adding figure

3 files changed, 30 insertions, 2 deletions

diff --git a/paper/sections/experiments.tex b/paper/sections/experiments.tex
index f4acc06..5d1ae45 100644
--- a/paper/sections/experiments.tex
+++ b/paper/sections/experiments.tex
@@ -1,3 +1,9 @@
+\begin{figure}
+\includegraphics[scale=.4]{figures/first_try.pdf}
+\caption{Watts-Strogatz Model. 300 nodes, 20000 edges.}
+\end{figure}
+
+
 \begin{itemize}
 \item Compare edge recovery to First Edge and Greedy as number of cascades grows on different types of graphs...
 \item Plot upper-bound of parameters in graph as number of cascades grows
diff --git a/src/convex_optimization.py b/src/convex_optimization.py
index 913fcb4..ed99e6b 100644
--- a/src/convex_optimization.py
+++ b/src/convex_optimization.py
@@ -80,7 +80,7 @@ def type_lasso(lbda):
 
     return f_x, f_xz
 
-@timeout.timeout(30)
+@timeout.timeout(70)
 def diff_and_opt(M_val, w_val, f_x, f_xz):
 
     if M_val.dtype == bool:
diff --git a/src/make_plots.py b/src/make_plots.py
index cb78034..d28d07e 100644
--- a/src/make_plots.py
+++ b/src/make_plots.py
@@ -44,6 +44,28 @@ def watts_strogatz(n_cascades, lbda, passed_function):
     algorithms.correctness_measure(G, G_hat, print_values=True)
 
 
+def plot_graph(figure_name):
+    """
+    plot information in a pretty way
+    """
+    plt.clf()
+    x = [100, 500, 1000, 2000, 5000]
+    greedy = [.15, .4, .63, .82, .92]
+    lasso = [.30, .46, .65, 0, 0]
+    max_likel = [.29, .67, .8, .87, .9]
+    sparse_recov = [.32, .7, .82, .89, 0]
+    plt.axis((0, 5000, 0, 1))
+    plt.xlabel("Number of Cascades")
+    plt.ylabel("F1 score")
+    plt.grid(color="lightgrey")
+    plt.plot(x, greedy, 'ko-', color="lightseagreen", label='Greedy')
+    plt.plot(x, lasso, 'ko-', color="orange", label="Lasso")
+    plt.plot(x, max_likel, 'ko-', color="coral", label="MLE")
+    plt.plot(x, sparse_recov, 'ko-', color="k", label="Sparse MLE")
+    plt.legend(loc="lower right")
+    plt.savefig("../paper/figures/"+figure_name)
+
+
 if __name__=="__main__":
-    watts_strogatz(n_cascades=2000, lbda=.002, passed_function=
+    watts_strogatz(n_cascades=5000, lbda=.002, passed_function=
         convex_optimization.sparse_recovery)
\ No newline at end of file