1 files changed, 67 insertions, 0 deletions
diff --git a/many_over.cpp b/many_over.cpp
new file mode 100644
index 0000000..5785ad3
--- /dev/null
+++ b/many_over.cpp
@@ -0,0 +1,67 @@
+#include <getopt.h>
+#include <iomanip>
+
+#include "fits.hpp"
+
+int main(int argc, char* argv[]) {
+  unsigned N = 80;
+
+  int opt;
+
+  while ((opt = getopt(argc, argv, "M:s:S:B:i:N:")) != -1) {
+    switch (opt) {
+    case 'N':
+      N = (unsigned)atof(optarg);
+      break;
+    default:
+      exit(1);
+    }
+  }
+
+  std::string firstline;
+  std::getline(std::cin, firstline);
+  std::stringstream ss;
+  ss << firstline;
+
+  Data data;
+
+  while (!ss.eof()) {
+    Real x, y;
+    ss >> x;
+    ss >> y;
+    data.push_back({x,y});
+  }
+
+  Rng r;
+
+  std::cout << std::setprecision(15);
+
+  for (unsigned i = 0; i < 5; i++) {
+    Vector a₀ = Vector::Zero(N);
+    for (Real& aa : a₀) {
+      aa = r.variate<Real, std::normal_distribution>(0, 2e-2);
+    }
+
+    Vector a = stochasticGradientDescent(data, a₀, 10, 1e12);
+
+    for (Real ai : a) {
+      std::cout << ai << " ";
+    }
+    std::cout << std::endl;
+  }
+  for (unsigned i = 0; i < 5; i++) {
+    Vector a₀ = Vector::Zero(N);
+    for (Real& aa : a₀) {
+      aa = r.variate<Real, std::normal_distribution>(0, 5);
+    }
+
+    Vector a = stochasticGradientDescent(data, a₀, 10, 1e12);
+
+    for (Real ai : a) {
+      std::cout << ai << " ";
+    }
+    std::cout << std::endl;
+  }
+
+  return 0;
+}