def test_remove_identical_seqs():
data_obj = pickle.load(open("tests/data/precooked/tiny_dataobj.p", 'rb'))
data_obj.workdir = absworkdir
ids = IdDicts(conf, workdir=data_obj.workdir)
ids.acc_ncbi_dict = pickle.load(
open("tests/data/precooked/tiny_acc_map.p", "rb"))
# print("start")
scraper = PhyscraperScrape(data_obj, ids)
scraper.ids.otu_rank = {}
scraper.config.gifilename = False
scraper._blasted = 1
blast_dir = "tests/data/precooked/fixed/tte_blast_files"
#scraper.gi_list_mrca = pickle.load(open("tests/data/precooked/gi_list_mrca.p", 'rb'))
scraper.read_blast_wrapper(blast_dir=blast_dir)
#print scraper.ncbi_mrca
assert (len(scraper.new_seqs) == 0)
assert (len(scraper.data.aln) == 5)
assert len(scraper.new_seqs_otu_id) == 17
#Now that we are pulling the full remote sequences, we don'thave any identical seuqnces in the test.
#TODO find an example where we do get identical sequences and need to discard them
# seqset = set()
# for otu in scraper.new_seqs_otu_id:
# seq = scraper.new_seqs_otu_id[otu]
# if seq in seqset:
# print otu
# seqset.add(seq)
#check that every new sequence is unique in the new seqs set, and is not a substring of another sequence.
## for otu in scraper.new_seqs_otu_id:
# qseq = scraper.new_seqs_otu_id[otu]
# count = 0
# for seq in seqset:
# if qseq in seq:
# count += 1
# assert count == 1
## for taxon in scraper.data.tre.taxon_namespace:
# assert(taxon.label in scraper.data.otu_dict)
# status = scraper.data.otu_dict[taxon.label].get(u'^physcraper:status')
# assert(status in ('original', 'query'))
aln_path1 = scraper.data.write_aln()
aln_path = scraper.write_all_unaligned('test.fas')
scraper.align_query_seqs()
assert len(scraper.data.aln) == 22
