def test():
# get to test status
concat = Concat(workdir_comb, email)
for item in genelist.keys():
concat.load_single_genes(genelist[item]['workdir'],
genelist[item]["pickle"], item)
concat.combine()
concat.sp_seq_counter()
sp_to_keep = concat.sp_to_keep()
# print(sp_to_keep.keys())
#
# print("tests sp_to_keep")
counter = 0
sp_keep = []
for sp in concat.sp_counter:
for gene in concat.sp_counter[sp]:
if concat.sp_counter[sp][gene] == 0:
sp_keep.append(sp)
# print(sp_keep)
# print(sp_to_keep.keys())
# print(len(sp_keep))
#
print(len(sp_to_keep.keys()))
try:
assert set(sp_to_keep.keys()) == set(sp_keep)
print("tests passed")
except:
print("test fails")
def test():
concat = Concat(workdir_comb, email)
for item in genelist.keys():
concat.load_single_genes(genelist[item]['workdir'], genelist[item]["pickle"], item)
concat.combine()
spnl = []
for genename in concat.single_runs:
for otu in concat.single_runs[genename].data.otu_dict.keys():
data = concat.single_runs[genename].data.otu_dict[otu]
if '^ot:ottTaxonName' in data:
spn = concat.get_taxon_info('^ot:ottTaxonName', data)
elif '^user:TaxonName' in data:
spn = concat.get_taxon_info('^user:TaxonName', data)
spnl.append(spn)
len_single = len(set(spnl))
# print(set(spnl))
# print(concat.sp_acc_comb)
len_concat_id_dict = len(concat.sp_acc_comb)
assert len_single == len_concat_id_dict
def test():
concat = Concat(workdir_comb, email)
for item in genelist.keys():
concat.load_single_genes(genelist[item]["workdir"],
genelist[item]["pickle"], item)
concat.combine()
concat.sp_seq_counter()
# print("tests if nothing gets lost from loading single runs to make sp_counter")
counter = 0
for sp in concat.sp_counter:
for gene in concat.sp_counter[sp]:
counter += concat.sp_counter[sp][gene]
# print(counter)
single_run_items = 0
for item in concat.single_runs:
single_run_items += (len(concat.single_runs[item].aln.taxon_namespace))
assert counter == single_run_items
def concat(genelistdict,
workdir_comb,
email,
num_threads=None,
percentage=0.37,
user_concat_fn=None,
backbone=False):
"""This is to concatenate different physcraper runs into a single alignment and tree.
genelistdict is a dict with gene names as key and the corresponding workdir
"""
license_print()
if not os.path.exists(path="{}/concat_checkpoint.p".format(workdir_comb)):
if not os.path.exists(
path="{}/load_single_data.p".format(workdir_comb)):
# save_copy_code(workdir_comb)
conc = Concat(workdir_comb, email)
conc.concatfile = user_concat_fn
for item in genelistdict.keys():
conc.load_single_genes(genelistdict[item]["workdir"],
genelistdict[item]["pickle"], item)
conc.combine()
else:
sys.stdout.write("load single data dump file\n")
conc = pickle.load(
open("{}/load_single_data.p".format(workdir_comb), "rb"))
# conc.dump()
conc.sp_seq_counter()
conc.get_largest_tre()
conc.make_sp_gene_dict()
conc.make_alns_dict()
conc.concatenate_alns()
conc.get_short_seq_from_concat(percentage)
conc.remove_short_seq()
conc.dump()
else:
sys.stdout.write("load concat_checkpoint dump file\n")
conc = pickle.load(
open("{}/concat_checkpoint.p".format(workdir_comb), "rb"))
conc.backbone = backbone
conc.make_concat_table()
conc.write_partition()
conc.write_otu_info()
conc.place_new_seqs(num_threads)
if backbone is False:
conc.calculate_bootstrap(num_threads)
conc.write_labelled('RAxML_bestTree.autoMRE_fa')
else:
conc.est_full_tree(num_threads)
conc.write_labelled('RAxML_bestTree.backbone_concat')
return conc
def test():
workdir_its = "runs/tiny_comb_its"
workdir_ets = "runs/tiny_comb_ets"
email = "*****@*****.**"
pickle_fn = "scrape_checkpoint.p"
