Merge pull request 'Temperature logger' (#39) from temperature-logger into main

Reviewed-on: #39

.gitignore

@@ -9,3 +9,5 @@ __pycache__
 debian/files
 .pybuild
 .junie
+debian/debhelper-build-stamp
+debian/.debhelper

src/damaris/data/DataPool.py

@@ -365,7 +365,13 @@ class DataPool(collections.abc.MutableMapping):
                         obj = read_from_hdf(node)
                         if obj is not None:
                             self[full_path] = obj
-                    
+
+                    elif damaris_type == "TemperatureResult":
+                        from damaris.data.Temperature import read_from_hdf
+                        obj = read_from_hdf(node)
+                        if obj is not None:
+                            self[full_path] = obj
+
                     # Skip further processing of this group since we handled it
                     continue
                 

src/damaris/data/Temperature.py

@@ -4,6 +4,7 @@ from .Resultable import Resultable
 from .Drawable import Drawable
 import numpy
 import threading
+import tables
 
 #############################################################################
 #                                                                           #
@@ -141,6 +142,100 @@ class TemperatureResult(Resultable, Drawable):
             return ydata[mask].min()
         return 0
     
+    def write_to_hdf(self, hdffile, where, name, title, complib=None, complevel=None):
+        """
+        Write the temperature result to an HDF5 group.
+
+        Stores x (timestamps), y (temperature readings), and setpoint arrays
+        as an HDF5 table, with metadata saved as group attributes.
+        """
+        h5_table_format = {
+            "x": tables.Float64Col(),
+            "y": tables.Float64Col(),
+            "setpoint": tables.Float64Col(),
+        }
+        filter = None
+        if complib is not None:
+            if complevel is None:
+                complevel = 9
+            filter = tables.Filters(complevel=complevel, complib=complib, shuffle=1)
+
+        with self.__listener_lock:
+            xdata = numpy.array(self.x, dtype=float) if self.x else numpy.array([], dtype=float)
+            ydata = numpy.array(self.y, dtype=float) if self.y else numpy.array([], dtype=float)
+            spdata = numpy.array(self.setpoint, dtype=float) if self.setpoint else numpy.array([], dtype=float)
+
+        # Use the length of the longest array; shorter ones are padded with 0
+        n = max(len(xdata), len(ydata), 1)
+        if len(xdata) < n:
+            xdata = numpy.pad(xdata, (0, n - len(xdata)), constant_values=0.0)
+        if len(ydata) < n:
+            ydata = numpy.pad(ydata, (0, n - len(ydata)), constant_values=0.0)
+        if len(spdata) < n:
+            spdata = numpy.pad(spdata, (0, n - len(spdata)), constant_values=0.0)
+
+        temp_table = hdffile.create_table(
+            where=where, name=name,
+            description=h5_table_format,
+            title=title,
+            filters=filter,
+            expectedrows=n,
+        )
+        temp_table.flavor = "numpy"
+        temp_table.attrs.damaris_type = "TemperatureResult"
+        temp_table.attrs.xlabel = self.xlabel
+        temp_table.attrs.ylabel = self.ylabel
+
+        if hasattr(self, "job_id") and self.job_id is not None:
+            temp_table.attrs.job_id = self.job_id
+        if hasattr(self, "job_date") and self.job_date is not None:
+            temp_table.attrs.time = "%04d%02d%02d %02d:%02d:%02d.%03d" % (
+                self.job_date.year,
+                self.job_date.month,
+                self.job_date.day,
+                self.job_date.hour,
+                self.job_date.minute,
+                self.job_date.second,
+                self.job_date.microsecond // 1000,
+            )
+        if hasattr(self, "description") and self.description is not None:
+            for (key, value) in self.description.items():
+                temp_table.attrs.__setattr__("description_" + key, str(value))
+
+        row = temp_table.row
+        for i in range(n):
+            row["x"] = xdata[i]
+            row["y"] = ydata[i]
+            row["setpoint"] = spdata[i]
+            row.append()
+
+        temp_table.flush()
+
     def __repr__(self):
         """String representation of the temperature result."""
         return f"TemperatureResult(points={len(self)}, job_id={self.job_id})"
+
+
+def read_from_hdf(hdf_node):
+    """
+    Read a TemperatureResult object from an HDF5 table node.
+    Returns None if the node is not suitable.
+    """
+    if not isinstance(hdf_node, tables.Table):
+        return None
+
+    if hdf_node._v_attrs.damaris_type != "TemperatureResult":
+        return None
+
+    tr = TemperatureResult()
+    tr.xlabel = getattr(hdf_node._v_attrs, "xlabel", "Time (s)")
+    tr.ylabel = getattr(hdf_node._v_attrs, "ylabel", "Temperature (C)")
+
+    for r in hdf_node.iterrows():
+        tr.x.append(r["x"])
+        tr.y.append(r["y"])
+        sp = r["setpoint"]
+        if sp != 0.0 or len(tr.setpoint) > 0:
+            tr.setpoint.append(sp)
+
+    return tr