def chemspectra_predict_by_peaks_form():
layout = request.form.get('layout', default=None)
peaks = request.form.get('peaks', default='{}')
peaks = json.loads(peaks)
shift = request.form.get('shift', default='{}')
shift = json.loads(shift)
molfile = FileContainer(request.files['molfile'])
mm = MoleculeModel(molfile, layout, decorate=True)
if not peaks:
spectrum = FileContainer(request.files['spectrum'])
if spectrum and layout == '13C':
cv = TraModel(spectrum, molfile=molfile, params={'ext': 'jdx'}).to_converter()
peaks = parse_array_to_dict_xys(cv.edit_peaks)
if (not peaks) or (not molfile):
abort(400)
outcome = InferModel.predict_nmr(
mm=mm,
layout=layout,
peaks=peaks,
shift=shift
)
if outcome:
return jsonify(outcome)
abort(400)
def __generated_jcamp_temp(path, params=False):
with open(path, 'rb') as f:
file = FileContainer(FileStorage(f))
molfile = FileContainer(FileStorage(None))
nicv, nicp = TraModel(file, molfile, params).jcamp2cvp()
jcamp = nicp.tf_jcamp()
return nicv, nicp, jcamp
def jcamp():
file = FileContainer(request.files['file'])
molfile = FileContainer(request.files.get('molfile'))
params = extract_params(request)
if file: # and allowed_file(file):
tf_jcamp = TraModel(file, molfile=molfile, params=params).convert2jcamp()
return send_file(
tf_jcamp,
attachment_filename='spectrum.jdx',
as_attachment=True
)
def __generated_peaks_meta(orig_filename, params=False):
with open(target_dir + source_dir + orig_filename, 'rb') as f:
file = FileContainer(FileStorage(f))
molfile = FileContainer(FileStorage(None))
_, nicp = TraModel(file, molfile, params).jcamp2cvp()
parts = ''.join(nicp.meta).split(separator)
assert len(parts) == 2
meta_content = parts[1]
return meta_content
def image():
file = FileContainer(request.files['file'])
molfile = FileContainer(request.files.get('molfile'))
params = extract_params(request)
if file: # and allowed_file(file):
tf_img = TraModel(file, molfile=molfile, params=params).convert2img()
return send_file(
tf_img,
attachment_filename='spectrum.png',
as_attachment=True,
mimetype='image/png'
)
def zip_image():
file = FileContainer(request.files['file'])
molfile = FileContainer(request.files.get('molfile'))
params = extract_params(request)
if file: # and allowed_file(file):
tf_img = TraModel(file, molfile=molfile, params=params).convert2img()
memory = to_zip_response([tf_img])
return send_file(
memory,
attachment_filename='spectrum.zip',
as_attachment=True
)
def chemspectra_file_convert():
file = FileContainer(request.files['file'])
molfile = FileContainer(request.files.get('molfile'))
params = extract_params(request)
if file:
tf_jcamp, tf_img = TraModel(file, molfile=molfile,
params=params).convert2jcamp_img()
if not tf_jcamp:
abort(400)
jcamp = base64.b64encode(tf_jcamp.read()).decode("utf-8")
img = base64.b64encode(tf_img.read()).decode("utf-8")
return jsonify(status=True, jcamp=jcamp, img=img)
def chemspectra_predict_infrared():
layout = request.form.get('layout', default=None)
spectrum = FileContainer(request.files['spectrum'])
molfile = FileContainer(request.files['molfile'])
mm = MoleculeModel(molfile, layout)
outcome = InferModel.predict_ir(
mm=mm,
spectrum=spectrum
)
if outcome:
return jsonify(outcome)
abort(400)
def chemspectra_predict_ms():
layout = request.form.get('layout', default=None)
spectrum = FileContainer(request.files['spectrum'])
