Remove compact from staking.

[kianenigma]

This PR introduces two changes that will be of help to polkadot with regards to nominators.

1. The companion will deduce the average on initialize weight to 2.5%, 1/4th of the current value and based on a sampling from @shawntabrizi the real value is around 0.35%, so we are still safe. This will leave more room for the npos solutions.

2. Remove the #[compact] attribute of the solution. This will increase the weight a wee bit, but should hopefully reduce the decoding time. We have to re-benchmark here and see what happens. Essentially, we disable: Custom Codec Implementation for NPoS Election #6720

The regression on the length is as follows:

/// Without compact
[2020-10-16T15:36:58Z INFO  staking_miner::offchain_miner] prepared a seq-phragmen solution with 10 balancing iterations and score ["27,552,369,270,134,705", "6,455,599,802,115,900,355", "209,722,308,278,769,244,421,375,166,777,465,483"] and weight = "1,444,783,774,000" and len = 38096

/// With compact
[2020-10-16T15:35:43Z INFO  staking_miner::offchain_miner] prepared a seq-phragmen solution with 10 balancing iterations and score ["27,552,369,270,134,705", "6,455,599,802,115,900,355", "209,722,308,278,769,244,421,375,166,777,465,483"] and weight = "1,444,783,774,000" and len = 25166

Both 25k and 38k solutions are way below limit, so we are cool.

---

polkadot companion: paritytech/polkadot#1827

• One might that it sucks that the specifications of the solution type (such as it being #[compact] or not) is encoded in the heart of pallet_staking.
  I could not agree more and my next PR on staking (Decouple Staking and Election #7319) should address this among many other issues.
• The type Call was not used so I also removed that while we're at it.

[kianenigma]

/benchmark runtime pallet pallet_staking

[parity-benchapp]

Finished benchmark for branch: kiz-remove-compact

Benchmark: Runtime Benchmarks Pallet

cargo run --release --features runtime-benchmarks --manifest-path bin/node/cli/Cargo.toml -- benchmark --chain dev --steps 50 --repeat 20 --extrinsic "*" --execution=wasm --wasm-execution=compiled --output ./bin/node/runtime/src/weights --header ./HEADER --pallet pallet_staking

Results

Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 101.2
µs

Reads = 5
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 101.2
µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 79.01
µs

Reads = 4
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 79.01
µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 71.84
µs

Reads = 5
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 71.84
µs

Reads = 5
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 73
+ s 0.07
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 71.72 0.088 0.1%
2 72.33 0.108 0.1%
4 72.11 0.143 0.1%
6 72.61 0.159 0.2%
8 73.15 0.179 0.2%
10 73.16 0.087 0.1%
12 73.6 0.092 0.1%
14 73.51 0.111 0.1%
16 73.99 0.154 0.2%
18 74.39 0.159 0.2%
20 74.45 0.15 0.2%
22 74.72 0.158 0.2%
24 75.12 0.156 0.2%
26 74.98 0.132 0.1%
28 75.18 0.111 0.1%
30 75.17 0.233 0.3%
32 75.52 0.162 0.2%
34 76.16 0.135 0.1%
36 75.84 0.129 0.1%
38 75.87 0.137 0.1%
40 75.78 0.358 0.4%
42 76.58 0.271 0.3%
44 76.57 0.093 0.1%
46 77.11 0.129 0.1%
48 76.26 0.376 0.4%
50 76.69 0.67 0.8%
52 76.7 0.143 0.1%
54 77.26 0.137 0.1%
56 77.22 0.256 0.3%
58 77.49 0.117 0.1%
60 77.25 0.136 0.1%
62 75.83 0.608 0.8%
64 77.78 0.229 0.2%
66 77.75 0.452 0.5%
68 78.3 0.168 0.2%
70 78.13 0.063 0.0%
72 76.72 1.039 1.3%
74 78.36 0.623 0.7%
76 77 1.054 1.3%
78 78.4 0.791 1.0%
80 76.57 0.448 0.5%
82 78.83 0.127 0.1%
84 79.25 0.071 0.0%
86 79.4 0.094 0.1%
88 79.17 0.127 0.1%
90 79.01 0.169 0.2%
92 79.1 0.228 0.2%
94 77.75 1.056 1.3%
96 78.83 1.187 1.5%
98 78.35 1.265 1.6%
100 77.96 1.442 1.8%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 73.03
+ s 0.065
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 118.9
+ s 3.971
µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 111.5 0.122 0.1%
2 125.2 0.126 0.1%
4 133.3 0.183 0.1%
6 141.5 0.181 0.1%
8 150.5 0.169 0.1%
10 157.9 0.186 0.1%
12 165.9 0.134 0.0%
14 175.2 0.217 0.1%
16 182.2 0.235 0.1%
18 191.1 0.242 0.1%
20 198.8 0.418 0.2%
22 206 0.216 0.1%
24 214.9 0.364 0.1%
26 222.5 0.229 0.1%
28 230.8 0.219 0.0%
30 239.4 0.405 0.1%
32 246.4 0.224 0.0%
34 254.6 0.233 0.0%
36 261.6 0.214 0.0%
38 269.9 0.211 0.0%
40 278.2 0.258 0.0%
42 286.3 0.351 0.1%
44 293.8 0.24 0.0%
46 301.9 0.188 0.0%
48 309 0.317 0.1%
50 318.5 0.307 0.0%
52 325.6 0.242 0.0%
54 332.8 0.417 0.1%
56 341.4 0.294 0.0%
58 349.5 0.306 0.0%
60 357.2 0.489 0.1%
62 365.6 0.325 0.0%
64 374.5 0.324 0.0%
66 383.1 0.973 0.2%
68 389.9 0.332 0.0%
70 398.4 0.483 0.1%
72 403.9 0.579 0.1%
74 411.3 1.196 0.2%
76 420.4 0.375 0.0%
78 428.5 0.6 0.1%
80 436.6 0.574 0.1%
82 443.7 0.99 0.2%
84 449.5 0.983 0.2%
86 457.9 0.232 0.0%
88 465.4 1.046 0.2%
90 474.9 0.546 0.1%
92 482.8 0.57 0.1%
94 490.3 0.4 0.0%
96 499.4 0.532 0.1%
98 509.8 1.022 0.2%
100 515.5 1.249 0.2%

