I am using http://elasticsearch-dsl.readthedocs.io 0.0.10 and ES 1.7.3.
I have faced some strange behavior during search: some words that I pass to "should" query breaks search, then search cannot find that words (I see that in console), but also a lot of other words too.
In code below, "should" query consist of 1000 clauses. My guess was that this word is not in vocabulary (I use Russian and English morphology config) - but no, with other unseen and special words search is good.
So, when I remove these "problem" words search is working again.
This is super strange - I tested "problem" words with https://django-haystack.readthedocs.io/en/v2.5.0/index.html and ES can find them....
for i in eat_search_raw_list_1024:
q = Q('bool',
#must=[Q('match', text='BBQ')],
should=[(Q("match", text="\'bad service\'~3") | Q("match", text="\'bad eat\'~3") .........1000 more................],
minimum_should_match=1,
_name=name_query
)
s = Search(using=client, index="haystack").query(q).query(~Q("match", text=minus_words))
s = s.highlight('text', fragment_size=50)
response = s.execute()
Related
I'm trying to use Django full-text search but I'm having a problem:
I've followed this documentation, and it works quite well. But my problem is that I don't want the postgress to consider the order or permutation of the words I search.
I mean I want the result of searching "good boy" and "boy good" to be the same.
and also when I search "good boy" I want to see the "good bad boy" in the results.
But none of these happen and I can't query "good bad boy" with typing "boy good" or even "good boy" (Because of the "bad" missing).
I've tried to split search_text by space and then & the search queries like this in order to remove the order of words but it didn't work.
I changed this code:
search_query = SearchQuery(
search_text
)
search_rank = SearchRank(search_vectors, search_query)
to this:
s = SearchQuery(search_text.split(' ')[0])
for x in search_text.split(' ')[1:]:
s = s & SearchQuery(x)
search_query = s
search_rank = SearchRank(search_vectors, search_query)
You can achieve this quite easily in PostgreSQL.
I suggest reading carefully the documentation on Basic Text Matching.
What you need is to use <->, (FOLLOWED BY) tsquery operator.
If you use an integer instead of - you can express the desired proximity :
<N>, where N is an integer standing for the difference between the positions of the matching lexemes.
So you should find a way to make Python to execute this PostgreSQL function:
to_tsquery('good <1> boy | boy <1> good' );.
Maybe just calling SearchQuery with the string 'good <1> boy | boy <1> good' just works, but you should refer to the tutorial documentation to find how to use <-> with the method SearchQuery.
Edited after comment.
Looking at Django source code you can see that the constructor for SearchQuery class pass a default parameter search_type='plain'.
You can pass a different parameter to implement a different kind of search.
In the Django project documentation, you can find one example for each accepted string value for the named parameter search_type: 'plain', 'phrase', 'raw', 'websearch'.
If you pass search_type=raw you can provide a formatted search query with terms and operators, but I'm not sure if Django supports the <Ineger> operator as I said before you should try it.
Have you tried a search with search_type='raw', and a value of "'good <1> boy | boy <1> good'"?
If the FOLLOWED BY operator (<->) is not supported the close you can get to what you wanted is calling SearchQuery with search_type='phrase'.
This will find both good boy and boy good but the exact behaviour depends on the definition of the stop words used by the Dictionary set for PostgreSQL.
Getting stuck on how to read and pretty up these values from a multiline cell via arrayformula.
Im using regex as preceding line can vary.
just formulas please, no custom code
The first column looks like a set of these:
```
[config]
name = the_name
texture = blah.dds
cost = 1000
[effect0]
value = 1000
type = ATTR_A
[effect1]
value = 8
type = ATTR_B
[feature0]
name = feature_blah
[components]
0 = comp_one,1
[resources]
res_one = 1
res_five = 1
res_four = 1
<br/>
Where to be useful elsewhere, at minimum it needs each [tag] set ([effect\d], [feature\d], ect) to be in one column each, for example the 'effects' column would look like:
ATTR_A:1000,ATTR_B:8
and so on.
