remove redundant nonsmooth methods, add types and docs (#158)

* Address review comments: remove redundant nonsmooth methods, add types, docs

- Remove is_atom_nonsmooth_convex/is_atom_nonsmooth_concave from base Atom
  class and 10 atom subclasses; use existing is_atom_convex/is_atom_concave
  in DNLP composition rules instead
- Add type annotations and docstrings to NLPsolver, Bounds, and Oracles
  in nlp_solver.py
- Document Variable.sample_bounds with class-level type annotation and
  docstring
- Revert GENERAL_PROJECTION_TOL back to 1e-10 (was loosened for removed
  IPOPT derivative checker)
- Update CLAUDE.md atom classification docs to reflect simplified API

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Move sample_bounds docs from #: comments into Variable class docstring

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: Transurgeon

CLAUDE.md

@@ -159,7 +159,7 @@ Adding a new diff engine atom requires:
 
 The diff engine supports CVXPY `Parameter` objects: `C_problem` registers parameters with the C engine and `update_params()` re-pushes values without rebuilding the expression tree. Sparse parameter values are fused into sparse matmul operations.
 
-`DerivativeChecker` in `nlp_solver.py` provides finite-difference verification of gradients, Jacobians, and Hessians during development.
+`DerivativeChecker` in `cvxpy/tests/nlp_tests/derivative_checker.py` provides finite-difference verification of gradients, Jacobians, and Hessians during development.
 
 Key files in `cvxpy/reductions/solvers/nlp_solvers/diff_engine/`:
 - `converters.py` - Converts CVXPY expression AST to C diff engine trees. Contains `ATOM_CONVERTERS` dict mapping ~40 atom types to C constructors. Includes optimizations like sparse parameter matmul fusion.
@@ -182,17 +182,17 @@ Convention: all arrays are flattened in **Fortran order** ('F') for column-major
 1. Create a canonicalizer in `cvxpy/reductions/dnlp2smooth/canonicalizers/`
 2. The canonicalizer converts non-smooth atoms to smooth equivalents using auxiliary variables
 3. Register in `canonicalizers/__init__.py` by adding to `SMOOTH_CANON_METHODS` dict
-4. Classify the atom using the three-way atom-level API (see below)
+4. If the atom is smooth, override `is_atom_smooth()` to return `True` (see classification below)
 
-### DNLP Atom Classification (Three-way)
+### DNLP Atom Classification
 
-Each atom implements exactly one of three atom-level methods:
+Atoms are classified as smooth or non-smooth.  Non-smooth atoms reuse the existing `is_atom_convex()`/`is_atom_concave()` methods for the DNLP composition rules—no separate method is needed.
 
 | Category | Method | Examples |
 |---|---|---|
 | **Smooth** | `is_atom_smooth() → True` | exp, log, power, sin, prod, quad_form |
-| **NS-convex** | `is_atom_nonsmooth_convex() → True` | abs, max, norm1, norm_inf, huber |
-| **NS-concave** | `is_atom_nonsmooth_concave() → True` | min, minimum |
+| **Non-smooth convex** | `is_atom_convex() → True` (and not smooth) | abs, max, norm1, norm_inf, huber |
+| **Non-smooth concave** | `is_atom_concave() → True` (and not smooth) | min, minimum |
 
 ### DNLP Expression-level Rules
 

cvxpy/atoms/atom.py

@@ -192,14 +192,6 @@ def is_atom_smooth(self) -> bool:
         """Is the atom smooth?"""
         return False
 
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return False
-
-    def is_atom_nonsmooth_concave(self) -> bool:
-        """Is the atom nonsmooth and concave?"""
-        return False
-
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?
         """
@@ -278,7 +270,7 @@ def is_linearizable_convex(self) -> bool:
         # Applies DNLP composition rule.
         if self.is_constant():
             return True
-        elif self.is_atom_smooth() or self.is_atom_nonsmooth_convex():
+        elif self.is_atom_smooth() or self.is_atom_convex():
             for idx, arg in enumerate(self.args):
                 if not (arg.is_smooth() or
                         (arg.is_linearizable_convex() and self.is_incr(idx)) or
@@ -287,15 +279,15 @@ def is_linearizable_convex(self) -> bool:
             return True
         else:
             return False
-        
+
     @perf.compute_once
     def is_linearizable_concave(self) -> bool:
         """Is the expression concave after linearizing all smooth subexpressions?
         """
         # Applies DNLP composition rule.
         if self.is_constant():
             return True
-        elif self.is_atom_smooth() or self.is_atom_nonsmooth_concave():
+        elif self.is_atom_smooth() or self.is_atom_concave():
             for idx, arg in enumerate(self.args):
                 if not (arg.is_smooth() or
                         (arg.is_linearizable_concave() and self.is_incr(idx)) or

cvxpy/atoms/elementwise/abs.py

@@ -55,10 +55,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_incr(self, idx) -> bool:
         """Is the composition non-decreasing in argument idx?

cvxpy/atoms/elementwise/huber.py

@@ -70,10 +70,6 @@ def is_atom_convex(self) -> bool:
     def is_atom_concave(self) -> bool:
         """Is the atom concave?"""
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_incr(self, idx) -> bool:
         """Is the composition non-decreasing in argument idx?"""

cvxpy/atoms/elementwise/maximum.py

@@ -66,10 +66,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?

cvxpy/atoms/elementwise/minimum.py

@@ -58,10 +58,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return True
-    
-    def is_atom_nonsmooth_concave(self) -> bool:
-        """Is the atom nonsmooth and concave?"""
-        return True
 
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?

cvxpy/atoms/max.py

@@ -99,10 +99,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?

cvxpy/atoms/min.py

@@ -99,10 +99,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return True
-    
-    def is_atom_nonsmooth_concave(self) -> bool:
-        """Is the atom nonsmooth and concave?"""
-        return True
 
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?

cvxpy/atoms/norm1.py

@@ -55,10 +55,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_incr(self, idx) -> bool:
         """Is the composition non-decreasing in argument idx?

cvxpy/atoms/norm_inf.py

@@ -58,10 +58,6 @@ def is_atom_concave(self) -> bool:
         """Is the atom concave?
         """
         return False
-    
-    def is_atom_nonsmooth_convex(self) -> bool:
-        """Is the atom nonsmooth and convex?"""
-        return True
 
     def is_atom_log_log_convex(self) -> bool:
         """Is the atom log-log convex?