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# Example to show how nested types can be dealed with PyTables
# F. Alted 2005/05/27
import random
import tables as tb
fileout = "nested1.h5"
# An example of enumerated structure
colors = tb.Enum(["red", "green", "blue"])
def read(file):
fileh = tb.open_file(file, "r")
print("table (short)-->", fileh.root.table)
print("table (long)-->", repr(fileh.root.table))
print("table (contents)-->", repr(fileh.root.table[:]))
fileh.close()
def write(file, desc, indexed):
fileh = tb.open_file(file, "w")
table = fileh.create_table(fileh.root, "table", desc)
for colname in indexed:
table.colinstances[colname].create_index()
row = table.row
for i in range(10):
row["x"] = i
row["y"] = 10.2 - i
row["z"] = i
row["color"] = colors[random.choice(["red", "green", "blue"])]
row["info/name"] = "name%s" % i
row["info/info2/info3/z4"] = i
# All the rest will be filled with defaults
row.append()
fileh.close()
# The sample nested class description
class Info(tb.IsDescription):
_v_pos = 2
Name = tb.UInt32Col()
Value = tb.Float64Col()
class Test(tb.IsDescription):
"""A description that has several columns."""
x = tb.Int32Col(shape=2, dflt=0, pos=0)
y = tb.Float64Col(dflt=1.2, shape=(2, 3))
z = tb.UInt8Col(dflt=1)
color = tb.EnumCol(colors, "red", base="uint32", shape=(2,))
Info = Info()
class IInfo(tb.IsDescription):
_v_pos = 1
name = tb.StringCol(10)
value = tb.Float64Col(pos=0)
y2 = tb.Float64Col(dflt=1, shape=(2, 3), pos=1)
z2 = tb.UInt8Col(dflt=1)
class IInfo2(tb.IsDescription):
y3 = tb.Float64Col(dflt=1, shape=(2, 3))
z3 = tb.UInt8Col(dflt=1)
name = tb.StringCol(10)
value = tb.EnumCol(colors, "blue", base="uint32", shape=(1,))
class IInfo3(tb.IsDescription):
name = tb.StringCol(10)
value = tb.Time64Col()
y4 = tb.Float64Col(dflt=1, shape=(2, 3))
z4 = tb.UInt8Col(dflt=1)
# Write the file and read it
write(fileout, Test, ["info/info2/z3"])
read(fileout)
print(f"You can have a look at '{fileout}' output file now.")
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