molfile = FileContainer(request.files['molfile'])
mm = MoleculeModel(molfile, layout)
tm = TraModel(spectrum, molfile=None, params={'ext': 'jdx'}).to_composer()
outcome = InferModel.predict_ms(
mm=mm,
tm=tm
)
if outcome:
return jsonify(outcome)
abort(400)
def chemspectra_file_refresh():
# src = FileContainer(request.files['src'])
dst = FileContainer(request.files['dst'])
molfile = FileContainer(request.files.get('molfile'))
# filename = request.form.get('filename', default=None)
params = extract_params(request)
if dst: # and allowed_file(file):
tm = TraModel(dst, molfile=molfile, params=params)
tf_jcamp, tf_img = tm.convert2jcamp_img()
if not tf_jcamp:
abort(400)
jcamp = base64.b64encode(tf_jcamp.read()).decode("utf-8")
img = base64.b64encode(tf_img.read()).decode("utf-8")
return jsonify(status=True, jcamp=jcamp, img=img)
def test_molfile2chem():
with open(target_dir + source_dir + '/molfile/svs813f1_B.mol', 'rb') as f:
molfile = FileContainer(FileStorage(f))
mm = MoleculeModel(molfile)
assert mm.smi == 'CCC1CCC(=O)C(C)C12SCCS2'
assert mm.mass == 230.079907196
def zip_jcamp_n_img():
file = FileContainer(request.files['file'])
molfile = FileContainer(request.files.get('molfile'))
params = extract_params(request)
if file: # and allowed_file(file):
cmpsr = TraModel(file, molfile=molfile, params=params).to_composer()
tf_jcamp, tf_img = cmpsr.tf_jcamp(), cmpsr.tf_img()
spc_type = cmpsr.core.ncl if cmpsr.core.typ == 'NMR' else cmpsr.core.typ
memory = to_zip_response([tf_jcamp, tf_img])
rsp = make_response(
send_file(
memory,
attachment_filename='spectrum.zip',
as_attachment=True
)
)
rsp.headers['X-Extra-Info-JSON'] = json.dumps({'spc_type': spc_type})
return rsp
def chemspectra_molfile_convert():
molfile = FileContainer(request.files.get('molfile'))
mm = MoleculeModel(molfile)
return jsonify(
status=True,
smi=mm.smi,
mass=mm.mass,
svg=mm.svg,
)
def chemspectra_file_save():
src = FileContainer(request.files['src'])
dst = FileContainer(request.files['dst'])
molfile = FileContainer(request.files.get('molfile'))
filename = request.form.get('filename', default=None)
params = extract_params(request)
if dst: # and allowed_file(file):
tm = TraModel(dst, molfile=molfile, params=params)
tf_jcamp, tf_img = tm.convert2jcamp_img()
tf_arr = [
src.temp_file(),
tf_jcamp,
tf_img,
tm.tf_predict(),
]
memory = to_zip_response(tf_arr, filename, src_idx=0)
return send_file(memory,
attachment_filename='spectrum.zip',
as_attachment=True)
def chemspectra_predict_by_peaks_json():
payload = request.json
layout = payload.get('layout')
peaks = payload.get('peaks')
shift = payload.get('shift')
molfile = FileContainer().from_str(payload.get('molfile'))
mm = MoleculeModel(molfile, layout, decorate=True)
outcome = InferModel.predict_nmr(
mm=mm,
layout=layout,
peaks=peaks,
shift=shift
)
if outcome:
return jsonify(outcome)
abort(400)
def test_ms_mzml_converter_composer():
params = {'mass': 230.079907196}
with open(target_dir + source_dir + '/ms/svs813f1.mzML', 'rb') as f:
file = FileStorage(f)
file = FileContainer(file)
mscv = MSConverter(file, params)
mscp = MSComposer(mscv)
lines = mscp.tf_jcamp().read()[:800] \
.decode('utf-8', errors='ignore').split('\n')
assert '##$CSSCANAUTOTARGET=3' in lines
assert '##$CSSCANEDITTARGET=3' in lines
assert '##$CSSCANCOUNT=24' in lines
assert '##$CSTHRESHOLD=0.05' in lines
assert '51.012176513671875, 34359.0' in lines
