Add load from csv, rename load from dir

cpdctrl/cpdctrl_interactive.py

@@ -190,7 +190,7 @@ def data_load(dirname:str) -> tuple[np.ndarray, dict]:
         dirpath = dirname
     else:
         dirpath = path.join(settings["datadir"], dirname)
-    data, md = DataCollector.load_data(dirpath, verbose=True)
+    data, md = DataCollector.load_data_from_dir(dirpath, verbose=True)
     
 # SETTINGS
 def set(setting, value):

cpdctrl/utility/data.py

@@ -130,7 +130,7 @@ class DataCollector:
         
     def get_data(self) -> tuple[np.ndarray, dict]:
         if self.fulldata is None:
-            return DataCollector.load_data(self.dirpath)
+            return DataCollector.load_data_from_dir(self.dirpath)
         else:
             return self.fulldata, self.metadata
     
@@ -145,7 +145,54 @@ class DataCollector:
         return csv.strip("\n")
 
     @staticmethod
-    def load_data(dirpath:str, verbose:bool=False) -> tuple[np.ndarray, dict]:
+    def load_data_from_csv(filepath:str) -> tuple[np.ndarray, dict]:
+        """
+        Loads data from a single csv file.
+        Lines with this format are interpreted as metadata:
+            # key: value
+        Lines with this format are interpreted as data:
+            index, timestamp [s], CPD [V], LED [%]
+        Parameters
+        ----------
+        filepath
+           Path to the csv file.
+
+        Returns
+        -------
+        data
+            2D numpy array with shape (n, 4) where n is the number of data points.
+        metadata
+            Dictionary with metadata.
+        """
+        metadata = {}
+        data = np.empty((0, 4))
+        with open(filepath, "r") as f:
+            for j, line in enumerate(f):
+                if line.startswith("#"):
+                    colon =  line.find(":")
+                    if colon == -1:  # normal comment
+                        continue
+                    key = line[1:colon].strip()
+                    value = line[colon+1:].strip()
+                    metadata[key] = value
+                    continue
+                if line.startswith("idx"):   # header line
+                    continue
+                vals = line.split(",")
+                if len(vals) != 4:
+                    raise ValueError(f"Line {j+1}: Line must have 4 values, but has {len(vals)}: '{line}'")
+                try:
+                    i = int(vals[0])
+                    t = float(vals[1])
+                    cpd = float(vals[2])
+                    led = float(vals[3])
+                except ValueError:
+                    raise ValueError(f"Line {j+1}: Failed to convert values to numbers: '{line}'")
+                data = np.append(data, [[i, t, cpd, led]], axis=0)
+        return data, metadata
+
+    @staticmethod
+    def load_data_from_dir(dirpath:str, verbose:bool=False) -> tuple[np.ndarray, dict]:
         """
         Combines all data files from a directory into a numpy array
 
@@ -219,7 +266,7 @@ def plot_cpd_data(data: str or pd.DataFrame or np.ndarray, t: str="seconds", tit
         Matplotlib figure object.
     """
     if type(data) == str:
-        _data, _ = DataCollector.load_data(data)
+        _data, _ = DataCollector.load_data_from_dir(data)
     else:
         _data = data
     fig, ax = plt.subplots()