From 3aa5baa15507f030e61236e1f4d396ac4249464f Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Fri, 12 Feb 2021 13:21:39 -0800
Subject: [PATCH 01/12] make Sankey test optional (#1538)

---
 docs/source/examples/performance_modeling.py | 14 ++++++++------
 gpkit/solution_array.py                      |  2 +-
 2 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/docs/source/examples/performance_modeling.py b/docs/source/examples/performance_modeling.py
index 48ffda6c9..7fcb0b3cb 100644
--- a/docs/source/examples/performance_modeling.py
+++ b/docs/source/examples/performance_modeling.py
@@ -242,9 +242,11 @@ def setup(self):
 sol = M.solve(verbosity=0)
 print(sol.diff("solution.pkl", showvars=vars_of_interest, sortbymodel=False))
 
-# this will only make an image when run in jupyter notebook
-# from gpkit.interactive.sankey import Sankey
-from gpkit.interactive.sankey import Sankey
-variablesankey = Sankey(sol, M).diagram(AC.wing.A)
-sankey = Sankey(sol, M).diagram(width=1200, height=400, maxlinks=30)
-sankey  # pylint: disable=pointless-statement
+try:
+    from gpkit.interactive.sankey import Sankey
+    variablesankey = Sankey(sol, M).diagram(AC.wing.A)
+    sankey = Sankey(sol, M).diagram(width=1200, height=400, maxlinks=30)
+    # the line below shows an interactive graph if run in jupyter notebook
+    sankey  # pylint: disable=pointless-statement
+except (ImportError, ModuleNotFoundError):
+    print("Making Sankey diagrams requires the ipysankeywidget package")
diff --git a/gpkit/solution_array.py b/gpkit/solution_array.py
index 8b5925945..20f97a645 100644
--- a/gpkit/solution_array.py
+++ b/gpkit/solution_array.py
@@ -377,7 +377,7 @@ def almost_equal(self, other, reltol=1e-3, sens_abstol=0.01):
     def diff(self, other, showvars=None, *,
              constraintsdiff=True, senssdiff=False, sensstol=0.1,
              absdiff=False, abstol=0, reldiff=True, reltol=1.0,
-             sortmodelsbysenss= True, **tableargs):
+             sortmodelsbysenss=True, **tableargs):
         """Outputs differences between this solution and another
 
         Arguments

From 6f4f481b3daa532f05e03166618331054d2ce3ad Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Fri, 26 Feb 2021 14:08:17 -0800
Subject: [PATCH 02/12] Variable References Plots (#1539)

---
 docs/source/examples/performance_modeling.py |   3 +
 docs/source/visint.rst                       |  47 ++++++-
 fulltests.sh                                 |   3 +-
 gpkit/interactive/references.py              |  86 ++++++++++++
 gpkit/interactive/referencesplot.html        | 139 +++++++++++++++++++
 runtests.sh                                  |   1 +
 6 files changed, 274 insertions(+), 5 deletions(-)
 create mode 100644 gpkit/interactive/references.py
 create mode 100644 gpkit/interactive/referencesplot.html

diff --git a/docs/source/examples/performance_modeling.py b/docs/source/examples/performance_modeling.py
index 7fcb0b3cb..a0a50f57a 100644
--- a/docs/source/examples/performance_modeling.py
+++ b/docs/source/examples/performance_modeling.py
@@ -250,3 +250,6 @@ def setup(self):
     sankey  # pylint: disable=pointless-statement
 except (ImportError, ModuleNotFoundError):
     print("Making Sankey diagrams requires the ipysankeywidget package")
+    
+from gpkit.interactive.references import referencesplot
+referencesplot(M, openimmediately=False)
diff --git a/docs/source/visint.rst b/docs/source/visint.rst
index 65fc32a49..cd5bcc354 100644
--- a/docs/source/visint.rst
+++ b/docs/source/visint.rst
@@ -1,5 +1,44 @@
 Visualization and Interaction
 *****************************
+
+Variable Reference Plots
+========================
+
+Code in this section uses the `CE solar model <https://github.com/convexengineering/solar/tree/gpkitdocs>`_
+
+.. code:: python
+    from solar.solar import *
+    Vehicle = Aircraft(Npod=3, sp=True)
+    M = Mission(Vehicle, latitude=[20])
+    M.cost = M[M.aircraft.Wtotal]
+    sol = M.localsolve()
+
+    from gpkit.interactive.references import referencesplot
+    referencesplot(M, openimmediately=True)
+
+Running the code above will produce two files in your working directory:
+``referencesplot.html`` and ``referencesplot.json``, and (unless you specify
+``openimmediately=False``) open the former in your web browser,
+showing you something like this:
+
+.. figure:: figures/referencesplot.png
+
+`Click to see the interactive version of this plot. <https://web.mit.edu/eburn/www/referencesplot/referencesplot.html>`_
+
+When a model's name is hovered over its connections are highlighted, showing in
+red the other models it imports variables from to use in its constraints and in
+blue the models that import variables from it.
+
+By default connections are shown with equal width ("Unweighted").
+When "Global Sensitivities" is selected, connection width is proportional to
+the sensitivity of all variables in that connection to the importing model,
+corresponding exactly to how much the model's cost would decrease if those variables were relaxed
+in only that importing model. This can give a sense of which connections are vital to
+the overall model. When "Normalized Sensitivities"  is selected, that
+global weight is divided by the weight of all variables in the importing model,
+giving a sense of which connections are vital to each subsystem.
+
+
 .. _sankey:
 Sensitivity Diagrams
 ====================
@@ -9,9 +48,9 @@ Requirements
 -  Jupyter Notebook
 -  `ipysankeywidget <https://github.com/ricklupton/ipysankeywidget>`__
     - Note that you'll need to activate these widgets on Jupyter by runnning
-    
+
       - ``jupyter nbextension enable --py --sys-prefix widgetsnbextension``
-      
+
       - ``jupyter nbextension enable --py --sys-prefix ipysankeywidget``
 
 Example
@@ -25,10 +64,10 @@ Code in this section uses the `CE solar model <https://github.com/convexengineer
     Vehicle = Aircraft(Npod=3, sp=True)
     M = Mission(Vehicle, latitude=[20])
     M.cost = M[M.aircraft.Wtotal]
-    sol = M.localsolve("mosek_cli")
+    sol = M.localsolve()
 
     from gpkit.interactive.sankey import Sankey
-    
+
 Once the code above has been run in a Jupyter notebook, the code below will create interactive hierarchies of your model's sensitivities, like so:
 