Desired output can also be seen in the included spreadsheet
<br/>
<b>Here is the example spreadsheet:</b>
https://docs.google.com/spreadsheets/d/1arMaaT56S_STTvRr2OxCINTyF-VvZ95Pm3mljju8Cxw/edit?usp=sharing
**Current REGEXREPLACE**
Kinda works, finds each 'type' and 'value' great, just cant figure out how to extract just that from the rest, tried capture (and non-capturing) groups before and after but didnt work
=ARRAYFORMULA(REGEXREPLACE($A3:$A,"[\n.][effect\d][\n.](.)\n(.)","1:$1 2:$2"))
**Current SUBSTITUTE + REGEXEXTRACT + REGEXREPLACE**
A different approach entirely, also kinda works, longer form though and left with having to parse the values out of that string, where got stuck again. Idea was to use this to simplify, then regexreplace like above. Getting stuck removing content around the final matches though, and if can do that then above approach is fine too.
// First ran a substitute
=ARRAYFORMULA(SUBSTITUTE(SUBSTITUTE($A3:$A,char(10),";"),";;",char(10)))
// Then variation of this (gave up on single line 'effect/d' so broke it up to try and get it working)
=ARRAYFORMULA(IF(A3:A<>"",IFERROR(REGEXEXTRACT(A3:A,"(?m)^(?:[effect0]);(.)$")&";;")&""&IFERROR(REGEXEXTRACT(A3:A,"(?m)^(?:[effect1]);(.)$")&";;")&""&IFERROR(REGEXEXTRACT(A3:A,"(?m)^(?:[effect2]);(.)$")&";;"),""))
// Then use regexreplace like above
=ARRAYFORMULA(REGEXREPLACE($B3:$B,"value = (.);type = (.);;","1:$1 2:$2"))
**--EDIT--**
Also, as my updated 'Desired Output' sheet shows (see timestamped comment below), bonus kudos if you can also extract just the values of matching 'type's to those extra columns (see spreadsheet).
All good if you cant though, just realized would need that too for lookups.
**--END OF EDIT--**
<br/>
Ive tried dozens of things, discarding each in turn, had a quick look in version history to grab out two promising attempts and shared them in separate sheets.
One of these also used SUBSTITUTE to simplify input column, im happy for a solution using either RAW or the SUBSTITUTE results.
<br/>
**Potentially Useful links:**
https://github.com/google/re2/wiki/Syntax
<br/>
<b>Just some more words:</b>
I also have looked at dozens of stackoverflow and google support pages, so tried both REGEXEXTRACT and REGEXREPLACE, both promising but missing that final tweak. And i tried dozens of tweaks already on both.
Any help would be great, and hopefully help others in future since examples with spreadsheets are great since every new REGEX seems to be a new adventure ;)
<br/>
P.S. if we can think of better title for OP, please say in comment or your answer :)
paste in B3:
=ARRAYFORMULA(SUBSTITUTE(TRIM(TRANSPOSE(QUERY(TRANSPOSE(
IF(C3:E<>"", C2:E2&":"&C3:E, )),,999^99))), " ", ", "))
paste in C3:
=ARRAYFORMULA(IFNA(REGEXEXTRACT($A3:$A, "(\d+)\ntype = "&C2)))
paste in D3:
=ARRAYFORMULA(IFNA(REGEXEXTRACT($A3:$A, "(\d+)\ntype = "&D2)))
paste in E3:
=ARRAYFORMULA(IFNA(REGEXEXTRACT($A3:$A, "(\d+)\ntype = "&E2)))
paste in F3:
=ARRAYFORMULA(IFNA(REGEXEXTRACT(A3:A, "\[feature\d+\]\nname = (.*)")))
paste in G3:
=ARRAYFORMULA(IFNA(REGEXEXTRACT(A3:A, "\[components\]\n\d+ = (.*)")))
paste in H3:
=ARRAYFORMULA(IFNA(REGEXREPLACE(INDEX(SPLIT(REGEXEXTRACT(
REGEXREPLACE(A3:A, "\n", ", "), "\[resources\], (.*)"), "["),,1), ", , $", )))
spreadsheet demo
This was a fun exercise. :-)
Caveat first: I have added some "input data". Examples:
[feature1]
name = feature_active_spoiler2
[components]
0 = spoiler,1
1 = spoilerA, 2
So the output has "extra" output.
See the tab ADW's Solution.
I'm using textacy's pos_regex_matches method to find certain chunks of text in sentences.
For instance, assuming I have the text: Huey, Dewey, and Louie are triplet cartoon characters., I'd like to detect that Huey, Dewey, and Louie is an enumeration.
