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Test BinnedPeaks
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@davidshumway
davidshumway committed Jun 10, 2021
1 parent 5e55400 commit d85a592
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29 changes: 29 additions & 0 deletions mdb/spectra/migrations/0007_auto_20210609_2238.py
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@@ -0,0 +1,29 @@
# Generated by Django 3.1 on 2021-06-09 22:38

from django.db import migrations, models
import django.db.models.deletion


class Migration(migrations.Migration):

dependencies = [
('spectra', '0006_auto_20210517_0456'),
]

operations = [
migrations.CreateModel(
name='BinnedPeaks',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('peak_mass', models.TextField(blank=True)),
('peak_intensity', models.TextField(blank=True)),
('peak_snr', models.TextField(blank=True)),
('spectra', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='spectra.collapsedspectra')),
],
),
migrations.AddField(
model_name='collapsedcosinescore',
name='binned_peaks',
field=models.ManyToManyField(to='spectra.BinnedPeaks'),
),
]
16 changes: 16 additions & 0 deletions mdb/spectra/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -234,8 +234,23 @@ class AbstractCosineScore(models.Model):
class Meta:
abstract = True

class BinnedPeaks(models.Model):
'''
Binned peaks version of a spectra when matched against set of spectra.
'''
peak_mass = models.TextField(blank = True)
peak_intensity = models.TextField(blank = True)
peak_snr = models.TextField(blank = True)
spectra = models.ForeignKey(
'CollapsedSpectra',
# ~ related_name = 'spectra',
on_delete = models.CASCADE)

# ~ class CollapsedCosineScore(AbstractCosineScore):
class CollapsedCosineScore(models.Model):
'''
Todo: Needs to save binned peaks representation of spectra
'''
spectra = models.ForeignKey(
'CollapsedSpectra',
# ~ related_name = 'spectra',
Expand All @@ -245,6 +260,7 @@ class CollapsedCosineScore(models.Model):
on_delete = models.CASCADE)
scores = models.TextField()
spectra_ids = models.TextField()
binned_peaks = models.ManyToManyField('BinnedPeaks')

# ~ class CollapsedCosineScore(AbstractCosineScore):
# ~ spectra1 = models.ForeignKey(
Expand Down
150 changes: 78 additions & 72 deletions mdb/spectra_search/views.py
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Original file line number Diff line number Diff line change
Expand Up @@ -133,10 +133,10 @@ def process_file(request, file, form, owner):
)

# TODO
# if multiple spectra, await user response
# if single spectra, continue
# If multiple spectra, await user response
# If single spectra, continue

# if more than one protein spectra, then collapse
# Collapse if there is a protein spectra
if info['spectra']['protein'] > 0: ##### > 1
data = {
'id': form.cleaned_data['library'].id,
Expand All @@ -146,33 +146,36 @@ def process_file(request, file, form, owner):
'http://plumber:8000/collapseLibrary',
params = data
)
# In the case of a collapsed spectra which had mass > 6000 but
# when collapsed lost those peaks, it is necessary to
# retrieve the CollapsedSpectra using the spectra_content
# attribute.
n1 = CollapsedSpectra.objects.filter( # unknown spectra
library_id__exact = form.cleaned_data['library'].id,
spectra_content__exact = 'PR'
#max_mass__gt = 6000
).first()
n2 = CollapsedSpectra.objects.filter(
library__exact = form.cleaned_data['search_library'].id,
max_mass__gt = 6000
).values('id')
data = {
'ids': [n1.id] + [s['id'] for s in list(n2)]
}
r = requests.post(
'http://plumber:8000/cosine',
params = data
)

# In the case of a collapsed spectra which had mass > 6000 but
# when collapsed lost those peaks, it is necessary to
# retrieve the CollapsedSpectra using the spectra_content
# attribute.
n1 = CollapsedSpectra.objects.filter( # unknown spectra
library_id__exact = form.cleaned_data['library'].id,
spectra_content__exact = 'PR'
).first()
n2 = CollapsedSpectra.objects.filter(
library__exact = form.cleaned_data['search_library'].id,
spectra_content__exact = 'PR'
#max_mass__gt = 6000
).values('id')
data = {
'ids': [n1.id] + [s['id'] for s in list(n2)]
}
r = requests.post(
'http://plumber:8000/cosine',
params = data
)

print('bp', r.json()['binnedPeaks'][1][0])

# ~ # test
# ~ from spectra.models import *
# ~ import requests
# ~ n2 = CollapsedSpectra.objects.filter(
# ~ library__title__exact = 'R01 Data',
# ~ max_mass__gt = 6000
# ~ library__title__exact = 'R01 Data',
# ~ max_mass__gt = 6000
# ~ ).values('id')
# ~ data = {'ids': [2] + [s['id'] for s in list(n2)]}
# ~ r = requests.post('http://plumber:8000/cosine', params = data)
Expand All @@ -181,57 +184,60 @@ def process_file(request, file, form, owner):
# ~ k = [str(s['id']) for s in list(n2)] # one less
# ~ v = r.json()[1:] # one more, remove first
# ~ o = OrderedDict(
# ~ sorted(dict(zip(k, v)).items(),
# ~ key = lambda x: (x[1], x[0]), reverse = True)
# ~ sorted(dict(zip(k, v)).items(),
# ~ key = lambda x: (x[1], x[0]), reverse = True)
# ~ )

# create a dictionary and sort by its values
from collections import OrderedDict
k = [str(s['id']) for s in list(n2)] # one less
v = r.json()[1:] # one more, remove first
o = OrderedDict(
sorted(dict(zip(k, v)).items(),
key = lambda x: (x[1], x[0]), reverse = True)
)
# create a dictionary and sort by its values
from collections import OrderedDict
k = [str(s['id']) for s in list(n2)] # one less
v = r.json()['similarity'][1:] # one more remove first???
o = OrderedDict(
sorted(dict(zip(k, v)).items(),
key = lambda x: (x[1], x[0]), reverse = True)
)

obj = CollapsedCosineScore.objects.create(
spectra = n1,
library = form.cleaned_data['library'], # lib unnecessary in ccs model
scores = ','.join(map(str, list(o.values()))),
spectra_ids = ','.join(map(str, o.keys())))

if obj:
l = {
'result': [],
'original': {
'peak_mass': n1.peak_mass,
'peak_intensity': n1.peak_intensity,
}
obj = CollapsedCosineScore.objects.create(
spectra = n1,
library = form.cleaned_data['library'], # lib unnecessary in ccs model
scores = ','.join(map(str, list(o.values()))),
spectra_ids = ','.join(map(str, o.keys())))

if obj:
l = {
'result': [],
'original': {
'peak_mass': n1.peak_mass,
'peak_intensity': n1.peak_intensity,
}

from django.db.models import Case, When
preserved = Case(*[When(pk = pk, then = pos) for pos, pk in enumerate(o)])
q = CollapsedSpectra.objects.filter(id__in = o.keys()).order_by(preserved)
rowcount = 1
for cs in q:
l['result'].append({
'score': o[str(cs.id)],
'strain': cs.strain_id.strain_id,
'kingdom': cs.strain_id.cKingdom,
'phylum': cs.strain_id.cPhylum,
'class': cs.strain_id.cClass,
'order': cs.strain_id.cOrder,
# ~ 'family': cs.strain_id.cFamily,
'genus': cs.strain_id.cGenus,
'species': cs.strain_id.cSpecies,
'rowcount': rowcount,
'peak_mass': cs.peak_mass,
'peak_intensity': cs.peak_intensity,
})
rowcount += 1
ws.send(json.dumps(l))
else:
pass
}

