Merge 37f1d59 into c8cf2b3

.pylintrc

@@ -83,7 +83,7 @@ attr-rgx=[a-z_][a-z0-9_]{2,30}$
 attr-name-hint=[a-z_][a-z0-9_]{2,30}$
 
 # Regular expression matching correct argument names
-argument-rgx=[a-z_][a-z0-9_]{2,30}|nu|la|ax$
+argument-rgx=[a-z_][a-z0-9_]{2,30}|nu|la|ax|vk$
 
 # Naming hint for argument names
 argument-name-hint=[a-z_][a-z0-9_]{2,30}$

docs/source/_static/css/custom.css

@@ -0,0 +1,5 @@
+@import 'theme.css';
+
+div[class^='highlight-breakdowns'] pre {
+  line-height: 1.15 !important;
+}

docs/source/conf.py

@@ -139,6 +139,12 @@
 # so a file named "default.css" will overwrite the builtin "default.css".
 html_static_path = ['_static']
 
+html_css_files = [
+    'css/custom.css',
+]
+
+html_style = 'css/custom.css'
+
 # Add any extra paths that contain custom files (such as robots.txt or
 # .htaccess) here, relative to this directory. These files are copied
 # directly to the root of the documentation.

docs/source/debugging.rst

@@ -1,7 +1,7 @@
 Debugging Models
 ****************
 
-A number of errors and warnings may be raised when attempting to solve a model. 
+A number of errors and warnings may be raised when attempting to solve a model.
 A model may be primal infeasible: there is no possible solution that satisfies all constraints. A model may be dual infeasible: the optimal value of one or more variables is 0 or infinity (negative and positive infinity in logspace).
 
 For a GP model that does not solve, solvers may be able to prove its primal or dual infeasibility, or may return an unknown status.
@@ -11,6 +11,7 @@ GPkit contains several tools for diagnosing which constraints and variables migh
 .. literalinclude:: examples/debug.py
 
 .. literalinclude:: examples/debug_output.txt
+    :language: breakdowns
 
 Note that certain modeling errors (such as omitting or forgetting a constraint) may be difficult to diagnose from this output.
 
@@ -33,7 +34,7 @@ Potential errors and warnings
 - ``RuntimeWarning: Dual cost nan does not match primal cost 1.00122315152``
     - Similarly to the above, this warning may be seen in dual infeasible models, see *Dual Infeasibility* below.
 
-.. 
+..
     note: remove the above when we match solver tolerance in GPkit (issue #753)
 
 
@@ -54,6 +55,7 @@ For example, Mosek returns ``DUAL_INFEAS_CER`` when attempting to solve the foll
 Upon viewing the printed output,
 
 .. literalinclude:: examples/unbounded_output.txt
+    :language: breakdowns
 
 The problem, unsurprisingly, is that the cost ``1/x`` has no lower bound because ``x`` has no upper bound.
 
@@ -84,3 +86,4 @@ If you suspect your model is primal infeasible, you can find the nearest primal
 .. literalinclude:: examples/relaxation.py
 
 .. literalinclude:: examples/relaxation_output.txt
+    :language: breakdowns

docs/source/examples.rst

@@ -17,6 +17,7 @@ minimize :math:`x` subject to the constraint :math:`x \ge 1`.
 Of course, the optimal value is 1. Output:
 
 .. literalinclude:: examples/x_greaterthan_1_output.txt
+    :language: breakdowns
 
 Maximizing the Volume of a Box
 ==============================
@@ -27,6 +28,7 @@ This example comes from Section 2.4 of the `GP tutorial <http://stanford.edu/~bo
 The output is
 
 .. literalinclude:: examples/simple_box_output.txt
+    :language: breakdowns
 
 Water Tank
 ==========
@@ -37,6 +39,7 @@ Say we had a fixed mass of water we wanted to contain within a tank, but also wa
 The output is:
 
 .. literalinclude:: examples/water_tank_output.txt
+    :language: breakdowns
 
 Simple Wing
 ===========
@@ -47,6 +50,7 @@ This example comes from Section 3 of `Geometric Programming for Aircraft Design
 The output is:
 
 .. literalinclude:: examples/simpleflight_output.txt
+    :language: breakdowns
 
 Simple Beam
 ===========
@@ -57,6 +61,7 @@ In this example we consider a beam subjected to a uniformly distributed transver
 The output is:
 
 .. literalinclude:: examples/beam_output.txt
+    :language: breakdowns
 
 By plotting the deflection, we can see that the agreement between the analytical solution and the GP solution is good.
 

