diff --git a/tangostationcontrol/tangostationcontrol/clients/statistics_client.py b/tangostationcontrol/tangostationcontrol/clients/statistics_client.py
index e602b410ab202906f2953ec1a722b74a2ff64734..08d2889d0b61c5bd9c9ce5468e35ac6bf82fdffb 100644
--- a/tangostationcontrol/tangostationcontrol/clients/statistics_client.py
+++ b/tangostationcontrol/tangostationcontrol/clients/statistics_client.py
@@ -99,10 +99,10 @@ class StatisticsClient(AsyncCommClient):
def read_function():
if annotation.get("reshape", False):
# force array into the shape of the attribute
- if attribute.max_dim_y > 1:
- return self.collector.parameters[parameter].reshape(attribute.max_dim_y, attribute.max_dim_x)
+ if attribute.dim_y > 1:
+ return self.collector.parameters[parameter].reshape(attribute.dim_y, attribute.dim_x)
else:
- return self.collector.parameters[parameter].reshape(attribute.max_dim_x)
+ return self.collector.parameters[parameter].reshape(attribute.dim_x)
else:
return self.collector.parameters[parameter]
elif annotation["type"] == "udp":
diff --git a/tangostationcontrol/tangostationcontrol/devices/sdp/statistics_collector.py b/tangostationcontrol/tangostationcontrol/devices/sdp/statistics_collector.py
index 05a76d9b39d0245251c1ddeb2ee67eb9f74870a9..9d4697cf2d64b3e9a03fa931b2c0e21b100322aa 100644
--- a/tangostationcontrol/tangostationcontrol/devices/sdp/statistics_collector.py
+++ b/tangostationcontrol/tangostationcontrol/devices/sdp/statistics_collector.py
@@ -151,7 +151,7 @@ class XSTCollector(StatisticsCollector):
# When the youngest data for each subband was received
"xst_timestamps": numpy.zeros((self.MAX_PARALLEL_SUBBANDS,), dtype=numpy.float64),
"xst_subbands": numpy.zeros((self.MAX_PARALLEL_SUBBANDS,), dtype=numpy.uint16),
- "integration_intervals": numpy.zeros((self.MAX_PARALLEL_SUBBANDS,), dtype=numpy.float32),
+ "xst_integration_intervals": numpy.zeros((self.MAX_PARALLEL_SUBBANDS,), dtype=numpy.float32),
})
return defaults
@@ -234,7 +234,7 @@ class XSTCollector(StatisticsCollector):
self.parameters["xst_timestamps"][subband_slot] = numpy.float64(fields.timestamp().timestamp())
self.parameters["xst_conjugated"][subband_slot, block_index] = conjugated
self.parameters["xst_subbands"][subband_slot] = numpy.uint16(fields.subband_index)
- self.parameters["integration_intervals"][subband_slot] = fields.integration_interval()
+ self.parameters["xst_integration_intervals"][subband_slot] = fields.integration_interval()
def xst_values(self, subband_indices=range(MAX_PARALLEL_SUBBANDS)):
""" xst_blocks, but as a matrix[len(subband_indices)][MAX_INPUTS][MAX_INPUTS] of complex values.
diff --git a/tangostationcontrol/tangostationcontrol/devices/sdp/xst.py b/tangostationcontrol/tangostationcontrol/devices/sdp/xst.py
index 38c9f76562530ff7735c54214b8bef3d023bbc9c..8be9cdb483ef4f21818791009a19e8fbc2b91cb9 100644
--- a/tangostationcontrol/tangostationcontrol/devices/sdp/xst.py
+++ b/tangostationcontrol/tangostationcontrol/devices/sdp/xst.py
@@ -116,15 +116,15 @@ class XST(Statistics):
# number of packets with invalid payloads
nof_payload_errors_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "nof_payload_errors"}, dims=(XSTCollector.MAX_FPGAS,), datatype=numpy.uint64)
# latest XSTs
- xst_blocks_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_blocks", "reshape": True}, dims=(XSTCollector.BLOCK_LENGTH * XSTCollector.BLOCK_LENGTH * XSTCollector.VALUES_PER_COMPLEX, XSTCollector.MAX_BLOCKS), datatype=numpy.int64)
+ xst_blocks_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_blocks", "reshape": True}, dims=(XSTCollector.MAX_BLOCKS * XSTCollector.BLOCK_LENGTH * XSTCollector.BLOCK_LENGTH * XSTCollector.VALUES_PER_COMPLEX, XSTCollector.MAX_PARALLEL_SUBBANDS), datatype=numpy.int64)
# whether the values in the block are conjugated and transposed
- xst_conjugated_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_conjugated", "reshape": True}, dims=(XSTCollector.MAX_BLOCKS,), datatype=numpy.bool_)
+ xst_conjugated_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_conjugated", "reshape": True}, dims=(XSTCollector.MAX_BLOCKS, XSTCollector.MAX_PARALLEL_SUBBANDS), datatype=numpy.bool_)
# reported timestamp for each subband in the latest XSTs
xst_timestamp_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_timestamps"}, dims=(XSTCollector.MAX_PARALLEL_SUBBANDS,), datatype=numpy.uint64)
# which subband the XSTs describe
xst_subbands_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_subbands"}, dims=(XSTCollector.MAX_PARALLEL_SUBBANDS,), datatype=numpy.uint16)
# integration interval for each subband in the latest XSTs
- integration_interval_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "integration_intervals"}, dims=(XSTCollector.MAX_PARALLEL_SUBBANDS,), datatype=numpy.float32)
+ xst_integration_interval_R = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_integration_intervals"}, dims=(XSTCollector.MAX_PARALLEL_SUBBANDS,), datatype=numpy.float32)
# xst_R, but as a matrix of subband x (input x input)
xst_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS * XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_PARALLEL_SUBBANDS, dtype=((numpy.float32,),))
@@ -145,57 +145,57 @@ class XST(Statistics):
return numpy.angle(self.statistics_client.collector.xst_values()).reshape(XSTCollector.MAX_PARALLEL_SUBBANDS, XSTCollector.MAX_INPUTS * XSTCollector.MAX_INPUTS)
