From cbd3aa0c7cc586ef00ed6d4522b949f095a54ab5 Mon Sep 17 00:00:00 2001
From: CPD <CPD@TUZEWSI-2LN203M.ads.mwn.de>
Date: Tue, 4 Feb 2025 16:55:38 +0100
Subject: [PATCH] save csv

---
 cpdctrl/utility/data.py | 46 +++++++++++++++++++++++++++++++++--------
 1 file changed, 37 insertions(+), 9 deletions(-)

diff --git a/cpdctrl/utility/data.py b/cpdctrl/utility/data.py
index e0c49c9..814386b 100644
--- a/cpdctrl/utility/data.py
+++ b/cpdctrl/utility/data.py
@@ -10,16 +10,17 @@ FLUSH_TYPE = "pickle-ndarray"
 METADATA_FILENAME = "_measurement_metadata.pkl"
 
 class DataCollector:
+    columns = ["idx", "t [s]", "V [V]", "LED [%]"]
     def __init__(self, 
                  data_path: str,
                  data_name: str="CPData", 
-                 header: dict[str, str]={},
+                 metadata: dict[str, str]={},
                  dirname: str|None=None,
                  dir_exists_is_ok=False,
                  ):
         self.data = []
         self.name = data_name
-        self.header = header
+        self.metadata = metadata
         self.path = os.path.abspath(os.path.expanduser(data_path))
         if dirname is None:
             self.dirname = sanitize_filename(datetime.datetime.now(datetime.UTC).strftime("%Y-%m-%d_%H-%M") + "_" + self.name)
@@ -33,14 +34,22 @@ class DataCollector:
         else:
             os.makedirs(self.dirpath)
         self.flushed = False
+        
     
     def _get_filename(self):
        return sanitize_filename(get_next_filename(self.name, self.dirpath, digits=5))
 
-    def _write_metadata(self):
+    def write_metadata(self):
+        f"""
+        Write the metadata to the disk as '{METADATA_FILENAME}'
+
+        Returns
+        -------
+        None.
+        """
         filepath = os.path.join(self.dirpath, METADATA_FILENAME)
         with open(filepath, "wb") as file:
-            pickle.dump(self.header, file)
+            pickle.dump(self.metadata, file)
 
     def flush(self, verbose:bool=False):
         """
@@ -66,7 +75,7 @@ class DataCollector:
             filename = self._get_filename() + ".csv"
             filepath = os.path.join(self.dirpath, filename)
             if verbose: print(f"Flushing data to {filepath}")
-            self.to_dataframe().to_csv(filepath, sep=",", index=False, header=True)
+            self.to_dataframe().to_csv(filepath, sep=",", index=False, metadata=True)
         elif FLUSH_TYPE == "pickle-ndarray":
             filename = self._get_filename() + ".ndarray.pkl"
             filepath = os.path.join(self.dirpath, filename)
@@ -85,15 +94,34 @@ class DataCollector:
         self.data.append((i, t, v, l))
     
     def to_dataframe(self):
-        df = pd.DataFrame(self.data, columns=["idx", "t [s]", "V [V]", "LED [%]"])
-        df.meta = str(self.header)
+        df = pd.DataFrame(self.data, columns=DataCollector.columns)
+        df.meta = str(self.metadata)
         return df
     
-    def save_csv(self):
-        self.to_dataframe().to_csv(os.path.join(self.path, self.name + ".csv"), index=False, header=True)
+    def to_csv(self, sep=","):
+        # self.to_dataframe().to_csv(os.path.join(self.path, self.name + ".csv"), index=False, metadata=True)
+        data, metadata = self.get_data()
+        return DataCollector.get_csv(data, self.metadata, sep=sep)
     
+    def save_csv(self, sep=",", verbose=False):
+        filepath = os.path.join(self.path, self.name + ".csv")
+        if verbose: print(f"Writing data to {filepath}")
+        with open(filepath, "w") as file:
+            file.write(self.to_csv(sep=sep))
+        
     def get_data(self):
         return DataCollector.load_data(self.dirpath)
+    
+    @staticmethod 
+    def get_csv(data, metadata, sep=","):
+        csv = ""
+        for k, v in metadata.items():
+            csv += f"# {k}: {v}\n"
+        csv += "".join(f"{colname}{sep}" for colname in DataCollector.columns).strip(sep) + "\n"
+        for i in range(data.shape[0]):
+            csv += f"{i}{sep}{data[i,1]}{sep}{data[i,2]}{sep}{data[i,3]}\n"
+        return csv.strip("\n")
+
     @staticmethod
     def load_data(dirpath:str, verbose:bool=False) -> np.ndarray:
         """