WIP: Regolith Grant Report Builder

regolith/builders/grantreportbuilder.py

@@ -1,5 +1,5 @@
 """Builder for Proposal Reviews."""
-from datetime import datetime, date
+import datetime
 import time
 from nameparser import HumanName
 
@@ -15,6 +15,13 @@
 )
 
 
+def subparser(subpi):
+    subpi.add_argument("start_date", help="start date of the reporting period, formatted as YYYY-MM-DD",
+                       default=None)
+    subpi.add_argument("end_date", help="end date of the reporting period, formatted as YYYY-MM-DD")
+    return subpi
+
+
 class GrantReportBuilder(LatexBuilderBase):
     """Build a proposal review from database entries"""
     btype = "grantreport"
@@ -36,12 +43,23 @@ def construct_global_ctx(self):
 
     def latex(self):
         """Render latex template"""
+        rc = self.rc
         # Get Dates
-        today = str(date.today()).split("-")
-        end_year, end_month, end_day = int(today[0]), int(today[1]), int(today[2])
-        begin_year, begin_month, begin_day = int(today[0]) - 1, int(today[1]), int(today[2])
-        end_date = date(end_year, end_month, end_day)
-        begin_date = date(begin_year, begin_month, begin_day)
+        start_date = rc.start_date.split("-")
+        end_date = rc.end_date.split("-")
+        begin_year, begin_month, begin_day = int(start_date[0]), int(start_date[1]), int(start_date[2])
+        end_year, end_month, end_day = int(end_date[0]), int(end_date[1]), int(end_date[2])
+        end_date = datetime.datetime(end_year, end_month, end_day)
+        begin_date = datetime.datetime(begin_year, begin_month, begin_day)
+
+        # NSF Grant _id
+        grant_name = "dmref"
+        # Get people linked to grant and active during reporting period
+        people = [person for person in self.gtx['people']
+                  if grant_name in person['grant']]
+        # Get prums linked to grant and active/finished during the reporting period
+
+        # Accomplishments
 
         # Get All Active Members
         current_members = [person for person in self.gtx['people'] if person['active']]
@@ -64,8 +82,6 @@ def latex(self):
 
         # Plans for Next Reporting Period to Accomplish Goals
 
-
-
         self.render(
             "grantreport.txt",
             "billinge_grant_report.txt",
@@ -76,5 +92,5 @@ def latex(self):
             beginMonth=begin_month,
             beginDay=begin_day,
             presentations=valid_presentations,
-            individuals=individuals_data
+            individuals=individuals_data,
         )

regolith/templates/grantreport.txt

@@ -1,10 +1,31 @@
-NSF {{beginYear}}-{{endYear}} Annual Report by
-{{authorFullName}}, ({{ institution }})
+NSF {{beginYear}}-{{endYear}} Annual Report by {{authorFullName}}, ({{ institution }})
 
 Accomplishments
 ------------------------------
 * What are the major goals of the project?
 
+In real-world applications, materials are rarely perfect crystals and their properties
+depend sensitively on defects, nanoscale structures, interfaces, surfaces and multi-scale
+heterogeneities. A major challenge is to gain a greater understanding of how such
+"imperfect" materials operate, including on different length and time-scales. In situations
+as complicated as this it is essential to validate theories against experiment, and vice versa.
+A more tightly coupled partnership between experiment and theory is needed, having its roots
+in information theory: the models need to capture all the physics of the problem become more
+complicated, while at the same time the information content of experimental data is reduced,
+due to lower resolution from finite size effects, defects, the presence of multiple components
+with overlapping problems, which yield unreliable and non-unique solutions, a bottleneck to
+predictive materials discovery. We will develop novel mathematical approaches to address this
+problem. We will study as a test case the nanostructure inverse problem (NIP), a well defined
+but generally ill-posed materials inverse problem; however, the methods that we develop will
+have much broader applicability in the world of materials discovery.
+
+Goal 1: Develop databases of nanostructure data from model systems
+Goal 2: Develop data analytic and stochastic optimization methodologies for robust
+nanostructure solutions
+Goal 3: Develop software infrastructure for nanostructure modeling that use the databases
+and the new methodologies for nanostructure solution
+Goal 4: Apply this to real scientific problems
+
 * What was accomplished under these goals (you must provide information for
 at least one of the 4 categories below)?
 Major Activities:

tests/outputs/grantreport/billinge_grant_report.txt

@@ -1,10 +1,31 @@
-NSF 2019-2020 Annual Report by
-Simon J. L. Billinge, (Columbia University)
+NSF 2019-2020 Annual Report by Simon J. L. Billinge, (Columbia University)
 
 Accomplishments
 ------------------------------
 * What are the major goals of the project?
 
+In real-world applications, materials are rarely perfect crystals and their properties
+depend sensitively on defects, nanoscale structures, interfaces, surfaces and multi-scale
+heterogeneities. A major challenge is to gain a greater understanding of how such
+"imperfect" materials operate, including on different length and time-scales. In situations
+as complicated as this it is essential to validate theories against experiment, and vice versa.
+A more tightly coupled partnership between experiment and theory is needed, having its roots
+in information theory: the models need to capture all the physics of the problem become more
+complicated, while at the same time the information content of experimental data is reduced,
+due to lower resolution from finite size effects, defects, the presence of multiple components
+with overlapping problems, which yield unreliable and non-unique solutions, a bottleneck to
+predictive materials discovery. We will develop novel mathematical approaches to address this
+problem. We will study as a test case the nanostructure inverse problem (NIP), a well defined
+but generally ill-posed materials inverse problem; however, the methods that we develop will
+have much broader applicability in the world of materials discovery.
+
+Goal 1: Develop databases of nanostructure data from model systems
+Goal 2: Develop data analytic and stochastic optimization methodologies for robust
+nanostructure solutions
+Goal 3: Develop software infrastructure for nanostructure modeling that use the databases
+and the new methodologies for nanostructure solution
+Goal 4: Apply this to real scientific problems
+
 * What was accomplished under these goals (you must provide information for
 at least one of the 4 categories below)?
 Major Activities: