WIP: update transform model to send history

chem_spectra/controller/transform_api.py

@@ -82,7 +82,11 @@ def zip_jcamp_n_img():
             tf_jcamp, tf_img, tf_csv, tf_nmrium = cmpsr.tf_jcamp(), cmpsr.tf_img(), cmpsr.tf_csv(), cmpsr.generate_nmrium()
             spc_type = cmpsr.core.ncl if cmpsr.core.typ == 'NMR' else cmpsr.core.typ
             if (tf_csv is not None and tf_csv != False):
-                memory = to_zip_response([tf_jcamp, tf_img, tf_csv])
+                if (cmpsr.core.is_cyclic_volta):
+                    history_logs = cmpsr.generate_changed_history()
+                    memory = to_zip_response([tf_jcamp, tf_img, tf_csv, history_logs])
+                else:
+                    memory = to_zip_response([tf_jcamp, tf_img, tf_csv])
             elif (tf_nmrium is not None):
                 memory = to_zip_response([tf_jcamp, tf_img, tf_nmrium])
             else:

chem_spectra/lib/composer/ni.py

@@ -828,11 +828,16 @@ def generate_changed_history(self):
         if self.core.is_cyclic_volta == False:
             return None
 
-        cyclicvolta = self.core.params.get('cyclicvolta', None)
+        params = self.core.params
+        cyclicvolta = params.get('cyclicvolta', None)
 
         history_data = {}
         if cyclicvolta is not None:
-            history_data = {}
+            jcamp_idx = params.get('jcamp_idx', 0)
+            spectra_list = cyclicvolta.get('spectraList', [])
+            if len(spectra_list) > 0:
+                current_history = spectra_list[jcamp_idx]
+                history_data = current_history
 
         json_data = json.dumps(history_data)
         tf_history_log = tempfile.NamedTemporaryFile(suffix='.json')

tests/test_cyclic_volta.py

@@ -19,6 +19,10 @@ def jcamp_file_cv():
 def jcamp_file_1H():
     return source_nmr
 
+@pytest.fixture
+def cv_params():
+    return {'select_x':'','ref_name':'- - -','ref_value':'0','peaks_str':'-0.4890399999999999,-0.000033747399999999995#1.9294829999999998,0.00023741','delta':0.0,'mass':58.078250319999995,'scan':0,'thres':100.0,'clear':False,'integration':{'stack':[],'refArea':1,'refFactor':1,'shift':0},'multiplicity':{'stack':[],'smExtext':False,'shift':0},'ext':'jdx','fname':'File053_BagIt.2_bagit','waveLength':{'name':'CuKalpha','value':0.15406,'label':'Cu Kα','unit':'nm'},'list_max_min_peaks':[{'min':{'x':1.8095560000000002,'y':2.2759699999999998e-05},'max':{'x':1.919489,'y':0.00023641},'isRef':False,'e12':1.8645225,'pecker':None}],'cyclicvolta':{'spectraList':[{'list':[{'min':None,'max':None,'isRef':False,'e12':None}],'origin':[{'min':None,'max':None,'isRef':False,'e12':None}],'selectedIdx':0,'isWorkMaxPeak':True,'jcampIdx':-1,'shift':{'ref':None,'val':0,'prevValue':0},'hasRefPeak':False},{'list':[{'min':{'x':1.8095560000000002,'y':2.2759699999999998e-05},'max':{'x':1.919489,'y':0.00023641},'isRef':False,'e12':1.8645225,'pecker':None}],'origin':[{'min':{'x':1.8095560000000002,'y':2.2759699999999998e-05},'max':{'x':1.919489,'y':0.00023641},'isRef':False,'e12':1.8645225,'pecker':None}],'selectedIdx':0,'isWorkMaxPeak':True,'jcampIdx':1,'shift':{'ref':None,'val':0,'prevValue':0},'hasRefPeak':False},{'list':[{'min':None,'max':None,'isRef':False,'e12':None}],'origin':[{'min':None,'max':None,'isRef':False,'e12':None}],'selectedIdx':0,'isWorkMaxPeak':True,'jcampIdx':-1,'shift':{'ref':None,'val':0,'prevValue':0},'hasRefPeak':False}]},'jcamp_idx':1,'axesUnits':None,}
+
 def test_cv_base_converter(jcamp_file_cv):
     jbcv = JcampBaseConverter(jcamp_file_cv)
     assert jbcv.is_cyclic_volta == True
@@ -62,4 +66,15 @@ def test_ni_composer_generate_changed_history_cv_no_history(jcamp_file_cv):
 
     with open(history_file.name) as log_file:
         history = json.load(log_file)
-        assert history == {}
+        assert history == {}
+
+def test_ni_composer_generate_changed_history_cv_has_history(jcamp_file_cv, cv_params):
+    base_converter = JcampBaseConverter(jcamp_file_cv)
+    base_converter.params = cv_params
+    ni_converter = JcampNIConverter(base=base_converter)
+    ni_composer = NIComposer(core=ni_converter)
+    history_file = ni_composer.generate_changed_history()
+
+    with open(history_file.name) as log_file:
+        history = json.load(log_file)
+        assert history == {'list':[{'min':{'x':1.8095560000000002,'y':2.2759699999999998e-05},'max':{'x':1.919489,'y':0.00023641},'isRef':False,'e12':1.8645225,'pecker':None}],'origin':[{'min':{'x':1.8095560000000002,'y':2.2759699999999998e-05},'max':{'x':1.919489,'y':0.00023641},'isRef':False,'e12':1.8645225,'pecker':None}],'selectedIdx':0,'isWorkMaxPeak':True,'jcampIdx':1,'shift':{'ref':None,'val':0,'prevValue':0},'hasRefPeak':False}