 .. figure:: figures/Mission.gif
diff --git a/fulltests.sh b/fulltests.sh
index a4d4570aa..2cfa1dc25 100755
--- a/fulltests.sh
+++ b/fulltests.sh
@@ -1,3 +1,4 @@
-python -c "from gpkit.tests import run; run()" 
+python -c "from gpkit.tests import run; run()"
 rm *.pkl
 rm solution.*
+rm referencesplot.*
diff --git a/gpkit/interactive/references.py b/gpkit/interactive/references.py
new file mode 100644
index 000000000..efc685ca6
--- /dev/null
+++ b/gpkit/interactive/references.py
@@ -0,0 +1,86 @@
+"Code to make variable references plots"
+
+import os
+import shutil
+import webbrowser
+from collections import defaultdict
+
+
+# pylint:disable=too-many-locals
+def referencesplot(model, *, openimmediately=True):
+    """Makes a references plot.
+
+    1) Creates the JSON file for a d3 references plot
+    2) Places it and the corresponding HTML file in the working directory
+    3) (optionally) opens that HTML file up immediately in a web browser
+
+    """
+    imports = {}
+    totalv_ss = defaultdict(dict)
+    for constraint in model.flat():
+        for varkey in constraint.vks:
+            vlineage = varkey.lineagestr()
+            clineage = constraint.lineagestr()
+            if not vlineage:
+                vlineage = "%s [%s]" % (varkey, varkey.unitstr())
+            for lin in (clineage, vlineage):
+                if lin not in imports:
+                    imports[lin] = set()
+            if vlineage != clineage:
+                imports[clineage].add(vlineage)
+                if constraint.v_ss:
+                    totalv_ss[clineage] += constraint.v_ss
+
+    def clean_lineage(lineage, clusterdepth=2):
+        prelineage = ".".join(lineage.split(".")[:clusterdepth])
+        last = "0".join(lineage.split(".")[clusterdepth:])
+        return "model."+prelineage + "." + last
+
+    lines = ['jsondata = [']
+    for lineage, limports in imports.items():
+        name, short = clean_lineage(lineage), lineage.split(".")[-1]
+        limports = map(clean_lineage, limports)
+        lines.append(
+            '  {"name":"%s","fullname":"%s","shortname":"%s","imports":%s},'
+            % (name, lineage, short, repr(list(limports)).replace("'", '"')))
+    lines[-1] = lines[-1][:-1]
+    lines.append("]")
+
+    if totalv_ss:
+        def get_total_senss(clineage, vlineage, normalize=False):
+            v_ss = totalv_ss[clineage]
+            num = sum(abs(ss) for vk, ss in v_ss.items()
+                      if vk.lineagestr() == vlineage)
+            if not normalize:
+                return num
+            return num/sum(abs(ss) for ss in v_ss.values())
+        lines.append("globalsenss = {")
+        for clineage, limports in imports.items():
+            if not limports:
+                continue
+            limports = {vl: get_total_senss(clineage, vl) for vl in limports}
+            lines.append('  "%s": %s,' %
+                         (clineage, repr(limports).replace("'", '"')))
+        lines[-1] = lines[-1][:-1]
+        lines.append("}")
+        lines.append("normalizedsenss = {")
+        for clineage, limports in imports.items():
+            if not limports:
+                continue
+            limports = {vl: get_total_senss(clineage, vl, normalize=True)
+                        for vl in limports}
+            lines.append('  "%s": %s,' %
+                         (clineage, repr(limports).replace("'", '"')))
+        lines[-1] = lines[-1][:-1]
+        lines.append("}")
+
+    with open("referencesplot.json", "w") as f:
+        f.write("\n".join(lines))
+
+    htmlfile = "referencesplot.html"
+    if not os.path.isfile(htmlfile):
+        shutil.copy(os.path.join(os.path.dirname(__file__), htmlfile), htmlfile)
+
+    if openimmediately:
+        webbrowser.open("file://" + os.path.join(os.getcwd(), htmlfile),
+                        autoraise=True)
diff --git a/gpkit/interactive/referencesplot.html b/gpkit/interactive/referencesplot.html
new file mode 100644
index 000000000..01ac852ba
--- /dev/null
+++ b/gpkit/interactive/referencesplot.html
@@ -0,0 +1,139 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>GPkit Variable Reference Map</title>
+<script src="https://d3js.org/d3.v6.min.js"></script>
+<script type="text/javascript" src="referencesplot.json"></script>
+<body style="font-family: Myriad Pro, sans-serif; color: #333;">
+  <div id="chart" style="width: 1000px; margin: 0 auto;">
+    <div id="controls" style="width: 500px; margin: 0 auto;">
+      <input type="radio" id="unweighted" name="linkwidth" checked class="control"
+          onchange="chooseStrokeWidth('unweighted')">
+        <label for="unweighted">Unweighted</label>
+      <input type="radio" id="global" name="linkwidth" class="control"
+          onchange="chooseStrokeWidth('global')">
+        <label for="global">Global Sensitivities</label>
+      <input type="radio" id="normalized" name="linkwidth" class="control"
+          onchange="chooseStrokeWidth('normalized')">
+        <label for="normalized">Normalized Sensitivities</label>
+    </div>
+  </div>
+</body>
+<script>
+colorin = "#59ade4"
+colorout = "#FA3333"
+colornone = "#eee"
+width = 954
+radius = width / 2
+
+function hierarchy(data, delimiter = ".") {
+  let root;
+  const map = new Map;
+  data.forEach(function find(data) {
+    const {name} = data;
+    if (map.has(name)) return map.get(name);
+    const i = name.lastIndexOf(delimiter);
+    map.set(name, data);
+    if (i >= 0) {
+      find({name: name.substring(0, i), children: []}).children.push(data);
+      data.name = name.substring(i + 1);
+    } else {
+      root = data;
+    }
+    return data;
+  });
+  return root;
+}
+
+function id(node) {
+  return `${node.parent ? id(node.parent) + "." : ""}${node.data.name}`;
+}
+
+function bilink(root) {
+  const map = new Map(root.leaves().map(d => [id(d), d]));
+  for (const d of root.leaves()) d.incoming = [], d.outgoing = d.data.imports.map(i => [d, map.get(i)]);
+  for (const d of root.leaves()) for (const o of d.outgoing) o[1].incoming.push(o);
+  return root;
+}
+
+line = d3.lineRadial()
+    .curve(d3.curveBundle.beta(0.85))
+    .radius(function(d) {if (d.data.fullname) return d.y + 15*((d.data.fullname.match(/\./g) || []).length - 1); return d.y})
+    .angle(d => d.x)
+
+tree = d3.cluster()
+    .size([2 * Math.PI, radius - 250])
+
+data = hierarchy(jsondata)
+
+root = tree(bilink(d3.hierarchy(data)
+    .sort((a, b) => d3.ascending(a.height, b.height) || d3.ascending(a.data.name, b.data.name))));
+
+svg = d3.select("#chart")
+            .append("svg").lower()
+    .attr("viewBox", [-width / 2, -width / 2, width, width]);
+
+function chooseStrokeWidth(type) {
+    switch(type) {
+      case "global":
+        d3.selectAll("path").attr("stroke-width",
+            ([i, o]) => 0.5*globalsenss[i.data.fullname][o.data.fullname]);
+        break;
+      case "normalized":
+        d3.selectAll("path").attr("stroke-width",
+            ([i, o]) => 36*normalizedsenss[i.data.fullname][o.data.fullname]);
+        break;
+      default:
+        d3.selectAll("path").attr("stroke-width", 12);
+    }
+}
+
+link = svg.append("g")
+    .attr("stroke", colornone)
+    .attr("fill", "none")
+  .selectAll("path")
+  .data(root.leaves().flatMap(leaf => leaf.outgoing))
+  .join("path")
+    .style("mix-blend-mode", "multiply")
+    .attr("d", ([i, o]) => line(i.path(o)))
+    .each(function(d) { d.path = this; });
+
+chooseStrokeWidth()
+
+node = svg.append("g")
+    .attr("fill", "#333")
+  .selectAll("g")
+  .data(root.leaves())
+  .join("g")
+    .attr("transform", d => `rotate(${d.x * 180 / Math.PI - 90}) translate(${d.y  - 1 + 15*((d.data.fullname.match(/\./g) || []).length - 1)},0)`)
+  .append("text")
+    .attr("font-size", d => 8*(1 + Math.pow(4, 1-(d.data.fullname.match(/\./g) || []).length)))
+    .attr("dy", "0.31em")
+    .attr("x", d => d.x < Math.PI ? 6 : -6)
+    .attr("text-anchor", d => d.x < Math.PI ? "start" : "end")
+    .attr("transform", d => d.x >= Math.PI ? "rotate(180)" : null)
+    .text(d => d.data.shortname)
+    .each(function(d) { d.text = this; })
+    .on("mouseover", overed)
+    .on("mouseout", outed)
+    .call(text => text.append("title").text(d => `${d.data.fullname}
+(red: the ${d.outgoing.length} models this imports variables from)
+(blue: the ${d.incoming.length} models that import these variables)`));
+
+function overed(event, d) {
+  link.style("mix-blend-mode", null);
+  d3.select(this).attr("font-weight", "bold");
+  d3.selectAll(d.incoming.map(d => d.path)).attr("stroke", colorin).raise();
+  d3.selectAll(d.incoming.map(([d]) => d.text)).attr("fill", colorin).attr("font-weight", "bold");
+  d3.selectAll(d.outgoing.map(d => d.path)).attr("stroke", colorout).raise();
+  d3.selectAll(d.outgoing.map(([, d]) => d.text)).attr("fill", colorout).attr("font-weight", "bold");
+}
+
+function outed(event, d) {
+  link.style("mix-blend-mode", "multiply");
+  d3.select(this).attr("font-weight", null);
+  d3.selectAll(d.incoming.map(d => d.path)).attr("stroke", null);
+  d3.selectAll(d.incoming.map(([d]) => d.text)).attr("fill", null).attr("font-weight", null);
+  d3.selectAll(d.outgoing.map(d => d.path)).attr("stroke", null);
+  d3.selectAll(d.outgoing.map(([, d]) => d.text)).attr("fill", null).attr("font-weight", null);
+}
+</script>
diff --git a/runtests.sh b/runtests.sh
index 0467a0f38..7e988fc17 100755
--- a/runtests.sh
+++ b/runtests.sh
@@ -5,3 +5,4 @@ python -c "import gpkit.tests; gpkit.tests.run()"  && mv settings gpkit/env
 rm *.pkl
 rm *.pgz
 rm solution.*
+rm referencesplot.*

From c21885a4515dbc7519d01b41e6254ed4922726e3 Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Fri, 26 Feb 2021 14:08:25 -0800
Subject: [PATCH 03/12] avoid DeprecationWarning (#1537)

---
 gpkit/keydict.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/gpkit/keydict.py b/gpkit/keydict.py
index bc86f5d9c..c6f393ed4 100644
--- a/gpkit/keydict.py
+++ b/gpkit/keydict.py
@@ -242,7 +242,13 @@ def __setitem__(self, key, value):
                 if not hasattr(value, "__len__"):
                     value = np.full(key.shape, value, "f")
                 elif not isinstance(value[0], np.ndarray):
-                    value = np.array([clean_value(key, v) for v in value])
+                    clean_values = [clean_value(key, v) for v in value]
+                    dtype = None
+                    if any(is_sweepvar(cv) for cv in clean_values):
+                        dtype = "object"
+                    value = np.array(clean_values, dtype=dtype)
+                    # else:
+                    #     value = np.array(clean_values)  # can't use dtype=None
         super().__setitem__(key, value)
         self.owned.add(key)
 

From 85b5ce70d94ab32c7ebe2856a07c1302798fb0fb Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 26 Feb 2021 14:10:17 -0800
Subject: [PATCH 04/12] add referenceplot.png

---
 docs/source/figures/referencesplot.png | Bin 0 -> 152495 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 docs/source/figures/referencesplot.png

diff --git a/docs/source/figures/referencesplot.png b/docs/source/figures/referencesplot.png
new file mode 100644
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DEfrll

literal 0
HcmV?d00001


From 65827ccc6523c3036424dfdf78174f74910f2d1f Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 26 Feb 2021 14:12:44 -0800
Subject: [PATCH 05/12] docs typo fixes

---
 docs/source/visint.rst | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/source/visint.rst b/docs/source/visint.rst
index cd5bcc354..234bf88dc 100644
--- a/docs/source/visint.rst
+++ b/docs/source/visint.rst
@@ -4,9 +4,10 @@ Visualization and Interaction
 Variable Reference Plots
 ========================
 
-Code in this section uses the `CE solar model <https://github.com/convexengineering/solar/tree/gpkitdocs>`_
+Code in this section uses the `CE solar model <https://github.com/convexengineering/solar/tree/gpkitdocs>`_.
 
 .. code:: python
+
     from solar.solar import *
     Vehicle = Aircraft(Npod=3, sp=True)
     M = Mission(Vehicle, latitude=[20])

From e768533800175c0e07a9494813a84480324c96e0 Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Wed, 10 Mar 2021 17:11:48 -0800
Subject: [PATCH 06/12] sweep-related fixes (#1540)

* don't add forward-differentiated sensitivities to constants no longer present
* fix warnings table for intermittent warnings in sweeps
* cleanup model sensitivity printing
* remove gradients from constants before calculating linked variables
---
 docs/source/examples/relaxation_output.txt |  2 +-
 gpkit/constraints/bounded.py               |  3 ++-
 gpkit/constraints/gp.py                    | 11 +++++-----
 gpkit/constraints/loose.py                 |  3 ++-
 gpkit/constraints/prog_factories.py        | 16 +++++++++++----
 gpkit/constraints/relax.py                 |  5 ++++-
 gpkit/constraints/tight.py                 |  3 ++-
 gpkit/small_scripts.py                     |  8 ++++++--
 gpkit/solution_array.py                    | 24 +++++++++++++++-------
 9 files changed, 52 insertions(+), 23 deletions(-)

diff --git a/docs/source/examples/relaxation_output.txt b/docs/source/examples/relaxation_output.txt
index 179e4cb74..24f295d22 100644
--- a/docs/source/examples/relaxation_output.txt
+++ b/docs/source/examples/relaxation_output.txt
@@ -150,7 +150,7 @@ Relaxed Constants
 Model Sensitivities (sorts models in sections below)
 -------------------
   +2.0 : Relax2.OriginalValues
- <1E-8 : Relax2
+ <1e-8 : Relax2
 
 Free Variables
 --------------
diff --git a/gpkit/constraints/bounded.py b/gpkit/constraints/bounded.py
index 8f87eda88..f9b66ead4 100644
--- a/gpkit/constraints/bounded.py
+++ b/gpkit/constraints/bounded.py
@@ -3,7 +3,7 @@
 import numpy as np
 from .. import Variable
 from .set import ConstraintSet
-from ..small_scripts import appendsolwarning
+from ..small_scripts import appendsolwarning, initsolwarning
 
 
 def varkey_bounds(varkeys, lower, upper):
@@ -77,6 +77,7 @@ def process_result(self, result):
     def check_boundaries(self, result):
         "Creates (and potentially prints) a dictionary of unbounded variables."
         out = defaultdict(set)
+        initsolwarning(result, "Arbitrarily Bounded Variables")
         for i, varkey in enumerate(self.bound_varkeys):
             value = result["variables"][varkey]
             c_senss = [result["sensitivities"]["constraints"].get(c, 0)
diff --git a/gpkit/constraints/gp.py b/gpkit/constraints/gp.py
index 06ed88b71..89a8fe294 100644
--- a/gpkit/constraints/gp.py
+++ b/gpkit/constraints/gp.py
@@ -222,15 +222,17 @@ def solve(self, solver=None, *, verbosity=1, gen_result=True, **kwargs):
                 msg = ("The model ran to an infinitely low cost;"
                        " bounding the right variables would prevent this.")
             elif isinstance(infeasibility, UnknownInfeasible):
-                msg = "The solver failed for an unknown reason."
+                msg = ("Solver failed for an unknown reason. Relaxing"
+                       " constraints/constants, bounding variables, or"
+                       " using a different solver might fix it.")
             if (verbosity > 0 and solver_out["soltime"] < 1
                     and hasattr(self, "model")):  # fast, top-level model
                 print(msg + "\nSince the model solved in less than a second,"
                       " let's run `.debug()` to analyze what happened.\n`")
                 return self.model.debug(solver=solver)
             # else, raise a clarifying error
-            msg += (" Running `.debug()` may pinpoint the trouble. You can"
-                    " also try another solver, or increase the verbosity.")
+            msg += (" Running `.debug()` or increasing verbosity may pinpoint"
+                    " the trouble.")
             raise infeasibility.__class__(msg) from infeasibility
 
         if not gen_result:
@@ -330,8 +332,7 @@ def _compile_result(self, solver_out):
                 with warnings.catch_warnings():  # skip pesky divide-by-zeros
                     warnings.simplefilter("ignore")
                     dlogv_dlogc = dv_dc * result["constants"][c]/val
-                    before = gpv_ss.get(c, 0)
-                    gpv_ss[c] = before + dlogcost_dlogv*dlogv_dlogc
+                    gpv_ss[c] = gpv_ss.get(c, 0) + dlogcost_dlogv*dlogv_dlogc
                 if v in cost_senss:
                     if c in self.cost.vks:
                         dlogcost_dlogv = cost_senss.pop(v)
diff --git a/gpkit/constraints/loose.py b/gpkit/constraints/loose.py
index 84d410d32..2baadc34a 100644
--- a/gpkit/constraints/loose.py
+++ b/gpkit/constraints/loose.py
@@ -1,6 +1,6 @@
 "Implements Loose"
 from .set import ConstraintSet
-from ..small_scripts import appendsolwarning
+from ..small_scripts import appendsolwarning, initsolwarning
 
 
 class Loose(ConstraintSet):
@@ -15,6 +15,7 @@ def __init__(self, constraints, *, senstol=None):
     def process_result(self, result):
         "Checks that all constraints are satisfied with equality"
         super().process_result(result)
+        initsolwarning(result, "Unexpectedly Tight Constraints")
         for constraint in self.flat():
             c_senss = result["sensitivities"]["constraints"].get(constraint, 0)
             if c_senss >= self.senstol:
diff --git a/gpkit/constraints/prog_factories.py b/gpkit/constraints/prog_factories.py
index 3468b0cb7..b846b4455 100644
--- a/gpkit/constraints/prog_factories.py
+++ b/gpkit/constraints/prog_factories.py
@@ -15,6 +15,9 @@ def evaluate_linked(constants, linked):
                    for k, v in constants.items()})
     kdc_plain = None
     array_calulated = {}
+    for key in constants:  # remove gradients from constants
+        if key.gradients:
+            del key.descr["gradients"]
     for v, f in linked.items():
         try:
             if v.veckey and v.veckey.original_fn:
@@ -130,7 +133,7 @@ def run_sweep(genfunction, self, solution, skipsweepfailures,
                    for (var, grid) in zip(sweepvars, sweep_grids)}
 
     if verbosity > 0:
-        print("Sweeping over %i solves." % N_passes)
+        print("Sweeping with %i solves:" % N_passes)
         tic = time()
 
     self.program = []
@@ -143,6 +146,8 @@ def run_sweep(genfunction, self, solution, skipsweepfailures,
         program, solvefn = genfunction(self, constants)
         self.program.append(program)  # NOTE: SIDE EFFECTS
         try:
+            if verbosity > 1:
+                print("\nSolve %i:" % i)
             result = solvefn(solver, verbosity=verbosity-1, **solveargs)
             if solveargs.get("process_result", True):
                 self.process_result(result)
@@ -151,10 +156,13 @@ def run_sweep(genfunction, self, solution, skipsweepfailures,
             last_error = e
             if not skipsweepfailures:
                 raise RuntimeWarning(
-                    "Sweep halted! Progress saved to m.program. To skip over"
-                    " such failures, solve with skipsweepfailures=True.") from e
+                    "Solve %i was infeasible; progress saved to m.program."
+                    " To continue sweeping after failures, solve with"
+                    " skipsweepfailures=True." % i) from e
+            if verbosity > 0:
+                print("Solve %i was %s." % (i, e.__class__.__name__))
     if not solution:
-        raise RuntimeWarning("No sweeps solved successfully.") from last_error
+        raise RuntimeWarning("All solves were infeasible.") from last_error
 
     solution["sweepvariables"] = KeyDict()
     ksweep = KeyDict(sweep)
diff --git a/gpkit/constraints/relax.py b/gpkit/constraints/relax.py
index 50147238f..0498eff93 100644
--- a/gpkit/constraints/relax.py
+++ b/gpkit/constraints/relax.py
@@ -3,7 +3,7 @@
 from ..nomials import Variable, VectorVariable, parse_subs, NomialArray
 from ..keydict import KeyDict
 from .. import NamedVariables, SignomialsEnabled
-from ..small_scripts import appendsolwarning, mag
+from ..small_scripts import appendsolwarning, initsolwarning, mag
 
 
 class ConstraintsRelaxedEqually(ConstraintSet):
@@ -50,6 +50,7 @@ def process_result(self, result):
 
     def check_relaxed(self, result):
         "Adds relaxation warnings to the result"
+        initsolwarning(result, "Relaxed Constraints")
         for val, msg in get_relaxed([result["freevariables"][self.relaxvar]],
                                     ["All constraints relaxed by %i%%"]):
             appendsolwarning(msg % (0.9+(val-1)*100), self, result,
@@ -103,6 +104,7 @@ def check_relaxed(self, result):
         "Adds relaxation warnings to the result"
         relaxed = get_relaxed(result["freevariables"][self.relaxvars],
                               range(len(self["relaxed constraints"])))
+        initsolwarning(result, "Relaxed Constraints")
         for relaxval, i in relaxed:
             relax_percent = "%i%%" % (0.5+(relaxval-1)*100)
             oldconstraint = self.original_constraints[i]
@@ -224,6 +226,7 @@ def check_relaxed(self, result):
         "Adds relaxation warnings to the result"
         relaxed = get_relaxed([result["freevariables"][r]
                                for r in self.relaxvars], self.freedvars)
+        initsolwarning(result, "Relaxed Constants")
         for (_, freed) in relaxed:
             msg = ("  %s: relaxed from %-.4g to %-.4g"
                    % (freed,
diff --git a/gpkit/constraints/tight.py b/gpkit/constraints/tight.py
index 063c4e7b2..9aa0d02a5 100644
--- a/gpkit/constraints/tight.py
+++ b/gpkit/constraints/tight.py
@@ -1,7 +1,7 @@
 "Implements Tight"
 from .set import ConstraintSet
 from ..small_scripts import mag
-from ..small_scripts import appendsolwarning
+from ..small_scripts import appendsolwarning, initsolwarning
 from .. import SignomialsEnabled
 
 
@@ -18,6 +18,7 @@ def process_result(self, result):
         "Checks that all constraints are satisfied with equality"
         super().process_result(result)
         variables = result["variables"]
+        initsolwarning(result, "Unexpectedly Loose Constraints")
         for constraint in self.flat():
             with SignomialsEnabled():
                 leftval = constraint.left.sub(variables).value
diff --git a/gpkit/small_scripts.py b/gpkit/small_scripts.py
index 3d282d2fa..1ce4406ee 100644
--- a/gpkit/small_scripts.py
+++ b/gpkit/small_scripts.py
@@ -3,12 +3,16 @@
 import numpy as np
 
 
-def appendsolwarning(msg, data, result, category="uncategorized"):
-    "Append a particular category of warnings to a solution."
+def initsolwarning(result, category="uncategorized"):
+    "Creates a results dictionary for a particular category of warning."
     if "warnings" not in result:
         result["warnings"] = {}
     if category not in result["warnings"]:
         result["warnings"][category] = []
+
+
+def appendsolwarning(msg, data, result, category="uncategorized"):
+    "Append a particular category of warnings to a solution."
     result["warnings"][category].append((msg, data))
 
 
diff --git a/gpkit/solution_array.py b/gpkit/solution_array.py
index 20f97a645..7af996894 100644
--- a/gpkit/solution_array.py
+++ b/gpkit/solution_array.py
@@ -67,24 +67,30 @@ def msenss_table(data, _, **kwargs):
     lines = ["Model Sensitivities", "-------------------"]
     if kwargs["sortmodelsbysenss"]:
         lines[0] += " (sorts models in sections below)"
+    previousmsenssstr = ""
     for model, msenss in data:
         if not model:  # for now let's only do named models
             continue
         if (msenss < 0.1).all():
             msenss = np.max(msenss)
             if msenss:
-                msenssstr = "%6s" % ("<1E%i" % np.log10(msenss))
+                msenssstr = "%6s" % ("<1e%i" % np.log10(msenss))
             else:
                 msenssstr = "  =0  "
         elif not msenss.shape:
             msenssstr = "%+6.1f" % msenss
         else:
             meansenss = np.mean(msenss)
+            msenssstr = "%+6.1f" % meansenss
             deltas = msenss - meansenss
-            deltastrs = ["%+4.1f" % d if abs(d) >= 0.1 else "  - "
-                         for d in deltas]
-            msenssstr = "%+6.1f + [ %s ]" % (meansenss, "  ".join(deltastrs))
-
+            if np.max(np.abs(deltas)) > 0.1:
+                deltastrs = ["%+4.1f" % d if abs(d) >= 0.1 else "  - "
+                             for d in deltas]
+                msenssstr += " + [ %s ]" % "  ".join(deltastrs)
+        if msenssstr == previousmsenssstr:
+            msenssstr = "      "
+        else:
+            previousmsenssstr = msenssstr
         lines.append("%s : %s" % (msenssstr, model))
     return lines + [""] if len(lines) > 3 else []
 
@@ -234,9 +240,13 @@ def warnings_table(self, _, **kwargs):
         return []
     for wtype in sorted(self["warnings"]):
         data_vec = self["warnings"][wtype]
+        if len(data_vec) == 0:
+            continue
         if not hasattr(data_vec, "shape"):
             data_vec = [data_vec]
         for i, data in enumerate(data_vec):
+            if len(data) == 0:
+                continue
             data = sorted(data, key=lambda l: l[0])  # sort by msg
             title = wtype
             if len(data_vec) > 1:
@@ -650,8 +660,8 @@ def summary(self, showvars=(), ntopsenss=5, **kwargs):
         return out
 
     def table(self, showvars=(),
-              tables=("cost", "warnings", "sweepvariables",
-                      "model sensitivities", "freevariables",
+              tables=("cost", "warnings", "model sensitivities",
+                      "sweepvariables", "freevariables",
                       "constants", "sensitivities", "tightest constraints"),
               sortmodelsbysenss=True, **kwargs):
         """A table representation of this SolutionArray

From 027bac062a9503659c8bd7196912bba048044f51 Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 19 Mar 2021 12:32:24 -0700
Subject: [PATCH 07/12] clean first x0, add test

---
 docs/source/examples/simple_sp.py | 4 ++++
 gpkit/constraints/sgp.py          | 7 +++++--
 2 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/docs/source/examples/simple_sp.py b/docs/source/examples/simple_sp.py
index 4cf7fea21..e755affd5 100644
--- a/docs/source/examples/simple_sp.py
+++ b/docs/source/examples/simple_sp.py
@@ -17,3 +17,7 @@
 # full interim solutions are available
 print("x values of each GP solve (note convergence)")
 print(", ".join("%.5f" % sol["freevariables"][x] for sol in m.program.results))
+
+# use x0 to give the solution, reducing number of GPs needed
+m.localsolve(verbosity=0, x0={x: 0.9, y:0.1})
+assert len(m.program.results) == 2
diff --git a/gpkit/constraints/sgp.py b/gpkit/constraints/sgp.py
index 321721273..159af174c 100644
--- a/gpkit/constraints/sgp.py
+++ b/gpkit/constraints/sgp.py
@@ -149,7 +149,7 @@ def localsolve(self, solver=None, *, verbosity=1, x0=None, reltol=1e-4,
                     "Unsolved after %s iterations. Check `m.program.results`;"
                     " if they're converging, try `.localsolve(...,"
                     " iteration_limit=NEWLIMIT)`." % len(self.gps))
-            gp = self.gp(x0, cleanx0=True)
+            gp = self.gp(x0, cleanx0=(len(self.gps) >= 1))  # clean the first x0
             self.gps.append(gp)  # NOTE: SIDE EFFECTS
             if verbosity > 1:
                 print("\nGP Solve %i" % len(self.gps))
@@ -217,7 +217,10 @@ def gp(self, x0=None, *, cleanx0=False):
         if not x0:
             return self._gp  # return last generated
         if not cleanx0:
-            x0 = KeyDict(x0)
+            cleanedx0 = KeyDict()
+            cleanedx0.varkeys = self._gp.x0.varkeys
+            cleanedx0.update(x0)
+            x0 = cleanedx0
         self._gp.x0.update({vk: x0[vk] for vk in self.sgpvks if vk in x0})
         p_idx = 0
         for sgpc in self.sgpconstraints:

From d318e38ff6b291bcae3b2ed43f991b5dc8c3ae57 Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 19 Mar 2021 12:33:23 -0700
Subject: [PATCH 08/12] fix docs typo

---
 docs/source/signomialprogramming.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/signomialprogramming.rst b/docs/source/signomialprogramming.rst
index 5b80da324..d50125944 100644
--- a/docs/source/signomialprogramming.rst
+++ b/docs/source/signomialprogramming.rst
@@ -33,7 +33,7 @@ Example Usage
 
 When using the ``localsolve`` method, the ``reltol`` argument specifies the relative tolerance of the solver: that is, by what percent does the solution have to improve between iterations? If any iteration improves less than that amount, the solver stops and returns its value.
 
-If you wish to start the local optimization at a particular point :math:`x_k`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``xk`` argument.
+If you wish to start the local optimization at a particular point :math:`x_k`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``x0`` argument.
 
 .. _sgp:
 

From 746985f7a4ba8cbdfd4553744e2470e7748ee1a2 Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 19 Mar 2021 13:06:28 -0700
Subject: [PATCH 09/12] use vks for susbtitutions keydicting

---
 gpkit/constraints/set.py |  3 +--
 gpkit/constraints/sgp.py | 10 ++++++----
 gpkit/keydict.py         | 10 ++++++----
 3 files changed, 13 insertions(+), 10 deletions(-)

diff --git a/gpkit/constraints/set.py b/gpkit/constraints/set.py
index 830d97b83..dc3dcf8fd 100644
--- a/gpkit/constraints/set.py
+++ b/gpkit/constraints/set.py
@@ -76,7 +76,7 @@ def __init__(self, constraints, substitutions=None, *, bonusvks=None):  # pylint
         self.vks = set(self.unique_varkeys)
         self.substitutions = KeyDict({k: k.value for k in self.unique_varkeys
                                       if "value" in k.descr})
-        self.substitutions.cset = self
+        self.substitutions.vks = self.vks
         self.bounded, self.meq_bounded = set(), defaultdict(set)
         for i, constraint in enumerate(self):
             if hasattr(constraint, "vks"):
@@ -95,7 +95,6 @@ def __init__(self, constraints, substitutions=None, *, bonusvks=None):  # pylint
             self.vks.update(bonusvks)
         if substitutions:
             self.substitutions.update(substitutions)
-            self._varkeys = None
         for key in self.vks:
             if key not in self.substitutions:
                 if key.veckey is None or key.veckey not in self.substitutions:
diff --git a/gpkit/constraints/sgp.py b/gpkit/constraints/sgp.py
index 159af174c..0463af3f5 100644
--- a/gpkit/constraints/sgp.py
+++ b/gpkit/constraints/sgp.py
@@ -66,7 +66,7 @@ def __init__(self, cost, model, substitutions, *,
         self.approxconstraints = []
         self.sgpvks = set()
         x0 = KeyDict(substitutions)
-        x0.varkeys = model.varkeys  # for string access and so forth
+        x0.vks = model.vks  # for string access and so forth
         for cs in model.flat():
             try:
                 if not hasattr(cs, "as_hmapslt1"):
@@ -199,8 +199,10 @@ def localsolve(self, solver=None, *, verbosity=1, x0=None, reltol=1e-4,
                     " %.2g%%. Calling .localsolve with a higher"
                     " `pccp_penalty` (it was %.3g this time) will reduce"
                     " final slack if the model is solvable with less. If"
-                    " you think it might not be, check by solving with "
-                    "`use_pccp=False, x0=(this model's final solution)`.\n"
+                    " you think it might not be, check by generating an SP with"
+                    "`use_pccp=False`, then solving with x0=(this model's final"
+                    " solution); e.g. `m.sp(use_pccp=False).localsolve("
+                    "x0=m.solution[\"variables\"])`.\n"
                     % (100*excess_slack, self.pccp_penalty))
         return self.result
 
@@ -218,7 +220,7 @@ def gp(self, x0=None, *, cleanx0=False):
             return self._gp  # return last generated
         if not cleanx0:
             cleanedx0 = KeyDict()
-            cleanedx0.varkeys = self._gp.x0.varkeys
+            cleanedx0.vks = self._gp.x0.vks
             cleanedx0.update(x0)
             x0 = cleanedx0
         self._gp.x0.update({vk: x0[vk] for vk in self.sgpvks if vk in x0})
diff --git a/gpkit/keydict.py b/gpkit/keydict.py
index c6f393ed4..a64ce9a61 100644
--- a/gpkit/keydict.py
+++ b/gpkit/keydict.py
@@ -45,7 +45,7 @@ class KeyMap:
     collapse_arrays = False
     keymap = []
     log_gets = False
-    cset = None
+    vks = varkeys = None
 
     def __init__(self, *args, **kwargs):
         "Passes through to super().__init__ via the `update()` method"
@@ -62,12 +62,14 @@ def parse_and_index(self, key):
                 return key.veckey, key.idx
             return key, None
         except AttributeError:
-            if self.cset is None:
+            if self.vks is None and self.varkeys is None:
                 return key, self.update_keymap()
         # looks like we're in a substitutions dictionary
-        if key not in self.cset.varkeys:
+        if self.varkeys is None:
+            self.varkeys = KeySet(self.vks)
+        if key not in self.varkeys:
             raise KeyError(key)
-        newkey, *otherkeys = self.cset.varkeys[key]
+        newkey, *otherkeys = self.varkeys[key]
         if otherkeys:
             if all(k.veckey == newkey.veckey for k in otherkeys):
                 return newkey.veckey, None

From 5423bf51a254426804e0d6c61137888e0ba10c99 Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Fri, 19 Mar 2021 13:44:20 -0700
Subject: [PATCH 10/12] Clean user-submitted x0s during localsolve (#1541)

* clean first x0, add test
* fix docs typo (xk instead of x0)
* use vks for susbtitutions keydicting
---
 docs/source/examples/simple_sp.py    |  4 ++++
 docs/source/signomialprogramming.rst |  2 +-
 gpkit/constraints/set.py             |  3 +--
 gpkit/constraints/sgp.py             | 15 ++++++++++-----
 gpkit/keydict.py                     | 10 ++++++----
 5 files changed, 22 insertions(+), 12 deletions(-)

diff --git a/docs/source/examples/simple_sp.py b/docs/source/examples/simple_sp.py
index 4cf7fea21..e755affd5 100644
--- a/docs/source/examples/simple_sp.py
+++ b/docs/source/examples/simple_sp.py
@@ -17,3 +17,7 @@
 # full interim solutions are available
 print("x values of each GP solve (note convergence)")
 print(", ".join("%.5f" % sol["freevariables"][x] for sol in m.program.results))
+
+# use x0 to give the solution, reducing number of GPs needed
+m.localsolve(verbosity=0, x0={x: 0.9, y:0.1})
+assert len(m.program.results) == 2
diff --git a/docs/source/signomialprogramming.rst b/docs/source/signomialprogramming.rst
index 5b80da324..d50125944 100644
--- a/docs/source/signomialprogramming.rst
+++ b/docs/source/signomialprogramming.rst
@@ -33,7 +33,7 @@ Example Usage
 
 When using the ``localsolve`` method, the ``reltol`` argument specifies the relative tolerance of the solver: that is, by what percent does the solution have to improve between iterations? If any iteration improves less than that amount, the solver stops and returns its value.
 
-If you wish to start the local optimization at a particular point :math:`x_k`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``xk`` argument.
+If you wish to start the local optimization at a particular point :math:`x_k`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``x0`` argument.
 
 .. _sgp:
 
diff --git a/gpkit/constraints/set.py b/gpkit/constraints/set.py
index 830d97b83..dc3dcf8fd 100644
--- a/gpkit/constraints/set.py
+++ b/gpkit/constraints/set.py
@@ -76,7 +76,7 @@ def __init__(self, constraints, substitutions=None, *, bonusvks=None):  # pylint
         self.vks = set(self.unique_varkeys)
         self.substitutions = KeyDict({k: k.value for k in self.unique_varkeys
                                       if "value" in k.descr})
-        self.substitutions.cset = self
+        self.substitutions.vks = self.vks
         self.bounded, self.meq_bounded = set(), defaultdict(set)
         for i, constraint in enumerate(self):
             if hasattr(constraint, "vks"):
@@ -95,7 +95,6 @@ def __init__(self, constraints, substitutions=None, *, bonusvks=None):  # pylint
             self.vks.update(bonusvks)
         if substitutions:
             self.substitutions.update(substitutions)
-            self._varkeys = None
         for key in self.vks:
             if key not in self.substitutions:
                 if key.veckey is None or key.veckey not in self.substitutions:
diff --git a/gpkit/constraints/sgp.py b/gpkit/constraints/sgp.py
index 321721273..0463af3f5 100644
--- a/gpkit/constraints/sgp.py
+++ b/gpkit/constraints/sgp.py
@@ -66,7 +66,7 @@ def __init__(self, cost, model, substitutions, *,
         self.approxconstraints = []
         self.sgpvks = set()
         x0 = KeyDict(substitutions)
-        x0.varkeys = model.varkeys  # for string access and so forth
+        x0.vks = model.vks  # for string access and so forth
         for cs in model.flat():
             try:
                 if not hasattr(cs, "as_hmapslt1"):
@@ -149,7 +149,7 @@ def localsolve(self, solver=None, *, verbosity=1, x0=None, reltol=1e-4,
                     "Unsolved after %s iterations. Check `m.program.results`;"
                     " if they're converging, try `.localsolve(...,"
                     " iteration_limit=NEWLIMIT)`." % len(self.gps))
-            gp = self.gp(x0, cleanx0=True)
+            gp = self.gp(x0, cleanx0=(len(self.gps) >= 1))  # clean the first x0
             self.gps.append(gp)  # NOTE: SIDE EFFECTS
             if verbosity > 1:
                 print("\nGP Solve %i" % len(self.gps))
@@ -199,8 +199,10 @@ def localsolve(self, solver=None, *, verbosity=1, x0=None, reltol=1e-4,
                     " %.2g%%. Calling .localsolve with a higher"
                     " `pccp_penalty` (it was %.3g this time) will reduce"
                     " final slack if the model is solvable with less. If"
-                    " you think it might not be, check by solving with "
-                    "`use_pccp=False, x0=(this model's final solution)`.\n"
+                    " you think it might not be, check by generating an SP with"
+                    "`use_pccp=False`, then solving with x0=(this model's final"
+                    " solution); e.g. `m.sp(use_pccp=False).localsolve("
+                    "x0=m.solution[\"variables\"])`.\n"
                     % (100*excess_slack, self.pccp_penalty))
         return self.result
 
@@ -217,7 +219,10 @@ def gp(self, x0=None, *, cleanx0=False):
         if not x0:
             return self._gp  # return last generated
         if not cleanx0:
-            x0 = KeyDict(x0)
+            cleanedx0 = KeyDict()
+            cleanedx0.vks = self._gp.x0.vks
+            cleanedx0.update(x0)
+            x0 = cleanedx0
         self._gp.x0.update({vk: x0[vk] for vk in self.sgpvks if vk in x0})
         p_idx = 0
         for sgpc in self.sgpconstraints:
diff --git a/gpkit/keydict.py b/gpkit/keydict.py
index c6f393ed4..a64ce9a61 100644
--- a/gpkit/keydict.py
+++ b/gpkit/keydict.py
@@ -45,7 +45,7 @@ class KeyMap:
     collapse_arrays = False
     keymap = []
     log_gets = False
-    cset = None
+    vks = varkeys = None
 
     def __init__(self, *args, **kwargs):
         "Passes through to super().__init__ via the `update()` method"
@@ -62,12 +62,14 @@ def parse_and_index(self, key):
                 return key.veckey, key.idx
             return key, None
         except AttributeError:
-            if self.cset is None:
+            if self.vks is None and self.varkeys is None:
                 return key, self.update_keymap()
         # looks like we're in a substitutions dictionary
-        if key not in self.cset.varkeys:
+        if self.varkeys is None:
+            self.varkeys = KeySet(self.vks)
+        if key not in self.varkeys:
             raise KeyError(key)
-        newkey, *otherkeys = self.cset.varkeys[key]
+        newkey, *otherkeys = self.varkeys[key]
         if otherkeys:
             if all(k.veckey == newkey.veckey for k in otherkeys):
                 return newkey.veckey, None

From c867b70d28dc9ad5a8ea322c7de32252842738c6 Mon Sep 17 00:00:00 2001
From: Edward Burnell <eburn@mit.edu>
Date: Fri, 19 Mar 2021 13:57:16 -0700
Subject: [PATCH 11/12] fix docs typo

---
 docs/source/signomialprogramming.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/signomialprogramming.rst b/docs/source/signomialprogramming.rst
index d50125944..61875dd8c 100644
--- a/docs/source/signomialprogramming.rst
+++ b/docs/source/signomialprogramming.rst
@@ -33,7 +33,7 @@ Example Usage
 
 When using the ``localsolve`` method, the ``reltol`` argument specifies the relative tolerance of the solver: that is, by what percent does the solution have to improve between iterations? If any iteration improves less than that amount, the solver stops and returns its value.
 
-If you wish to start the local optimization at a particular point :math:`x_k`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``x0`` argument.
+If you wish to start the local optimization at a particular point :math:`x_0`, however, you may do so by putting that position (a dictionary formatted as you would a substitution) as the ``x0`` argument.
 
 .. _sgp:
 

From 1b09b7f5f484433208d8cfc8dad15ef1c1424f27 Mon Sep 17 00:00:00 2001
From: Ned Burnell <eburn@mit.edu>
Date: Sun, 21 Mar 2021 14:18:56 -0700
Subject: [PATCH 12/12] Working MIGP (#1527)

* migp with choice variables
* add test and use warnings to discuss migp results
* update docs
---
 docs/source/advancedcommands.rst     | 59 ++++++++++++++++++
 docs/source/examples/migp.py         | 10 ++++
 docs/source/examples/migp_output.txt | 59 ++++++++++++++++++
 docs/source/installation.rst         | 32 +++++-----
 gpkit/constraints/gp.py              | 30 +++++++++-
 gpkit/small_classes.py               |  5 +-
 gpkit/solution_array.py              | 14 +++--
 gpkit/solvers/mosek_conif.py         | 89 +++++++++++++++++++++-------
 gpkit/tests/helpers.py               |  5 +-
 gpkit/tests/t_examples.py            |  7 +++
 10 files changed, 264 insertions(+), 46 deletions(-)
 create mode 100644 docs/source/examples/migp.py
 create mode 100644 docs/source/examples/migp_output.txt

diff --git a/docs/source/advancedcommands.rst b/docs/source/advancedcommands.rst
index 5afa5e8f3..a01d3b529 100644
--- a/docs/source/advancedcommands.rst
+++ b/docs/source/advancedcommands.rst
@@ -1,6 +1,65 @@
 Advanced Commands
 *****************
 
+.. _migp:
+
+Choice Variables
+================
+If MOSEK 9 is installed, GPkit supports discretized free variables with the ``mosek_conif`` solver.
+Choice variables are free in the sense of having multiple possible choices, but discretized in the
+sense of having a limited set of possible solutions.
+
+.. literalinclude:: examples/migp.py
+
+If solved with the mosek_conif solver, the script above will print::
+
+    Optimal Cost
+    ------------
+     [ 1.5       2.15      2.8       3.22     ... ]
+
+    ~~~~~~~~
+    WARNINGS
+    ~~~~~~~~
+    No Dual Solution
+    ----------------
+    This model has the discretized choice variables [x] and hence no dual
+    solution. You can fix those variables to their optimal value and get
+    sensitivities to the resulting continuous problem by updating your model's
+    substitions with `sol["choicevariables"]`.
+    ~~~~~~~~
+
+    Swept Variables
+    ---------------
+    numerator : [ 0.5
+                  1.15
+                  1.8
+                  2.45
+                  3.1
+                  3.75
+                  4.4
+                  5.05
+                  5.7
+                  6.35
+                  7         ]
+
+    Free Variables
+    --------------
+    x : [ 1
+          1
+          1
+          2
+          2
+          2
+          2
+          2
+          2
+          3
+          3         ]
+
+Note that the optimal values for ``x`` are discretized, clicking from 1
+to 2 to 3 during the sweep, and that the solution has no dual variables.
+
+
 Derived Variables
 =================
 
diff --git a/docs/source/examples/migp.py b/docs/source/examples/migp.py
new file mode 100644
index 000000000..372c7ab1f
--- /dev/null
+++ b/docs/source/examples/migp.py
@@ -0,0 +1,10 @@
+import numpy as np
+from gpkit import *
+
+x = Variable("x", choices=range(1,4))
+num = Variable("numerator", np.linspace(0.5, 7, 11))
+
+m = Model(x + num/x)
+sol = m.solve(verbosity=0)
+
+print(sol.table())
diff --git a/docs/source/examples/migp_output.txt b/docs/source/examples/migp_output.txt
new file mode 100644
index 000000000..8dfe175c2
--- /dev/null
+++ b/docs/source/examples/migp_output.txt
@@ -0,0 +1,59 @@
+
+Optimal Cost
+------------
+ [ 1.41      2.14      2.68      3.13     ... ]
+
+~~~~~~~~
+WARNINGS
+~~~~~~~~
+Freed Choice Variables
+----------------------
+This model has the discretized choice variables [x], but since the 'cvxopt' solver doesn't support discretization they were treated as continuous variables.
+~~~~~~~~
+
+Swept Variables
+---------------
+numerator : [ 0.5
+              1.15
+              1.8
+              2.45
+              3.1
+              3.75
+              4.4
+              5.05
+              5.7
+              6.35
+              7         ]
+
+Free Variables
+--------------
+x : [ 0.707
+      1.07
+      1.34
+      1.57
+      1.76
+      1.94
+      2.1
+      2.25
+      2.39
+      2.52
+      2.65      ]
+
+Variable Sensitivities
+----------------------
+numerator : [ +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5
+              +0.5      ]
+
+Most Sensitive Constraints (in last sweep)
+------------------------------------------
+(none)
+
diff --git a/docs/source/installation.rst b/docs/source/installation.rst
index 96dc5d84a..15fb59528 100644
--- a/docs/source/installation.rst
+++ b/docs/source/installation.rst
@@ -4,42 +4,44 @@ Installation
 ************
 
 1. If you are on Mac or Windows, we recommend installing `Anaconda <http://www.continuum.io/downloads>`_. Alternatively, `install pip and create a virtual environment <https://packaging.python.org/guides/installing-using-pip-and-virtualenv/>`_.
-2. (optional) Install the MOSEK solver as directed below
-3. Run ``pip install gpkit`` in the appropriate terminal or command prompt.
-4. Open a Python prompt and run ``import gpkit`` to finish installation and run unit tests.
+2. (optional) Install the MOSEK 9 solver with ``pip install Mosek``, then a license as described below
+3. (optional) Install the MOSEK 8 solver as described below
+4. Run ``pip install gpkit`` in the appropriate terminal or command prompt.
+5. Open a Python prompt and run ``import gpkit`` to finish installation and run unit tests.
 
 If you encounter any bugs please email ``gpkit@mit.edu``
 or `raise a GitHub issue <http://github.com/convexengineering/gpkit/issues/new>`_.
 
 
-Installing MOSEK
-================
-GPkit interfaces with two off the shelf solvers: cvxopt, and MOSEK.
+Installing MOSEK 8
+==================
+GPkit interfaces with two off the shelf solvers: cvxopt, and MOSEK (versions 8 and 9).
 Cvxopt is open source and installed by default; MOSEK requires a commercial licence or (free)
-academic license.
+academic license. In MOSEK version 8 GPkit uses the command-line interface ``mskexpopt`` solver, while
+in MOSEK 9 it uses the more active exponential-cone interface (and hence supports :ref:`migp`).
 
 Mac OS X
   - If ``which gcc`` does not return anything, install the `Apple Command Line Tools <https://developer.apple.com/downloads/index.action?=command%20line%20tools>`_.
   - Download `MOSEK 8 <https://www.mosek.com/downloads/>`_, then:
       - Move the ``mosek`` folder to your home directory
       - Follow `these steps for Mac <http://docs.mosek.com/7.0/toolsinstall/Mac_OS_X_installation.html>`_.
-      - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``~/mosek/``
+  - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``~/mosek/``
 
 Linux
   - Download `MOSEK 8 <https://www.mosek.com/downloads/>`_, then:
       - Move the ``mosek`` folder to your home directory
       - Follow `these steps for Linux <http://docs.mosek.com/7.0/toolsinstall/Linux_UNIX_installation_instructions.html>`_.
-      - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``~/mosek/``
+  - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``~/mosek/``
 
 Windows
+    - Make sure ``gcc`` is on your system path.
+        - To do this, type ``gcc`` into a command prompt.
+        - If you get ``executable not found``, then install the 64-bit version (x86_64 installer architecture dropdown option) with GCC version 6.4.0 or older of `mingw <http://sourceforge.net/projects/mingw-w64/>`_.
+        - In an Anaconda command prompt (or equivalent), run ``cd C:\Program Files\mingw-w64\x86_64-6.4.0-posix-seh-rt_v5-rev0\`` (or whatever corresponds to the correct installation directory; note that if mingw is in ``Program Files (x86)`` instead of ``Program Files`` you've installed the 32-bit version by mistake)
+        - Run ``mingw-w64`` to add it to your executable path. For step 3 of the install process you'll need to run ``pip install gpkit`` from this prompt.
     - Download `MOSEK 8 <https://www.mosek.com/downloads/>`_, then:
         - Follow `these steps for Windows <http://docs.mosek.com/7.0/toolsinstall/Windows_installation.html>`_.
-        - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``C:\Users\(your_username)\mosek\``
-        - Make sure ``gcc`` is on your system path.
-            - To do this, type ``gcc`` into a command prompt.
-            - If you get ``executable not found``, then install the 64-bit version (x86_64 installer architecture dropdown option) with GCC version 6.4.0 or older of `mingw <http://sourceforge.net/projects/mingw-w64/>`_.
-            - In an Anaconda command prompt (or equivalent), run ``cd C:\Program Files\mingw-w64\x86_64-6.4.0-posix-seh-rt_v5-rev0\`` (or whatever corresponds to the correct installation directory; note that if mingw is in ``Program Files (x86)`` instead of ``Program Files`` you've installed the 32-bit version by mistake)
-            - Run ``mingw-w64`` to add it to your executable path. For step 3 of the install process you'll need to run ``pip install gpkit`` from this prompt.
+    - Request an `academic license file <http://license.mosek.com/academic>`_ and put it in ``C:\Users\(your_username)\mosek\``
 
 Debugging your installation
 ===========================
diff --git a/gpkit/constraints/gp.py b/gpkit/constraints/gp.py
index 89a8fe294..b236596e7 100644
--- a/gpkit/constraints/gp.py
+++ b/gpkit/constraints/gp.py
@@ -69,6 +69,7 @@ class GeometricProgram:
     >>> gp.solve()
     """
     _result = solve_log = solver_out = model = v_ss = nu_by_posy = None
+    choicevaridxs = integersolve = None
 
     def __init__(self, cost, constraints, substitutions, *, checkbounds=True):
         self.cost, self.substitutions = cost, substitutions
@@ -155,6 +156,8 @@ def gen(self):
                 m_idx += 1
         self.p_idxs = np.array(self.p_idxs, "int32")  # to use array equalities
         self.varidxs = {vk: i for i, vk in enumerate(self.varlocs)}
+        self.choicevaridxs = {vk: i for i, vk in enumerate(self.varlocs)
+                              if vk.choices}
         for j, (var, locs) in enumerate(self.varlocs.items()):
             row.extend(locs)
             col.extend([j]*len(locs))
@@ -191,6 +194,9 @@ def solve(self, solver=None, *, verbosity=1, gen_result=True, **kwargs):
 
         solverargs = DEFAULT_SOLVER_KWARGS.get(solvername, {})
         solverargs.update(kwargs)
+        if self.choicevaridxs and solvername == "mosek_conif":
+            solverargs["choicevaridxs"] = self.choicevaridxs
+            self.integersolve = True
         starttime = time()
         solver_out, infeasibility, original_stdout = {}, None, sys.stdout
         try:
@@ -304,6 +310,27 @@ def _compile_result(self, solver_out):
         result["constants"] = KeyDict(self.substitutions)
         result["variables"] = KeyDict(result["freevariables"])
         result["variables"].update(result["constants"])
+        result["soltime"] = solver_out["soltime"]
+        if self.integersolve:
+            result["choicevariables"] = KeyDict( \
+                {k: v for k, v in result["freevariables"].items()
+                 if k in self.choicevaridxs})
+            result["warnings"] = {"No Dual Solution": [(\
+                "This model has the discretized choice variables"
+                " %s and hence no dual solution. You can fix those variables"
+                " to their optimal value and get sensitivities to the resulting"
+                " continuous problem by updating your model's substitions with"
+                " `sol[\"choicevariables\"]`."
+                % sorted(self.choicevaridxs.keys()), self.choicevaridxs)]}
+            return SolutionArray(result)
+        elif self.choicevaridxs:
+            result["warnings"] = {"Freed Choice Variables": [(\
+                "This model has the discretized choice variables"
