Implement extract by EMPI only

modules/cold-extraction/ColdDataRetriever.py

@@ -177,6 +177,22 @@ def retrieve():
                 subprocess.call("{0}/movescu -c {1} -b {2} -M PatientRoot -m PatientID={3} -m AccessionNumber={4} --dest {5}".format(DCM4CHE_BIN, SRC_AET, QUERY_AET, PatientID, Accession, DEST_AET), shell=True)
                 extracted_ones.append(temp_id)
 
+    # For the cases that have the EMPI.
+    elif (extraction_type == 'empi'):
+        # Create our Identifier (query) dataset
+        for pid in range(0, len(patients)):
+            PatientID = patients[pid]
+            if NIGHTLY_ONLY:
+                if (datetime.datetime.now().hour >= END_HOUR and datetime.datetime.now().hour < START_HOUR):
+                    # log once while sleeping
+                    logging.info("Nightly mode. Niffler schedules the extraction to resume at start hour {0} and start within 30 minutes after that. It will then pause at the end hour {1}".format(START_HOUR, END_HOUR))
+                while (datetime.datetime.now().hour >= END_HOUR and datetime.datetime.now().hour < START_HOUR):
+                    # sleep for 5 minutes
+                    time.sleep(300)
+            if ((not resume) or (resume and (PatientID not in extracted_ones))):
+                subprocess.call("{0}/movescu -c {1} -b {2} -M PatientRoot -m PatientID={3} --dest {4}".format(DCM4CHE_BIN, SRC_AET, QUERY_AET, PatientID, DEST_AET), shell=True)
+                extracted_ones.append(PatientID)
+
     # For the cases that does not have the typical EMPI and Accession values together.
     elif (extraction_type == 'empi_date' or extraction_type == 'accession'):
         # Create our Identifier (query) dataset

modules/cold-extraction/README.md

@@ -45,43 +45,39 @@ First, place the csv file adhering to the correct formats in a folder (by defaul
 
 * Please include a header for the csv, such as "EMPI,Accession", as otherwise the first line will be ignored.
 
-* Usual fields that Niffler supports by default: AccessionNumber, AccessionNumber and EMPI, EMPI and a date (indicate whether StudyDate or AcquisitionDate). 
+* Usual fields that Niffler supports by default: EMPI, AccessionNumber, AccessionNumber and EMPI, EMPI and a date (indicate whether StudyDate or AcquisitionDate). 
 
 The format examples:
-
+```
 [1]
-
 EMPI,Accession
-
 AAAAA,BBBBBYYBBBBB
-
 AAAAA,BBBBBYYBBBBB
-
 AAAAA,BBBBBYYBBBBB
 
 [2]
-
 EMPI, Study Date
-
 AAAAA,20180723
-
 AAAAA,20180724
-
 AAAAA,20180725
 
 Make sure the accession's year is in the YY format.
 
 
 [3]
 Accession
-
 BBBBBYYBBBBB
-
 BBBBBYYBBBBB
-
 BBBBBYYBBBBB
 
 
+[4]
+EMPI
+AAAAA
+AAAAA
+AAAAA
+```
+
 ## Configuring Extraction Profile with config.json.
 
 Find the config.json file in the folder and modify accordingly.
@@ -96,7 +92,7 @@ config.json entries are to be set *for each* Niffler on-demand DICOM extractions
 
 * *CsvFile*: Enter the correct csv file name with a relative path to the current folder or a full path. The default value given assumes the CSV file to be in a "csv" folder in the current folder.
 
-* *ExtractionType*: Currently supported options, empi_accession (extractions based on EMPI and AccessionNumber), accession (extractions based solely on AccessionNumber), empi_date (extractions based on EMPI and a date such as StudyDate or AcquisitionDate).
+* *ExtractionType*: Currently supported options, empi (extractions based on EMPI), empi_accession (extractions based on EMPI and AccessionNumber), accession (extractions based solely on AccessionNumber), empi_date (extractions based on EMPI and a date such as StudyDate or AcquisitionDate).
 
 * *AccessionIndex*: Set the CSV column index of AccessionNumber for extractions with Accessions (with or without EMPI provided). Entry count starts with 0. For extractions other than types of accession and empi_accession, leave this entry unmodified.