Update viz.

breakpoint_tasks.py

@@ -101,7 +101,8 @@ def requires(self):
             'climate': export_tasks.ClimateExportTask(),
             'sweep': export_tasks.SweepExportTask(),
             'hist': export_tasks.HistExportTask(),
-            'summary': export_tasks.SummaryExportTask()
+            'summary': export_tasks.SummaryExportTask(),
+            'combined': export_tasks.CombinedTasksRecordTask()
         }
 
     def output(self):

paper/fill_template.py

@@ -20,7 +20,11 @@ def main():
         source_contents = f.read()
 
     loader = jinja2.BaseLoader()
-    template = jinja2.Environment(loader=loader).from_string(source_contents)
+    template = jinja2.Environment(
+        loader=loader,
+        comment_start_string='{//',
+        comment_end_string='//}'
+    ).from_string(source_contents)
 
     with open(template_loc) as f:
         template_vals = json.load(f)

paper/paper.bib

@@ -1484,3 +1484,26 @@ @article{hunt_fossil_2020
 	langid = {english},
 	file = {Full Text:/home/sam/Zotero/storage/2T72GJT4/Hunt et al. - 2020 - Fossil Energy Use, Climate Change Impacts, and Air.pdf:application/pdf},
 }
+
+@article{knight_developing_2010,
+	title = {Developing Variable Unit-Structure Premium Rate Differentials in Crop Insurance},
+	volume = {92},
+	issn = {00029092, 14678276},
+	url = {http://www.jstor.org/stable/40647972},
+	abstract = {Federal crop insurance programs offer producers the option of insuring farm units individually or as an aggregate unit. Existing programs offer a fixed 10\% discount for most growers taking coverage at the aggregate level. This article describes an analysis of risk changes when units are aggregated. The methods described here, which base unit aggregation discounts on observable farm characteristics, are approved for implementation into the Federal Crop Insurance Program.},
+	pages = {141--151},
+	number = {1},
+	journaltitle = {American Journal of Agricultural Economics},
+	author = {Knight, Thomas O. and Coble, Keith H. and Goodwin, Barry K. and Rejesus, Roderick M. and Seo, Sangtaek},
+	urldate = {2024-07-11},
+	date = {2010},
+	note = {Publisher: [Agricultural \& Applied Economics Association, Oxford University Press]},
+}
+
+@misc{zulauf_importance_2023,
+	title = {The Importance of Insurance Unit in Crop Insurance Policy Debates},
+	url = {https://farmdocdaily.illinois.edu/2023/06/the-importance-of-insurance-unit-in-crop-insurance-policy-debates.html},
+	publisher = {University of Illinois},
+	author = {Zulauf, Carl},
+	date = {2023-06-12},
+}

paper/render.sh

@@ -4,9 +4,9 @@ cd ..
 
 python3 fill_template.py ./paper.md ./outputs/stats.json ./paper_filled.md
 
-pandoc -o paper_filled.pdf --citeproc --number-sections --template=default.tex paper_filled.md
-pandoc -o paper_filled.tex --citeproc --number-sections --template=default.tex paper_filled.md
-pandoc -o paper_filled.docx --citeproc --number-sections paper_filled.md
+pandoc -o paper_filled.pdf --citeproc --number-sections --filter pandoc-tablenos --filter pandoc-fignos --template=default.tex paper_filled.md
+pandoc -o paper_filled.tex --citeproc --number-sections --filter pandoc-tablenos --filter pandoc-fignos --template=default.tex paper_filled.md
+pandoc -o paper_filled.docx --citeproc --number-sections --filter pandoc-tablenos --filter pandoc-fignos paper_filled.md
 
 rm -r arxiv
 mkdir arxiv

paper/requirements.txt

@@ -0,0 +1,2 @@
+pandoc-fignos==2.4.0
+pandoc-tablenos==2.3.0

paper/viz/const.py

@@ -25,13 +25,13 @@
 BUTTON_WIDTH_COMPACT = 78
 BUTTON_WIDTH_NARROW = 60
 
-YIELD_MIN_VALUE = 0
-YIELD_MAX_VALUE = 3000
-YIELD_INCREMENT = 250
+YIELD_MIN_VALUE = -0.4
+YIELD_MAX_VALUE = 0.4
+YIELD_INCREMENT = 0.05
 
-YIELD_CHANGE_MIN_VALUE = -100
-YIELD_CHANGE_MAX_VALUE = 100
-YIELD_CHANGE_INCREMENT = 10
+YIELD_CHANGE_MIN_VALUE = -0.4
+YIELD_CHANGE_MAX_VALUE = 0.4
+YIELD_CHANGE_INCREMENT = 0.05
 
 RISK_MIN_VALUE = -30
 RISK_MAX_VALUE = 60
@@ -46,52 +46,52 @@
 ADAPT_INCREMENT = 10
 
 VAR_MINS = {
-    'chirps': -2,
-    'rhn': -4,
-    'rhx': -4,
-    'svp': -0.1,
-    'tmax': -5,
-    'tmin': -5,
-    'vpd': -0.1,
-    'wbgtmax': -5
+    'chirps': -3,
+    'rhn': -3,
+    'rhx': -3,
+    'svp': -3,
+    'tmax': -3,
+    'tmin': -3,
+    'vpd': -3,
+    'wbgtmax': -3
 }
 
 VAR_MAXS = {
-    'chirps': 2,
-    'rhn': 4,
-    'rhx': 4,
-    'svp': 0.5,
-    'tmax': 5,
-    'tmin': 5,
-    'vpd': 0.5,
-    'wbgtmax': 5
+    'chirps': 3,
+    'rhn': 3,
+    'rhx': 3,
+    'svp': 3,
+    'tmax': 3,
+    'tmin': 3,
+    'vpd': 3,
+    'wbgtmax': 3
 }
 
 VAR_INCREMENTS = {
     'chirps': 0.5,
     'rhn': 0.5,
     'rhx': 0.5,
-    'svp': 0.1,
-    'tmax': 1,
-    'tmin': 1,
-    'vpd': 0.1,
-    'wbgtmax': 1
+    'svp': 0.5,
+    'tmax': 0.5,
+    'tmin': 0.5,
+    'vpd': 0.5,
+    'wbgtmax': 0.5
 }
 
 MAX_COUNT = 0.1
 
 CATEGORY_COLORS = {
     'not significant': '#c0c0c0',
-    'decrease': '#d95f02',
-    'increase': '#1b9e77',
+    'decrease': '#a6cee3',
+    'increase': '#b2df8a',
     'increased risk, can adapt': '#1f78b4',
     'increased risk, cant adapt': '#a6cee3',
     'decreased risk, can adapt': '#33a02c',
     'decreased risk, cant adapt': '#b2df8a',
-    'increase risk, increase variability': '#1f78b4',
-    'increase risk, decrease variability': '#a6cee3',
-    'decrease risk, increase variability': '#33a02c',
-    'decrease risk, decrease variability': '#b2df8a'
+    'increase risk, increase yield': '#a6cee3',
+    'increase risk, decrease yield': '#1f78b4',
+    'decrease risk, increase yield': '#b2df8a',
+    'decrease risk, decrease yield': '#33a02c'
 }
 
 MONTH_NUMS = {
@@ -113,7 +113,7 @@
 MAP_SCALE_POSITIVE = ['#e6f5d0a0', '#b8e186a0', '#7fbc41a0', '#4d9221a0']
 
 SELECTION_INSTRUCTION = ' '.join([
-    'Click select to find fields (dots below) that would be good for a pilot.',
+    'Click select to find neighborhoods (dots below) that would be good for a pilot.',
     'Toggle yield, risk and adaptation or map vs scatter.',
     'Do different views change your answer?'
 ])

paper/viz/data_struct.py

@@ -49,6 +49,11 @@ def combine(self, other):
         self_count = self.get_count()
         other_count = other.get_count()
 