docs/source/examples/beam_output.txt

@@ -1,7 +1,48 @@
 
-Optimal Cost
-------------
- 1.621
+         ┃┓         ┓         ┓         ┓          ┓
+         ┃┃         ┃         ┃         ┃          ┣╸th[2]╶⎨
+         ┃┃         ┃         ┃         ┣╸w[2]     ┛ (0.285)
+         ┃┃         ┃         ┃         ┃ (0.384m) ┣╸th[1]╶⎨
+         ┃┃         ┃         ┣╸w[3]    ┛          ┣╸w[1]╶⎨
+         ┃┃         ┃         ┃ (0.76m) ┣╸th[3]   ┣╸th[2]╶⎨
+         ┃┃         ┃         ┃         ┛ (0.341) ┛
+         ┃┃         ┣╸w[4]    ┃         ┣╸th[2]╶⎨
+         ┃┃         ┃ (1.18m) ┛         ┛
+    Cost╺┫┃         ┃         ┣╸th[3] ┣╸th[2]╶⎨
+ (1.62m) ┃┣╸w[5]    ┃         ┛       ┛
+         ┃┃ (1.62m) ┃         ┓         ┓
+         ┃┃         ┃         ┣╸th[4]   ┣╸th[2]╶⎨
+         ┃┃         ┛         ┛ (0.363) ┛
+         ┃┃         ┓         ┓
+         ┃┃         ┣╸th[5]   ┣╸th[2]╶⎨
+         ┃┃         ┛ (0.367) ┛
+         ┃┃         ┓       ┓
+         ┃┃         ┣╸th[4] ┣╸th[2]╶⎨
+         ┃┛         ┛       ┛
+
+
+
+       ┃┓      ┓
+       ┃┃      ┃
+       ┃┃      ┣╸L = 5·dx
+       ┃┃      ┛
+       ┃┃      ┓
+       ┃┃      ┃
+       ┃┃      ┣╸L = 6m
+       ┃┃      ┛
+       ┃┃      ┣╸EI = 11,000N·m²
+ Model╺┫┃      ┣╸w[5] ≥ w[4] + 0.5·dx·(th[5] + th[4])
+       ┃┣╸Beam ┣╸th[2] ≥ th[1] + 0.5·dx·(M[2] + M[1])/EI
+       ┃┃      ┣╸w[4] ≥ w[3] + 0.5·dx·(th[4] + th[3])
+       ┃┃      ┣╸M[1] ≥ M[2] + 0.5·dx·(V[1] + V[2])
+       ┃┃      ┣╸th[3] ≥ th[2] + 0.5·dx·(M[3] + M[2])/EI
+       ┃┃      ┣╸V[3] ≥ V[4] + 0.5·dx·(q[3] + q[4])
+       ┃┃      ┣╸th[1] ≥ th[0] + 0.5·dx·(M[1] + M[0])/EI
+       ┃┃      ┓
+       ┃┃      ┃
+       ┃┃      ┣╸[17 terms]
+       ┃┛      ┛
+
 
 Free Variables
 --------------
@@ -11,17 +52,3 @@ dx : 1.2                                                             [m]   Lengt
 th : [ 0.0002    0.177     0.285     0.341     0.363     0.367    ]        Slope
  w : [ 0.0002    0.107     0.384     0.76      1.18      1.62     ]  [m]   Displacement
 
-Most Sensitive Variables
-------------------------
- L : +4                                                             Overall beam length
-EI : -1                                                             Bending stiffness
- q : [ +0.0072   +0.042    +0.12     +0.23     +0.37     +0.22    ] Distributed load
-
-Most Sensitive Constraints
---------------------------
-    +4 : L = 5·dx
-    +1 : w[5] ≥ w[4] + 0.5·dx·(th[5] + th[4])
- +0.74 : th[2] ≥ th[1] + 0.5·dx·(M[2] + M[1])/EI
- +0.73 : w[4] ≥ w[3] + 0.5·dx·(th[4] + th[3])
- +0.64 : M[1] ≥ M[2] + 0.5·dx·(V[1] + V[2])
-

docs/source/examples/breakdowns.py

@@ -0,0 +1,54 @@
+"An example to show off Breakdowns"
+import os
+import sys
+import pickle
+from gpkit.breakdowns import Breakdowns
+
+# the code to create solar.p is in ./breakdowns/solartest.py
+filepath = os.path.dirname(os.path.realpath(__file__)) + os.sep + "solar.p"
+print(filepath)
+sol = pickle.load(open(filepath, "rb"))
+bds = Breakdowns(sol)
+
+print("Cost breakdown (you may be familiar with this from solution tables)")
+print("==============")
+try:
+    bds.plot("cost")
+except AttributeError:  # if the pint version differs from the pickled solution
+    sys.exit(0)
+
+print("Variable breakdowns (note the two methods of access)")
+print("===================")
+varkey, = sol["variables"].keymap[("Mission.FlightSegment.AircraftPerf"
+                                   ".AircraftDrag.Poper")]
+bds.plot(varkey)
+bds.plot("AircraftPerf.AircraftDrag.MotorPerf.Q")
+
+print("Combining the two above by increasing maxwidth")
+print("----------------------------------------------")
+bds.plot("AircraftPerf.AircraftDrag.Poper", maxwidth=105)
+
+print("Model sensitivity breakdowns (note the two methods of access)")
+print("============================")
+bds.plot("model sensitivities")
+bds.plot("Aircraft")
+
+print("Exhaustive variable breakdown traces (and configuration arguments)")
+print("====================================")
+# often useful as a reference point when reading traces
+bds.plot("AircraftPerf.AircraftDrag.Poper", height=12)
+# includes factors, can be useful for reading traces as well
+bds.plot("AircraftPerf.AircraftDrag.Poper", showlegend=True)
+print("\nPermissivity = 2 (the default)")
+print("----------------")
+bds.trace("AircraftPerf.AircraftDrag.Poper")
+print("\nPermissivity = 1 (stops at Pelec = v·i)")
+print("----------------")
+bds.trace("AircraftPerf.AircraftDrag.Poper", permissivity=1)
+
+# you can also produce Plotly treemaps/icicle plots of your breakdowns
+fig = bds.treemap("model sensitivities", returnfig=True)
+fig = bds.icicle("cost", returnfig=True)
+# uncommenting any of the below makes and shows the plot directly
+# bds.icicle("model sensitivities")
+# bds.treemap("cost")

docs/source/examples/breakdowns/solartest.py

@@ -0,0 +1,6 @@
+from solar.solar import *
+Vehicle = Aircraft(Npod=3, sp=True)
+M = Mission(Vehicle, latitude=[20])
+M.cost = M[M.aircraft.Wtotal]
+
+M.localsolve().save("solar.p")