def export_dataStage02PhysiologyPairWiseTestMetabolites_js(self,analysis_id_I,data_dir_I='tmp'):
'''Export data for a volcano plot
Visuals:
1. volcano plot
2. sample vs. sample (FC)
3. sample vs. sample (concentration)
4. sample vs. sample (p-value)'''
#get the data for the analysis
data_O = [];
data_O = self.get_rows_analysisID_dataStage02PhysiologyPairWiseTestMetabolites(analysis_id_I);
# make the data parameters
data1_keys = ['analysis_id','simulation_id_1','simulation_id_2',
'met_id','flux_units','test_description'
];
data1_nestkeys = ['analysis_id'];
data1_keymap = {'ydata':'pvalue_negLog10',
'xdata':'fold_change',
'serieslabel':'',
'featureslabel':'met_id'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'volcanoplot2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 50, 'bottom': 50, 'left': 50 },
"svgwidth":500,
"svgheight":350,
"svgx1axislabel":'Fold Change [geometric]',
"svgy1axislabel":'Probability [-log10(P)]'};
svgtileparameters_O = {'tileheader':'Volcano plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tableclass":"table table-condensed table-hover",
"tablefilters":None,
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'pairWiseTest','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
filtermenuobject_O = None;
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01RNASequencingGenesFpkmTracking_js(self,analysis_id_I,data_dir_I='tmp'):
'''Export data for a box and whiskers plot'''
# get the analysis information
experiment_ids,sample_names = [],[];
experiment_ids,sample_names = self.get_experimentIDAndSampleName_analysisID_dataStage01RNASequencingAnalysis(analysis_id_I);
data_O = [];
for sample_name_cnt,sample_name in enumerate(sample_names):
# query fpkm data:
fpkms = [];
fpkms = self.get_rows_experimentIDAndSampleName_dataStage01RNASequencingGenesFpkmTracking(experiment_ids[sample_name_cnt],sample_name);
data_O.extend(fpkms);
# dump chart parameters to a js files
data1_keys = ['experiment_id','sample_name','gene_short_name'
];
data1_nestkeys = ['gene_short_name'];
data1_keymap = {'xdata':'gene_short_name',
'ydatamean':'FPKM',
'ydatalb':'FPKM_conf_lo',
'ydataub':'FPKM_conf_hi',
'serieslabel':'sample_name',
'featureslabel':'gene_short_name'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"gene","svgy1axislabel":"FPKM",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'FPKM','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_thermodynamicAnalysisEscher_js(self,analysis_id_I,simulation_id_I=None,
measured_concentration_coverage_criteria_I=0.49,
measured_dG_f_coverage_criteria_I=0.99,
data_dir_I = 'tmp'):
data_O = [];
# Get the simulation information
if simulation_id_I:
simulation_id = simulation_id_I;
else:
simulation_ids = [];
simulation_ids = self.get_simulationID_analysisID_dataStage03QuantificationAnalysis(analysis_id_I);
if not simulation_ids:
print('No simulation found for the analysis_id ' + analysis_id_I);
elif len(simulation_ids)>1:
print('More than 1 simulation found for the analysis_id ' + analysis_id_I);
simulation_id_I = simulation_ids[0];
else:
simulation_id_I = simulation_ids[0];
# get the simulation info
simulation = [];
simulation = self.get_rows_simulationID_dataStage03QuantificationSimulation(simulation_id_I);
for row in simulation:
model_id = row['model_id'];
# get the time-points
tp = row['time_point'];
# get the sample name abbreviations
sna = row['sample_name_abbreviation'];
# get the experiment
experiment_id = row['experiment_id'];
# get metabolomicsData
concentrations = [];
concentrations = self.get_rows_experimentIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationMetabolomicsData(experiment_id,tp,sna);
# get dGr
dG_r = [];
dG_r = self.get_rows_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(experiment_id,model_id,tp,sna,measured_concentration_coverage_criteria_I,measured_dG_f_coverage_criteria_I);
if dG_r:
for cnt,d in enumerate(dG_r):
dG_r[cnt]['dG_r_mean'] = numpy.mean([d['dG_r_lb'],d['dG_r_ub']]);
# Get the map information
map = [];
map = self.get_rows_modelID_modelsEschermaps('iJO1366');
# Make the ddt objects
data1_keys = ['experiment_id',
#'model_id',
'time_point','sample_name_abbreviation','dG_r','dG_r_units'
];
data1_nestkeys = ['sample_name_abbreviation'];
data1_keymap = {'values':'dG_r_mean','key':'rxn_id'};
data2_keys = ['experiment_id','time_point',
'sample_name_abbreviation','met_id',
'concentration_units'
];
data2_nestkeys = ['sample_name_abbreviation'];
data2_keymap = {'values':'concentration','key':'met_id'};
data3_keys = ['model_id','eschermap_id'
];
data3_nestkeys = ['model_id'];
data3_keymap = {'data':'eschermap_json'};
# make the data object
dataobject_O = [{"data":dG_r,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":concentrations,"datakeys":data2_keys,"datanestkeys":data2_nestkeys},
{"data":map,"datakeys":data3_keys,"datanestkeys":data3_nestkeys}];
# make the tile parameter objects
# form 1
formtileparameters1_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters1_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters1_O.update(formparameters1_O);
# form 2
formtileparameters2_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters2_O = {'htmlid':'filtermenuform2',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit2','text':'submit'},"formresetbuttonidtext":{'id':'reset2','text':'reset'},"formupdatebuttonidtext":{'id':'update2','text':'update'}};
formtileparameters2_O.update(formparameters2_O);
# form 3
formtileparameters3_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters3_O = {'htmlid':'filtermenuform3',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit3','text':'submit'},"formresetbuttonidtext":{'id':'reset3','text':'reset'},"formupdatebuttonidtext":{'id':'update3','text':'update'}};
formtileparameters3_O.update(formparameters3_O);
# form 3
# escher
htmlparameters_O = {"htmlkeymap":[data1_keymap,data2_keymap],
'htmltype':'escher_01','htmlid':'html1',
'escherdataindex':{"reactiondata":0,"metabolitedata":1,"mapdata":2},
'escherembeddedcss':None,
'escheroptions':None};
htmltileparameters_O = {'tileheader':'Escher map','tiletype':'html','tileid':"tile1",'rowid':"row3",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
htmltileparameters_O.update(htmlparameters_O);
# table 1
tableparameters1_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters1_O = {'tileheader':'dG_r','tiletype':'table','tileid':"table1",'rowid':"row4",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters1_O.update(tableparameters1_O);
# table 2
tableparameters2_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters2_O = {'tileheader':'Concentrations','tiletype':'table','tileid':"table2",'rowid':"row5",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters2_O.update(tableparameters2_O);
# output objects
parametersobject_O = [formtileparameters1_O,formtileparameters2_O,formtileparameters3_O,htmltileparameters_O,tabletileparameters1_O,tabletileparameters2_O];
tile2datamap_O = {"filtermenu1":[0],"filtermenu2":[1],"filtermenu3":[2],"tile1":[0,1,2],"table1":[0],"table2":[1]};
filtermenuobject_O = [{"filtermenuid":"filtermenu1","filtermenuhtmlid":"filtermenuform1",
"filtermenusubmitbuttonid":"submit1","filtermenuresetbuttonid":"reset1",
"filtermenuupdatebuttonid":"update1"},{"filtermenuid":"filtermenu2","filtermenuhtmlid":"filtermenuform2",
"filtermenusubmitbuttonid":"submit2","filtermenuresetbuttonid":"reset2",
"filtermenuupdatebuttonid":"update2"},{"filtermenuid":"filtermenu3","filtermenuhtmlid":"filtermenuform3",
"filtermenusubmitbuttonid":"submit3","filtermenuresetbuttonid":"reset3",
"filtermenuupdatebuttonid":"update3"}];
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_thermodynamicAnalysis_js(self,analysis_id_I,simulation_ids_I=[],
measured_concentration_coverage_criteria_I=0.49,
measured_dG_f_coverage_criteria_I=0.99,
bullet_chart_I = True,
data_dir_I = 'tmp'):
'''Export the results of the thermodynamic analysis to js'''
concentrations_O = [];
dG_r_O = [];
tcc_O = [];
# Get the simulation information
if simulation_ids_I:
simulation_ids = simulation_ids_I;
else:
simulation_ids = [];
simulation_ids = self.get_simulationID_analysisID_dataStage03QuantificationAnalysis(analysis_id_I);
for simulation_id in simulation_ids:
# get the simulation info
simulation = [];
simulation = self.get_rows_simulationID_dataStage03QuantificationSimulation(simulation_id);
for row in simulation:
model_id = row['model_id'];
# get the time-points
tp = row['time_point'];
# get the sample name abbreviations
sna = row['sample_name_abbreviation'];
# get the experiment
experiment_id = row['experiment_id'];
## get metabolomicsData
#concentrations = [];
#concentrations = self.get_rows_experimentIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationMetabolomicsData(experiment_id_I,tp,sna);
## extend the data
#concentrations_O.extend(concentrations);
## get dGr
#dG_r = [];
#dG_r = self.get_rows_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(experiment_id_I,model_id,tp,sna,measured_concentration_coverage_criteria_I,measured_dG_f_coverage_criteria_I);
## extend the data
#dG_r_O.extend(dG_r);
# get the tcc data
tcc = [];
tcc = self.get_rows_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(experiment_id,model_id,tp,sna,measured_concentration_coverage_criteria_I,measured_dG_f_coverage_criteria_I);
# record data
if tcc:
for cnt,d in enumerate(tcc):
tcc[cnt]['dG_r_mean'] = numpy.mean([d['dG_r_lb'],d['dG_r_ub']]);
tcc_O.extend(tcc);
# dump chart parameters to a js files
data1_keys = ['experiment_id',
'model_id',
'time_point','sample_name_abbreviation','rxn_id','dG_r_units','feasible'
];
data1_nestkeys = ['rxn_id'];
if bullet_chart_I:
data1_keymap = {'xdata':'rxn_id',
'ydatamean':'dG_r_mean',
'ydatalb':'dG_r_lb',
'ydataub':'dG_r_ub',
'serieslabel':'sample_name_abbreviation',
'featureslabel':'rxn_id'};
else: # not implemented
data1_keymap = {'xdata':'rxn_id',
'ydatamean':'dG_r_mean',
'ydatalb':'dG_r_lb',
'ydataub':'dG_r_ub',
'ydatamin':'min',
'ydatamax':'max',
'ydataiq1':'dG_r_lb_stdev',
'ydataiq3':'dG_r_ub_stdev',
'ydatamedian':'dG_r',
'serieslabel':'sample_name_abbreviation',
'featureslabel':'rxn_id'};
# make the data object
dataobject_O = [{"data":tcc_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_01',"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 350, 'bottom': 50, 'left': 50 },
"svgwidth":750,"svgheight":350,
"svgx1axislabel":"rxn_id","svgy1axislabel":"dG_r",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'dG_r','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'dG_r','tiletype':'table','tileid':"tile3",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_visualizationPipeline_js(self,pipeline_id_I,data_dir_I="tmp"):
"""export visualization_pipeline for visualization"""
print("exporting visualization_pipeline...")
# query the pipeline info
data1_pipeline = {};
data1_pipeline = self.get_pipeline_pipelineID_visualizationPipeline(pipeline_id_I);
data1_O = [];
data1_O = self.get_rows_pipelineID_visualizationPipeline(pipeline_id_I);
# query the pipeline description
data2_O = [];
data2_O = self.get_rows_pipelineID_visualizationPipelineDescription(pipeline_id_I);
# query user privileges (new table?)
data1_query_O=[];
#data1_query_O.g
# data parameters
data1_keys = ['table_name','data_export_id','pipeline_id'#,'container_export_id'
];
data1_nestkeys = ['data_export_id'];
data1_keymap = {'buttonparameter':'data_export_id','liparameter':'table_name',
'buttontext':'data_export_id','litext':'table_name'};
data2_keys = ['pipeline_id','pipeline_section','pipeline_heading','pipeline_tileorder'
];
data2_nestkeys = ['pipeline_id'];
data2_keymap = {'htmlmediasrc':'pipeline_media','htmlmediaalt':'',
'htmlmediahref':'pipeline_href','htmlmediaheading':'pipeline_heading',
'htmlmediaparagraph':'pipeline_paragraph'};
# make the data, parameters, and tile2datamap variables:
dataobject_O = [];
parametersobject_O = [];
tile2datamap_O = {};
tile_cnt = 0;
# pipeline_description:
if data2_O:
for i,d in enumerate(data2_O):
tileid = "tile" + str(tile_cnt);
colid = "col" + str(i);
tileheader = d['pipeline_section'];
htmlid = "html" + str(tile_cnt);
tileparameters = {'tileheader':tileheader,'tiletype':'html','tileid':tileid,'rowid':"row1",'colid':colid,
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
htmlparameters={"htmlkeymap":[data2_keymap],
'htmltype':'media_01','htmlid':htmlid};
tileparameters.update(htmlparameters);
parametersobject_O.append(tileparameters);
dataobject_O.append({"data":[d],"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
tile2datamap_O.update({tileid:[tile_cnt]});
tile_cnt+=1;
# pipeline:
if data1_pipeline:
data1_dict = {};
for data_export_id in data1_pipeline['data_export_id']:
if data_export_id is not None:
data1_dict[data_export_id]=[];
for d in data1_O:
if d['data_export_id'] is not None:
data1_dict[d['data_export_id']].append(d);
data1_keys = list(data1_dict.keys());
data1_keys.sort();
col_cnt = 0;
#for k,v in data1_dict.iteritems():
for k in data1_keys:
tileid = "tile" + str(tile_cnt);
colid = "col" + str(col_cnt);
tileheader = data1_dict[k][0]['pipeline_id'];
htmlid = "html" + str(tile_cnt);
#tileparameters = {'tileheader':tileheader,'tiletype':'html','tileid':tileid,'rowid':"row2",'colid':colid,
# 'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
#hrefparameters = {"hrefurl":'pipeline.html',"htmlkeymap":[data1_keymap],
# 'htmltype':'href_01','htmlid':htmlid};
tileparameters = {
'tileheader':tileheader,
'tiletype':'html',
'tileid':tileid,
'rowid':"row2",
'colid':colid,
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-6",
"formsubmitbuttonidtext":{'id':'submit1','text':'submit'}};
hrefparameters = {
"hrefurl":'pipeline.html',
"htmlkeymap":[data1_keymap],
'htmltype':'href_02',
'htmlid':htmlid};
tileparameters.update(hrefparameters);
parametersobject_O.append(tileparameters);
dataobject_O.append({"data":data1_dict[k],"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
tile2datamap_O.update({tileid:[tile_cnt]});
tile_cnt+=1;
col_cnt+=1;
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01MQResultsTable_metricPlot_js(self,experiment_id_I,sample_names_I=[],component_names_I=[],measurement_I='calculated_concentration',data_dir_I="tmp"):
''' export a metric plot
INPUT:
experiment_id_I = experiment_id
sample_names_I = sample_names
component_names_I = component names
measurement_I = measurement to plot, supports calculated_concentration, height_ratio, area_ratio, height, area, rt'''
# get the data:
data_O = [];
cnt = 0;
#Query unique sample_name/component_name for the analysis
# get sample names
if sample_names_I:
sample_names = sample_names_I;
else:
sample_names = [];
sample_types = ['Quality Control','Unknown','Standard','Blank'];
for st in sample_types:
sample_names_tmp = [];
sample_names_tmp = self.get_sampleNames_experimentIDAndSampleType(experiment_id_I,st);
sample_names.extend(sample_names_tmp);
# create database table
for sn in sample_names:
# get component names
if component_names_I:
component_names = component_names_I;
else:
component_names = [];
component_names = self.get_componentsNames_experimentIDAndSampleName(experiment_id_I,sn);
for cn in component_names:
# get the row
rows = {};
rows = self.get_row_sampleNameAndComponentName(sn,cn);
if rows:
rows['acquisition_date_and_time'] = self.convert_datetime2string(rows['acquisition_date_and_time'])
rows['index_'] = cnt;
rows['experiment_id']=experiment_id_I;
data_O.append(rows);
cnt+=1;
# get the sample_names_I
# dump chart parameters to a js files
data1_keys = [
'experiment_id',
'sample_name',
'component_name',
measurement_I,
'acquisition_date_and_time',
'sample_type',
];
data1_nestkeys = ['component_name'];
data1_keymap = {'xdata':'index_',
'ydata':measurement_I,
'serieslabel':'component_name',
'featureslabel':'sample_name'};
parameters = {"chart1margin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"chart1width":500,"chart1height":350,
"chart1title":"Metric Plot", "chart1x1axislabel":"sample_name","chart1y1axislabel":"measurement"}
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1','htmltype':'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'scatterlineplot2d_01',"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"sample_name","svgy1axislabel":"measurement_value",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Metric Plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Metric plot','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0,1],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01NormalizedAndAverages_js(self,
analysis_id_I,
sample_name_abbreviations_I=[],
sample_names_I=[],
component_names_I=[],
cv_threshold_I=40,
extracellular_threshold_I=80,
data_dir_I='tmp'):
'''export data_stage01_quantification_normalized and averages for visualization with ddt'''
calc = calculate_interface();
print('export_dataStage01Normalized_js...')