To do so, I use the following code (on testacy 0.3.4, the version available at the time of writing):
import textacy
sentence = 'Huey, Dewey, and Louie are triplet cartoon characters.'
pattern = r'<PROPN>+ (<PUNCT|CCONJ> <PUNCT|CCONJ>? <PROPN>+)*'
doc = textacy.Doc(sentence, lang='en')
lists = textacy.extract.pos_regex_matches(doc, pattern)
for list in lists:
print(list.text)
which prints:
Huey, Dewey, and Louie
However, if I have something like the following:
sentence = 'Donald Duck - Disney'
then the - (dash) is recognised as <PUNCT> and the whole sentence is recognised as a list -- which it isn't.
Is there a way to specify that only , and ; are valid <PUNCT> for lists?
I've looked for some reference about this regex language for matching PoS tags with no luck, can anybody help? Thanks in advance!
PS: I tried to replace <PUNCT|CCONJ> with <[;,]|CCONJ>, <;,|CCONJ>, <[;,]|CCONJ>, <PUNCT[;,]|CCONJ>, <;|,|CCONJ> and <';'|','|CCONJ> as suggested in the comments, but it didn't work...
Is short, it is not possible: see this official page.
However the merge request contains the code of the modified version described in the page, therefore one can recreate the functionality, despite it's less performing than using a SpaCy's Matcher (see code and example -- though I have no idea how to reimplement my problem using a Matcher).
If you want to go down this lane anyway, you have to change the line:
words.extend(map(lambda x: re.sub(r'\W', '', x), keyword_map[w]))
with the following:
words.extend(keyword_map[w])
otherwise every symbol (like , and ; in my case) will be stripped off.
I have a CSV file containing user (tweetid, tweets, userid).
396124436476092416,"Think about the life you livin but don't think so hard it hurts Life is truly a gift, but at the same it is a curse",Obey_Jony09
396124436740317184,"“#BleacherReport: Halloween has given us this amazing Derrick Rose photo (via #amandakaschube, #ScottStrazzante) http://t.co/tM0wEugZR1” yes",Colten_stamkos
396124436845178880,"When's 12.4k gonna roll around",Matty_T_03
Now I need to write a Pig Query that returns all the tweets that include the word 'favorite', ordered by tweet id.
For this I have the following code:
A = load '/user/pig/tweets' as (line);
B = FOREACH A GENERATE FLATTEN(REGEX_EXTRACT_ALL(line,'(.*)[,”:-](.*)[“,:-](.*)')) AS (tweetid:long,msg:chararray,userid:chararray);
C = filter B by msg matches '.*favorite.*';
D = order C by tweetid;
How does the regular expression work here in splitting the output in desired way?
I tried using REGEX_EXTRACT instead of REGEX_EXTRACT_ALL as I find that much more simpler, but couldn't get the code working except for extracting just the tweets:
B = FOREACH A GENERATE FLATTEN(REGEX_EXTRACT(line,'[,”:-](.*)[“,:-]',1)) AS (msg:chararray);
the above alias gets me the tweets, but if I use REGEX_EXTRACT to get the tweet_id, I do not get the desired o/p: B = FOREACH A GENERATE FLATTEN(REGEX_EXTRACT(line,'(.*)[,”:-]',1)) AS (tweetid:long);
(396124554353197056,"Just saw #samantha0wen and #DakotaFears at the drake concert #waddup")
(396124554172432384,"#Yutika_Diwadkar I'm just so bright 😁")
(396124554609033216,"#TB23GMODE i don't know, i'm just saying, why you in GA though? that's where you from?")
(396124554805776385,"#MichaelThe_Lion me too 😒")
(396124552540852226,"Happy Halloween from us 2 #maddow & #Rev_AlSharpton :) http://t.co/uC35lDFQYn")
grunt>
Please help.
Can't comment, but from looking at this and testing it out, it looks like your quotes in the regex are different from those in the csv.
" in the csv
” in the regex code.
To get the tweetid try this:
B = FOREACH A GENERATE FLATTEN(REGEX_EXTRACT(line,'.*(,")',1)) AS (tweetid:long);
I’m trying to use a Python Regular Expression to extract a genome sequence from a genome database; I’ve pasted a snippet of the database below.
