add matplotlib fallback plotting

Author: ptooley

bin/ipynb_to_report

@@ -8,10 +8,25 @@ output_filename="$(echo ${report_nb} | sed 's/ /_/g' | sed 's/.ipynb$//').tex"
 
 export TEXINPUTS="${template_dir}//:"
 
+export PYPOP_HEADLESS="TRUE"
+
 jupyter nbconvert "${report_nb}" \
                   --execute \
                   --to latex \
-                  --template=${template_dir}/pop_report.tplx \
+                  --template latex \
+                  --template-file ${template_dir}/pop_report.tplx \
                   --output=${output_filename}
 
-texi2pdf ${output_filename}
+if [ $? -ne 0 ]; then
+  echo Error: nbconvert failed - see documentation or PyPOP github for assistance.
+  exit -1
+fi
+
+texi2pdf ${output_filename} &>/dev/null
+
+if [ $? -ne 0 ]; then
+  echo Error: latex compilation failed. See ${output_filename/.tex/.log} for details
+  exit -1
+fi
+
+echo ${output_filename/.tex/.pdf} written successfully.

ipython_templates/pop_report.tplx

@@ -1,4 +1,4 @@
-((*- extends 'article.tplx' -*))
+((*- extends 'report.tex.j2' -*))
 
 ## Set pop_report class
 ((* block docclass *))
@@ -54,6 +54,12 @@
                                cell.metadata.get("label", "")) )))
 ((* endblock data_svg *))
 
+((*- block data_html *))
+((* endblock data_html *))
+
+((*- block data_text *))
+((* endblock data_text *))
+
 
 ## macro to encapsulate output files in figures
 ((* macro draw_figure_with_caption(filename, caption, label) -*))

pypop/backends/__init__.py

@@ -0,0 +1,91 @@
+# Copyright (c) 2019, The Numerical Algorithms Group, Ltd. All rights reserved.
+
+"""\
+PCF File Parser
+---------------
+
+Provides lightweight support for interrogating the contents of a PRV file, including all
+event types and id->string lookups for value types.
+"""
+
+from collections import namedtuple
+
+import pandas
+
+Event = namedtuple("Event", ["ID", "Name", "State", "Values"])
+Value = namedtuple("Value", ["ID", "Name"])
+State = namedtuple("State", ["ID", "Name"])
+
+class PCF:
+
+    def __init__(self, pcf_path):
+
+        self._pcf_path = pcf_path
+
+        self._state_names = {}
+        self._event_names = {}
+        self._event_states = {}
+        self._event_vals = {}
+
+        self._states = None
+        self._events = None
+        self._parse_pcf()
+
+    @property
+    def filename(self):
+        return self._pcf_path
+
+    @property
+    def event_names(self):
+        return self._event_names
+
+    @property
+    def event_values(self):
+        return self._event_vals
+
+    @property
+    def events(self):
+        return self._events
+
+
+    def _parse_pcf(self):
+
+        states = []
+        events = []
+        values = []
+
+        try:
+            with open(self._pcf_path, "rt") as fh:
+                block_mode = None
+                for line in fh:
+                    if not line.strip():
+                        continue
+                    if not line[0].isdigit():
+                        block_mode = line.split()[0]
+                        continue
+
+                    if block_mode == "EVENT_TYPE":
+                        elem = line.strip().split(maxsplit=2)
+                        event_id = int(elem[1])
+                        events.append(Event(event_id, elem[2], elem[0], {}))
+                        values[event_id] = []
+                        continue
+
+                    if block_mode == "VALUES":
+                        elem = line.strip().split(maxsplit=1)
+                        value_id = int(elem[0])
+                        values[event_id].append(Value(value_id, elem[1]))
+
+                    if block_mode == "STATES":
+                        elem = line.strip().split(maxsplit=1)
+                        state_id = int(elem[0])
+                        states.append(State(state_id, elem[1]))
+
+        except FileNotFoundError:
+            pass
+
+        self._events = pandas.DataFrame(events)
+        self._states = pandas.DataFrame(states)
+        self._event_values = {k:pandas.DataFrame(v) for k,v in values.items}
+
+