data_norm_broth = [];
data_norm_filtrate = [];
data_norm_combined = [];
data_ave = [];
#SPLIT 1:
#1 query unique calculated_concentration_units/sample_name_abbreviations/component_names/component_group_names/time_points/sample_names/sample_ids/sample_description
uniqueRows_all = self.getQueryResult_groupNormalizedAveragesSamples_analysisID_dataStage01QuantificationNormalizedAndAverages(
analysis_id_I
);
#2 filter in broth samples
uniqueRows = self.filter_groupNormalizedAveragesSamples_experimentID_dataStage01QuantificationNormalizedAndAverages_limsSampleAndSampleID(
uniqueRows_all,
calculated_concentration_units_I=[],
component_names_I=component_names_I,
component_group_names_I=[],
sample_names_I=sample_names_I,
sample_name_abbreviations_I=sample_name_abbreviations_I,
time_points_I=[],
);
if type(uniqueRows)==type(listDict()):
uniqueRows.convert_dataFrame2ListDict()
uniqueRows = uniqueRows.get_listDict();
replicates_tmp = {};#reorganize the data into a dictionary for quick traversal of the replicates
for uniqueRow_cnt,uniqueRow in enumerate(uniqueRows):
unique = (
uniqueRow['sample_name_abbreviation'],
uniqueRow['experiment_id'],
uniqueRow['time_point'],
uniqueRow['component_name'],
uniqueRow['calculated_concentration_units'])
if not unique in replicates_tmp.keys():
replicates_tmp[unique] = [];
replicates_tmp[unique].append(uniqueRow);
for unique,replicates in replicates_tmp.items():
#get data from averages once per sample_name_abbreviation/component_name
#print('exporting sample_name_abbreviation ' + replicates[0]['sample_name_abbreviation'] + " and component_name " + replicates[0]['component_name']);
# get the averages and %CV samples
row_ave = {};
row_ave = self.get_row_experimentIDAndSampleNameAbbreviationAndTimePointAndComponentNameAndCalculatedConcentrationCVAndExtracellularPercent_dataStage01Averages(
replicates[0]['experiment_id'],
replicates[0]['sample_name_abbreviation'],
replicates[0]['time_point'],
replicates[0]['component_name'],
cv_threshold_I=cv_threshold_I,
extracellular_threshold_I=extracellular_threshold_I);
if row_ave:
stdev = calc.convert_cv2StDev(row_ave['calculated_concentration_filtrate_average'],row_ave['calculated_concentration_filtrate_cv']);
row_ave['calculated_concentration_filtrate_lb'] = row_ave['calculated_concentration_filtrate_average']-stdev;
row_ave['calculated_concentration_filtrate_ub'] = row_ave['calculated_concentration_filtrate_average']+stdev;
stdev = calc.convert_cv2StDev(row_ave['calculated_concentration_broth_average'],row_ave['calculated_concentration_broth_cv']);
row_ave['calculated_concentration_broth_lb'] = row_ave['calculated_concentration_broth_average']-stdev;
row_ave['calculated_concentration_broth_ub'] = row_ave['calculated_concentration_broth_average']+stdev;
stdev = calc.convert_cv2StDev(row_ave['calculated_concentration_average'],row_ave['calculated_concentration_cv']);
row_ave['calculated_concentration_lb'] = row_ave['calculated_concentration_average']-stdev;
row_ave['calculated_concentration_ub'] = row_ave['calculated_concentration_average']+stdev;
row_ave['analysis_id'] = analysis_id_I;
# get data from normalized
filtrate_conc = [];
broth_conc = [];
for rep in replicates:
row = {};
row['analysis_id'] = analysis_id_I;
row['extracellular_percent'] = row_ave['extracellular_percent']
row['calculated_concentration_cv'] = row_ave['calculated_concentration_cv']
row.update(rep)
if rep['sample_desc'] == 'Filtrate':
data_norm_filtrate.append(row);
filtrate_conc.append(rep['calculated_concentration'])
if rep['sample_desc'] == 'Broth':
data_norm_broth.append(row);
broth_conc.append(rep['calculated_concentration'])
data_norm_combined.append(row);
#add data to aggregate and sample_name_abbreviations_all
if not broth_conc: broth_conc = [0];
if not filtrate_conc: filtrate_conc = [0];
row_ave['calculated_concentration_min']=min(broth_conc+filtrate_conc)
row_ave['calculated_concentration_max']=max(broth_conc+filtrate_conc)
row_ave['calculated_concentration_broth_min']=min(broth_conc)
row_ave['calculated_concentration_broth_max']=max(broth_conc)
row_ave['calculated_concentration_filtrate_min']=min(filtrate_conc)
row_ave['calculated_concentration_filtrate_max']=max(filtrate_conc)
data_ave.append(row_ave);
# dump chart parameters to a js files
data1_keys = ['analysis_id',
'experiment_id',
'sample_name',
'sample_id',
'sample_name_abbreviation',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_cv'
];
data1_nestkeys = ['component_name'];
data1_keymap = {'xdata':'component_name',
'ydata':'calculated_concentration',
#'ydatalb':'peakInfo_lb',
#'ydataub':'peakInfo_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'sample_name'};
data2_keys = ['analysis_id',
'experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_broth_cv'
];
data2_nestkeys = ['component_name'];
data2_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration_broth_average',
'ydatalb':'calculated_concentration_broth_lb',
'ydataub':'calculated_concentration_broth_ub',
'ydatamin':'calculated_concentration_broth_min',
'ydatamax':'calculated_concentration_broth_max',
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
data3_keys = ['analysis_id',
'experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_filtrate_cv',
];
data3_nestkeys = ['component_name'];
data3_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration_filtrate_average',
'ydatalb':'calculated_concentration_filtrate_lb',
'ydataub':'calculated_concentration_filtrate_ub',
'ydatamin':'calculated_concentration_filtrate_min',
'ydatamax':'calculated_concentration_filtrate_max',
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
data4_keys = ['analysis_id',
'experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_cv'
];
data4_nestkeys = ['component_name'];
data4_keymap = {'xdata':'component_name',
'ydata':'calculated_concentration_average',
'ydatamean':'calculated_concentration_average',
'ydatalb':'calculated_concentration_lb',
'ydataub':'calculated_concentration_ub',
#'ydatamin':'calculated_concentration_min',
#'ydatamax':'calculated_concentration_max',
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
# make the data object
dataobject_O = [{"data":data_norm_broth,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_norm_filtrate,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_norm_combined,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_ave,"datakeys":data2_keys,"datanestkeys":data2_nestkeys},
{"data":data_ave,"datakeys":data3_keys,"datanestkeys":data3_nestkeys},
{"data":data_ave,"datakeys":data4_keys,"datanestkeys":data4_nestkeys}];
# make the tile parameter objects for the normalized and averages
formtileparameters_averages_O = {'tileheader':'Filter menu averages','tiletype':'html','tileid':"filtermenu2",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters_averages_O = {'htmlid':'filtermenuform2',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit2','text':'submit'},"formresetbuttonidtext":{'id':'reset2','text':'reset'},"formupdatebuttonidtext":{'id':'update2','text':'update'}};
formtileparameters_averages_O.update(formparameters_averages_O);
# make the svg objects for the averages data
svgparameters_averages_broth_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data2_keymap,data1_keymap],
'svgid':'svg4',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_broth_O = {'tileheader':'Broth data','tiletype':'svg','tileid':"tile4",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_broth_O.update(svgparameters_averages_broth_O);
if data_norm_filtrate:
svgparameters_averages_filtrate_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data3_keymap,data1_keymap],
'svgid':'svg5',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_filtrate_O = {'tileheader':'Filtrate data','tiletype':'svg','tileid':"tile5",'rowid':"row2",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_filtrate_O.update(svgparameters_averages_filtrate_O);
else:
svgparameters_averages_filtrate_O = {"svgtype":'boxandwhiskersplot2d_01',"svgkeymap":[data3_keymap],
'svgid':'svg5',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_filtrate_O = {'tileheader':'Filtrate data','tiletype':'svg','tileid':"tile5",'rowid':"row2",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_filtrate_O.update(svgparameters_averages_filtrate_O);
svgparameters_averages_combined_O = {
#"svgtype":'boxandwhiskersplot2d_02',
"svgtype":'boxandwhiskersplot2d_01',
#"svgkeymap":[data4_keymap,data1_keymap],
"svgkeymap":[data4_keymap],
'svgid':'svg6',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_combined_O = {'tileheader':'Broth-Filtrate data','tiletype':'svg','tileid':"tile6",'rowid':"row2",'colid':"col3",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_combined_O.update(svgparameters_averages_combined_O);
# make the tables for the normalized and averages data
tableparameters_normalized_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_normalized_O = {'tileheader':'normalized data','tiletype':'table','tileid':"tile7",'rowid':"row4",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_normalized_O.update(tableparameters_normalized_O);
tableparameters_averages_O = {"tabletype":'responsivetable_01',
'tableid':'table2',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu2','tableresetbuttonid':'reset2','tablesubmitbuttonid':'submit2'};
tabletileparameters_averages_O = {'tileheader':'averages data','tiletype':'table','tileid':"tile8",'rowid':"row5",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_averages_O.update(tableparameters_averages_O);
parametersobject_O = [
formtileparameters_averages_O,
svgtileparameters_averages_broth_O,
svgtileparameters_averages_filtrate_O,
svgtileparameters_averages_combined_O,
tabletileparameters_normalized_O,
tabletileparameters_averages_O];
tile2datamap_O = {
"filtermenu2":[5],
"tile4":[3,0],
"tile5":[4,1],
#"tile6":[5,2],
"tile6":[5],
"tile7":[2],
"tile8":[5]
};
#if data_norm_filtrate: tile2datamap_O.update({"tile5":[4,1]})
#else: tile2datamap_O.update({"tile5":[4]})
filtermenuobject_O = [
#{"filtermenuid":"filtermenu1","filtermenuhtmlid":"filtermenuform1",
#"filtermenusubmitbuttonid":"submit1","filtermenuresetbuttonid":"reset1",
#"filtermenuupdatebuttonid":"update1"},
{"filtermenuid":"filtermenu2","filtermenuhtmlid":"filtermenuform2",
"filtermenusubmitbuttonid":"submit2","filtermenuresetbuttonid":"reset2",
"filtermenuupdatebuttonid":"update2"}
];
#
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_quantitationMethod_js(self,QMethod_id_I,component_names_I=[],data_dir_I='tmp'):
'''Export the quantitation and calibrators to ddt'''
#get the calibrator data
data_1 = [];
data_2 = [];
data_1a = [];
# get the sample names that were used to generate the calibration curve:
if component_names_I:
component_names = component_names_I;
else:
component_names = [];
component_names = self.get_components(QMethod_id_I);
for cn in component_names:
# get the quant method parameters for each component
fit,weighting,use_area = self.get_quantMethodParameters(QMethod_id_I,cn);
# get the sample names for that component
sample_names = [];
sample_names = self.get_sampleNames_QMethodIDAndComponentNameAndSampleType(QMethod_id_I,cn,sample_type_I='Standard');
if not sample_names: continue;
concentrations = []
ratios = [];
for sn in sample_names:
# get the quant method rows
row = {};
row = self.get_row_sampleNameAndComponentName(sn,cn);
if row and not row is None and not row['concentration_ratio'] is None:
if use_area: row['ratio'] = row['area_ratio'];
else: row['ratio'] = row['height_ratio'];
row['acquisition_date_and_time'] = None;
data_1.append(row);
concentrations.append(row['concentration_ratio']);
ratios.append(row['ratio']);
if not concentrations: continue;
# get the quant method statistics
row = {};
row = self.get_row_QMethodIDAndComponentNamequantitationMethod(QMethod_id_I,cn);
if row:
data_2.append(row);
# generate the line of best fit
min_ratio = min(ratios);
max_ratio = max(ratios);
index_min = [cnt for cnt,x in enumerate(ratios) if x == min_ratio][0];
index_max = [cnt for cnt,x in enumerate(ratios) if x == max_ratio][0];
conc_min = min(concentrations);
conc_max = max(concentrations);
sample_name_min = sample_names[index_min];
sample_name_max = sample_names[index_max];
data_1a.append({'concentration_ratio':row['lloq'],
'ratio':min_ratio,
'component_name':cn,
'sample_name':sample_name_min,
'id':QMethod_id_I});
data_1a.append({'concentration_ratio':row['uloq'],
'ratio':max_ratio,
'component_name':cn,
'sample_name':sample_name_max,
'id':QMethod_id_I});
# dump chart parameters to a js files
data1_keys = [
'id',
'concentration_ratio',
'sample_name',
'component_name',
'ratio',
];
data1_nestkeys = ['component_name'];
data1_keymap = {'xdata':'concentration_ratio',
'ydata':'ratio',
'serieslabel':'component_name',
'featureslabel':'sample_name'};
data2_keys = ['id',
'q1_mass',
'q3_mass',
'met_id',
'component_name',
'is_name',
'fit',
'weighting',
'intercept',
'slope',
'correlation',
'use_area',
'lloq',
'uloq',
'points',
];
data2_nestkeys = ['component_name'];
data2_keymap = {'xdata':'concentration_ratio',
'ydata':'ratio',
'serieslabel':'component_name',
'featureslabel':None};
parameters = {"chart1margin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"chart1width":500,"chart1height":350,
"chart1title":"Metric Plot", "chart1x1axislabel":"sample_name","chart1y1axislabel":"measurement"}
# make the data object
dataobject_O = [{"data":data_1,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_1a,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_2,"datakeys":data2_keys,"datanestkeys":data2_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1','htmltype':'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'scatterlineplot2d_01',"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"concentration_ratio","svgy1axislabel":"measurement_ratio",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Regression','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Regression Statistics','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0,1],"tile3":[2]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage02PhysiologySampledPointsSubsystemsDescriptiveStats_js(self,analysis_id_I,plot_points_I=True,vertical_I=True,data_dir_I='tmp'):
'''Export data for a box and whiskers plot
INPUT:
analysis_id_I = string,
plot_points_I = boolean, default=False, raw data points will not be plotted on the same plot
vertical_I = boolean, default=True, orient the boxes vertical as opposed to horizontal
'''
physiology_analysis_query=stage02_physiology_analysis_query(self.session,self.engine,self.settings);
physiology_analysis_query.initialize_supportedTables();
data_O = [];
data_points_O = [];
#get the analysis information
simulation_ids = [];
simulation_ids = physiology_analysis_query.get_simulationID_analysisID_dataStage02PhysiologyAnalysis(analysis_id_I);
#get the data for the analysis
if plot_points_I:
#get the replicate data for the analysis
#TODO... (copy code from above io function)
#data_points_O = [];
#data_points_O = quantification_dataPreProcessing_replicates_query.get_rowsAndSampleNameAbbreviations_analysisID_dataStage02QuantificationDataPreProcessingReplicates(analysis_id_I);
for simulation in simulation_ids:
data_tmp = self.get_rows_simulationID_dataStage02PhysiologySampledSubsystemData(simulation);
data_O.extend(data_tmp);
else:
for simulation in simulation_ids:
data_tmp = self.get_rows_simulationID_dataStage02PhysiologySampledSubsystemData(simulation);
data_O.extend(data_tmp);
# make the tile objects
parametersobject_O = [];
tile2datamap_O = {};
filtermenuobject_O = [];
dataobject_O = [];
# dump chart parameters to a js files
data1_keys = [
#'analysis_id',
'simulation_id',
'simulation_dateAndTime',
'subsystem_id',
'flux_units',
];
data1_nestkeys = ['subsystem_id'];
data2_keys = [
#'analysis_id',
'simulation_id',
'simulation_dateAndTime',
'rxn_id',
'flux_units',
];
data2_nestkeys = ['subsystem_id'];
if vertical_I:
data1_keymap = {
'xdata':'subsystem_id',
'ydata':'sampling_ave',
