fix: Use var.typeStr metadata for type coercion in _caput

python/pysmurf/client/command/smurf_command.py

@@ -103,13 +103,7 @@ def _caput(self, pvname, val, index=-1, cast_type=True, write_log=False, log_lev
                 # setDisp handles enum values
                 var.setDisp(val, index=index)
             elif cast_type:
-                # rogue is strict about variable types for arrays
-                var_val = var.value()  # like get(read=False)
-                if isinstance(var_val, np.ndarray):
-                    var_type = var_val.dtype.type
-                else:
-                    var_type = type(var_val)
-                val = var_type(val)
+                val = tools.coerce_value_for_var(var, val)
                 var.set(val, check=wait_done, index=index)
             else:
                 var.set(val, check=wait_done, index=index)
@@ -1173,7 +1167,7 @@ def set_eta_scan_amplitude(self, band, val, **kwargs):
         """
         self._caput(
             self._cryo_root(band) + self._eta_scan_amplitude_reg,
-            np.uint(val), **kwargs)
+            np.uint64(val), **kwargs)
 
     def get_eta_scan_amplitude(self, band, **kwargs):
         """
@@ -1424,7 +1418,7 @@ def set_amplitude_scale_array(self, band, val, **kwargs):
         """
         self._caput(
             self._cryo_root(band) + self._amplitude_scale_array_reg,
-            np.array(val).astype(np.uint), **kwargs)
+            np.array(val).astype(np.uint64), **kwargs)
 
     def get_amplitude_scale_array(self, band, **kwargs):
         """
@@ -1461,7 +1455,7 @@ def set_amplitude_scale_array_currentchans(self, band, tone_power,
 
         old_amp = self.get_amplitude_scale_array(band, **kwargs)
         n_channels=self.get_number_channels(band)
-        new_amp = np.zeros((n_channels,),dtype=np.uint)
+        new_amp = np.zeros((n_channels,), dtype=np.uint64)
         new_amp[np.where(old_amp!=0)] = tone_power
         self.set_amplitude_scale_array(self, new_amp, **kwargs)
 
@@ -2637,7 +2631,7 @@ def set_amplitude_scale_channel(self, band, channel, val,
         self._caput(
             self._channel_root(band, channel) +
             self._amplitude_scale_channel_reg,
-            np.uint(val), **kwargs)
+            np.uint64(val), **kwargs)
 
     def get_amplitude_scale_channel(self, band, channel, **kwargs):
         """

python/pysmurf/client/util/tools.py

@@ -16,6 +16,67 @@
 import numpy as np
 from scipy.optimize import curve_fit
 
+
+TYPEMAP = {
+    'UInt8':   np.uint8,
+    'UInt16':  np.uint16,
+    'UInt32':  np.uint32,
+    'UInt64':  np.uint64,
+    'Int8':    np.int8,
+    'Int16':   np.int16,
+    'Int32':   np.int32,
+    'Int64':   np.int64,
+    'Float32': np.float32,
+    'Double':  np.float64,
+    'Bool':    bool,
+    'String':  str,
+}
+
+
+def coerce_value_for_var(var, val):
+    """Coerce val to the type expected by a Rogue 6 variable.
+
+    Uses var.typeStr metadata to determine the expected type without
+    performing a register read.  Handles scalar registers, array registers
+    identified by the '[np]' typeStr suffix, and raises TypeError for any
+    unrecognized typeStr.
+
+    Parameters
+    ----------
+    var : pyrogue.Variable
+        The rogue variable node that will receive the value.
+    val : any
+        The value to coerce.
+
+    Returns
+    -------
+    any
+        val cast to the type expected by var.  For scalar registers, returns
+        TYPEMAP[var.typeStr](val).  For array registers (typeStr ending in
+        '[np]'), returns np.asarray(val, dtype=element_dtype), which is a
+        zero-copy passthrough when the dtype already matches (ARRY-02).
+
+    Raises
+    ------
+    TypeError
+        If var.typeStr is not recognized.  The exception message includes
+        both the variable path (var.path) and the unrecognized typeStr.
+    """
+    ts = var.typeStr
+    if ts.endswith('[np]'):
+        base = ts[:-4]
+        if base not in TYPEMAP:
+            raise TypeError(
+                f"Unrecognized typeStr '{ts}' for variable '{var.path}'"
+            )
+        return np.asarray(val, dtype=TYPEMAP[base])
+    if ts not in TYPEMAP:
+        raise TypeError(
+            f"Unrecognized typeStr '{ts}' for variable '{var.path}'"
+        )
+    return TYPEMAP[ts](val)
+
+
 def skewed_lorentzian(x, bkg, bkg_slp, skw, mintrans, res_f, Q):
     """ Skewed Lorentzian model.