Added clang-tidy; Update readme;

.clang-format

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.github/workflows/build_and_test.yml

@@ -12,7 +12,7 @@ jobs:
 
     steps:
     - name: clone
-      uses: actions/checkout@v4 # Action to check out your repository
+      uses: actions/checkout@v4
 
     - name: dependencies
       run: |

CMakeLists.txt

@@ -7,7 +7,7 @@ project(cloth_sim_tutorial LANGUAGES CXX)
 option(CLOTH_DEBUG "run with debug options" OFF)
 option(CLOTH_TESTING_ONLY "only compile unit tests" OFF)
 
-set(CMAKE_CXX_STANDARD 14)
+set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 list(PREPEND CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake)
 add_definitions(-DCLOTH_ROOT_DIR="${CMAKE_CURRENT_SOURCE_DIR}")

README.md

@@ -15,7 +15,7 @@ This results in a block-sparse linear system for which the velocity deltas are s
 
 The B&W method is conceptually straight forward. However, there are numerous gotchas not apparent in the original references.
 In particular, working out the Jacobians of some models can be nontrivial. Even when correct, the derivatives can still produce hard-to-debug instabilities.
-The [dynamic deformables course notes](https://doi.org/10.1145/3388769.3407490) describes this well, and I highly recommend reviewing the later chapters on cloth simulation for a thorough review of the topic.
+The [dynamic deformables course notes](https://doi.org/10.1145/3388769.3407490) describes this well, and I highly recommend reviewing the later chapters on cloth simulation.
 Nonetheless, implicit time integration remains a valuable and sometimes necessary tool for modern graphics applications.
 
 Recently, optimization-based methods have grown in popularity. This approach formulates the Eqs. of motion as an [iteratively minimized objective function](https://en.wikipedia.org/wiki/Optimization_problem).
@@ -26,6 +26,8 @@ Below we describe a simple implicit solver for mass-spring systems using gradien
 This is meant solely as a tutorial to optimization-based time stepping, and not for practical applications.
 For that, you'll want to consider higher-order optimization algorithms or [local-global type solvers](https://github.com/alecjacobson/computer-graphics-mass-spring-systems).
 
+<p align="center"><img src="data/sphere.png" align=middle/></p>
+
 ## Implementation
 
 The objective we aim to minimize is the sum of internal elastic energy potentials plus a quadratic penalty of linear momentum:
@@ -34,7 +36,7 @@ $`\bar{x} = x + hv + h^2 M^{-1} f_{ext}`$,
 
 $`g(x) = \frac{1}{2h^2}\|M^{1/2}(x-\bar{x})\|^2 + \sum E(x)`$,
 
-for vertex locations $x$, time step (sec) $h$, diagonal mass matrix $M$, velocities $v$, and external forces (gravity, wind, etc...)
+for vertex locations $x$, time step (seconds) $h$, diagonal mass matrix $M$, velocities $v$, and external forces (gravity, wind, etc...)
 $`f_{ext}`$. The term $`\bar{x}`$ is the *explicit predictor*
 that is computed at the beginning of the time step. Computing a frame of animation amounts to iteratively minimizing the above objective until some convergence criteria is met
 (e.g., the norm of the gradient is below some threshold).
@@ -91,4 +93,5 @@ There are many ways to improve the solver illustrated above:
 - Collision against triangle meshes with a [signed distance field](https://github.com/InteractiveComputerGraphics/TriangleMeshDistance)
 - Better energy models with triangular elements ([Dynamic Deformables appendix D](https://doi.org/10.1145/3388769.3407490))
 - Preconditioning or accelerated versions of gradient descent
+- Non-conservative forces like friction
 - Optimizers with better convergence like [L-BFGS](https://en.wikipedia.org/wiki/Limited-memory_BFGS) or [projected Newton](https://doi.org/10.1145/1073368.1073394)

src/ClothAssert.hpp

@@ -4,29 +4,28 @@
 #ifndef CLOTHASSERT_HPP
 #define CLOTHASSERT_HPP 1
 
-#include <cstdlib> 
-#include <string>
+#include <cstdlib>
 #include <stdexcept>
+#include <string>
 
-namespace cloth
-{
+namespace cloth {
 
-static inline void AssertHandler(bool cond, const std::string& file, const int& line)
+static inline void
+AssertHandler(bool cond, const std::string& file, const int& line)
 {
-	if (!cond)
-	{
-		std::string err_msg = "Assertion failed in "+file+" line "+std::to_string(line);
-		throw std::runtime_error(err_msg.c_str());
-	}
+    if (!cond) {
+        std::string err_msg = "Assertion failed in " + file + " line " + std::to_string(line);
+        throw std::runtime_error(err_msg.c_str());
+    }
 }
 
-static inline void AssertHandlerMsg(bool cond, const std::string& file, const int& line, const std::string &msg)
+static inline void
+AssertHandlerMsg(bool cond, const std::string& file, const int& line, const std::string& msg)
 {
-	if (!cond)
-	{
-		std::string err_msg = "Assertion failed in "+file+" line "+std::to_string(line)+": "+msg;
-		throw std::runtime_error(err_msg.c_str());
-	}
+    if (!cond) {
+        std::string err_msg = "Assertion failed in " + file + " line " + std::to_string(line) + ": " + msg;
+        throw std::runtime_error(err_msg.c_str());
+    }
 }
 
 }
@@ -37,12 +36,9 @@ static inline void AssertHandlerMsg(bool cond, const std::string& file, const in
 
 #define ClothAssert_withmsg(cond, msg) AssertHandlerMsg(cond, std::string(__FILE__), __LINE__, msg)
 #define ClothAssert_nomsg(cond) AssertHandler(cond, std::string(__FILE__), __LINE__)
-#define ClothAssert_stripargs(xx,cond,msg,FUNC, ...) FUNC
+#define ClothAssert_stripargs(xx, cond, msg, FUNC, ...) FUNC
 
-#define ClothAssert(...) \
-	ClothAssert_stripargs(,##__VA_ARGS__,\
-	ClothAssert_withmsg(__VA_ARGS__),\
-	ClothAssert_nomsg(__VA_ARGS__),\
-	)
+#define ClothAssert(...)                                                                                               \
+    ClothAssert_stripargs(, ##__VA_ARGS__, ClothAssert_withmsg(__VA_ARGS__), ClothAssert_nomsg(__VA_ARGS__), )
 
 #endif