'ydatamean':'sampling_ave',
'ydatalb':'sampling_lb',
'ydataub':'sampling_ub',
'ydatamin':'sampling_min',
'ydatamax':'sampling_max',
'ydataiq1':'sampling_iq_1',
'ydataiq3':'sampling_iq_3',
'ydatamedian':'sampling_median',
'serieslabel':'simulation_id',
'featureslabel':'subsystem_id'};
data2_keymap = {
'xdata':'subsystem_id',
'ydata':'sampling_points',
'serieslabel':'simulation_id',
'featureslabel':'subsystem_id'};
else:
data1_keymap = {
'ydata':'subsystem_id',
'xdatamean':'sampling_ave',
'xdata':'sampling_ave',
'xdatalb':'sampling_lb',
'xdataub':'sampling_ub',
'xdatamin':'sampling_min',
'xdatamax':'sampling_max',
'xdataiq1':'sampling_iq_1',
'xdataiq3':'sampling_iq_3',
'xdatamedian':'sampling_median',
'serieslabel':'simulation_id',
'featureslabel':'subsystem_id'};
data2_keymap = {
'ydata':'subsystem_id',
'xdata':'sampling_points',
'serieslabel':'simulation_id',
'featureslabel':'subsystem_id'};
# make the data object
dataobject_O.append({"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
parametersobject_O.append(formtileparameters_O);
if plot_points_I:
tile2datamap_O.update({"filtermenu1":[1]});
else:
tile2datamap_O.update({"filtermenu1":[0]});
#make the svg object
if plot_points_I and vertical_I:
dataobject_O.append({"data":data_points_O,"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_02',
"svgkeymap":[data1_keymap,data2_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"subsystem_id",
"svgy1axislabel":"sampling points",
"svgdata2pointsradius":5.0,
};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0,1]});
elif not plot_points_I and vertical_I:
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"subsystem_id","svgy1axislabel":"sampling points",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0]});
elif plot_points_I and not vertical_I:
dataobject_O.append({"data":data_points_O,"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
svgparameters_O = {"svgtype":'horizontalBoxAndWhiskersPlot2d_02',
"svgkeymap":[data1_keymap,data2_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"sampling points",
"svgy1axislabel":"rxn_id",
"svgdata2pointsradius":5.0,
};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0,1]});
elif not plot_points_I and not vertical_I:
svgparameters_O = {"svgtype":'horizontalBoxAndWhiskersPlot2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"sampling points",
"svgy1axislabel":"subsystem_id",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0]});
#make the table object
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'descriptiveStats','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O.append(tabletileparameters_O);
tile2datamap_O.update({"tile3":[0]});
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage02IsotopomerFittedNetFluxDifferences_js(self,analysis_id_I = None,data_dir_I="tmp"):
'''Plot the flux differences and fold_change as bar plots for a given analysis
Input:
analysis_id_I = string
data_dir_I = output .js file directory and filename
DDT tiles:
1. filter menu
2. horizontal bar plot of flux differences
3. horizontal bar plot of flux fold_change
4. table
'''
# get the data
data_O =[];
flux_data = [];
flux_data = self.get_rows_analysisID_dataStage02IsotopomerFittedNetFluxDifferences(analysis_id_I);
# convert dataAndTime to string types
for i,row in enumerate(flux_data):
row['simulation_dateAndTime_1'] = self.convert_datetime2string(row['simulation_dateAndTime_1']);
row['simulation_dateAndTime_2'] = self.convert_datetime2string(row['simulation_dateAndTime_2']);
#row['flux_units'] = row['flux_units'].replace('*','x');
if row['significant']: row['significant'] = 'Yes';
else: row['significant'] = 'No';
data_O.append(row);
# dump chart parameters to a js files
data1_keys = ['simulation_id_1','simulation_dateAndTime_1','simulation_id_2','simulation_dateAndTime_2','rxn_id','flux_units','significant'
];
data1_nestkeys = ['rxn_id'];
data1_keymap = {'xdata':'flux_distance',
'ydata':'rxn_id',
'serieslabel':'simulation_id_2',
'featureslabel':'rxn_id'
};
data2_keymap = {'xdata':'fold_change_geo',
'ydata':'rxn_id',
'serieslabel':'simulation_id_2',
'featureslabel':'rxn_id'
};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
# tile 1: form (row 1, col1)
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
# tile 2: vertical bars plot of the flux_difference (row 2, col 1)
svgparameters1_O = {"svgtype":'horizontalbarschart2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 250, 'bottom': 50, 'left': 50 },
"svgwidth":350,"svgheight":900,
"svgx1axislabel":"flux_distance","svgy1axislabel":"rxn_id",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters1_O = {'tileheader':'Flux distance','tiletype':'svg','tileid':"tile1",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
svgtileparameters1_O.update(svgparameters1_O);
# tile 3: vertical bars plot of the flux_difference (row 2, col 2)
svgparameters2_O = {"svgtype":'horizontalbarschart2d_01',"svgkeymap":[data2_keymap],
'svgid':'svg2',
"svgmargin":{ 'top': 50, 'right': 250, 'bottom': 50, 'left': 50 },
"svgwidth":350,"svgheight":900,
"svgx1axislabel":"fold_change","svgy1axislabel":"rxn_id",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters2_O = {'tileheader':'Fold change','tiletype':'svg','tileid':"tile2",'rowid':"row2",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
svgtileparameters2_O.update(svgparameters2_O);
# tile 4: table of data (row 3, col 1)
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Flux difference','tiletype':'table','tileid':"tile3",'rowid':"row3",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,
svgtileparameters1_O,
svgtileparameters2_O,
tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],
"tile1":[0],
"tile2":[0],
"tile3":[0]};
# dump the data to a json file
data_str = 'var ' + 'data' + ' = ' + json.dumps(dataobject_O) + ';';
parameters_str = 'var ' + 'parameters' + ' = ' + json.dumps(parametersobject_O) + ';';
tile2datamap_str = 'var ' + 'tile2datamap' + ' = ' + json.dumps(tile2datamap_O) + ';';
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_visualizationProject_js(self,project_id_I,data_dir_I="tmp"):
"""export visualization_project for visualization"""
print("exporting visualization_project...")
# query the project info
data1_project = {};
data1_project = self.get_project_projectID_visualizationProject(project_id_I);
data1_O = [];
data1_O = self.get_rows_projectID_visualizationProject(project_id_I);
# query the project description
data2_O = [];
data2_O = self.get_rows_projectID_visualizationProjectDescription(project_id_I);
# query the project status
data3_O = [];
data3_O = self.get_rows_projectID_visualizationProjectStatus(project_id_I);
# data parameters
data1_keys = ['analysis_id','data_export_id','pipeline_id'#,'container_export_id'
];
data1_nestkeys = ['data_export_id'];
data1_keymap = {'buttonparameter':'data_export_id','liparameter':'analysis_id',
'buttontext':'data_export_id','litext':'analysis_id'};
data2_keys = ['project_id','project_section','project_heading','project_tileorder'
];
data2_nestkeys = ['project_id'];
data2_keymap = {'htmlmediasrc':'project_media','htmlmediaalt':'',
'htmlmediahref':'project_href','htmlmediaheading':'project_heading',
'htmlmediaparagraph':'project_paragraph'};
data3_keys = ['project_id','pipeline_id','pipeline_progress'
];
data3_nestkeys = ['pipeline_id'];
data3_keymap = {
#'xdata':'pipeline_id',
#'ydata':'pipeline_progress',
'xdata':'pipeline_progress',
'ydata':'pipeline_id',
'serieslabel':'pipeline_id',
'featureslabel':'pipeline_id',
'ydatalb':None,
'ydataub':None};
# make the data, parameters, and tile2datamap variables:
dataobject_O = [];
parametersobject_O = [];
tile2datamap_O = {};
tile_cnt = 0;
row_cnt = 1;
# project_status:
if data3_O:
cnt = 1;
tileid = "tile" + str(tile_cnt);
colid = "col" + str(cnt);
rowid = "row" + str(row_cnt);
# make the tile parameter objects
# tile 0: form
formtileparameters_O = {
'tileheader':'Filter menu',
'tiletype':'html',
'tileid':"filtermenu1",
'rowid':rowid,
'colid':colid,
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-4"};
formparameters_O = {
'htmlid':'filtermenuform1',
'htmltype':'form_01',
"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},
"formresetbuttonidtext":{'id':'reset1','text':'reset'},
"formupdatebuttonidtext":{'id':'update1','text':'update'}
};
formtileparameters_O.update(formparameters_O);
dataobject_O.append({"data":data3_O,"datakeys":data3_keys,"datanestkeys":data3_nestkeys});
parametersobject_O.append(formtileparameters_O);
tile2datamap_O.update({"filtermenu1":[tile_cnt]});
cnt+=1;
svgtileid = "tilesvg"+str(tile_cnt);
svgid = 'svg'+str(tile_cnt);
colid = "col" + str(cnt);
# make the svg object
svgparameters1_O = {
#"svgtype":'verticalpieschart2d_01',
#"svgtype":'verticalbarschart2d_01',
"svgtype":'horizontalbarschart2d_01',
"svgkeymap":[data3_keymap],
'svgid':'svg'+str(cnt),
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 150 },
"svgwidth":350,
"svgheight":250,
"svgy1axislabel":"fraction"
};
svgtileparameters1_O = {
'tileheader':'Project status',
'tiletype':'svg',
'tileid':svgtileid,
'rowid':rowid,
'colid':colid,
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-8"};
svgtileparameters1_O.update(svgparameters1_O);
parametersobject_O.append(svgtileparameters1_O);
tile2datamap_O.update({svgtileid:[tile_cnt]});
tile_cnt+=1;
row_cnt+=1;
# project_description:
if data2_O:
for i,d in enumerate(data2_O):
tileid = "tile" + str(tile_cnt);
colid = "col" + str(i);
rowid = "row" + str(row_cnt);
tileheader = d['project_section'];
htmlid = "html" + str(tile_cnt);
tileparameters = {'tileheader':tileheader,'tiletype':'html','tileid':tileid,'rowid':rowid,'colid':colid,
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
htmlparameters={"htmlkeymap":[data2_keymap],
'htmltype':'media_01','htmlid':htmlid};
tileparameters.update(htmlparameters);
parametersobject_O.append(tileparameters);
dataobject_O.append({"data":[d],"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
tile2datamap_O.update({tileid:[tile_cnt]});
tile_cnt+=1;
row_cnt+=1;
# project:
if data1_project:
data1_dict = {};
for data_export_id in data1_project['data_export_id']:
data1_dict[data_export_id]=[];
for d in data1_O:
data1_dict[d['data_export_id']].append(d);
data1_keys = list(data1_dict.keys());
data1_keys.sort();
col_cnt = 0;
#for k,v in data1_dict.iteritems():
for k in data1_keys:
tileid = "tile" + str(tile_cnt);
colid = "col" + str(col_cnt);
rowid = "row" + str(row_cnt);
tileheader = data1_dict[k][0]['pipeline_id'];
htmlid = "html" + str(tile_cnt);
#tileparameters = {'tileheader':tileheader,'tiletype':'html','tileid':tileid,'rowid':"row2",'colid':colid,
# 'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
#hrefparameters = {"hrefurl":'project.html',"htmlkeymap":[data1_keymap],
# 'htmltype':'href_01','htmlid':htmlid};
tileparameters = {'tileheader':tileheader,'tiletype':'html','tileid':tileid,'rowid':rowid,'colid':colid,
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6","formsubmitbuttonidtext":{'id':'submit1','text':'submit'}};
hrefparameters = {"hrefurl":'project.html',"htmlkeymap":[data1_keymap],
'htmltype':'href_02','htmlid':htmlid};
tileparameters.update(hrefparameters);
parametersobject_O.append(tileparameters);
dataobject_O.append({"data":data1_dict[k],"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
tile2datamap_O.update({tileid:[tile_cnt]});
tile_cnt+=1;
col_cnt+=1;
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage02PhysiologyGraphDataShortestPathStats_js(self,
analysis_id_I,
plot_points_I=False,
vertical_I=True,
data_dir_I='tmp'):
'''export descriptive stats of shortest paths'''
data_O = [];
data_points_O = [];
if plot_points_I:
#get the replicate data for the analysis
#TODO... (copy code from above io function)
#data_points_O = [];
#data_points_O = quantification_dataPreProcessing_replicates_query.get_rowsAndSampleNameAbbreviations_analysisID_dataStage02QuantificationDataPreProcessingReplicates(analysis_id_I);
data_tmp = self.get_rows_analysisID_dataStage02PhysiologyGraphDataShortestPathStats(analysis_id_I);
for d in data_tmp:
d['path_id'] = d['path_start'] + '-->' + d['path_stop']
if np.isnan(d['path_ci_lb']):d['path_ci_lb']=d['path_average'];
if np.isnan(d['path_ci_ub']):d['path_ci_ub']=d['path_average'];
data_O.append(d);
else:
data_tmp = self.get_rows_analysisID_dataStage02PhysiologyGraphDataShortestPathStats(analysis_id_I);
for d in data_tmp:
d['path_id'] = d['path_start'] + '-->' + d['path_stop']
if np.isnan(d['path_ci_lb']):d['path_ci_lb']=d['path_average'];
if np.isnan(d['path_ci_ub']):d['path_ci_ub']=d['path_average'];
data_O.append(d);
# make the tile objects
parametersobject_O = [];
tile2datamap_O = {};
filtermenuobject_O = [];
dataobject_O = [];
# dump chart parameters to a js files
data1_keys = [
#'analysis_id',
'simulation_id',
'path_start',
'path_stop',
'algorithm',
];
data1_nestkeys = ['path_id'];
data2_keys = [
#'analysis_id',
'simulation_id',
'path_start',
'path_stop',
'algorithm',
];
data2_nestkeys = ['path_id'];
if vertical_I:
data1_keymap = {
'xdata':'path_id',
'ydata':'path_average',
'ydatamean':'path_average',
'ydatalb':'path_ci_lb',
'ydataub':'path_ci_ub',
'ydatamin':'path_min',
'ydatamax':'path_max',
'ydataiq1':'path_iq_1',
'ydataiq3':'path_iq_3',
'ydatamedian':'path_median',
'serieslabel':'simulation_id',
#'serieslabel':'algorithm',
'featureslabel':'path_id'};
data2_keymap = {
'xdata':'path_id',
'ydata':'path_length',
'serieslabel':'simulation_id',
#'serieslabel':'algorithm',
'featureslabel':'path_id'};
else:
data1_keymap = {
'ydata':'path_id',
'xdatamean':'path_average',
'xdata':'path_average',
'xdatalb':'path_ci_lb',
'xdataub':'path_ci_ub',
'xdatamin':'path_min',
'xdatamax':'path_max',
'xdataiq1':'path_iq_1',
'xdataiq3':'path_iq_3',
'xdatamedian':'path_median',
#'serieslabel':'simulation_id',
'serieslabel':'algorithm',
'featureslabel':'path_id'};
data2_keymap = {
'ydata':'path_id',
'xdata':'path_length',
#'serieslabel':'simulation_id',
'serieslabel':'algorithm',
'featureslabel':'path_id'};
# make the data object
dataobject_O.append({"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
parametersobject_O.append(formtileparameters_O);
if plot_points_I:
tile2datamap_O.update({"filtermenu1":[1]});
else:
tile2datamap_O.update({"filtermenu1":[0]});
#make the svg object
if plot_points_I and vertical_I:
dataobject_O.append({"data":data_points_O,"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_02',
"svgkeymap":[data1_keymap,data2_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"path id",
"svgy1axislabel":"path length",
"svgdata2pointsradius":5.0,
};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0,1]});
elif not plot_points_I and vertical_I:
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"path id",
"svgy1axislabel":"path length",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0]});
elif plot_points_I and not vertical_I:
dataobject_O.append({"data":data_points_O,"datakeys":data2_keys,"datanestkeys":data2_nestkeys});
svgparameters_O = {"svgtype":'horizontalBoxAndWhiskersPlot2d_02',
"svgkeymap":[data1_keymap,data2_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"path length",
"svgy1axislabel":"path id",
"svgdata2pointsradius":5.0,
};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0,1]});
elif not plot_points_I and not vertical_I:
svgparameters_O = {"svgtype":'horizontalBoxAndWhiskersPlot2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"path length",
"svgy1axislabel":"path id",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({"tile2":[0]});
#make the table object
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'descriptiveStats','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O.append(tabletileparameters_O);
tile2datamap_O.update({"tile3":[0]});
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01AleTrajectories_js(self,analysis_id_I,fit_func_I='lowess',data_dir_I="tmp"):
"""export data_stage01_ale_trajectories for visualization"""
print("exporting data_stage01_ale_trajectories...")
calc = calculate_smoothingFunctions();
# query the analysis info
experiment_ids,ale_ids = [],[];
experiment_ids,ale_ids = self.get_experimentIDAndALEID_analysisID_dataStage01ResequencingAnalysis(analysis_id_I);
# collect the data and calculate the fitted trajectories
data_O = [];
data1_O={};
data2_O={};
data1_O['ale_time'] = [];
data1_O['generations'] = [];
data1_O['ccd'] = [];
data2_O['ale_time'] = [];
data2_O['generations'] = [];
data2_O['ccd'] = [];
for sna_cnt,sna in enumerate(ale_ids):
#query growth rates and times
growth_rates = [];
growth_rates = self.get_rows_experimentIDAndALEID_dataStage01AleTrajectories(experiment_ids[sna_cnt],sna)
ale_time_units = growth_rates[0]['ale_time_units'];
rate_units = growth_rates[0]['rate_units'];
# parse out the data for each ale_id
x,x_g,x_ccd,y=[],[],[],[];
for k in growth_rates:
x.append(k['ale_time'])
x_g.append(k['generations'])
x_ccd.append(k['ccd'])
y.append(k['rate'])
data1_O['ale_time'].append({'ale_id':sna,
'ale_time':k['ale_time'],
'ale_time_units':ale_time_units,
'rate':k['rate'],
'rate_units':rate_units,
'used_':True,
'comment_':k['comment_']});
data1_O['generations'].append({'ale_id':sna,
'generations':k['generations'],
'rate':k['rate'],
'rate_units':rate_units,
'used_':True,
'comment_':k['comment_']});
data1_O['ccd'].append({'ale_id':sna,
'ccd':k['ccd'],
'rate':k['rate'],
'rate_units':rate_units,
'used_':True,
'comment_':k['comment_']});
data_O.append({'ale_id':sna,
'ale_time':k['ale_time'],
'ale_time_units':ale_time_units,
'generations':k['generations'],
'ccd':k['ccd'],
'rate':k['rate'],
'rate_units':rate_units,
'used_':True,
'comment_':k['comment_']});
# generate the fitted data for ale_time
x_fit,y_fit=[],[];
x_fit,y_fit=calc.fit_trajectories(x,y,fit_func_I,plot_fit_I=False);
# restructure into input for d3
for i,x in enumerate(x_fit):
data2_O['ale_time'].append({'ale_id':sna,
'ale_time':x_fit[i],
'ale_time_units':ale_time_units,
'rate':y_fit[i],
'rate_units':rate_units,
'used_':True,
'comment_':None});
# generate the fitted data for generations
x_g_fit,y_g_fit=[],[];
x_g_fit,y_g_fit=calc.fit_trajectories(x_g,y,fit_func_I,plot_fit_I=False);
# restructure into input for d3
for i,x in enumerate(x_g_fit):
data2_O['generations'].append({'ale_id':sna,
'generations':x_g_fit[i],
'rate':y_g_fit[i],
'rate_units':rate_units,
'used_':True,
'comment_':None});
# generate the fitted data for ccd
x_ccd_fit,y_ccd_fit=[],[];
x_ccd_fit,y_ccd_fit=calc.fit_trajectories(x_ccd,y,fit_func_I,plot_fit_I=False);
# restructure into input for d3
for i,x in enumerate(x_ccd_fit):
data2_O['ccd'].append({'ale_id':sna,
'ccd':x_ccd_fit[i],
'rate':y_ccd_fit[i],
'rate_units':rate_units,
'used_':True,
'comment_':None});
#initialize ddt objects
dataobject_O = [];
parametersobject_O = [];
tile2datamap_O = {};
filtermenuobject_O=None;
# make the tile parameter objects
# tile 1: form
formtileparameters_O = {
'tileheader':'Filter menu',
'tiletype':'html',
'tileid':"filtermenu1",
'rowid':"row1",
'colid':"col1",
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-4"};
formparameters_O = {
"htmltype":'form_01',
"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},
"formresetbuttonidtext":{'id':'reset1','text':'reset'},
"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
parametersobject_O.append(formtileparameters_O)
data1_keys = ['ale_id'];
data1_nestkeys = ['ale_id'];
data1_keymap = {'xdata':'ale_time','ydata':'rate','serieslabel':'ale_id','featureslabel':''};
dataobject_O.append({"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
tile2datamap_O.update({"filtermenu1":[0]});
# tile 2-4: trajectors for ale_time, generations, and CCDs
cnt = 1;
data_cnt = 1;
for k in data1_O.keys():
tileid = "tile"+str(cnt);
svgid = "svg"+str(cnt);
colid = "col"+str(cnt+1);
if k=='ale_time':
svgx1axislabel = "time (days)";
else:
svgx1axislabel = k;
data1_keys = ['ale_id'];
data1_nestkeys = ['ale_id'];
data1_keymap = {
'xdata':k,
'ydata':'rate',
'serieslabel':'ale_id',
'featureslabel':''};
dataobject_O.append({"data":data1_O[k],"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
dataobject_O.append({"data":data2_O[k],"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
svgparameters_O = {
"svgtype":'scatterlineplot2d_01',
"svgkeymap":[data1_keymap,data1_keymap],
'svgid':svgid,
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":svgx1axislabel,
"svgy1axislabel":"growth rate (hr-1)",
};
svgtileparameters_O = {
'tileheader':'ALE trajectories',
'tiletype':'svg',
'tileid':tileid,
'rowid':"row1",
'colid':colid,
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
parametersobject_O.append(svgtileparameters_O);
tile2datamap_O.update({tileid:[data_cnt,data_cnt+1]});
data_cnt+=2;
cnt+=1;
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01IsotopomerNormalized_js(self,experiment_id_I,sample_names_I=[],sample_name_abbreviations_I=[],time_points_I=[],scan_types_I=[],met_ids_I=[],data_dir_I="tmp",
single_plot_I = True):
"""Export data_stage01_isotopomer_normalized to js file"""
mids = mass_isotopomer_distributions();
# get the data
data_O = [];
data_dict_O = {};
sample_names_O = [];
# get time points
if time_points_I:
time_points = time_points_I;
else:
time_points = self.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I);
for tp in time_points:
print('Plotting precursor and product spectrum from isotopomer normalized for time-point ' + str(tp));
if sample_names_I:
sample_abbreviations = [];
sample_types = ['Unknown','QC'];
sample_types_lst = [];
for sn in sample_names_I:
for st in sample_types:
sample_abbreviations_tmp = [];
sample_abbreviations_tmp = self.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn);
sample_abbreviations.extend(sample_abbreviations_tmp);
sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]);
elif sample_name_abbreviations_I:
sample_abbreviations = [];
sample_types = ['Unknown','QC'];
sample_types_lst = [];
for sn in sample_name_abbreviations_I:
for st in sample_types:
sample_abbreviations_tmp = [];
sample_abbreviations_tmp = self.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleNameAbbreviation_dataStage01Normalized(experiment_id_I,st,tp,sn);
sample_abbreviations.extend(sample_abbreviations_tmp);
sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]);
# query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized
else:
# get sample names and sample name abbreviations
sample_abbreviations = [];
sample_types = ['Unknown','QC'];
sample_types_lst = [];
for st in sample_types:
sample_abbreviations_tmp = [];
sample_abbreviations_tmp = self.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp);
sample_abbreviations.extend(sample_abbreviations_tmp);
sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]);
for sna_cnt,sna in enumerate(sample_abbreviations):
print('Plotting precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna);
# get the scan_types
if scan_types_I:
scan_types = [];
scan_types_tmp = [];
scan_types_tmp = self.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]);
scan_types = [st for st in scan_types_tmp if st in scan_types_I];
else:
scan_types = [];
scan_types = self.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]);
for scan_type in scan_types:
print('Plotting precursor and product spectrum for scan type ' + scan_type)
# met_ids
if not met_ids_I:
met_ids = [];
met_ids = self.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \
experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type);
else:
met_ids = met_ids_I;
if not(met_ids): continue #no component information was found
for met in met_ids:
print('Plotting precursor and product spectrum for metabolite ' + met);
if sample_names_I:
sample_names = sample_names_I;
else:
sample_names,replicate_numbers,sample_types = [],[],[];
sample_names,replicate_numbers,sample_types = self.get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndMetIDAndTimePointAndScanType_dataStage01Normalized( \
experiment_id_I,sna,met,tp,scan_type);
if not(replicate_numbers): continue; #no replicates found
for rep_cnt,rep in enumerate(replicate_numbers):
#if not(sample_names): continue; #no replicates found
#for sn_cnt,sn in enumerate(sample_names):
print('Plotting precursor and product spectrum for replicate_number ' + str(rep));
#print('Plotting precursor and product spectrum for sample_name ' + sn);
#sample_names_O.append(sn);
#get data
peakData_I = {};
peakData_I = self.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \
experiment_id_I,sna,tp,scan_type,met,rep);
#peakData_I = self.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndSampleName_dataStage01Normalized( \
# experiment_id_I,sna,tp,scan_type,met,sn);
if peakData_I:
data_sample_names_tmp=[];
fragment_formulas = list(peakData_I.keys());
peakSpectrum_corrected, peakSpectrum_normalized = mids.extract_peakList_normMax(\
peakData_I, fragment_formulas, True);
for fragment_formula in fragment_formulas:
for fragment_mass,intensity_normalized in peakSpectrum_normalized[fragment_formula].items():
sample_name = sna + "_" + str(rep);
sample_names_O.append(sample_name);
fragment_id = mids.make_fragmentID(met,fragment_formula,fragment_mass);
intensity = 0.0;
if intensity_normalized:
intensity = intensity_normalized;
data_tmp = {
'experiment_id':experiment_id_I,
'sample_name':sample_name,
#'sample_name':sn,
'sample_name_abbreviation':sna,
'sample_type':sample_types_lst[sna_cnt],
'time_point':tp,
#'dilution':dil,
'replicate_number':rep,
'met_id':met,
'fragment_formula':fragment_formula,
'fragment_mass':fragment_mass,
'intensity_normalized':intensity,
'intensity_normalized_units':"normMax",
'scan_type':scan_type,
'fragment_id':fragment_id};
data_O.append(data_tmp);
if not sample_name in data_dict_O.keys():
data_dict_O[sample_name] = [];
data_dict_O[sample_name].append(data_tmp);
else:
data_dict_O[sample_name].append(data_tmp);
# record the unique sample names:
sample_names_unique = list(set(sample_names_O));
sample_names_unique.sort();
# get the table data
data_table_O = [];
if time_points_I:
time_points = time_points_I;
else:
time_points = self.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I);
for tp in time_points:
print('Tabulating precursor and product spectrum from isotopomer normalized for time-point ' + str(tp));
dataListUpdated = [];
# get dilutions
dilutions = [];
dilutions = self.get_sampleDilution_experimentIDAndTimePoint_dataStage01Normalized(experiment_id_I,tp);
for dil in dilutions:
print('Tabulating precursor and product spectrum from isotopomer normalized for dilution ' + str(dil));
if sample_names_I:
sample_abbreviations = [];
sample_types = ['Unknown','QC'];
for sn in sample_names_I:
for st in sample_types:
sample_abbreviations_tmp = [];
sample_abbreviations_tmp = self.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndDilutionAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,dil,sn);
sample_abbreviations.extend(sample_abbreviations_tmp);
elif sample_name_abbreviations_I:
sample_abbreviations = sample_name_abbreviations_I;
else:
# get sample names and sample name abbreviations
sample_abbreviations = [];
sample_types = ['Unknown','QC'];
for st in sample_types:
sample_abbreviations_tmp = [];
sample_abbreviations_tmp = self.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndDilution_dataStage01Normalized(experiment_id_I,st,tp,dil);
sample_abbreviations.extend(sample_abbreviations_tmp);
for sna_cnt,sna in enumerate(sample_abbreviations):
print('Tabulating precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna);
# get the scan_types
if scan_types_I:
scan_types = scan_types_I;
else:
scan_types = [];
scan_types = self.get_scanTypes_experimentIDAndTimePointAndDilutionAndSampleAbbreviations_dataStage01Normalized(experiment_id_I,tp,dil,sna);
for scan_type in scan_types:
print('Tabulting precursor and product spectrum for scan type ' + scan_type)
# met_ids
if not met_ids_I:
met_ids = [];
met_ids = self.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndDilutionAndScanType_dataStage01Normalized( \
experiment_id_I,sna,tp,dil,scan_type);
else:
met_ids = met_ids_I;
if not(met_ids): continue #no component information was found
for met in met_ids:
# get the data
data = [];
data = self.get_rows_experimentIDAndSampleAbbreviationAndTimePointAndDilutionAndScanTypeAndMetID_dataStage01Normalized( \
experiment_id_I,sna,tp,dil,scan_type,met);
for d in data:
d['sample_name'] = d['sample_name_abbreviation']+"_"+str(d['replicate_number']);
d['fragment_id'] = mids.make_fragmentID(d['met_id'],d['fragment_formula'],d['fragment_mass']);
data_table_O.extend(data);
# visualization parameters
data1_keys = ['sample_name','sample_name_abbreviation',
'sample_type',
'met_id','time_point','fragment_formula','fragment_mass','scan_type','fragment_id'];
data1_nestkeys = [
#'fragment_id',
'fragment_mass'
];
data1_keymap = {
#'xdata':'fragment_id',
'xdata':'fragment_mass',
'ydata':'intensity_normalized',
'serieslabel':'scan_type',
#'serieslabel':'sample_name', #single plot
#'featureslabel':'fragment_id',
'featureslabel':'fragment_mass',
'tooltipdata':'sample_name_abbreviation',
'ydatalb':None,
'ydataub':None};
# initialize the ddt objects
dataobject_O = [];
parametersobject_O = [];
tile2datamap_O = {};
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
dataobject_O.append({"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
parametersobject_O.append(formtileparameters_O);
tile2datamap_O.update({"filtermenu1":[0]});
if not single_plot_I:
rowcnt = 1;
colcnt = 1;
cnt = 0;
for sn in sample_names_unique:
svgtileid = "tilesvg"+str(cnt);
svgid = 'svg'+str(cnt);
iter=cnt+1; #start at 1
if (cnt % 2 == 0):
rowcnt = rowcnt+1;#even
colcnt = 1;
else:
colcnt = colcnt+1;
# make the svg object
svgparameters1_O = {"svgtype":'verticalbarschart2d_01',"svgkeymap":[data1_keymap],
#'svgid':'svg1',
'svgid':'svg'+str(cnt),
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":350,"svgheight":250,"svgy1axislabel":"intensity (norm)",
};
svgtileparameters1_O = {'tileheader':sn,'tiletype':'svg',
#'tileid':"tile2",
'tileid':svgtileid,
#'rowid':"row1",
'rowid':"row"+str(rowcnt),
#'colid':"col1",
'colid':"col"+str(colcnt),
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
svgtileparameters1_O.update(svgparameters1_O);
parametersobject_O.append(svgtileparameters1_O);
tile2datamap_O.update({svgtileid:[iter]});
dataobject_O.append({"data":data_dict_O[sn],"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
cnt+=1;
else:
cnt = 0;
svgtileid = "tilesvg"+str(cnt);
svgid = 'svg'+str(cnt);
rowcnt = 2;
colcnt = 1;
# make the svg object
svgparameters1_O = {"svgtype":'verticalbarschart2d_01',"svgkeymap":[data1_keymap],
#'svgid':'svg1',
'svgid':'svg'+str(cnt),
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,"svgy1axislabel":"intensity (norm)",
};
svgtileparameters1_O = {'tileheader':'Isotopomer distribution','tiletype':'svg',
#'tileid':"tile2",
'tileid':svgtileid,
#'rowid':"row1",
#'colid':"col1",
'rowid':"row"+str(rowcnt),
'colid':"col"+str(colcnt),
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters1_O.update(svgparameters1_O);
parametersobject_O.append(svgparameters1_O);
tile2datamap_O.update({svgtileid:[0]});
iter+=1;
# make the table object
tableparameters1_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
#"tableheaders":[],
"tableclass":"table table-condensed table-hover",
'tableformtileid':'tile1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters1_O = {'tileheader':'Isotopomer distribution','tiletype':'table','tileid':"tabletile1",
'rowid':"row"+str(rowcnt+1),
'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters1_O.update(tableparameters1_O);
#dataobject_O.append({"data":data_table_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
parametersobject_O.append(tabletileparameters1_O);
tile2datamap_O.update({"tabletile1":[0]})
#filtermenunsvgtable = ddt_container_filterMenuNSvgTable();
#filtermenunsvgtable.make_filterMenuNSvgTable(
# data_filtermenu=data_O,
# data_filtermenu_keys=[data1_keymap],
# data_filtermenu_nestkeys=data1_nestkeys,
# data_filtermenu_keymap=[data1_keymap],
# data_svg_keys=[data1_keymap],
# data_svg_nestkeys=data1_nestkeys,
# data_svg_keymap=[data1_keymap],
# data_table_keys=data1_keys,
# data_table_nestkeys=data1_nestkeys,
# data_table_keymap=[data1_keymap],
# data_svg=data_dict_O,
# data_table=data_table_O,
# svgtype='verticalbarschart2d_01',
# tabletype='responsivetable_01',
# svgx1axislabel=None,
# svgy1axislabel="intensity (norm)",
# single_plot_I=True,
# formtile2datamap=[0],
# tabletile2datamap=[1],
# svgtile2datamap=None,
# svgfilters=None,
# svgtileheader='Isotopomer distribution',
# tablefilters=None,
# tableheaders=None
# );
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01RNASequencingGeneExpDiff_js(self,analysis_id_I,p_value_I=0.01,fold_change_log2_I=1.0,data_dir_I='tmp'):
'''Export data differentially expressed genes as a Volcano Plot
INPUT:
OUTPUT:
'''
# get the analysis information
experiment_ids,sample_name_abbreviations = [],[];
experiment_ids,sample_name_abbreviations = self.get_experimentIDAndSampleNameAbbreviation_analysisID_dataStage01RNASequencingAnalysis(analysis_id_I);
data_O = [];
for sample_name_abbreviation_cnt_1,sample_name_abbreviation_1 in enumerate(sample_name_abbreviations):
for sample_name_abbreviation_cnt_2,sample_name_abbreviation_2 in enumerate(sample_name_abbreviations):