# Add binned peaks representation for each spectra


from django.db.models import Case, When
preserved = Case(*[When(pk = pk, then = pos) for pos, pk in enumerate(o)])
q = CollapsedSpectra.objects.filter(id__in = o.keys()).order_by(preserved)
rowcount = 1
for cs in q:
l['result'].append({
'score': o[str(cs.id)],
'strain': cs.strain_id.strain_id,
'kingdom': cs.strain_id.cKingdom,
'phylum': cs.strain_id.cPhylum,
'class': cs.strain_id.cClass,
'order': cs.strain_id.cOrder,
# ~ 'family': cs.strain_id.cFamily,
'genus': cs.strain_id.cGenus,
'species': cs.strain_id.cSpecies,
'rowcount': rowcount,
'peak_mass': cs.peak_mass,
'peak_intensity': cs.peak_intensity,
})
rowcount += 1
ws.send(json.dumps(l))
# ~ else:
# ~ pass
# ~ r = requests.post(
# ~ 'http://plumber:8000/cosine',
# ~ params = data
Expand Down
21 changes: 12 additions & 9 deletions rplumber/plumber.R
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Original file line number Diff line number Diff line change
Expand Up @@ -64,11 +64,12 @@ print.data.frame <- function (
#* Todo: library=, lab=, strain=, user=, ...
#* @param req Built-in
#* @param ids List of IDs from Spectra table
#* @return Returns first row from cosine similarity matrix
#* @return -----------Returns first row from cosine similarity matrix
#* @return Returns first cos. similarity matrix row, and binnedPeaks
#* @post /cosine
function(req, ids) {
ids <- as.numeric(ids)
if (length(ids) < 2) {#----
if (length(ids) < 2) {
stop('less than two comparison ids given!')
}

Expand All @@ -81,11 +82,16 @@ function(req, ids) {
binnedPeaks <- MALDIquant::binPeaks(allPeaks, tolerance = 0.002)
featureMatrix <- MALDIquant::intensityMatrix(binnedPeaks, allSpectra)
# manual inspection...
print(toString(head(binnedPeaks, 2)))
#~ print(toString(binnedPeaks))
#print(toString(featureMatrix[1,]))
#print(toString(featureMatrix[2,]))
#print(coop::cosine(featureMatrix[1,], featureMatrix[2,]))
d <- coop::cosine(t(featureMatrix))
d <- round(d, 3)

return(list('similarity' = d[1,], 'binnedPeaks' = capture.output(binnedPeaks)))

return(d[1,])

emptyProtein <- unlist(
Expand Down Expand Up @@ -114,6 +120,8 @@ function(req, ids) {
d <- as.matrix(d)
d <- round(d, 3)
d <- d[1,]


return(d)

## not used
Expand Down Expand Up @@ -238,7 +246,7 @@ function(req, ids) {
#~ jsonlite::toJSON(a)
}

# Helper function to retrive list of IDs from Django's DB
# Helper function to retrieve list of IDs from Django's DB
dbSpectra <- function(ids) {
#~ if (class(ids) != 'integer') {
#~ stop('dbSpectra: not integer!') # stop throws 500
Expand All @@ -249,9 +257,6 @@ dbSpectra <- function(ids) {

c <- connect()
s <- paste(unlist(ids), collapse = ',')
#~ s <- paste0('SELECT peak_mass, peak_intensity, peak_snr
#~ FROM spectra_spectra
#~ WHERE id IN (', s, ')')
s <- paste0('SELECT peak_mass, peak_intensity, peak_snr, id
FROM spectra_collapsedspectra
WHERE id IN (', s, ')')
Expand Down Expand Up @@ -375,9 +380,7 @@ collapseStrainsInLibrary <- function(lid, sid, type, owner) {
t <- MALDIquant::filterPeaks(t, minFrequency = 70 / 100)
t <- MALDIquant::mergeMassPeaks(t, method = 'mean')

# save to Django's DB
# --curl
# "Content-Type: application/json"
# Save to Django's DB
h <- new_handle()
x <- paste0(
'{',
Expand Down

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