>GSVIVT01031739001 pacid=17837850 polypeptide=GSVIVT01031739001 locus=GSVIVG01031739001 ID=GSVIVT01031739001.Genoscope12X annot-version=Genoscope.12X ATGAAAACGGAACTCTTTCTAGGTCATTTCCTCTTCAAACAAGAAAGAAGTAAAAGTTGCATACCAAATATGGACTCGAT TTGGAGTCGTAGTGCCCTGTCCACAGCTTCGGACTTCCTCACTGCAATCTACTTCGCCTTCATCTTCATCGTCGCCAGGT TTTTCTTGGACAGATTCATCTATCGAAGGTTGGCCATCTGGTTATTGAGCAAGGGAGCTGTTCCATTGAAGAAAAATGAT GCTACACTGGGAAAAATTGTAAAATGTTCGGAGTCTTTGTGGAAACTAACATACTATGCAACTGTTGAAGCATTCATTCT TGCTATTTCCTACCAAGAGCCATGGTTTAGAGATTCAAAGCAGTACTTTAGAGGGTGGCCAAATCAAGAGTTGACGCTTC CCCTCAAGCTTTTCTACATGTGCCAATGTGGGTTCTACATCTACAGCATTGCTGCCCTTCTTACATGGGAAACTCGCAGG AGGGATTTCTCTGTGATGATGTCTCATCATGTAGTCACTGTTATCCTAATTGGGTACTCATACATATCAAGTTTTGTCCG GATCGGCTCAGTTGTCCTTGCCCTGCACGATGCAAGTGATGTCTTCATGGAAGCTGCAAAAGTTTTTAAATATTCTGAGA AGGAGCTTGCAGCAAGTGTGTGCTTTGGATTTTTTGCCATCTCATGGCTTGTCCTACGGTTAATATTCTTTCCCTTTTGG GTTATCAGTGCATCAAGCTATGATATGCAAAATTGCATGAATCTATCGGAGGCCTATCCCATGTTGCTATACTATGTTTT CAATACAATGCTCTTGACACTACTTGTGTTCCATATATACTGGTGGATTCTTATATGCTCAATGATTATGAGACAGCTGA AAAATAGAGGACAAGTTGGAGAAGATATAAGATCTGATTCAGAGGACGATGAATAG
>GSVIVT01031740001 pacid=17837851 polypeptide=GSVIVT01031740001 locus=GSVIVG01031740001 ID=GSVIVT01031740001.Genoscope12X annot-version=Genoscope.12X ATGGGTATTACTACTTCCCTCTCATATCTTTTATTCTTCAACATCATCCTCCCAACCTTAACGGCTTCTCCAATACTGTT TCAGGGGTTCAATTGGGAATCATCCAAAAAGCAAGGAGGGTGGTACAACTTCCTCATCAACTCCATTCCTGAACTATCTG CCTCTGGAATCACTCATGTTTGGCTTCCTCCACCCTCTCAGTCTGCTGCATCTGAAGGGTACCTGCCAGGAAGGCTTTAT GATCTCAATGCATCCCACTATGGTACCCAATATGAACTAAAAGCATTGATAAAGGCATTTCGCAGCAATGGGATCCAGTG CATAGCAGACATAGTTATAAACCACAGGACTGCTGAGAAGAAAGATTCAAGAGGAATATGGGCCATCTTTGAAGGAGGAA CCCCAGATGATCGCCTTGACTGGGGTCCATCTTTTATCTGCAGTGATGACACTCTTTTTTCTGATGGCACAGGAAATCCT GATACTGGAGCAGGCTTCGATCCTGCTCCAGACATTGATCATGTAAACCCCCGGGTCCAGCGAGAGCTATCAGATTGGAT GAATTGGTTAAAGATTGAAATAGGCTTTGCTGGATGGCGATTCGATTTTGCTAGAGGATACTCCCCAGATTTTACCAAGT TGTATATGGAAAACACTTCGCCAAACTTTGCAGTAGGGGAAATATGGAATTCTCTTTCTTATGGAAATGACAGTAAGCCA AACTACAACCAAGATGCTCATCGGCGTGAGCTTGTGGACTGGGTGAAAGCTGCTGGAGGAGCAGTGACTGCATTTGATTT TACAACCAAAGGGATACTCCAAGCTGCAGTGGAAGGGGAATTGTGGAGGCTGAAGGACTCAAATGGAGGGCCTCCAGGAA TGATTGGCTTAATGCCTGAAAATGCTGTGACTTTCATAGATAATCATGACACAGGTTCTACACAAAAAATTTGGCCATTC CCATCAGACAAAGTCATGCAGGGATATGTTTATATCCTCACTCATCCTGGGATTCCATCCATATTCTATGACCACTTCTT TGACTGGGGTCTGAAGGAGGAGATTTCTAAGCTGATCAGTATCAGGACCAGGAACGGGATCAAACCCAACAGTGTGGTGC GTATTCTGGCATCTGACCCAGATCTTTATGTAGCTGCCATAGATGAGAAAATCATTGCTAAGATTGGACCAAGGTATGAT GTTGGGAACCTTGTACCTTCAACCTTCAAACTTGCCACCTCTGGCAACAATTATGCTGTGTGGGAGAAACAGTAA