if sample_name_abbreviation_cnt_1 != sample_name_abbreviation_cnt_2:
# query geneExpDiff data:
geneExpDiff_tmp = [];
geneExpDiff_tmp = self.get_rows_experimentIDsAndSampleNameAbbreviations_dataStage01RNASequencingGeneExpDiff(experiment_ids[sample_name_abbreviation_cnt_1],experiment_ids[sample_name_abbreviation_cnt_2],sample_name_abbreviation_1,sample_name_abbreviation_2);
geneExpDiff = [];
for d in geneExpDiff_tmp:
if not 'p_value_negLog10' in d:
d['p_value_negLog10']=-log(d['p_value'],10.0);
if p_value_I and fold_change_log2_I and d['p_value'] and d['fold_change_log2'] and d['p_value']<=p_value_I and (d['fold_change_log2']>=fold_change_log2_I or d['fold_change_log2']<=-fold_change_log2_I):
geneExpDiff.append(d);
elif not p_value_I and not fold_change_log2_I and d['p_value'] and d['fold_change_log2']:
geneExpDiff.append(d);
data_O.extend(geneExpDiff);
# make the data parameters
data1_keys = ['experiment_id_1','experiment_id_2','sample_name_abbreviation_1','sample_name_abbreviation_2','gene','fold_change_log2','p_value_negLog10','significant'
];
data1_nestkeys = ['experiment_id_1'];
data1_keymap = {'ydata':'p_value_negLog10',
'xdata':'fold_change_log2',
'serieslabel':'',
'featureslabel':'gene'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'volcanoplot2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 50, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":'Fold Change [log2(FC)]',"svgy1axislabel":'Probability [-log10(P)]',
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Volcano plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'pairWiseTest','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage02IsotopomerFittedExchangeFluxes_js(self,analysis_id_I = None,
simulation_ids_I = [],
bullet_chart_I = True,
data_dir_I="tmp"):
'''Plot the flux precision for a given set of simulations and a given set of reactions
Input:
analysis_id_I = string, analysis id
Optional Input:
simulation_ids_I = [] of strings, simulation_ids in a specific order
bullet_chart_I = True: show the flux estimation +/- StDev
False: show the 95% confidence invervals and flux estimation +/- StDev
'''
MFAmethods = MFA_methods();
#Input:
# analysis_id_I or
# simulation_ids_I
if simulation_ids_I:
simulation_ids = simulation_ids_I;
else:
simulation_ids = [];
simulation_ids = self.get_simulationID_analysisID_dataStage02IsotopomerAnalysis(analysis_id_I);
data_O =[];
for simulation_id in simulation_ids:
# get the flux information for each simulation
flux_data = [];
flux_data = self.get_rows_simulationID_dataStage02IsotopomerfittedExchangeFluxes(simulation_id);
#min_flux,max_flux = None,None;
#min_flux,max_flux = self.get_fluxMinAndMax_simulationID_dataStage02IsotopomerfittedExchangeFluxes(simulation_id)
for i,row in enumerate(flux_data):
observable = MFAmethods.check_observableExchangeFlux(row['flux'],row['flux_lb'],row['flux_ub']);
if not row['flux'] is None:
row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
#row['flux_units'] = row['flux_units'].replace('*','x');
row['flux_lb_stdev'] = row['flux'] - row['flux_stdev'];
row['flux_ub_stdev'] = row['flux'] + row['flux_stdev'];
row['flux_mean'] = numpy.mean([row['flux_lb'],row['flux_ub']]);
if observable: row['observable'] = 'Yes';
else: row['observable'] = 'No';
data_O.append(row);
#if not row['flux'] is None and observable:
# row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
# row['flux_units'] = row['flux_units'].replace('*','x');
# row['flux_lb_stdev'] = row['flux'] - row['flux_stdev'];
# row['flux_ub_stdev'] = row['flux'] + row['flux_stdev'];
# row['flux_mean'] = numpy.mean([row['flux_lb'],row['flux_ub']]);
# data_O.append(row);
#elif not row['flux'] is None and not observable:
# row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
# row['flux_units'] = row['flux_units'].replace('*','x');
# row['flux_lb'] = None;
# row['flux_ub'] = None;
# row['flux_mean'] = None;
# data_O.append(row);
#elif row['flux']==0.0 and observable:
# row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
# row['flux_units'] = row['flux_units'].replace('*','x');
# row['flux_lb_stdev'] = 0.0;
# row['flux_ub_stdev'] = 0.0;
# row['flux_mean'] = numpy.mean([row['flux_lb'],row['flux_ub']]);
# data_O.append(row);
#elif row['flux']==0.0 and not observable:
# row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
# row['flux_units'] = row['flux_units'].replace('*','x');
# row['flux_lb'] = None;
# row['flux_ub'] = None;
# #row['flux_mean'] = None;
# row['flux_lb_stdev'] = None;
# row['flux_ub_stdev'] = None;
# row['flux']=None;
# data_O.append(row);
elif row['flux']==0.0:
row['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
row['flux_units'] = row['flux_units'].replace('*','x');
row['flux_lb_stdev'] = 0.0;
row['flux_ub_stdev'] = 0.0;
row['flux_mean'] = numpy.mean([row['flux_lb'],row['flux_ub']]);
if observable: row['observable'] = 'Yes';
else: row['observable'] = 'No';
data_O.append(row);
# dump chart parameters to a js files
data1_keys = ['simulation_id','rxn_id','simulation_dateAndTime','flux_units','observable'
];
data1_nestkeys = ['rxn_id'];
if bullet_chart_I:
data1_keymap = {'xdata':'rxn_id',
'ydatamean':'flux',
'ydatalb':'flux_lb_stdev',
'ydataub':'flux_ub_stdev',
'serieslabel':'simulation_id',
'featureslabel':'rxn_id'};
else:
data1_keymap = {'xdata':'rxn_id',
#'ydata':'flux',
'ydatamean':'flux_mean',
'ydatalb':'flux_lb',
'ydataub':'flux_ub',
#'ydatamin':'min',
#'ydatamax':'max',
'ydataiq1':'flux_lb_stdev',
'ydataiq3':'flux_ub_stdev',
'ydatamedian':'flux',
'serieslabel':'simulation_id',
'featureslabel':'rxn_id'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 350, 'bottom': 50, 'left': 50 },
"svgwidth":750,"svgheight":350,
"svgx1axislabel":"rxn_id","svgy1axislabel":"flux",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Flux precision','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Flux precision','tiletype':'table','tileid':"tile3",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage02IsotopomerFluxMap_js(self,analysis_id_I,simulation_id_I = None,data_dir_I="tmp"):
'''Export flux map for viewing'''
MFAmethods = MFA_methods();
# Get the simulation information
if simulation_id_I:
simulation_id = simulation_id_I;
else:
simulation_ids = [];
simulation_ids = self.get_simulationID_analysisID_dataStage02IsotopomerAnalysis(analysis_id_I);
if not simulation_ids:
print('No simulation found for the analysis_id ' + analysis_id_I);
elif len(simulation_ids)>1:
print('More than 1 simulation found for the analysis_id ' + analysis_id_I);
simulation_id_I = simulation_ids[0];
else:
simulation_id_I = simulation_ids[0];
# Get the flux information
flux = [];
flux_tmp = [];
#flux = self.get_rowsEscherFluxList_simulationID_dataStage02IsotopomerfittedExchangeFluxes(simulation_id_I);
flux_tmp = self.get_rows_simulationID_dataStage02IsotopomerfittedExchangeFluxes(simulation_id_I);
for i,row in enumerate(flux_tmp):
observable = MFAmethods.check_observableExchangeFlux(row['flux'],row['flux_lb'],row['flux_ub']);
if not row['flux'] is None and row['flux']!=0.0 and numpy.abs(row['flux']) < 10.0:
flux_tmp[i]['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
flux_tmp[i]['flux_units'] = self.remove_jsRegularExpressions(row['flux_units']);
if observable: flux_tmp[i]['observable'] = 'Yes';
else: flux_tmp[i]['observable'] = 'No';
flux.append(flux_tmp[i]);
elif row['flux']==0.0 and numpy.abs(numpy.mean([row['flux_lb'],row['flux_ub']]))<10.0:
flux_tmp[i]['simulation_dateAndTime'] = self.convert_datetime2string(row['simulation_dateAndTime']);
flux_tmp[i]['flux_units'] = self.remove_jsRegularExpressions(row['flux_units']);
#flux_tmp[i]['flux'] = numpy.mean([row['flux_lb'],row['flux_ub']]);
if observable: flux_tmp[i]['observable'] = 'Yes';
else: flux_tmp[i]['observable'] = 'No';
flux.append(flux_tmp[i]);
# Get the map information
map = [];
map = self.get_rows_modelID_modelsEschermaps('iJO1366');
# dump chart parameters to a js files
data1_keys = ['simulation_id','rxn_id','simulation_dateAndTime','flux_units','observable'
];
data1_nestkeys = ['simulation_id'];
data1_keymap = {'values':'flux','key':'rxn_id'};
data2_keys = ['model_id','eschermap_id'
];
data2_nestkeys = ['model_id'];
data2_keymap = {'data':'eschermap_json'};
# make the data object
dataobject_O = [{"data":flux,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":map,"datakeys":data2_keys,"datanestkeys":data2_nestkeys}];
# make the tile parameter objects
formtileparameters1_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters1_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters1_O.update(formparameters1_O);
formtileparameters2_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters2_O = {'htmlid':'filtermenuform2',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit2','text':'submit'},"formresetbuttonidtext":{'id':'reset2','text':'reset'},"formupdatebuttonidtext":{'id':'update2','text':'update'}};
formtileparameters2_O.update(formparameters2_O);
htmlparameters_O = {"htmlkeymap":[data1_keymap,data2_keymap],
'htmltype':'escher_01','htmlid':'html1',
'escherdataindex':{"reactiondata":0,"mapdata":1},
'escherembeddedcss':None,
'escheroptions':None};
htmltileparameters_O = {'tileheader':'Escher map','tiletype':'html','tileid':"tile1",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
htmltileparameters_O.update(htmlparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Flux precision','tiletype':'table','tileid':"tile2",'rowid':"row3",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters1_O,formtileparameters2_O,htmltileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"filtermenu2":[1],"tile1":[0,1],"tile2":[0]};
filtermenuobject_O = [{"filtermenuid":"filtermenu1","filtermenuhtmlid":"filtermenuform1",
"filtermenusubmitbuttonid":"submit1","filtermenuresetbuttonid":"reset1",
"filtermenuupdatebuttonid":"update1"},{"filtermenuid":"filtermenu2","filtermenuhtmlid":"filtermenuform2",
"filtermenusubmitbuttonid":"submit2","filtermenuresetbuttonid":"reset2",
"filtermenuupdatebuttonid":"update2"}];
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01PhysiologyRatesAverages_js_v01(self,analysis_id_I,data_dir_I="tmp"):
"""Export data_stage01_physiology_ratesAverages to js file"""
# get the analysis information
experiment_ids,sample_name_abbreviations = [],[];
experiment_ids,sample_name_abbreviations = self.get_experimentIDAndSampleName_analysisID_dataStage01PhysiologyAnalysis(analysis_id_I);
data_O = [];
for sna_cnt,sna in enumerate(sample_name_abbreviations):
data_tmp = [];
data_tmp = self.get_rows_experimentIDAndSampleNameAbbreviation_dataStage01PhysiologyRatesAverages(experiment_ids[sna_cnt],sna);
if data_tmp: data_O.extend(data_tmp);
## remove js regular expressions
#for i,d in enumerate(data_O):
# data_O[i]['rate_units'] = self.remove_jsRegularExpressions(d['rate_units']);
# get metabolite ids:
met_ids_all = [];
for d in data_O:
met_ids_all.append(d['met_id']);
met_ids = list(set(met_ids_all));
biomass_met_ids = ['biomass','yield_ss'];
uptakesecretion_met_ids = [x for x in met_ids if not x in biomass_met_ids];
# visualization parameters
data1_keys = ['experiment_id','sample_name_abbreviation', 'met_id','rate_units'];
data1_nestkeys = ['met_id'];
data1_keymap = {'xdata':'met_id','ydata':'rate_average',
'serieslabel':'sample_name_abbreviation','featureslabel':'met_id',
'ydatalb':'rate_lb','ydataub':'rate_ub'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
svgparameters1_O = {"svgtype":'verticalbarschart2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,"svgy1axislabel":"rate (mmol*gDCW-1*hr-1)",
"svgfilters":{'met_id':uptakesecretion_met_ids}
};
svgtileparameters1_O = {'tileheader':'Uptake/secretion rates','tiletype':'svg','tileid':"tile1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters1_O.update(svgparameters1_O);
svgparameters2_O = {"svgtype":'verticalbarschart2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg2',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgy1axislabel":"rate (hr-1)",
#"svgy1axislabel":"rate (hr-1) or yield (gDCW*mmol of C-source)",
"svgfilters":{'met_id':biomass_met_ids}
};
svgtileparameters2_O = {'tileheader':'Growth rate','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters2_O.update(svgparameters2_O);
tableparameters1_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableheaders":['experiment_id','sample_name_abbreviation','met_id','rate_average','rate_var','rate_lb','rate_ub','rate_units','n','comment_','used_'],
"tableclass":"table table-condensed table-hover",
'tableformtileid':'tile1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters1_O = {'tileheader':'Uptake/secretion rates','tiletype':'table','tileid':"tile3",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters1_O.update(tableparameters1_O);
tableparameters2_O = {"tabletype":'responsivetable_01',
'tableid':'table2',
"tablefilters":None,
"tableheaders":['experiment_id','sample_name_abbreviation','met_id','rate_average','rate_var','rate_lb','rate_ub','rate_units','n','comment_','used_'],
"tableclass":"table table-condensed table-hover",
'tableformtileid':'tile1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters2_O = {'tileheader':'Growth rates','tiletype':'table','tileid':"tile4",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters2_O.update(tableparameters2_O);
parametersobject_O = [svgtileparameters1_O,svgtileparameters2_O,tabletileparameters1_O,tabletileparameters2_O];
tile2datamap_O = {"tile1":[0],"tile2":[1],"tile3":[0],"tile4":[1]};
filtermenuobject_O = None;
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_quantitationMethods_js(self,analysis_id_I,data_dir_I='tmp'):
'''Export the quantitation and calibrators to ddt'''
#get the calibrator data
data_1 = [];
data_2 = [];
data_1a = [];
#query all the data
data_all = self.getRowsJoin_analysisID_dataStage01QuantificationMQResultsTable_limsQuantitationMethod(analysis_id_I)
#reorganize into a dictionary of (QMethods,component_names)
data_dict = {};
for d in data_all:
unique = (d['quantitation_method_id'],d['component_name']);
if not unique in data_dict.keys():
data_dict[unique] = [];
data_dict[unique].append(d);
#split and modify the data
for QMethod_id,rows in data_dict.items():
concentrations = []
ratios = [];
sample_names = [];
for row in rows:
if row and not row is None and not row['concentration_ratio'] is None:
if row['use_area']: row['ratio'] = row['area_ratio'];
else: row['ratio'] = row['height_ratio'];
row['quantitation_method_id']=rows[0]['quantitation_method_id'];
data_1.append(row);
concentrations.append(row['concentration_ratio']);
ratios.append(row['ratio']);
sample_names.append(row['sample_name']);
if not concentrations: continue;
# get the quant method statistics
data_2.append(row);
# generate the line of best fit
min_ratio = min(ratios);
max_ratio = max(ratios);
index_min = [cnt for cnt,x in enumerate(ratios) if x == min_ratio][0];
index_max = [cnt for cnt,x in enumerate(ratios) if x == max_ratio][0];
conc_min = min(concentrations);
conc_max = max(concentrations);
sample_name_min = sample_names[index_min];
sample_name_max = sample_names[index_max];
data_1a.append({'concentration_ratio':rows[0]['lloq'],
'ratio':min_ratio,
'component_name':rows[0]['component_name'],
'sample_name':sample_name_min,
'quantitation_method_id':rows[0]['quantitation_method_id']});
data_1a.append({'concentration_ratio':rows[0]['uloq'],
'ratio':max_ratio,
'component_name':rows[0]['component_name'],
'sample_name':sample_name_max,
'quantitation_method_id':rows[0]['quantitation_method_id']});
# dump chart parameters to a js files
data1_keys = [
'quantitation_method_id',
'concentration_ratio',
'sample_name',
'component_name',
'ratio',
];
data1_nestkeys = ['component_name'];
data1_keymap = {'xdata':'concentration_ratio',
'ydata':'ratio',
'serieslabel':'component_name',
'featureslabel':'sample_name'};
data2_keys = ['quantitation_method_id',
'q1_mass',
'q3_mass',
'met_id',
'component_name',
'is_name',
'fit',
'weighting',
'intercept',
'slope',
'correlation',
'use_area',
'lloq',
'uloq',
'points',
];
data2_nestkeys = ['component_name'];
data2_keymap = {'xdata':'concentration_ratio',
'ydata':'ratio',
'serieslabel':'component_name',
'featureslabel':None};
parameters = {"chart1margin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"chart1width":500,"chart1height":350,
"chart1title":"Metric Plot", "chart1x1axislabel":"sample_name","chart1y1axislabel":"measurement"}
# make the data object
dataobject_O = [{"data":data_1,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_1a,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_2,"datakeys":data2_keys,"datanestkeys":data2_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1','htmltype':'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'scatterlineplot2d_01',"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"concentration_ratio","svgy1axislabel":"measurement_ratio",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Regression','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Regression Statistics','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0,1],"tile3":[2]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01QuantificationPhysiologicalRatios_js(self,experiment_id_I,sample_name_abbreviations_I=[],ratio_ids_I=[],
data_dir_I = 'tmp'):
'''Export the data from data_stage01_phyisiogicalRatios for visualization with DDT
NOTES:
Broken...
