first idea for polarization parallel phases

phases/dataconverter.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python
+
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument("finput", help="name of excel file to load")
+parser.add_argument("foutput", help="name of json file to write")
+clargs = parser.parse_args()
+
+
+from collections import defaultdict
+import pandas as pd
+from slic.utils import json_save
+
+
+def load(fn, nparams=6, skip_cols=3):
+    engine = "xlrd" if fn.endswith(".xls") else "openpyxl"
+    df = pd.read_excel(fn, engine=engine)
+
+    header = df.columns
+    data = df.values
+
+    nrows, ncols = data.shape
+    assert nrows % nparams == 0
+    nunds = nrows // nparams
+
+    res = defaultdict(dict)
+    for i in range(nunds):
+        start = i * nparams
+        stop = start + nparams
+
+        und_name = data[start, 1]
+        idata = data[start:stop, 1:]
+
+        for j in range(skip_cols, ncols):
+            param_name = header[j]
+            jdata = idata[:, j-1].astype(float)
+            res[und_name][param_name] = list(jdata)
+
+    return dict(**res)
+
+
+def print_overview(data):
+    unds = data.keys()
+    unds = sorted(unds)
+
+    params = data[unds[0]].keys()
+    params = sorted(params)
+
+    nunds = len(unds)
+    nparams = len(params)
+
+    print(f"read {nparams} parameters for {nunds} undulators")
+    print("\nUndulators:", ", ".join(unds))
+    print("\nParameters:", ", ".join(params))
+
+
+
+
+
+if __name__ == "__main__":
+    data = load(clargs.finput)
+    print_overview(data)
+    json_save(data, clargs.foutput)
+
+
+