workdir_comb = "tests/output/impl_concat"
genelist = {
"its": {
"workdir": workdir_its,
"pickle": pickle_fn
},
"ets": {
"workdir": workdir_ets,
"pickle": pickle_fn
}
}
# get to test status
sys.stdout.write("\ntests Concat func select_rnd_seq\n")
concat = Concat(workdir_comb, email)
for item in genelist.keys():
concat.load_single_genes(genelist[item]['workdir'],
genelist[item]["pickle"], item)
concat.combine()
concat.sp_seq_counter()
sp_to_keep = concat.sp_to_keep()
concat.get_largest_tre()
# print("test: select rnd seq")
count = 2
concat.tmp_dict = deepcopy(concat.sp_acc_comb)
# print("while")
# part of make_sp_gene_dict
len_before = len(concat.comb_seq)
while len(concat.tmp_dict.keys()) >= 1:
del_gi = {}
for spn in concat.tmp_dict.keys():
# print(spn)
sp_to_keep_list = sp_to_keep.keys()
# debug(sp_to_keep_list)
if spn.replace(" ", "_") in sp_to_keep_list:
tmp_gene = deepcopy(concat.genes_present)
for gene in concat.tmp_dict[spn]:
tmp_gene.remove(gene)
# print("select_rnd_seq")
# print(spn, gene,del_gi, count)
del_gi = concat.select_rnd_seq(spn, gene, del_gi)
# print("now it should break")
break
break
break
break
len_after = len(concat.comb_seq[gene])
#
assert len_before + 1 == len_after
def test_concat_combine():
workdir_its = "tests/data/precooked/concat_pre"
workdir_ets = "tests/data/precooked/concat_pre"
email = "*****@*****.**"
pickle_fn = "final_ATT_checkpoint.p"
email = "*****@*****.**"
percentage = 0.4
num_threads = 2
workdir_comb = "./tests/output/concat_test"
genelistdict = {"its": {"workdir": workdir_its, "pickle": "its_{}".format(pickle_fn)},
"ets": {"workdir": workdir_ets, "pickle": "ets_{}".format(pickle_fn)}}
conc = Concat(workdir_comb, email)
for item in genelistdict.keys():
conc.load_single_genes(genelistdict[item]["workdir"], genelistdict[item]["pickle"], item)
conc.combine()
assert os.path.exists("{}/load_single_data.p".format(workdir_comb))
conc.sp_seq_counter()
conc.get_largest_tre()
assert conc.tre_start_gene == "ets"
conc.make_sp_gene_dict()
conc.make_alns_dict()
for gene in conc.aln_all:
conc.li((conc.aln_all[gene].taxon_namespace))
assert len(conc.aln_all[gene]) == 20
conc.concatenate_alns()
conc.get_short_seq_from_concat(percentage)
conc.remove_short_seq()
conc.dump()
assert len(conc.concatenated_aln) == 5
def test_run_raxml_concat():
time.sleep(10) # needs time so that file of order1 is written before
workdir_its = "tests/data/precooked/concat_pre"
workdir_ets = "tests/data/precooked/concat_pre"
email = "*****@*****.**"
pickle_fn = "final_ATT_checkpoint.p"
email = "*****@*****.**"
percentage = 0.4
num_threads = 2
workdir_comb = "./tests/output/concat_test"
genelistdict = {"its": {"workdir": workdir_its, "pickle": "its_{}".format(pickle_fn)},
"ets": {"workdir": workdir_ets, "pickle": "ets_{}".format(pickle_fn)}}
conc = Concat(workdir_comb, email)
for item in genelistdict.keys():
conc.load_single_genes(genelistdict[item]["workdir"], genelistdict[item]["pickle"], item)
conc.combine()
assert os.path.exists("{}/load_single_data.p".format(workdir_comb))
conc.sp_seq_counter()
conc.get_largest_tre()
assert conc.tre_start_gene == "ets"
conc.make_sp_gene_dict()
conc.make_alns_dict()
conc.concatenate_alns()
conc.get_short_seq_from_concat(percentage)
conc.remove_short_seq()
conc.backbone = True
conc.make_concat_table()
conc.write_partition()
conc.write_otu_info()
if conc.backbone is False:
conc.calculate_bootstrap(num_threads)
conc.write_labelled('RAxML_bestTree.autoMRE_fa')
else:
conc.est_full_tree(num_threads)
conc.write_labelled('RAxML_bestTree.backbone_concat')
conc.backbone = False
conc.place_new_seqs(num_threads)