Package: anda
anda[toc]pipinstallandaThis is a Python package for collecting, manipulation and visualizing various ancient Mediterranean data. It focus on their temporal, textual and spatial aspects. It is structured into several gradually evolving submodules, namelygr,imda,concs, andtextnet.anda.grfromandaimportgrThis module is dedicated to preprocessing of ancient Greek textual data. It contains functions for lemmatization, posttagging and translation. It relies heavely on Morhesus Dictionary.LemmatizationA minimal usage is to lemmatize individual word. You can  either ask for only the first lemma (return_first_lemma()) or for all possibilities (return_all_unique_lemmata().  In most cases , the outcome is the same:gr.return_first_lemma("ἐπιστήμην")>'ἐπιστήμη'gr.return_all_unique_lemmata("ἐπιστήμην")>'ἐπιστήμη'Above these are functionslemmatize_string()andgr.get_lemmatized_sentences(). Both work with string of any length. The first returns a list of lemmata. The second returns a list of lemmatized sentences.string="Πρότασις μὲν οὖν ἐστὶ λόγος καταφατικὸς ἢ ἀποφατικὸς τινὸς κατά τινος. Οὗτος δὲ ἢ καθόλου ἢ ἐν μέρει ἢ ἀδιόριστος. Λέγω δὲ καθόλου μὲν τὸ παντὶ ἢ μηδενὶ ὑπάρχειν, ἐν μέρει δὲ τὸ τινὶ ἢ μὴ τινὶ ἢ μὴ παντὶ ὑπάρχειν, ἀδιόριστον δὲ τὸ ὑπάρχειν ἢ μὴ ὑπάρχειν ἄνευ τοῦ καθόλου, ἢ κατὰ μέρος, οἷον τὸ τῶν ἐναντίων εἶναι τὴν αὐτὴν ἐπιστήμην ἢ τὸ τὴν ἡδονὴν μὴ εἶναι ἀγαθόν."gr.lemmatize_string(string)>['πρότασις','λόγος','καταφατικός','ἀποφατικός','καθόλου','μέρος','ἀδιόριστος','λέγω','καθόλου','πᾶς','μηδείς','ὑπάρχω','μέρος','πᾶς','ὑπάρχω','ἀδιόριστον','ὑπάρχω','ὑπάρχω','ἄνευ','καθόλου','μέρος','οἷος','ἐναντίος','αὐτην','ἐπιστήμη','ἡδονην','ἀγαθός']gr.get_lemmatized_sentences(string)>[['πρότασις','λόγος','καταφατικός','ἀποφατικός'],['καθόλου','μέρος','ἀδιόριστος'],['λέγω','καθόλου','πᾶς','μηδείς','ὑπάρχω','μέρος','πᾶς','ὑπάρχω','ἀδιόριστον','ὑπάρχω','ὑπάρχω','ἄνευ','καθόλου','μέρος','οἷος','ἐναντίος','αὐτην','ἐπιστήμη','ἡδονην','ἀγαθός']]All lemmatization functions can be further parametrized by several argumentsall_lemmata=False:filter_by_postag=["n","a","v"]: returns only nouns ("n"), adjectives ("a") and verbs ("v")involve_unknown=True, ifFalse, it returns only words found in the dictionaryThus, you can run:lemmatized_sentences=gr.get_lemmatized_sentences(string,all_lemmata=False,filter_by_postag=["n","a","v"],involve_unknown=False)print(lemmatized_sentences)>[['λόγος'],['μέρος'],['πᾶς','μηδείς','ὑπάρχω','μέρος','πᾶς','ὑπάρχω','ὑπάρχω','ὑπάρχω','ἄνω/ἀνίημι','μέρος','οἷος','ἐναντίος','ἐπιστήμη','ἀγαθός']](1)get_lemmatized_sentences(string, all_lemmata=False, filter_by_postag=None, involve_unknown=False):  it receives a raw Greek text of any kind and extent as its input  Such input is  processed by a series of subsequent functions embedded within each other, which might be also used independently(1)get_sentences()splits the string into sentences by common sentence separators.(2)lemmatize_string(sentence)first callstokenize_string(), which makes a basic cleaning and stopwords filtering for the sentence, and returns a list of words. Subsequently, each word from the tokenized sentence is sent either toreturn_first_lemma()or toreturn_all_unique_lemmata(), on the basis of the value of the parameterall_lemmata=(set toFalseby default).(4)return_all_unique_lemmata()goes to themorpheus_dictvalues and returns all unique lemmata.(5) Parameterfilter_by_postag=(defaultNone) enables to sub-select  chosen word types from the tokens, on the basis of first character in the tag "p" . Thus, to choose only  nouns, adjectives, and verbs, you can setfilter_by_postag=["n", "a", "v"].PREFERENCE: If verb, noun, and adjective variants are available, only  then  noun and adjective form is returned. If both noun and adjective is available, only noun is returned.TranslationNext to the lemmatization, there is also a series of functions for translations, likereturn_all_unique_translations(word, filter_by_postag=None, involve_unknown=False), useful for any wordform, andlemma_translator(word), where we already have a lemma.gr.return_all_unique_translations("ὑπάρχειν",filter_by_postag=None,involve_unknown=False)>'to begin, make a beginning'gr.lemma_translator("λόγος")>'the word'Morphological analysisYou can also do a morphological analysis of a stringgr.morphological_analysis(string)[1:4]>[{'i':'564347','f':'μέν','b':'μεν','l':'μέν','e':'μεν','p':'g--------','d':'20753','s':'on the one hand, on the other hand','a':None},{'i':'642363','f':'οὖν','b':'ουν','l':'οὖν','e':'ουν','p':'g--------','d':'23870','s':'really, at all events','a':None},{'i':'264221','f':'ἐστί','b':'εστι','l':'εἰμί','e':'ειμι','p':'v3spia---','d':'9722','s':'I have','a':None}]imdaThis module will serve for importing various ancient Mediterranean resources. Most of them will be imported directly from open third-party online resources. However, some of them have been preprocessed as part of the SDAM project.The ideal is that it will work like this:imda.list_datasets()
>>> ['roman_provinces_117', 'EDH', 'roman_cities_hanson', 'orbis_network']And:rp=imda.import_dataset("roman_provinces_117","gdf")type(rp)>>>geopandas.geodataframeconcsThis module contains functions for workingtextnetThis module contains functions for generating, analyzing and visualizing word co-occurrence networks. It has been designed especially for working with textual data in ancient Greek.Versions history0.0.8 - bugs removed0.0.7 -filter_by_postagwith preference of nouns and adjectives by default0.0.6 - greek dictionaries included within the package0.0.5 - experimenting with data inclusion0.0.4 - docs