mirror of https://github.com/m-labs/artiq.git
worker: trust that h5py maps all types as we want
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@ -157,56 +157,6 @@ def get_hdf5_output(start_time, rid, name):
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return h5py.File(os.path.join(dirname, filename), "w")
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_type_to_hdf5 = {
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int: h5py.h5t.STD_I64BE,
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float: h5py.h5t.IEEE_F64BE,
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np.int8: h5py.h5t.STD_I8BE,
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np.int16: h5py.h5t.STD_I16BE,
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np.int32: h5py.h5t.STD_I32BE,
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np.int64: h5py.h5t.STD_I64BE,
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np.uint8: h5py.h5t.STD_U8BE,
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np.uint16: h5py.h5t.STD_U16BE,
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np.uint32: h5py.h5t.STD_U32BE,
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np.uint64: h5py.h5t.STD_U64BE,
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np.float16: h5py.h5t.IEEE_F16BE,
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np.float32: h5py.h5t.IEEE_F32BE,
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np.float64: h5py.h5t.IEEE_F64BE
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}
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def result_dict_to_hdf5(f, rd):
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for name, data in rd.items():
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flag = None
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# beware: isinstance(True/False, int) == True
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if isinstance(data, bool):
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data = np.int8(data)
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flag = "py_bool"
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elif isinstance(data, int):
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data = np.int64(data)
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flag = "py_int"
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if isinstance(data, np.ndarray):
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dataset = f.create_dataset(name, data=data)
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else:
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ty = type(data)
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if ty is str:
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ty_h5 = "S{}".format(len(data))
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data = data.encode()
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else:
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try:
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ty_h5 = _type_to_hdf5[ty]
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except KeyError:
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raise TypeError("Type {} is not supported for HDF5 output"
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.format(ty)) from None
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dataset = f.create_dataset(name, (), ty_h5)
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dataset[()] = data
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if flag is not None:
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dataset.attrs[flag] = np.int8(1)
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class DatasetManager:
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def __init__(self, ddb):
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self.broadcast = Notifier(dict())
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@ -241,4 +191,5 @@ class DatasetManager:
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def write_hdf5(self, f):
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g = f.create_group("datasets")
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result_dict_to_hdf5(g, self.local)
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for k, v in self.local.items():
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g[k] = v
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@ -3,8 +3,6 @@ import unittest
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import h5py
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import numpy as np
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from artiq.master.worker_db import result_dict_to_hdf5
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class TypesCase(unittest.TestCase):
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def test_types(self):
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@ -25,4 +23,5 @@ class TypesCase(unittest.TestCase):
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d["f"+str(size)] = getattr(np, "float" + str(size))(42)
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with h5py.File("h5types.h5", "w", "core", backing_store=False) as f:
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result_dict_to_hdf5(f, d)
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for k, v in d.items():
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f[k] = v
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