From 4ccf4eb9a05a390678637de311eec3e78a549ef6 Mon Sep 17 00:00:00 2001
From: Robin Scheibler <robin.scheibler@linecorp.com>
Date: Fri, 17 Apr 2020 18:06:31 +0900
Subject: [PATCH] Analysis script, environment

---
 analysis.py     | 29 +++++++++++++++++++++++++++++
 environment.yml | 10 ++++++++++
 process.py      |  4 ++--
 3 files changed, 41 insertions(+), 2 deletions(-)
 create mode 100644 analysis.py
 create mode 100644 environment.yml

diff --git a/analysis.py b/analysis.py
new file mode 100644
index 0000000..041c32a
--- /dev/null
+++ b/analysis.py
@@ -0,0 +1,29 @@
+import json
+import pandas as pd
+import argparse
+from pathlib import Path
+import numpy as np
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser(description="Sparse minimum distortion simulation results analaysis")
+    parser.add_argument("results_dir", type=Path, help="Location of simulation results")
+    args = parser.parse_args()
+    
+
+    with open(args.results_dir / "data.json") as f:
+        data = json.load(f)
+
+    with open(args.results_dir / "parameters.json") as f:
+        params = json.load(f)
+
+    # concatenate all the results
+    results = []
+    for r in data:
+        results += r
+
+    for r in results:
+        for metric in ["sdr", "sir"]:
+            r[metric] = np.mean(r[metric])
+
+    df = pd.DataFrame(results)
diff --git a/environment.yml b/environment.yml
new file mode 100644
index 0000000..4c3e2ee
--- /dev/null
+++ b/environment.yml
@@ -0,0 +1,10 @@
+name: sparse_projection_back
+dependencies:
+  - numpy
+  - scipy
+  - pandas
+  - matplotlib
+  - pip
+  - seaborn
+  - pip:
+    - repsimtools
diff --git a/process.py b/process.py
index f22424d..be4d6b9 100644
--- a/process.py
+++ b/process.py
@@ -111,8 +111,8 @@ def process(args, config):
     # minimum distortion
     lo, hi, step = config["minimum_distortion"]["p_list"]
     kwargs = config["minimum_distortion"]["kwargs"]
-    for p in np.arange(lo, hi, step):
-        for q in np.arange(p, hi, step):
+    for p in np.arange(lo, hi + step, step):
+        for q in np.arange(p, hi + step, step):
             t["p"], t["q"], t["proj_algo"] = (
                 f"{p:.1f}",
                 f"{q:.1f}",