>GSVIVT01031741001 pacid=17837852 polypeptide=GSVIVT01031741001 locus=GSVIVG01031741001 ID=GSVIVT01031741001.Genoscope12X annot-version=Genoscope.12X ATGTCCAAATTAACTTATTTATTATCTCGGTACATGCCAGGAAGGCTTTATGATCTGAATGCATCCAAATATGGCACCCA AGATGAACTGAAAACACTGATAAAGGTGTTTCACAGCAAGGGGGTCCAGTGCATAGCAGACATAGTTATAAACCACAGAA CTGCAGAGAAGCAAGACGCAAGAGGAATATGGCCATCTTTGAAGGAGGAACCCCAGATGATCGCCTTGACTGGACCCCAT CTTTCCTTTGCAAGGACGACACTCCTTATTCCGACGGCACCGGAAACCCTGATTCTGGAGATGACTACAGTGCCGCACCA GACATCGACCACATCAACCCACGGGTTCAGCAAGAGCTAA
What I’m trying to do is get the genome (ACGT) sequence for GSVIV01031740001 (the middle sequence), and none of the others. My current regex is
sequence = re.compile('(?<=>GSVIVT01031740001) pacid=.*annot-version=.*\n[ACGT\n]*[^(?<!>GSVIVT01031740001) pacid]’)
with my logic being find the header with the genbank ID for the correct organism, give me that line, then go to a new line and give me all ACGT and new lines until I get to a header for an organism with a different genbank ID. This fails to give any results.
Yes, I know that re.compile doesn’t actually perform a search; I’m searching against a file opened as ‘target’ so my execution looks like
>>> for nucl in target:
... if re.search(sequence, nucl):
... print(nucl)
Can someone tell me what I’m doing wrong, either in my regex or by using regex in the first place? When I try this on regex101.com, it works, but when I try it in the Python interpreter (2.7.1), it fails.
Thanks!
If I understand correctly , you want JUST the genomic sequence for a given locus. So You can do something like this.(assumes your data is in a file)
lines = [line.split(' ') for line in open('results.txt') ]
somedict = {}
for each in lines:
locus = each[3].split('=')[-1]
seq = ''.join(each[6:])
somedict[locus] = seq
print somedict
It outputs a dictionary with the locus as key and sequence as value