Update to use box and whiskers with points for individual replicates
Update to use ddt_python interface
INPUT:
experiment_id_I
sample_name_abbreviations_I
ratio_ids_I
data_dir_I
OUTPUT:
'''
print('Generating scatterLinePlot for physiologicalRatios')
data_replicates = [];
data_averages = [];
data_numAndDen = [];
# get time points
time_points = [];
time_points = self.get_timePoint_experimentID_dataStage01PhysiologicalRatiosReplicates(experiment_id_I);
for tp in time_points:
print('Generating scatterLinePlot for physiologicalRatios for time_point ' + tp);
# get physiological ratio_ids
ratios = {};
ratios = self.get_ratioIDs_experimentIDAndTimePoint_dataStage01PhysiologicalRatiosReplicates(experiment_id_I,tp);
for k,v in ratios.items():
if ratio_ids_I:
if not k in ratio_ids_I:
continue;
print('Generating scatterLinePlot for physiologicalRatios for ratio ' + k);
# get sample_names
if sample_name_abbreviations_I:
sample_name_abbreviations = sample_name_abbreviations_I;
else:
sample_name_abbreviations = [];
sample_name_abbreviations = self.get_sampleNameAbbreviations_experimentIDAndTimePointAndRatioID_dataStage01PhysiologicalRatiosAverages(experiment_id_I,tp,k);
ratios_num = [];
ratios_den = [];
for sna_cnt,sna in enumerate(sample_name_abbreviations):
print('Generating scatterLinePlot for physiologicalRatios for sample name abbreviation ' + sna);
# get the data
data = {};
data = self.get_data_experimentIDAndTimePointAndRatioIDAndSampleNameAbbreviation_dataStage01PhysiologicalRatiosAverages(experiment_id_I,tp,k,sna)
if not data: continue;
data_averages.append(data);
# get the replicates
ratio_values = [];
ratio_values = self.get_rows_experimentIDAndSampleNameAbbreviationAndTimePointAndRatioID_dataStage01PhysiologicalRatiosReplicates(experiment_id_I,sna,tp,k);
for ratio in ratio_values:
ratio['sample_name_abbreviation']=sna;
data_replicates.extend(ratio_values);
ratio_values = [];
ratio_values = self.get_rows_experimentIDAndSampleNameAbbreviationAndTimePointAndRatioID_dataStage01PhysiologicalRatiosReplicates(experiment_id_I,sna,tp,k+'_numerator');
for ratio in ratio_values:
ratio['sample_name_abbreviation']=sna;
data_replicates.extend(ratio_values);
ratio_values = [];
ratio_values = self.get_rows_experimentIDAndSampleNameAbbreviationAndTimePointAndRatioID_dataStage01PhysiologicalRatiosReplicates(experiment_id_I,sna,tp,k+'_denominator');
for ratio in ratio_values:
ratio['sample_name_abbreviation']=sna;
data_replicates.extend(ratio_values);
# get ratios_numerator
ratio_num = None;
ratio_num = self.get_data_experimentIDAndTimePointAndRatioIDAndSampleNameAbbreviation_dataStage01PhysiologicalRatiosAverages(experiment_id_I,tp,k+'_numerator',sna)
if not ratio_num: continue;
# get ratios_denominator
ratio_den = None;
ratio_den = self.get_data_experimentIDAndTimePointAndRatioIDAndSampleNameAbbreviation_dataStage01PhysiologicalRatiosAverages(experiment_id_I,tp,k+'_denominator',sna)
if not ratio_den: continue;
# modify
ratio = {};
if ratio_num['sample_name_abbreviation']==ratio_den['sample_name_abbreviation']:
ratio = {'experiment_id':ratio_num['experiment_id'],
'sample_name_abbreviation':ratio_num['sample_name_abbreviation'],
'time_point':ratio_num['time_point'],
'physiologicalratio_name':ratio_num['physiologicalratio_name'],
'physiologicalratio_description':ratio_num['physiologicalratio_description']}
ratio['physiologicalratio_id'] = ratio_num['physiologicalratio_id'].replace('_numerator','');
ratio['physiologicalratio_value_numerator'] = ratio_num['physiologicalratio_value_ave'];
ratio['physiologicalratio_value_denominator'] = ratio_den['physiologicalratio_value_ave'];
else:
print('physiologicalratio sample_name_shorts do not match');
data_numAndDen.append(ratio);
# dump chart parameters to a js files
data1_keys = ['experiment_id',
'sample_name_abbreviation',
'sample_name_short',
'time_point',
'physiologicalratio_id',
'physiologicalratio_name',
'physiologicalratio_description',
];
data1_nestkeys = ['physiologicalratio_id'];
data1_keymap = {'xdata':'physiologicalratio_id',
'ydata':'physiologicalratio_value',
#'ydatalb':'physiologicalratio_value_lb',
#'ydataub':'physiologicalratio_value_ub',
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_short',
'featureslabel':'physiologicalratio_id'};
data2_keys = ['experiment_id',
'sample_name_abbreviation',
'time_point',
'physiologicalratio_id',
'physiologicalratio_name',
'physiologicalratio_description',
'physiologicalratio_cv'
];
data2_nestkeys = ['physiologicalratio_id'];
data2_keymap = {'xdata':'physiologicalratio_id',
'ydatamean':'physiologicalratio_value_ave',
'ydatalb':'physiologicalratio_value_lb',
'ydataub':'physiologicalratio_value_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'physiologicalratio_id'};
data3_keys = [
'experiment_id',
'sample_name_abbreviation',
'time_point',
'physiologicalratio_id',
'physiologicalratio_name',
'physiologicalratio_description'
];
data3_nestkeys = ['physiologicalratio_id'];
data3_keymap = {'xdata':'physiologicalratio_value_denominator',
'ydata':'physiologicalratio_value_numerator',
'serieslabel':'physiologicalratio_id',
'featureslabel':'sample_name_abbreviation'};
# make the data object
dataobject_O = [{"data":data_replicates,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_averages,"datakeys":data2_keys,"datanestkeys":data2_nestkeys},
{"data":data_numAndDen,"datakeys":data3_keys,"datanestkeys":data3_nestkeys}];
# make the tile parameter objects for the replicates and averages
formtileparameters_replicates_O = {'tileheader':'Filter menu replicates','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters_replicates_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_replicates_O.update(formparameters_replicates_O);
formtileparameters_averages_O = {'tileheader':'Filter menu averages','tiletype':'html','tileid':"filtermenu2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters_averages_O = {'htmlid':'filtermenuform2',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit2','text':'submit'},"formresetbuttonidtext":{'id':'reset2','text':'reset'},"formupdatebuttonidtext":{'id':'update2','text':'update'}};
formtileparameters_averages_O.update(formparameters_averages_O);
# make the svg objects for the replicates data
svgparameters_replicates_O = {"svgtype":'boxandwhiskersplot2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"physiologicalratio_id","svgy1axislabel":"value",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_replicates_O = {'tileheader':'Replicates','tiletype':'svg','tileid':"tile1",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters_replicates_O.update(svgparameters_replicates_O);
# make the svg objects for the box and whiskers data
svgparameters_boxAndWhiskers_O = {"svgtype":'boxandwhiskersplot2d_01',"svgkeymap":[data2_keymap],
'svgid':'svg2',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":350,"svgheight":350,
"svgx1axislabel":"physiologicalratio_id","svgy1axislabel":"value",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_boxAndWhiskers_O = {'tileheader':'Ratio','tiletype':'svg','tileid':"tile2",'rowid':"row3",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters_boxAndWhiskers_O.update(svgparameters_boxAndWhiskers_O);
# make the svg objects for the scatter line plot data
svgparameters_scatterLinePlot_O = {"svgtype":'scatterlineplot2d_01',"svgkeymap":[data3_keymap,data3_keymap],
'svgid':'svg3',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":350,"svgheight":350,
"svgx1axislabel":"physiologicalratio_denominator","svgy1axislabel":"physiologicalratio_numerator",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_scatterLinePlot_O = {'tileheader':'Ratio numerator vs. denominator','tiletype':'svg','tileid':"tile3",'rowid':"row4",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
svgtileparameters_scatterLinePlot_O.update(svgparameters_scatterLinePlot_O);
# make the tables for the replicates and averages data
tableparameters_replicates_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_replicates_O = {'tileheader':'replicates data','tiletype':'table','tileid':"tile7",'rowid':"row5",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_replicates_O.update(tableparameters_replicates_O);
tableparameters_averages_O = {"tabletype":'responsivetable_01',
'tableid':'table2',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu2','tableresetbuttonid':'reset2','tablesubmitbuttonid':'submit2'};
tabletileparameters_averages_O = {'tileheader':'averages data','tiletype':'table','tileid':"tile8",'rowid':"row6",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_averages_O.update(tableparameters_averages_O);
parametersobject_O = [formtileparameters_replicates_O,
formtileparameters_averages_O,
svgtileparameters_replicates_O,
svgtileparameters_boxAndWhiskers_O,
svgtileparameters_scatterLinePlot_O,
tabletileparameters_replicates_O,
tabletileparameters_averages_O];
tile2datamap_O = {"filtermenu1":[0],"filtermenu2":[1],
"tile1":[0],"tile2":[1],"tile3":[2,2],
"tile7":[0],"tile8":[1]};
filtermenuobject_O = [
{"filtermenuid":"filtermenu1","filtermenuhtmlid":"filtermenuform1",
"filtermenusubmitbuttonid":"submit1","filtermenuresetbuttonid":"reset1",
"filtermenuupdatebuttonid":"update1"},
{"filtermenuid":"filtermenu2","filtermenuhtmlid":"filtermenuform2",
"filtermenusubmitbuttonid":"submit2","filtermenuresetbuttonid":"reset2",
"filtermenuupdatebuttonid":"update2"}
];
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01NormalizedAndAverages_checkCVAndExtracelluar_js(self,experiment_id_I,sample_name_abbreviations_I=[],sample_names_I=[],component_names_I=[],
cv_threshold_I=40,extracellular_threshold_I=80,
data_dir_I='tmp'):
'''export data_stage01_quantification_normalized and averages for visualization with ddt'''
calc = calculate_interface();
print('export_dataStage01Normalized_js...')
data_norm_broth = [];
data_norm_filtrate = [];
data_norm_combined = [];
data_ave = [];
# get sample_name_abbreviations
if sample_name_abbreviations_I:
sample_name_abbreviations = sample_name_abbreviations_I
else:
sample_name_abbreviations = [];
sample_name_abbreviations = self.get_sampleNameAbbreviations_experimentID_dataStage01Normalized(experiment_id_I);
# create database table
for sna in sample_name_abbreviations:
print('exporting sample_name_abbreviation ' + sna);
# get component names
if component_names_I:
component_names = component_names_I
else:
component_names = [];
component_names = self.get_componentsNames_experimentIDAndSampleNameAbbreviation_dataStage01Normalized(experiment_id_I,sna);
for cn in component_names:
print('exporting component_name ' + cn);
component_group_name = self.get_componentGroupName_experimentIDAndComponentName_dataStage01Normalized(experiment_id_I,cn);
# get time points
time_points = self.get_timePoint_experimentIDAndSampleNameAbbreviation_dataStage01Normalized(experiment_id_I,sna);
for tp in time_points:
print('exporting time_point ' + tp);
# get the averages and %CV samples
row = {};
#row = self.get_row_experimentIDAndSampleNameAbbreviationAndTimePointAndComponentName_dataStage01Averages(experiment_id_I,sna,tp,cn);
row = self.get_row_experimentIDAndSampleNameAbbreviationAndTimePointAndComponentNameAndCalculatedConcentrationCVAndExtracellularPercent_dataStage01Averages(experiment_id_I,
sna,tp,cn,
cv_threshold_I=cv_threshold_I,
extracellular_threshold_I=extracellular_threshold_I);
if not row: continue;
stdev = calc.convert_cv2StDev(row['calculated_concentration_filtrate_average'],row['calculated_concentration_filtrate_cv']);
row['calculated_concentration_filtrate_lb'] = row['calculated_concentration_filtrate_average']-stdev;
row['calculated_concentration_filtrate_ub'] = row['calculated_concentration_filtrate_average']+stdev;
stdev = calc.convert_cv2StDev(row['calculated_concentration_broth_average'],row['calculated_concentration_broth_cv']);
row['calculated_concentration_broth_lb'] = row['calculated_concentration_broth_average']-stdev;
row['calculated_concentration_broth_ub'] = row['calculated_concentration_broth_average']+stdev;
stdev = calc.convert_cv2StDev(row['calculated_concentration_average'],row['calculated_concentration_cv']);
row['calculated_concentration_lb'] = row['calculated_concentration_average']-stdev;
row['calculated_concentration_ub'] = row['calculated_concentration_average']+stdev;
data_ave.append(row);
# get filtrate sample names
sample_names = [];
sample_description = 'Filtrate';
sample_names = self.get_sampleNames_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndComponentNameAndTimePoint_dataStage01Normalized(experiment_id_I,sna,sample_description,cn,tp);
if sample_names_I: # screen out sample names that are not in the input
sample_names = [x for x in sample_names if x in sample_names_I];
for sn in sample_names:
# get the row
row = None;
row = self.get_row_sampleNameAndComponentName_dataStage01Normalized(sn,cn);
if not(row): continue;
row['sample_name_abbreviation'] = sna;
data_norm_filtrate.append(row);
data_norm_combined.append(row);
# get filtrate sample names
sample_names = [];
sample_description = 'Broth';
sample_names = self.get_sampleNames_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndComponentNameAndTimePoint_dataStage01Normalized(experiment_id_I,sna,sample_description,cn,tp);
if sample_names_I: # screen out sample names that are not in the input
sample_names = [x for x in sample_names if x in sample_names_I];
for sn in sample_names:
# get the row
row = None;
row = self.get_row_sampleNameAndComponentName_dataStage01Normalized(sn,cn);
if not(row): continue;
row['sample_name_abbreviation'] = sna;
data_norm_broth.append(row);
data_norm_combined.append(row);
# dump chart parameters to a js files
data1_keys = ['experiment_id',
'sample_name',
'sample_id',
'sample_name_abbreviation',
'component_group_name',
'component_name',
'calculated_concentration_units'
];
data1_nestkeys = ['component_name'];
data1_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration',
#'ydatalb':'peakInfo_lb',
#'ydataub':'peakInfo_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name',
'featureslabel':'component_name'};
data2_keys = ['experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_broth_cv'
];
data2_nestkeys = ['component_name'];
data2_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration_broth_average',
'ydatalb':'calculated_concentration_broth_lb',
'ydataub':'calculated_concentration_broth_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
data3_keys = ['experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_filtrate_cv'
];
data3_nestkeys = ['component_name'];
data3_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration_filtrate_average',
'ydatalb':'calculated_concentration_filtrate_lb',
'ydataub':'calculated_concentration_filtrate_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
data4_keys = ['experiment_id',
'sample_name_abbreviation',
'time_point',
'component_group_name',
'component_name',
'calculated_concentration_units',
'extracellular_percent',
'calculated_concentration_cv'
];
data4_nestkeys = ['component_name'];
data4_keymap = {'xdata':'component_name',
'ydatamean':'calculated_concentration_average',
'ydatalb':'calculated_concentration_lb',
'ydataub':'calculated_concentration_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'sample_name_abbreviation',
'featureslabel':'component_name'};
# make the data object
dataobject_O = [{"data":data_norm_broth,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_norm_filtrate,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_norm_combined,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":data_ave,"datakeys":data2_keys,"datanestkeys":data2_nestkeys},
{"data":data_ave,"datakeys":data3_keys,"datanestkeys":data3_nestkeys},
{"data":data_ave,"datakeys":data4_keys,"datanestkeys":data4_nestkeys}];
# make the tile parameter objects for the normalized and averages
formtileparameters_normalized_O = {'tileheader':'Filter menu normalized','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters_normalized_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_normalized_O.update(formparameters_normalized_O);
formtileparameters_averages_O = {'tileheader':'Filter menu averages','tiletype':'html','tileid':"filtermenu2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-6"};
formparameters_averages_O = {'htmlid':'filtermenuform2',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit2','text':'submit'},"formresetbuttonidtext":{'id':'reset2','text':'reset'},"formupdatebuttonidtext":{'id':'update2','text':'update'}};
formtileparameters_averages_O.update(formparameters_averages_O);
# make the svg objects for the normalized data
svgparameters_broth_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_broth_O = {'tileheader':'Broth data','tiletype':'svg','tileid':"tile1",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_broth_O.update(svgparameters_broth_O);
svgparameters_filtrate_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data1_keymap],
'svgid':'svg2',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_filtrate_O = {'tileheader':'Filtrate data','tiletype':'svg','tileid':"tile2",'rowid':"row2",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_filtrate_O.update(svgparameters_filtrate_O);
svgparameters_combined_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data1_keymap],
'svgid':'svg3',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_combined_O = {'tileheader':'Broth-Filtrate data','tiletype':'svg','tileid':"tile3",'rowid':"row2",'colid':"col3",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_combined_O.update(svgparameters_combined_O);
# make the svg objects for the averages data
svgparameters_averages_broth_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data2_keymap],
'svgid':'svg4',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_broth_O = {'tileheader':'Broth data','tiletype':'svg','tileid':"tile4",'rowid':"row3",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_broth_O.update(svgparameters_averages_broth_O);
svgparameters_averages_filtrate_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data3_keymap],
'svgid':'svg5',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_filtrate_O = {'tileheader':'Filtrate data','tiletype':'svg','tileid':"tile5",'rowid':"row3",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_filtrate_O.update(svgparameters_averages_filtrate_O);
svgparameters_averages_combined_O = {"svgtype":'boxandwhiskersplot2d_02',"svgkeymap":[data4_keymap],
'svgid':'svg6',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":250,"svgheight":250,
"svgx1axislabel":"component_name","svgy1axislabel":"concentration",
'svgformtileid':'filtermenu2','svgresetbuttonid':'reset2','svgsubmitbuttonid':'submit2'};
svgtileparameters_averages_combined_O = {'tileheader':'Broth-Filtrate data','tiletype':'svg','tileid':"tile6",'rowid':"row3",'colid':"col3",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
svgtileparameters_averages_combined_O.update(svgparameters_averages_combined_O);
# make the tables for the normalized and averages data
tableparameters_normalized_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_normalized_O = {'tileheader':'normalized data','tiletype':'table','tileid':"tile7",'rowid':"row4",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_normalized_O.update(tableparameters_normalized_O);
tableparameters_averages_O = {"tabletype":'responsivetable_01',
'tableid':'table2',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu2','tableresetbuttonid':'reset2','tablesubmitbuttonid':'submit2'};
tabletileparameters_averages_O = {'tileheader':'averages data','tiletype':'table','tileid':"tile8",'rowid':"row5",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_averages_O.update(tableparameters_averages_O);
parametersobject_O = [formtileparameters_normalized_O,
formtileparameters_averages_O,
svgtileparameters_broth_O,
svgtileparameters_filtrate_O,
svgtileparameters_combined_O,
svgtileparameters_averages_broth_O,
svgtileparameters_averages_filtrate_O,
svgtileparameters_averages_combined_O,
tabletileparameters_normalized_O,
tabletileparameters_averages_O];
tile2datamap_O = {"filtermenu1":[2],"filtermenu2":[5],
"tile1":[0],"tile2":[1],"tile3":[2],
"tile4":[3],"tile5":[4],"tile6":[5],
"tile7":[2],"tile8":[5]};
filtermenuobject_O = [{"filtermenuid":"filtermenu1","filtermenuhtmlid":"filtermenuform1",
"filtermenusubmitbuttonid":"submit1","filtermenuresetbuttonid":"reset1",
"filtermenuupdatebuttonid":"update1"},{"filtermenuid":"filtermenu2","filtermenuhtmlid":"filtermenuform2",
"filtermenusubmitbuttonid":"submit2","filtermenuresetbuttonid":"reset2",
"filtermenuupdatebuttonid":"update2"}
];
# dump the data to a json file
data_str = 'var ' + 'data' + ' = ' + json.dumps(dataobject_O) + ';';
parameters_str = 'var ' + 'parameters' + ' = ' + json.dumps(parametersobject_O) + ';';
tile2datamap_str = 'var ' + 'tile2datamap' + ' = ' + json.dumps(tile2datamap_O) + ';';
filtermenu_str = 'var ' + 'filtermenu' + ' = ' + json.dumps(filtermenuobject_O) + ';';
#
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = filtermenuobject_O);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01ResequencingMutationsAnnotated_js(self,analysis_id_I,mutation_id_exclusion_list=[],frequency_threshold=0.1,max_position=4630000,data_dir_I="tmp"):
'''export data_stage01_resequencing_mutationsAnnotated to js file
Visualization: treemap of the mutations
'''
print('exportingdataStage01ResequencingMutationsAnnotated...')
