[5,7],sum:2,summari:[3,4,9],sunspott:14,support:[1,3,6],survei:3,swapnil:5,swapsha96:2,t2cep:4,tackl:[3,5,7],take:2,tar:3,target:[0,9,10,13],technic:5,techniqu:[2,5,7],technolog:5,tell:[5,7],tensorflow:[1,2,3,6],term:5,test:[1,2,3,6],test_siz:2,them:[5,7],therefor:3,thi:[3,5,7],time:[2,3],to_categor:[3,4],to_datetim:0,to_numer:12,total:[2,3,4],tqdm:12,train:[1,2,3,4,6,9,10],train_test_split:[1,2,6],trainabl:[3,4],tune:2,tutori:[5,7],txt:5,type:[3,4],under:5,unpickl:12,unsaf:2,updat:[9,10],use:[1,2,3],used:[2,5,7,11],using:[1,3,5,7,9,11,13,14],util:[2,3,4,8],val_acc:4,val_loss:[2,3,4],valid:[2,3,4,9,10],validation_data:[2,3,9,10],valu:[0,3,6,9,10,11,12,13],van:3,variabl:[5,7],variat:2,variou:[2,3],verbos:[1,2,4,9,10],visual:[5,7,8,14],visualize_2d:[0,13],visualize_3d:[0,13],vol:3,w1n1:3,w2n2:3,wai:[3,5,7],walk:1,weight:[1,6,10,14],what:[3,5,7],which:3,width_shift_rang:2,wiener:2,without:2,work:3,would:[5,7],write:3,wspace:3,www:3,x_scale:0,x_test:[1,2,3,4,6],x_test_noisi:2,x_train:[1,2,3,4,6,10],x_train_noisi:2,xpsf:2,xrai:14,xraybinaryclassifi:[6,10],xvzf:3,y_pred:[3,11,12],y_predict:[1,6],y_test:[1,3,4,6],y_train:[1,3,4,6,10],y_true:[11,12],yaml:2,yamlloadwarn:2,year:5,you:[2,3,5,7,14],your:[5,7],zoom_rang:2,zooniverse_id:0,zoorank:0,zurich:0},titles:["Playing with Sunspotter Dataset","<no title>","Astronomical Image Reconstruction using Autoencoder","HTRU1 Batched Dataset Classification","<no title>","MiraPy: Python Package for Deep Learning in Astronomy","XRay Binary Classification","Welcome to MiraPy\u2019s documentation!","MiraPy API","mirapy.autoencoder package","mirapy.classifiers package","mirapy.fitting package","mirapy.utils package","mirapy.visualization package","Tutorials"],titleterms:{"class":3,Using:3,about:5,api:8,applic:[5,7],astronom:2,astronomi:5,autoencod:[2,9],batch:3,binari:6,citat:3,classif:[3,6],classifi:10,compar:2,content:[9,10,11,12,13],contribut:5,dataset:[0,3],date:0,deep:5,document:7,fit:11,fitsfil:0,handl:3,htru1:3,imag:[0,2],imbalanc:3,indic:7,instal:5,join:0,learn:5,licens:5,loss:11,mirapi:[0,5,7,8,9,10,11,12,13],model:[9,10,11],modul:[9,10,11,12,13],optim:11,packag:[5,9,10,11,12,13],plai:0,python:5,rank:0,reconstruct:2,result:2,submodul:[9,10,11,12,13],subpackag:8,sunspott:0,tabl:7,tutori:14,using:[0,2],util:12,visual:[0,13],weight:3,welcom:7,xrai:6}})