{'GSVIVG01031741001': 'ATGTCCAAATTAACTTATTTATTATCTCGGTACATGCCAGGAAGGCTTTATGATCTGAATGCATCCAAATATGGCACCCAAGATGAACTGAAAACACTGATAAAGGTGTTTCACAGCAAGGGGGTCCAGTGCATAGCAGACATAGTTATAAACCACAGAACTGCAGAGAAGCAAGACGCAAGAGGAATATGGCCATCTTTGAAGGAGGAACCCCAGATGATCGCCTTGACTGGACCCCATCTTTCCTTTGCAAGGACGACACTCCTTATTCCGACGGCACCGGAAACCCTGATTCTGGAGATGACTACAGTGCCGCACCAGACATCGACCACATCAACCCACGGGTTCAGCAAGAGCTAA\n', 'GSVIVG01031740001': 'ATGGGTATTACTACTTCCCTCTCATATCTTTTATTCTTCAACATCATCCTCCCAACCTTAACGGCTTCTCCAATACTGTTTCAGGGGTTCAATTGGGAATCATCCAAAAAGCAAGGAGGGTGGTACAACTTCCTCATCAACTCCATTCCTGAACTATCTGCCTCTGGAATCACTCATGTTTGGCTTCCTCCACCCTCTCAGTCTGCTGCATCTGAAGGGTACCTGCCAGGAAGGCTTTATGATCTCAATGCATCCCACTATGGTACCCAATATGAACTAAAAGCATTGATAAAGGCATTTCGCAGCAATGGGATCCAGTGCATAGCAGACATAGTTATAAACCACAGGACTGCTGAGAAGAAAGATTCAAGAGGAATATGGGCCATCTTTGAAGGAGGAACCCCAGATGATCGCCTTGACTGGGGTCCATCTTTTATCTGCAGTGATGACACTCTTTTTTCTGATGGCACAGGAAATCCTGATACTGGAGCAGGCTTCGATCCTGCTCCAGACATTGATCATGTAAACCCCCGGGTCCAGCGAGAGCTATCAGATTGGATGAATTGGTTAAAGATTGAAATAGGCTTTGCTGGATGGCGATTCGATTTTGCTAGAGGATACTCCCCAGATTTTACCAAGTTGTATATGGAAAACACTTCGCCAAACTTTGCAGTAGGGGAAATATGGAATTCTCTTTCTTATGGAAATGACAGTAAGCCAAACTACAACCAAGATGCTCATCGGCGTGAGCTTGTGGACTGGGTGAAAGCTGCTGGAGGAGCAGTGACTGCATTTGATTTTACAACCAAAGGGATACTCCAAGCTGCAGTGGAAGGGGAATTGTGGAGGCTGAAGGACTCAAATGGAGGGCCTCCAGGAATGATTGGCTTAATGCCTGAAAATGCTGTGACTTTCATAGATAATCATGACACAGGTTCTACACAAAAAATTTGGCCATTCCCATCAGACAAAGTCATGCAGGGATATGTTTATATCCTCACTCATCCTGGGATTCCATCCATATTCTATGACCACTTCTTTGACTGGGGTCTGAAGGAGGAGATTTCTAAGCTGATCAGTATCAGGACCAGGAACGGGATCAAACCCAACAGTGTGGTGCGTATTCTGGCATCTGACCCAGATCTTTATGTAGCTGCCATAGATGAGAAAATCATTGCTAAGATTGGACCAAGGTATGATGTTGGGAACCTTGTACCTTCAACCTTCAAACTTGCCACCTCTGGCAACAATTATGCTGTGTGGGAGAAACAGTAA\n', 'GSVIVG01031739001': 'ATGAAAACGGAACTCTTTCTAGGTCATTTCCTCTTCAAACAAGAAAGAAGTAAAAGTTGCATACCAAATATGGACTCGATTTGGAGTCGTAGTGCCCTGTCCACAGCTTCGGACTTCCTCACTGCAATCTACTTCGCCTTCATCTTCATCGTCGCCAGGTTTTTCTTGGACAGATTCATCTATCGAAGGTTGGCCATCTGGTTATTGAGCAAGGGAGCTGTTCCATTGAAGAAAAATGATGCTACACTGGGAAAAATTGTAAAATGTTCGGAGTCTTTGTGGAAACTAACATACTATGCAACTGTTGAAGCATTCATTCTTGCTATTTCCTACCAAGAGCCATGGTTTAGAGATTCAAAGCAGTACTTTAGAGGGTGGCCAAATCAAGAGTTGACGCTTCCCCTCAAGCTTTTCTACATGTGCCAATGTGGGTTCTACATCTACAGCATTGCTGCCCTTCTTACATGGGAAACTCGCAGGAGGGATTTCTCTGTGATGATGTCTCATCATGTAGTCACTGTTATCCTAATTGGGTACTCATACATATCAAGTTTTGTCCGGATCGGCTCAGTTGTCCTTGCCCTGCACGATGCAAGTGATGTCTTCATGGAAGCTGCAAAAGTTTTTAAATATTCTGAGAAGGAGCTTGCAGCAAGTGTGTGCTTTGGATTTTTTGCCATCTCATGGCTTGTCCTACGGTTAATATTCTTTCCCTTTTGGGTTATCAGTGCATCAAGCTATGATATGCAAAATTGCATGAATCTATCGGAGGCCTATCCCATGTTGCTATACTATGTTTTCAATACAATGCTCTTGACACTACTTGTGTTCCATATATACTGGTGGATTCTTATATGCTCAATGATTATGAGACAGCTGAAAAATAGAGGACAAGTTGGAGAAGATATAAGATCTGATTCAGAGGACGATGAATAG\n'}