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28 changes: 28 additions & 0 deletions benchmarks/pandas/bench_compare.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,28 @@
import pandas as pd
import json
import time

N = 100_000
data = [i % 1000 for i in range(N)]
s = pd.Series(data, dtype=float)

# Warm-up
for _ in range(20):
s.eq(500)
s.lt(300)
s.ge(700)

iterations = 300
start = time.perf_counter()
for _ in range(iterations):
s.eq(500)
s.lt(300)
s.ge(700)
total_ms = (time.perf_counter() - start) * 1000

print(json.dumps({
"function": "compare",
"mean_ms": total_ms / iterations,
"iterations": iterations,
"total_ms": total_ms,
}))
30 changes: 30 additions & 0 deletions benchmarks/pandas/bench_update.py
Original file line number Diff line number Diff line change
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import pandas as pd
import numpy as np
import json
import time

N = 100_000
data = list(range(N))
other_data = [i * 10 if i % 3 == 0 else None for i in range(N)]

s = pd.Series(data, dtype=float)
o = pd.Series(other_data, dtype=float)

# Warm-up
for _ in range(20):
sc = s.copy()
sc.update(o)

iterations = 200
start = time.perf_counter()
for _ in range(iterations):
sc = s.copy()
sc.update(o)
total_ms = (time.perf_counter() - start) * 1000

print(json.dumps({
"function": "update",
"mean_ms": total_ms / iterations,
"iterations": iterations,
"total_ms": total_ms,
}))
24 changes: 24 additions & 0 deletions benchmarks/pandas/bench_xs.py
Original file line number Diff line number Diff line change
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import pandas as pd
import json
import time

N = 100_000
index = [str(i) for i in range(N)]
df = pd.DataFrame({"a": range(N), "b": [i * 2 for i in range(N)]}, index=index)

# Warm-up
for i in range(100):
df.xs("500")

iterations = 10_000
start = time.perf_counter()
for i in range(iterations):
df.xs(str(i % N))
total_ms = (time.perf_counter() - start) * 1000

print(json.dumps({
"function": "xs",
"mean_ms": total_ms / iterations,
"iterations": iterations,
"total_ms": total_ms,
}))
30 changes: 30 additions & 0 deletions benchmarks/tsb/bench_compare.ts
Original file line number Diff line number Diff line change
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import { Series, seriesEq, seriesLt, seriesGe } from "../../src/index.ts";

const N = 100_000;
const data = Float64Array.from({ length: N }, (_, i) => i % 1000);
const s = new Series({ data });

// Warm-up
for (let i = 0; i < 20; i++) {
seriesEq(s, 500);
seriesLt(s, 300);
seriesGe(s, 700);
}

const iterations = 300;
const start = performance.now();
for (let i = 0; i < iterations; i++) {
seriesEq(s, 500);
seriesLt(s, 300);
seriesGe(s, 700);
}
const total_ms = performance.now() - start;

console.log(
JSON.stringify({
function: "compare",
mean_ms: total_ms / iterations,
iterations,
total_ms,
}),
);
29 changes: 29 additions & 0 deletions benchmarks/tsb/bench_update.ts
Original file line number Diff line number Diff line change
@@ -0,0 +1,29 @@
import { Series, seriesUpdate } from "../../src/index.ts";

const N = 100_000;
const data = Float64Array.from({ length: N }, (_, i) => i);
const other = Float64Array.from({ length: N }, (_, i) => (i % 3 === 0 ? i * 10 : null as unknown as number));

const s = new Series({ data });
const o = new Series({ data: other });

// Warm-up
for (let i = 0; i < 20; i++) {
seriesUpdate(s, o);
}

const iterations = 200;
const start = performance.now();
for (let i = 0; i < iterations; i++) {
seriesUpdate(s, o);
}
const total_ms = performance.now() - start;

console.log(
JSON.stringify({
function: "update",
mean_ms: total_ms / iterations,
iterations,
total_ms,
}),
);
30 changes: 30 additions & 0 deletions benchmarks/tsb/bench_xs.ts
Original file line number Diff line number Diff line change
@@ -0,0 +1,30 @@
import { DataFrame, xsDataFrame } from "../../src/index.ts";

const N = 100_000;
const rows = Array.from({ length: N }, (_, i) => i);
const a = Float64Array.from(rows);
const b = Float64Array.from(rows.map((x) => x * 2));
const index = rows.map(String);

const df = DataFrame.fromColumns({ a, b }, { index });

// Warm-up
for (let i = 0; i < 100; i++) {
xsDataFrame(df, "500");
}

const iterations = 10_000;
const start = performance.now();
for (let i = 0; i < iterations; i++) {
xsDataFrame(df, String(i % N));
}
const total_ms = performance.now() - start;

console.log(
JSON.stringify({
function: "xs",
mean_ms: total_ms / iterations,
iterations,
total_ms,
}),
);
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