# xst_R, but as a matrix of input x input, for each specific subband index
- xst_0_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(0))
- xst_0_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(0))
- xst_0_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(0))
- xst_0_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(0))
-
- xst_1_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(1))
- xst_1_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(1))
- xst_1_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(1))
- xst_1_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(1))
-
- xst_2_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(2))
- xst_2_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(2))
- xst_2_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(2))
- xst_2_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(2))
-
- xst_3_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(3))
- xst_3_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(3))
- xst_3_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(3))
- xst_3_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(3))
-
- xst_4_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(4))
- xst_4_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(4))
- xst_4_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(4))
- xst_4_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(4))
-
- xst_5_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(5))
- xst_5_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(5))
- xst_5_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(5))
- xst_5_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(5))
-
- xst_6_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(6))
- xst_6_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(6))
- xst_6_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(6))
- xst_6_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(6))
-
- xst_7_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real(7))
- xst_7_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag(7))
- xst_7_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power(7))
- xst_7_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase(7))
+ xst_0_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(0))
+ xst_0_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(0))
+ xst_0_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(0))
+ xst_0_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(0))
+
+ xst_1_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(1))
+ xst_1_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(1))
+ xst_1_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(1))
+ xst_1_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(1))
+
+ xst_2_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(2))
+ xst_2_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(2))
+ xst_2_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(2))
+ xst_2_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(2))
+
+ xst_3_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(3))
+ xst_3_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(3))
+ xst_3_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(3))
+ xst_3_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(3))
+
+ xst_4_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(4))
+ xst_4_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(4))
+ xst_4_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(4))
+ xst_4_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(4))
+
+ xst_5_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(5))
+ xst_5_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(5))
+ xst_5_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(5))
+ xst_5_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(5))
+
+ xst_6_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(6))
+ xst_6_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(6))
+ xst_6_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(6))
+ xst_6_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(6))
+
+ xst_7_real_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_real_R(7))
+ xst_7_imag_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_imag_R(7))
+ xst_7_power_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_power_R(7))
+ xst_7_phase_R = attribute(max_dim_x=XSTCollector.MAX_INPUTS, max_dim_y=XSTCollector.MAX_INPUTS, dtype=((numpy.float32,),), fget = lambda self: self.read_xst_N_phase_R(7))
def read_xst_N_real_R(self, subband_idx):
- return numpy.real(self.statistics_client.collector.xst_values(subband_idx)[0])
+ return numpy.real(self.statistics_client.collector.xst_values([subband_idx])[0])
def read_xst_N_imag_R(self, subband_idx):
- return numpy.imag(self.statistics_client.collector.xst_values(subband_idx)[0])
+ return numpy.imag(self.statistics_client.collector.xst_values([subband_idx])[0])
def read_xst_N_power_R(self, subband_idx):
- return numpy.abs(self.statistics_client.collector.xst_values(subband_idx)[0])
+ return numpy.abs(self.statistics_client.collector.xst_values([subband_idx])[0])
def read_xst_N_phase_R(self, subband_idx):
- return numpy.angle(self.statistics_client.collector.xst_values(subband_idx)[0])
+ return numpy.angle(self.statistics_client.collector.xst_values([subband_idx])[0])
# ----------
# Summarising Attributes