+        if self_count == 0:
+            return other
+        elif other_count == 0:
+            return self
+
         self_weighted_p = self.get_p_value() * self_count
         other_weighted_p = other.get_p_value() * other_count
         weighted_p = (self_weighted_p + other_weighted_p) / (self_count + other_count)
@@ -99,6 +104,11 @@ def get_count(self):
     def combine(self, other):
         self_count = self.get_count()
         other_count = other.get_count()
+
+        if self_count == 0:
+            return other
+        elif other_count == 0:
+            return self
 
         self_weighted_mean = self.get_mean() * self_count
         other_weighted_mean = other.get_mean() * other_count
@@ -107,7 +117,11 @@ def combine(self, other):
         self_var_piece = (self_count - 1) * self.get_std()**2
         other_var_piece = (other_count - 1) * other.get_std()**2
         pooled_count = self_count + other_count - 2
-        new_std = math.sqrt((self_var_piece + other_var_piece) / pooled_count)
+
+        if pooled_count == 0:
+            new_std = (self.get_std() + other.get_std()) / 2
+        else:
+            new_std = math.sqrt((self_var_piece + other_var_piece) / pooled_count)
 
         new_count = self_count + other_count
         return YieldDistribution(new_mean, new_std, new_count)
@@ -132,6 +146,12 @@ def get_p_value(self):
     def combine(self, other):
         self_count = self.get_predicted().get_count()
         other_count = other.get_predicted().get_count()
+
+        if self_count == 0:
+            return other
+        elif other_count == 0:
+            return self
+
         self_weighted_p = self.get_p_value() * self_count
         other_weighted_p = other.get_p_value() * other_count
         weighted_p = (self_weighted_p + other_weighted_p) / (self_count + other_count)

paper/viz/hist_viz.py

@@ -537,7 +537,7 @@ def _draw_title(self):
         self._sketch.draw_text(
             SUB_CHART_WIDTH / 2 + 40,
             30,
-            'Histogram of Simulated Change in Risk Unit-Level Yields'
+            'Histogram of Change in Risk Unit-Level Yields Relative to Expected (Avg Yield)'
         )
 
         self._sketch.pop_style()

paper/viz/preprocess.py

@@ -182,14 +182,12 @@ def make_point_risk(record):
         risk_change = record.get_predicted_risk().get_risk_change()
         risk_p = record.get_predicted_risk().get_p_value()
 
-        std_before = record.get_yield_comparison().get_prior().get_std_percent()
-        std_after = record.get_yield_comparison().get_predicted().get_std_percent()
-        std_change = std_after - std_before
+        yield_change = record.get_yield_comparison().get_predicted().get_mean()
 
-        if std_change > 0:
-            var_str = 'increase variability'
+        if yield_change > 0:
+            var_str = 'increase yield'
         else:
-            var_str = 'decrease variability'
+            var_str = 'decrease yield'
 
         if risk_p > p_threshold:
             category = 'not significant'
@@ -199,7 +197,7 @@ def make_point_risk(record):
             category = 'decrease risk, ' + var_str
 
         var_x = get_var_x(record)
-        effective_x = std_change * 100 if var_x is None else var_x
+        effective_x = yield_change if var_x is None else var_x
 
         return ScatterPoint(
             record.get_geohash(),

paper/viz/results_viz.py

@@ -47,15 +47,15 @@ def __init__(self, target, loading_id, default_configuration=None, data_loc=None
             self._config = default_configuration
         else:
             self._config = buttons.Configuration(
-                '2030 conditions',
+                '2050 conditions',
                 '1 year',
                 'yield',
                 'scatter',
                 'p < 0.05',
                 'Bonferroni',
                 'significant only',
                 'no var',
-                'jun',
+                'jul',
                 '75% cov'
             )