genomediff = genome_diff();
# get the analysis information
experiment_ids,sample_names,time_points = [],[],[];
experiment_ids,sample_names,time_points = self.get_experimentIDAndSampleNameAndTimePoint_analysisID_dataStage01ResequencingAnalysis(analysis_id_I);
mutation_data_O = [];
mutation_ids = [];
for sample_name_cnt,sample_name in enumerate(sample_names):
# query mutation data:
mutations = [];
mutations = self.get_mutations_experimentIDAndSampleName_dataStage01ResequencingMutationsAnnotated(experiment_ids[sample_name_cnt],sample_name);
for end_cnt,mutation in enumerate(mutations):
if mutation['mutation_position'] > max_position:
continue;
if mutation['mutation_frequency']<frequency_threshold:
continue;
if not mutation['mutation_genes']:
mutation['mutation_genes'] = ['unknown'];
# mutation id
mutation_id = genomediff._make_mutationID(mutation['mutation_genes'],mutation['mutation_type'],mutation['mutation_position']);
if mutation_id in mutation_id_exclusion_list:
continue;
tmp = {};
tmp['analysis_id']=analysis_id_I;
tmp['time_point']=time_points[sample_name_cnt]
tmp['experiment_id']=experiment_ids[sample_name_cnt]
tmp['sample_name']=sample_name
tmp['mutation_id']=mutation_id;
if mutation['mutation_annotations']:
tmp['mutation_annotations']=";".join([x for x in mutation['mutation_annotations'] if x is not None]);
else: tmp['mutation_annotations']=mutation['mutation_annotations'];
if mutation['mutation_links']:
tmp['mutation_links']=";".join([x for x in mutation['mutation_links'] if x is not None]);
else: tmp['mutation_links']=mutation['mutation_links'];
if mutation['mutation_genes']:
tmp['mutation_genes']=";".join([x for x in mutation['mutation_genes'] if x is not None]);
else: tmp['mutation_genes']=mutation['mutation_genes'];
if mutation['mutation_position']:
tmp['mutation_position']=mutation['mutation_position'];
else: tmp['mutation_position']=mutation['mutation_position'];
if mutation['mutation_locations']:
tmp['mutation_locations']=";".join([x for x in mutation['mutation_locations'] if x is not None]);
else: tmp['mutation_locations']=mutation['mutation_locations'];
tmp.update(mutation);
mutation_data_O.append(tmp);
# dump chart parameters to a js files
data1_keys = [
'experiment_id',
'sample_name',
'mutation_id',
#'mutation_frequency',
'mutation_type',
'mutation_position',
#'mutation_data',
'mutation_annotations',
'mutation_genes',
#'mutation_links',
'mutation_locations'
];
data1_nestkeys = ['analysis_id',
'mutation_genes',
'mutation_position',
'mutation_type',
#'sample_name'
];
data1_keymap = {'xdata':'intermediate',
'ydata':'mutation_frequency',
'serieslabel':'mutation_id',
'featureslabel':''};
# make the data object
dataobject_O = [{"data":mutation_data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},
{"data":mutation_data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}
];
# make the tile parameter objects
# tile 0: form
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
formparameters_O = {'htmlid':'filtermenuform1','htmltype':'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
# tile 1: treelayout2d_01
svgparameters_O = {"svgtype":'treelayout2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 100, 'right': 100, 'bottom': 100, 'left': 100 },
"svgwidth":1000,
"svgheight":1000,
"svgduration":750,
"datalastchild":'sample_name'
};
svgtileparameters_O = {
'tileheader':'Mutations annotated',
'tiletype':'svg',
'tileid':"tile1",
'rowid':"row2",
'colid':"col1",
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-12"
};
svgtileparameters_O.update(svgparameters_O);
# tile 2: table
tableparameters_O = {
"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
};
tabletileparameters_O = {
'tileheader':'Mutations annotated',
'tiletype':'table',
'tileid':"tile2",
'rowid':"row3",
'colid':"col1",
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-12"
};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile1":[0],"tile2":[1]}; #pass two identical data objects to the treemap and table
# dump the data to a json file
data_str = 'var ' + 'data' + ' = ' + json.dumps(dataobject_O) + ';';
parameters_str = 'var ' + 'parameters' + ' = ' + json.dumps(parametersobject_O) + ';';
tile2datamap_str = 'var ' + 'tile2datamap' + ' = ' + json.dumps(tile2datamap_O) + ';';
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01ResequencingHistogram_js(self,analysis_id_I,single_plot_I=False,data_dir_I="tmp"):
'''export data_stage01_resequencing_histogram to js file
Visualization: histogram of bins for each feature
'''
#get the table data
data_table_O = [];
data_table_O = self.get_rows_analysisID_dataStage01ResequencingHistogram(analysis_id_I);
#get the data as a dictionary for each feature
data_dict_O = {};
data_dict_O = self.get_rowsAsFeaturesDict_analysisID_dataStage01ResequencingHistogram(analysis_id_I);
# initialize the ddt objects
dataobject_O = [];
parametersobject_O = [];
tile2datamap_O = {};
# visualization parameters
data1_keys = ['feature_id',
'feature_units',
];
data1_nestkeys = [
'bin'
];
data1_keymap = {
'xdata':'bin',
'ydata':'frequency',
'serieslabel':'feature_id',
'featureslabel':'bin',
'ydatalb':None,
'ydataub':None};
# make the tile parameter objects
# tile 0: form
formtileparameters_O = {
'tileheader':'Filter menu',
'tiletype':'html',
'tileid':"filtermenu1",
'rowid':"row1",
'colid':"col1",
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-12"};
formparameters_O = {
'htmlid':'filtermenuform1',
'htmltype':'form_01',
"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},
"formresetbuttonidtext":{'id':'reset1','text':'reset'},
"formupdatebuttonidtext":{'id':'update1','text':'update'}
};
formtileparameters_O.update(formparameters_O);
dataobject_O.append({"data":data_table_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
parametersobject_O.append(formtileparameters_O);
tile2datamap_O.update({"filtermenu1":[0]});
# tile 1-n features: histogram
if not single_plot_I:
rowcnt = 1;
colcnt = 1;
cnt = 0;
for k,v in data_dict_O.items():
svgtileid = "tilesvg"+str(cnt);
svgid = 'svg'+str(cnt);
iter=cnt+1; #start at 1
if (cnt % 2 == 0):
rowcnt = rowcnt+1;#even
colcnt = 1;
else:
colcnt = colcnt+1;
# make the svg object
svgparameters1_O = {
"svgtype":'verticalbarschart2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg'+str(cnt),
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":350,
"svgheight":250,
"svgy1axislabel":"frequency"
};
svgtileparameters1_O = {
'tileheader':'Histogram',
'tiletype':'svg',
'tileid':svgtileid,
'rowid':"row"+str(rowcnt),
'colid':"col"+str(colcnt),
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-6"};
dataobject_O.append({"data":v,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
svgtileparameters1_O.update(svgparameters1_O);
parametersobject_O.append(svgtileparameters1_O);
tile2datamap_O.update({svgtileid:[iter]});
cnt+=1;
else:
cnt = 0;
svgtileid = "tilesvg"+str(cnt);
svgid = 'svg'+str(cnt);
rowcnt = 2;
colcnt = 1;
# make the svg object
svgparameters1_O = {
"svgtype":'verticalbarschart2d_01',
"svgkeymap":[data1_keymap],
'svgid':'svg'+str(cnt),
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":350,
"svgheight":250,
"svgy1axislabel":"frequency"
};
svgtileparameters1_O = {
'tileheader':'Histogram',
'tiletype':'svg',
'tileid':svgtileid,
'rowid':"row"+str(rowcnt),
'colid':"col"+str(colcnt),
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-6"};
svgtileparameters1_O.update(svgparameters1_O);
parametersobject_O.append(svgparameters1_O);
tile2datamap_O.update({svgtileid:[1]});
# make the table object
tableparameters1_O = {
"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'tile1',
};
tabletileparameters1_O = {
'tileheader':'Histogram',
'tiletype':'table',
'tileid':"tabletile1",
'rowid':"row"+str(rowcnt+1),
'colid':"col1",
'tileclass':"panel panel-default",
'rowclass':"row",
'colclass':"col-sm-12"
};
tabletileparameters1_O.update(tableparameters1_O);
dataobject_O.append({"data":data_table_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys});
parametersobject_O.append(tabletileparameters1_O);
tile2datamap_O.update({"tabletile1":[0]})
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01ResequencingMutationsAnnotatedLineageArea_js(self,analysis_id_I,mutation_id_exclusion_list=[],frequency_threshold=0.1,max_position=4630000,data_dir_I="tmp"):
'''export data_stage01_resequencing_mutationsAnnotated to js file
Visualization: scatterlineplot of mutation frequency across jump time
'''
genomediff = genome_diff();
print('exportingdataStage01ResequencingMutationsAnnotated...')
# get the analysis information
experiment_ids,sample_names,time_points = [],[],[];
experiment_ids,sample_names,time_points = self.get_experimentIDAndSampleNameAndTimePoint_analysisID_dataStage01ResequencingAnalysis(analysis_id_I);
# convert time_point to intermediates
time_points_int = [int(x) for x in time_points];
intermediates,time_points,experiment_ids,sample_names = (list(t) for t in zip(*sorted(zip(time_points_int,time_points,experiment_ids,sample_names))))
intermediates = [i for i,x in enumerate(intermediates)];
mutation_data_O = [];
mutation_ids = [];
for sample_name_cnt,sample_name in enumerate(sample_names):
# query mutation data:
mutations = [];
mutations = self.get_mutations_experimentIDAndSampleName_dataStage01ResequencingMutationsAnnotated(experiment_ids[sample_name_cnt],sample_name);
for end_cnt,mutation in enumerate(mutations):
if mutation['mutation_position'] > max_position: #ignore positions great than 4000000
continue;
if mutation['mutation_frequency']<frequency_threshold:
continue;
# mutation id
mutation_id = genomediff._make_mutationID(mutation['mutation_genes'],mutation['mutation_type'],mutation['mutation_position']);
#mutation_id = self._make_mutationID(mutation['mutation_genes'],mutation['mutation_type'],mutation['mutation_position']);
tmp = {};
tmp.update(mutation);
tmp.update({'mutation_id':mutation_id});
mutation_data_O.append(tmp);
mutation_ids.append(mutation_id);
# screen out mutations
mutation_ids_screened = [x for x in mutation_ids if not x in mutation_id_exclusion_list];
mutation_ids_unique = list(set(mutation_ids_screened));
# get mutation information for all unique mutations
mutation_ids_uniqueInfo = [];
for mutation_id in mutation_ids_unique:
for mutation in mutation_data_O:
if mutation_id == mutation['mutation_id']:
tmp = {};
#tmp['mutation_id']=mutation['mutation_id']
#tmp['mutation_frequency']=mutation['mutation_frequency'];
#tmp['mutation_genes']=mutation['mutation_genes'];
#tmp['mutation_position']=mutation['mutation_position'];
#tmp['mutation_annotations']=mutation['mutation_annotations'];
#tmp['mutation_locations']=mutation['mutation_locations'];
#tmp['mutation_links']=mutation['mutation_links'];
#tmp['mutation_type']=mutation['mutation_type'];
tmp['mutation_id']=mutation['mutation_id'];
tmp['mutation_frequency']=mutation['mutation_frequency'];
if mutation['mutation_genes']:
tmp['mutation_genes']=";".join([x for x in mutation['mutation_genes'] if x is not None]);
else: tmp['mutation_genes']=mutation['mutation_genes'];
if mutation['mutation_position']:
tmp['mutation_position']=mutation['mutation_position'];
else: tmp['mutation_position']=mutation['mutation_position'];
if mutation['mutation_annotations']:
tmp['mutation_annotations']=";".join([x for x in mutation['mutation_annotations'] if x is not None]);
else: tmp['mutation_annotations']=mutation['mutation_annotations'];
if mutation['mutation_locations']:
tmp['mutation_locations']=";".join([x for x in mutation['mutation_locations'] if x is not None]);
else: tmp['mutation_locations']=mutation['mutation_locations'];
if mutation['mutation_links']:
tmp['mutation_links']=";".join([x for x in mutation['mutation_links'] if x is not None]);
else: tmp['mutation_links']=mutation['mutation_links'];
tmp['mutation_type']=mutation['mutation_type'];
tmp['used_']=mutation['used_'];
tmp['comment_']=mutation['comment_'];
mutation_ids_uniqueInfo.append(tmp);
break;
data_O = [];
# add in 0.0 frequency for mutations that are not found
for sample_name_cnt,sample_name in enumerate(sample_names):
for mutation_id in mutation_ids_uniqueInfo:
tmp = {};
tmp_fitted = {};
tmp['mutation_id']=mutation_id['mutation_id']
tmp['time_point']=time_points[sample_name_cnt]
tmp['intermediate']=intermediates[sample_name_cnt]
tmp['experiment_id']=experiment_ids[sample_name_cnt]
tmp['sample_name']=sample_name
tmp['mutation_frequency']=0.0;
tmp['mutation_genes']=mutation_id['mutation_genes'];
tmp['mutation_position']=mutation_id['mutation_position'];
tmp['mutation_annotations']=mutation_id['mutation_annotations'];
tmp['mutation_locations']=mutation_id['mutation_locations'];
tmp['mutation_links']=mutation_id['mutation_links'];
tmp['mutation_type']=mutation_id['mutation_type'];
tmp['used_']=mutation_id['used_'];
tmp['comment_']=mutation_id['comment_'];
for mutation in mutation_data_O:
if sample_name == mutation['sample_name'] and mutation_id['mutation_id'] == mutation['mutation_id']:
tmp['mutation_frequency']=mutation['mutation_frequency'];
tmp['comment_']=mutation['comment_'];
break;
data_O.append(tmp);
# dump chart parameters to a js files
data1_keys = [
#'experiment_id',
#'sample_name',
'mutation_id',
#'mutation_frequency',
'mutation_type',
'mutation_position',
#'mutation_data',
#'mutation_annotations',
'mutation_genes',
#'mutation_links',
'mutation_locations'
];
data1_nestkeys = ['mutation_id']; #horizontalareaplot2d_01
#data1_nestkeys = ['intermediate']; #verticalbarschart2d_01
data1_keymap = {'xdata':'intermediate',
'ydata':'mutation_frequency',
'serieslabel':'mutation_id',
'featureslabel':''};
parameters = {"chart1margin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"chart1width":500,"chart1height":350,
"chart1title":"Population mutation frequency", "chart1x1axislabel":"jump_time_point","chart1y1axislabel":"frequency"}
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys},{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1','htmltype':'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {
#"svgtype":'verticalbarschart2d_01',
"svgtype":'horizontalareaplot2d_01',
"svgkeymap":[data1_keymap,data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgstackoffset":"extend",
"svgx1axislabel":"jump_time_point","svgy1axislabel":"frequency",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Population mutation frequency','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'Population mutation frequency','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='project':
filename_str = self.settings['visualization_data'] + '/project/' + analysis_id_I + '_data_stage01_resequencing_mutationsAnnotated' + '.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
def export_dataStage01ResequencingAmplifications_js(self, analysis_id_I, data_dir_I="tmp"):
"""export amplifications and statistics to js file"""
ddtutilities = ddt_container()
# get the analysis info
# analysis_info = {};
# analysis_info = self.get_analysis_analysisID_dataStage01ResequencingAnalysis(analysis_id_I);
experiment_ids = []
lineage_names = []
sample_names = []
time_points = []
experiment_ids, lineage_names, sample_names, time_points = self.get_experimentIDAndLineageNameAndSampleNameAndTimePoint_analysisID_dataStage01ResequencingAnalysis(
analysis_id_I
)
# convert time_point to intermediates
time_points_int = [int(x) for x in time_points]
intermediates, time_points, experiment_ids, sample_names, lineage_names = (
list(t)
for t in zip(*sorted(zip(time_points_int, time_points, experiment_ids, sample_names, lineage_names)))
)
intermediates = [i for i, x in enumerate(intermediates)]
# get the data for the analysis
data1_O = []
data2_O = []
data3_O = []
for sn_cnt, sn in enumerate(sample_names):
data1_tmp = []
data1_tmp = self.get_rows_experimentIDAndSampleName_dataStage01ResequencingAmplifications_visualization(
experiment_ids[sn_cnt], sn
)
data1_O.extend(ddtutilities.make_listDict_JSONAndJSCompatible(data1_tmp))
data2_tmp = []
data2_tmp = self.get_rows_experimentIDAndSampleName_dataStage01ResequencingAmplificationStats(
experiment_ids[sn_cnt], sn
)
data2_O.extend(ddtutilities.make_listDict_JSONAndJSCompatible(data2_tmp))
data3_tmp = []
data3_tmp = self.get_rows_experimentIDAndSampleName_dataStage01ResequencingAmplificationAnnotations(
experiment_ids[sn_cnt], sn
)
data3_O.extend(ddtutilities.make_listDict_JSONAndJSCompatible(data3_tmp))
# dump chart parameters to a js files
data1_keys = [
"experiment_id",
"sample_name",
"genome_chromosome",
"genome_strand",
"amplification_start",
"amplification_stop",
"sample_name_strand",
]
data1_nestkeys = [
#'sample_name',
"genome_strand"
]
data1_keymap = {
"xdata": "genome_index",
"ydata": "reads",
"serieslabel": "sample_name_strand", # custom for vis
#'serieslabel':'genome_strand',
"featureslabel": "reads",
}
data2_keys = [
"experiment_id",
"sample_name",
"genome_chromosome",
"genome_strand",
#'reads_min',
#'reads_max',
#'reads_lb',
#'reads_ub',
#'reads_iq1',
#'reads_iq3',
#'reads_median',
#'reads_mean',
#'reads_var',
#'reads_n',
"amplification_start",
"amplification_stop",
]
data2_nestkeys = ["sample_name"]
data2_keymap = {
"xdata": "genome_index",
"ydata": "reads",
"serieslabel": "genome_strand",
"featureslabel": "reads",
}
data3_keys = [
"experiment_id",
"sample_name",
"genome_chromosome",
"genome_strand",
"feature_annotations",
"feature_genes",
"feature_locations",
"feature_links",
"feature_start",
"feature_stop",
"feature_types",
"amplification_start",
"amplification_stop",
]
data3_nestkeys = ["sample_name"]
data3_keymap = {
"xdata": "genome_index",
"ydata": "reads",
"serieslabel": "genome_strand",
"featureslabel": "reads",
}
# make the data object
dataobject_O = [
{"data": data1_O, "datakeys": data1_keys, "datanestkeys": data1_nestkeys},
{"data": data2_O, "datakeys": data2_keys, "datanestkeys": data2_nestkeys},
{"data": data3_O, "datakeys": data3_keys, "datanestkeys": data3_nestkeys},
]
# make the tile parameter objects
# linked set #1
formtileparameters_O = {
"tileheader": "Filter menu",
"tiletype": "html",
"tileid": "filtermenu1",
"rowid": "row1",
"colid": "col1",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-4",
}
formparameters_O = {
"htmlid": "filtermenuform1",
"htmltype": "form_01",
"formsubmitbuttonidtext": {"id": "submit1", "text": "submit"},
"formresetbuttonidtext": {"id": "reset1", "text": "reset"},
"formupdatebuttonidtext": {"id": "update1", "text": "update"},
}
formtileparameters_O.update(formparameters_O)
svgparameters_O = {
"svgtype": "scatterplot2d_01",
"svgkeymap": [data1_keymap, data1_keymap],
"svgid": "svg1",
"svgmargin": {"top": 50, "right": 150, "bottom": 50, "left": 50},
"svgwidth": 500,
"svgheight": 350,
"svgx1axislabel": "index",
"svgy1axislabel": "reads",
"svgformtileid": "filtermenu1",
"svgresetbuttonid": "reset1",
"svgsubmitbuttonid": "submit1",
"svgx1axistickformat": ".2e",
"svgx1axisticktextattr": {
"transform": "matrix(0,1,-1,0,16,6)",
# "transform":'rotate(90)',"transform":'translate(0,10)'
},
"svgx1axisticktextstyle": {"text-anchor": "start"},
}
svgtileparameters_O = {
"tileheader": "Amplifications",
"tiletype": "svg",
"tileid": "tile2",
"rowid": "row1",
"colid": "col2",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-8",
}
svgtileparameters_O.update(svgparameters_O)
# linked set #2
formtileparameters2_O = {
"tileheader": "Filter menu",
"tiletype": "html",
"tileid": "filtermenu2",
"rowid": "row2",
"colid": "col1",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-4",
}
formparameters2_O = {
"htmlid": "filtermenuform2",
"htmltype": "form_01",
"formsubmitbuttonidtext": {"id": "submit2", "text": "submit"},
"formresetbuttonidtext": {"id": "reset2", "text": "reset"},
"formupdatebuttonidtext": {"id": "update2", "text": "update"},
}
formtileparameters2_O.update(formparameters2_O)
tableparameters_O = {
"tabletype": "responsivetable_01",
"tableid": "table1",
"tablefilters": None,
"tableclass": "table table-condensed table-hover",
"tableformtileid": "filtermenu2",
"tableresetbuttonid": "reset2",
"tablesubmitbuttonid": "submit2",
}
tabletileparameters_O = {
"tileheader": "Amplification statistics",
"tiletype": "table",
"tileid": "tile3",
"rowid": "row2",
"colid": "col2",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-12",
}
tabletileparameters_O.update(tableparameters_O)
# linked set #3
formtileparameters3_O = {
"tileheader": "Filter menu",
"tiletype": "html",
"tileid": "filtermenu3",
"rowid": "row3",
"colid": "col1",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-4",
}
formparameters3_O = {
"htmlid": "filtermenuform3",
"htmltype": "form_01",
"formsubmitbuttonidtext": {"id": "submit3", "text": "submit"},
"formresetbuttonidtext": {"id": "reset3", "text": "reset"},
"formupdatebuttonidtext": {"id": "update3", "text": "update"},
}
formtileparameters3_O.update(formparameters3_O)
tableparameters2_O = {
"tabletype": "responsivetable_01",
"tableid": "table2",
"tablefilters": None,
"tableclass": "table table-condensed table-hover",
"tableformtileid": "filtermenu3",
"tableresetbuttonid": "reset3",
"tablesubmitbuttonid": "submit3",
}
tabletileparameters2_O = {
"tileheader": "Amplification annotations",
"tiletype": "table",
"tileid": "tile4",
"rowid": "row3",
"colid": "col2",
"tileclass": "panel panel-default",
"rowclass": "row",
"colclass": "col-sm-12",
}
tabletileparameters2_O.update(tableparameters2_O)
parametersobject_O = [
formtileparameters_O,
svgtileparameters_O,
formtileparameters2_O,
tabletileparameters_O,
formtileparameters3_O,
tabletileparameters2_O,
]
tile2datamap_O = {
"filtermenu1": [0],
"tile2": [0, 0],
"tile3": [1],
"tile4": [2],
"filtermenu2": [1],
"filtermenu3": [2],
}
filtermenuobject_O = [
{
"filtermenuid": "filtermenu1",
"filtermenuhtmlid": "filtermenuform1",
"filtermenusubmitbuttonid": "submit1",
"filtermenuresetbuttonid": "reset1",
"filtermenuupdatebuttonid": "update1",
},
{
"filtermenuid": "filtermenu2",
"filtermenuhtmlid": "filtermenuform2",
"filtermenusubmitbuttonid": "submit2",
"filtermenuresetbuttonid": "reset2",
"filtermenuupdatebuttonid": "update2",
},
{
"filtermenuid": "filtermenu3",
"filtermenuhtmlid": "filtermenuform3",
"filtermenusubmitbuttonid": "submit3",
"filtermenuresetbuttonid": "reset3",
"filtermenuupdatebuttonid": "update3",
},
]
# dump the data to a json file
ddtutilities = ddt_container(
parameters_I=parametersobject_O,
data_I=dataobject_O,
tile2datamap_I=tile2datamap_O,
filtermenu_I=filtermenuobject_O,
)
if data_dir_I == "tmp":
filename_str = self.settings["visualization_data"] + "/tmp/ddt_data.js"
elif data_dir_I == "data_json":
data_json_O = ddtutilities.get_allObjects_js()
return data_json_O
with open(filename_str, "w") as file:
file.write(ddtutilities.get_allObjects())
def export_boxAndWhiskersPlot_peakResolution_js(self,experiment_id_I,
component_name_pairs_I=[],
peakInfo_parameter_I = ['rt_dif','resolution'],
data_dir_I='tmp'):
'''Export data for a box and whiskers plot'''
print('export_boxAndWhiskersPlot...')
data_O=[];
if peakInfo_parameter_I:
peakInfo_parameter = peakInfo_parameter_I;
else:
peakInfo_parameter = [];
peakInfo_parameter = self.get_peakInfoParameter_experimentID_dataStage01PeakResolution(experiment_id_I);
for parameter in peakInfo_parameter:
if component_name_pairs_I:
component_name_pairs = component_name_pairs_I;
else:
component_name_pairs = [];
component_name_pairs = self.get_componentNamePairs_experimentIDAndPeakInfoParameter_dataStage01PeakResolution(experiment_id_I,parameter);
for cn in component_name_pairs:
# get the data
row = {};
row = self.get_row_experimentIDAndPeakInfoParameterComponentName_dataStage01PeakResolution(experiment_id_I,parameter,cn)
if row and row['peakInfo_ave']:
#TODO: fix type in database 'acqusition_date_and_times'
tmp_list = [];
for d in row['acqusition_date_and_times']:
tmp = None;
tmp = self.convert_datetime2string(d);
tmp_list.append(tmp);
row['acqusition_date_and_times'] = tmp_list;
data_O.append(row);
# dump chart parameters to a js files
data1_keys = ['experiment_id',
'component_group_name_pair',
'component_name_pair',
'peakInfo_parameter',
#'peakInfo_ave',
#'peakInfo_cv',
#'peakInfo_lb',
#'peakInfo_ub',
#'peakInfo_units',
'sample_names',
'sample_types',
#'acqusition_date_and_times'
];
data1_nestkeys = ['component_name_pair'];
data1_keymap = {'xdata':'component_name_pair',
'ydatamean':'peakInfo_ave',
'ydatalb':'peakInfo_lb',
'ydataub':'peakInfo_ub',
#'ydatamin':None,
#'ydatamax':None,
#'ydataiq1':None,
#'ydataiq3':None,
#'ydatamedian':None,
'serieslabel':'peakInfo_parameter',
'featureslabel':'component_name_pair'};
# make the data object
dataobject_O = [{"data":data_O,"datakeys":data1_keys,"datanestkeys":data1_nestkeys}];
# make the tile parameter objects
formtileparameters_O = {'tileheader':'Filter menu','tiletype':'html','tileid':"filtermenu1",'rowid':"row1",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-4"};
formparameters_O = {'htmlid':'filtermenuform1',"htmltype":'form_01',"formsubmitbuttonidtext":{'id':'submit1','text':'submit'},"formresetbuttonidtext":{'id':'reset1','text':'reset'},"formupdatebuttonidtext":{'id':'update1','text':'update'}};
formtileparameters_O.update(formparameters_O);
svgparameters_O = {"svgtype":'boxandwhiskersplot2d_01',"svgkeymap":[data1_keymap],
'svgid':'svg1',
"svgmargin":{ 'top': 50, 'right': 150, 'bottom': 50, 'left': 50 },
"svgwidth":500,"svgheight":350,
"svgx1axislabel":"component_name_pair","svgy1axislabel":"parameter_value",
'svgformtileid':'filtermenu1','svgresetbuttonid':'reset1','svgsubmitbuttonid':'submit1'};
svgtileparameters_O = {'tileheader':'Custom box and whiskers plot','tiletype':'svg','tileid':"tile2",'rowid':"row1",'colid':"col2",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-8"};
svgtileparameters_O.update(svgparameters_O);
tableparameters_O = {"tabletype":'responsivetable_01',
'tableid':'table1',
"tablefilters":None,
"tableclass":"table table-condensed table-hover",
'tableformtileid':'filtermenu1','tableresetbuttonid':'reset1','tablesubmitbuttonid':'submit1'};
tabletileparameters_O = {'tileheader':'peakResolution','tiletype':'table','tileid':"tile3",'rowid':"row2",'colid':"col1",
'tileclass':"panel panel-default",'rowclass':"row",'colclass':"col-sm-12"};
tabletileparameters_O.update(tableparameters_O);
parametersobject_O = [formtileparameters_O,svgtileparameters_O,tabletileparameters_O];
tile2datamap_O = {"filtermenu1":[0],"tile2":[0],"tile3":[0]};
# dump the data to a json file
ddtutilities = ddt_container(parameters_I = parametersobject_O,data_I = dataobject_O,tile2datamap_I = tile2datamap_O,filtermenu_I = None);
if data_dir_I=='tmp':
filename_str = self.settings['visualization_data'] + '/tmp/ddt_data.js'
elif data_dir_I=='data_json':
data_json_O = ddtutilities.get_allObjects_js();
return data_json_O;
with open(filename_str,'w') as file:
file.write(ddtutilities.get_allObjects());