+                " %s, but since the '%s' solver doesn't support discretization"
+                " they were treated as continuous variables."
+                % (sorted(self.choicevaridxs.keys()), solver_out["solver"]),
+                self.choicevaridxs)]}
+
         result["sensitivities"] = {"constraints": {}}
         la, self.nu_by_posy = self._generate_nula(solver_out)
         cost_senss = sum(nu_i*exp for (nu_i, exp) in zip(self.nu_by_posy[0],
@@ -342,7 +369,6 @@ def _compile_result(self, solver_out):
         result["sensitivities"]["variables"] = KeyDict(gpv_ss)
         result["sensitivities"]["constants"] = \
             result["sensitivities"]["variables"]  # NOTE: backwards compat.
-        result["soltime"] = solver_out["soltime"]
         return SolutionArray(result)
 
     def check_solution(self, cost, primal, nu, la, tol, abstol=1e-20):
@@ -379,6 +405,8 @@ def almost_equal(num1, num2):
                 raise Infeasible("Primal solution violates constraint: %s is "
                                  "greater than 1" % primal_exp_vals[mi].sum())
         # check dual sol #
+        if self.integersolve:
+            return
         # note: follows dual formulation in section 3.1 of
         # http://web.mit.edu/~whoburg/www/papers/hoburg_phd_thesis.pdf
         if not almost_equal(self.nu_by_posy[0].sum(), 1):
diff --git a/gpkit/small_classes.py b/gpkit/small_classes.py
index b66d71464..81d5043fc 100644
--- a/gpkit/small_classes.py
+++ b/gpkit/small_classes.py
@@ -74,9 +74,10 @@ def __init__(self, output=None, *, verbosity=0):
 
     def write(self, writ):
         "Append and potentially write the new line."
+        if writ[:2] == "b'":
+            writ = writ[2:-1]
         if writ != "\n":
-            writ = writ.rstrip("\n")
-            self.append(str(writ))
+            self.append(writ.rstrip("\n"))
         if self.verbosity > 0:  # pragma: no cover
             self.output.write(writ)
 
diff --git a/gpkit/solution_array.py b/gpkit/solution_array.py
index 7af996894..30fe3eda9 100644
--- a/gpkit/solution_array.py
+++ b/gpkit/solution_array.py
@@ -243,7 +243,9 @@ def warnings_table(self, _, **kwargs):
         if len(data_vec) == 0:
             continue
         if not hasattr(data_vec, "shape"):
-            data_vec = [data_vec]
+            data_vec = [data_vec]  # not a sweep
+        if all((data == data_vec[0]).all() for data in data_vec[1:]):
+            data_vec = [data_vec[0]]  # warnings identical across all sweeps
         for i, data in enumerate(data_vec):
             if len(data) == 0:
                 continue
@@ -340,7 +342,8 @@ class SolutionArray(DictOfLists):
     """
     modelstr = ""
     _name_collision_varkeys = None
-    table_titles = {"sweepvariables": "Swept Variables",
+    table_titles = {"choicevariables": "Choice Variables",
+                    "sweepvariables": "Swept Variables",
                     "freevariables": "Free Variables",
                     "constants": "Fixed Variables",  # TODO: change everywhere
                     "variables": "Variables"}
@@ -683,7 +686,7 @@ def table(self, showvars=(),
         -------
         str
         """
-        if sortmodelsbysenss:
+        if sortmodelsbysenss and "sensitivities" in self:
             kwargs["sortmodelsbysenss"] = self["sensitivities"]["models"]
         else:
             kwargs["sortmodelsbysenss"] = False
@@ -700,7 +703,10 @@ def table(self, showvars=(),
         showvars = self._parse_showvars(showvars)
         strs = []
         for table in tables:
-            if table == "cost":
+            if "sensitivities" not in self and ("sensitivities" in table or
+                                                "constraints" in table):
+                continue
+            elif table == "cost":
                 cost = self["cost"]  # pylint: disable=unsubscriptable-object
                 if kwargs.get("latex", None):  # cost is not printed for latex
                     continue
diff --git a/gpkit/solvers/mosek_conif.py b/gpkit/solvers/mosek_conif.py
index 75c4b123c..450acaef1 100644
--- a/gpkit/solvers/mosek_conif.py
+++ b/gpkit/solvers/mosek_conif.py
@@ -180,6 +180,35 @@ def optimize(*, c, A, k, p_idxs, **kwargs):
         task.putconboundlist(con_indices, type_constraint, h, h)
         cur_con_idx += log_c_lin.size
     #
+    #   Constrain choice variables to discrete choices
+    #
+    choicevaridxs = kwargs.get("choicevaridxs", {})
+    if choicevaridxs:
+        n_choicevars = 0
+        for var, idx in choicevaridxs.items():
+            choices = sorted(var.choices)
+            m_choices = len(choices) - 1  # the first option is the default
+            choiceidxs = np.arange(msk_nvars + n_choicevars,
+                                   msk_nvars + n_choicevars + m_choices)
+            n_choicevars += m_choices
+            task.appendvars(m_choices)
+            task.putvartypelist(choiceidxs,
+                                [mosek.variabletype.type_int]*m_choices)
+            task.putvarboundlist(choiceidxs, [mosek.boundkey.ra]*m_choices,
+                                 np.zeros(m_choices), np.ones(m_choices))
+            task.appendcons(m_choices)
+            for i in range(m_choices - 1):
+                # each larger choice requires those before it
+                task.putarow(cur_con_idx + i, choiceidxs[i:i+2], [1.0, -1.0])
+                task.putconbound(cur_con_idx + i, mosek.boundkey.lo, 0.0, 0.0)
+                cur_con_idx += 1
+            base = np.log(choices[0])
+            logdiffs = np.diff(np.log(choices)).tolist()
+            task.putarow(cur_con_idx, choiceidxs.tolist() + [idx],
+                         logdiffs + [-1])  # choices are summed
+            task.putconbound(cur_con_idx, mosek.boundkey.fx, -base, -base)
+            cur_con_idx += 1
+    #
     #   Set the objective function
     #
     task.putclist([int(m + 3*n_lse)], [1])
@@ -212,40 +241,54 @@ def streamprinter(text):
     #
     #   Recover the solution
     #
-    msk_solsta = task.getsolsta(mosek.soltype.itr)
+    if choicevaridxs:
+        sol = mosek.soltype.itg
+        optimal = mosek.solsta.integer_optimal
+    else:
+        sol = mosek.soltype.itr
+        optimal = mosek.solsta.optimal
+    msk_solsta = task.getsolsta(sol)
     if msk_solsta == mosek.solsta.prim_infeas_cer:
         raise PrimalInfeasible()
     if msk_solsta == mosek.solsta.dual_infeas_cer:
         raise DualInfeasible()
-    if msk_solsta != mosek.solsta.optimal:  # pragma: no cover
+    if msk_solsta != optimal:  # pragma: no cover
         raise UnknownInfeasible("solution status: ", msk_solsta)
 
     # recover primal variables
     x = [0.] * m
-    task.getxxslice(mosek.soltype.itr, 0, m, x)
+    task.getxxslice(sol, 0, m, x)
+    # recover binary variables
+    # xbin = [0.] * (n_choicevars)
+    # task.getxxslice(sol, msk_nvars, msk_nvars + n_choicevars, xbin)
+    # wrap things up in a dictionary
+    solution = {"status": "optimal", "primal": np.array(x),
+                "objective": np.exp(task.getprimalobj(sol))}
     # recover dual variables for log-sum-exp epigraph constraints
     # (skip epigraph of the objective function).
-    z_duals = [0.] * (p_lse - 1)
-    task.getsuxslice(mosek.soltype.itr, m + 3*n_lse + 1, msk_nvars, z_duals)
-    z_duals = np.array(z_duals)
-    z_duals[z_duals < 0] = 0
-    # recover dual variables for the remaining user-provided constraints
-    if log_c_lin is not None:
-        aff_duals = [0.] * log_c_lin.size
-        task.getsucslice(mosek.soltype.itr, n_lse + p_lse, cur_con_idx,
-                         aff_duals)
-        aff_duals = np.array(aff_duals)
-        aff_duals[aff_duals < 0] = 0
-        # merge z_duals with aff_duals
-        merged_duals = np.zeros(len(k))
-        merged_duals[lse_posys[1:]] = z_duals  # skipping the cost
-        merged_duals[lin_posys] = aff_duals
-        merged_duals = merged_duals[1:]
+    if choicevaridxs:  # no dual solution
+        solution["la"] = []
+        solution["nu"] = []
     else:
-        merged_duals = z_duals
-    # wrap things up in a dictionary
-    solution = {"status": "optimal", "primal": np.array(x), "la": merged_duals,
-                "objective": np.exp(task.getprimalobj(mosek.soltype.itr))}
+        z_duals = [0.] * (p_lse - 1)
+        task.getsuxslice(mosek.soltype.itr, m + 3*n_lse + 1, msk_nvars, z_duals)
+        z_duals = np.array(z_duals)
+        z_duals[z_duals < 0] = 0
+        # recover dual variables for the remaining user-provided constraints
+        if log_c_lin is None:
+            solution["la"] = z_duals
+        else:
+            aff_duals = [0.] * log_c_lin.size
+            task.getsucslice(mosek.soltype.itr, n_lse + p_lse, cur_con_idx,
+                             aff_duals)
+            aff_duals = np.array(aff_duals)
+            aff_duals[aff_duals < 0] = 0
+            # merge z_duals with aff_duals
+            merged_duals = np.zeros(len(k))
+            merged_duals[lse_posys[1:]] = z_duals  # skipping the cost
+            merged_duals[lin_posys] = aff_duals
+            solution["la"] = merged_duals[1:]
+
     task.__exit__(None, None, None)
     env.__exit__(None, None, None)
     return solution
diff --git a/gpkit/tests/helpers.py b/gpkit/tests/helpers.py
index 206575032..dadad448b 100644
--- a/gpkit/tests/helpers.py
+++ b/gpkit/tests/helpers.py
@@ -84,7 +84,10 @@ def test(self):
         filepath = ("".join([path, os.sep, "%s_output.txt" % name])
                     if name not in imported else None)
         with StdoutCaptured(logfilepath=filepath):
-            imported[name] = importlib.import_module(name)
+            if name in imported:
+                importlib.reload(imported[name])
+            else:
+                imported[name] = importlib.import_module(name)
         getattr(self, name)(imported[name])
     return test
 
diff --git a/gpkit/tests/t_examples.py b/gpkit/tests/t_examples.py
index 41db5f576..c84bb9cb6 100644
--- a/gpkit/tests/t_examples.py
+++ b/gpkit/tests/t_examples.py
@@ -92,6 +92,13 @@ def test_evaluated_free_variables(self, example):
     def test_external_constraint(self, example):
         pass
 
+    def test_migp(self, example):
+        if settings["default_solver"] == "mosek_conif":
+            assert_logtol(example.sol(example.x), [1]*3 + [2]*6 + [3]*2)
+        else:
+            assert_logtol(example.sol(example.x),
+                          np.sqrt(example.sol(example.num)))
+
     def test_external_function(self, example):
         external_code = example.external_code
         self.assertEqual(external_code(0), 0)