1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
|
import sys
from time import perf_counter as clock
from pathlib import Path
import numpy as np
import numexpr as ne
import tables as tb
shape = (1000, 160_000)
# shape = (10,1600)
filters = tb.Filters(complevel=1, complib="blosc2", shuffle=1)
ofilters = tb.Filters(complevel=1, complib="blosc2", shuffle=1)
# filters = tb.Filters(complevel=1, complib="lzo", shuffle=0)
# ofilters = tb.Filters(complevel=1, complib="lzo", shuffle=0)
# TODO: Makes it sense to add a 's'tring typecode here?
typecode_to_dtype = {
"b": "bool",
"i": "int32",
"l": "int64",
"f": "float32",
"d": "float64",
"c": "complex128",
}
def _compute(result, function, arguments, start=None, stop=None, step=None):
"""Compute the `function` over the `arguments` and put the outcome in
`result`"""
arg0 = arguments[0]
if hasattr(arg0, "maindim"):
maindim = arg0.maindim
(start, stop, step) = arg0._process_range_read(start, stop, step)
nrowsinbuf = arg0.nrowsinbuf
print("nrowsinbuf-->", nrowsinbuf)
else:
maindim = 0
(start, stop, step) = (0, len(arg0), 1)
nrowsinbuf = len(arg0)
shape = list(arg0.shape)
shape[maindim] = len(range(start, stop, step))
# The slices parameter for arg0.__getitem__
slices = [slice(0, dim, 1) for dim in arg0.shape]
# This is a hack to prevent doing unnecessary conversions
# when copying buffers
if hasattr(arg0, "maindim"):
for arg in arguments:
arg._v_convert = False
# Start the computation itself
for start2 in range(start, stop, step * nrowsinbuf):
# Save the records on disk
stop2 = start2 + step * nrowsinbuf
if stop2 > stop:
stop2 = stop
# Set the proper slice in the main dimension
slices[maindim] = slice(start2, stop2, step)
start3 = (start2 - start) / step
stop3 = start3 + nrowsinbuf
if stop3 > shape[maindim]:
stop3 = shape[maindim]
# Compute the slice to be filled in destination
sl = []
for i in range(maindim):
sl.append(slice(None, None, None))
sl.append(slice(start3, stop3, None))
# Get the values for computing the buffer
values = [arg.__getitem__(tuple(slices)) for arg in arguments]
result[tuple(sl)] = function(*values)
# Activate the conversion again (default)
if hasattr(arg0, "maindim"):
for arg in arguments:
arg._v_convert = True
return result
def evaluate(ex, out=None, local_dict=None, global_dict=None, **kwargs):
"""Evaluate expression and return an array."""
# First, get the signature for the arrays in expression
context = ne.necompiler.getContext(kwargs)
names, _ = ne.necompiler.getExprNames(ex, context)
# Get the arguments based on the names.
call_frame = sys._getframe(1)
if local_dict is None:
local_dict = call_frame.f_locals
if global_dict is None:
global_dict = call_frame.f_globals
arguments = []
types = []
for name in names:
try:
a = local_dict[name]
except KeyError:
a = global_dict[name]
arguments.append(a)
if hasattr(a, "atom"):
types.append(a.atom)
else:
types.append(a)
# Create a signature
signature = [
(name, ne.necompiler.getType(type_))
for (name, type_) in zip(names, types)
]
print("signature-->", signature)
# Compile the expression
compiled_ex = ne.necompiler.NumExpr(ex, signature, **kwargs)
print("fullsig-->", compiled_ex.fullsig)
_compute(out, compiled_ex, arguments)
return
if __name__ == "__main__":
iarrays = 0
oarrays = 0
doprofile = 1
dokprofile = 0
f = tb.open_file("evaluate.h5", "w")
# Create some arrays
if iarrays:
a = np.ones(shape, dtype="float32")
b = np.ones(shape, dtype="float32") * 2
c = np.ones(shape, dtype="float32") * 3
else:
a = f.create_carray(
f.root, "a", tb.Float32Atom(dflt=1), shape=shape, filters=filters
)
a[:] = 1
b = f.create_carray(
f.root, "b", tb.Float32Atom(dflt=2), shape=shape, filters=filters
)
b[:] = 2
c = f.create_carray(
f.root, "c", tb.Float32Atom(dflt=3), shape=shape, filters=filters
)
c[:] = 3
if oarrays:
out = np.empty(shape, dtype="float32")
else:
out = f.create_carray(
f.root, "out", tb.Float32Atom(), shape=shape, filters=ofilters
)
t0 = clock()
if iarrays and oarrays:
# out = ne.evaluate("a*b+c")
out = a * b + c
elif doprofile:
import pstats
import cProfile
cProfile.run('evaluate("a*b+c", out)', "evaluate.prof")
stats = pstats.Stats("evaluate.prof")
stats.strip_dirs()
stats.sort_stats("time", "calls")
stats.print_stats(20)
elif dokprofile:
import cProfile
import lsprofcalltree
prof = cProfile.Profile()
prof.run('evaluate("a*b+c", out)')
kcg = lsprofcalltree.KCacheGrind(prof)
with Path("evaluate.kcg").open("w") as ofile:
kcg.output(ofile)
else:
evaluate("a*b+c", out)
print(f"Time for evaluate--> {clock() - t0:.3f}")
# print "out-->", `out`
# print `out[:]`
f.close()
|