Quality and confidence:
param error
s 0.002

Model:
Time ~= 118.6
+ s 3.972
µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 25.58
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 25.58
µs

Reads = 2
Writes = 2
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.82
+ n 0.243
µs

Reads = 3 + (0 * n)
Writes = 2 + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 33.02 0.059 0.1%
2 34.28 0.122 0.3%
3 35.18 0.1 0.2%
4 36.64 0.119 0.3%
5 39.09 0.055 0.1%
6 39.67 0.121 0.3%
7 39.96 0.098 0.2%
8 36.16 0.118 0.3%
9 37.13 0.12 0.3%
10 37.21 0.066 0.1%
11 37.73 0.047 0.1%
12 38.03 0.101 0.2%
13 37.97 0.157 0.4%
14 37.92 0.055 0.1%
15 38.24 0.14 0.3%
16 38.13 0.145 0.3%

Quality and confidence:
param error
n 0.026

Model:
Time ~= 35.45
+ n 0.215
µs

Reads = 3 + (0 * n)
Writes = 2 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 25.56
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 25.56
µs

Reads = 2
Writes = 2
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 17.65
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 17.65
µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 37.44
µs

Reads = 3
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 37.44
µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.458
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.458
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 4.007
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 4.007
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 4.02
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 4.02
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.94
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.94
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 4.198
+ v 0.009
µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
0 3.939 0.025 0.6%
20 4.386 0.016 0.3%
40 4.687 0.033 0.7%
60 4.882 0.023 0.4%
80 5.018 0.029 0.5%
100 5.225 0.023 0.4%
120 5.348 0.038 0.7%
140 5.496 0.036 0.6%
160 5.719 0.026 0.4%
180 5.858 0.008 0.1%
200 6.042 0.04 0.6%
220 6.213 0.021 0.3%
240 6.407 0.032 0.4%
260 6.567 0.015 0.2%
280 6.719 0.027 0.4%
300 6.902 0.026 0.3%
320 7.061 0.038 0.5%
340 7.318 0.028 0.3%
360 7.452 0.027 0.3%
380 7.675 0.02 0.2%
400 7.86 0.026 0.3%
420 8.003 0.037 0.4%
440 8.222 0.021 0.2%
460 8.323 0.037 0.4%
480 8.429 0.021 0.2%
500 8.645 0.028 0.3%
520 8.821 0.031 0.3%
540 8.994 0.022 0.2%
560 9.213 0.03 0.3%
580 9.415 0.039 0.4%
600 9.652 0.026 0.2%
620 9.821 0.047 0.4%
640 10.02 0.016 0.1%
660 10.18 0.039 0.3%
680 10.39 0.039 0.3%
700 10.61 0.019 0.1%
720 10.81 0.023 0.2%
740 11.03 0.039 0.3%
760 11.16 0.036 0.3%
780 11.36 0.047 0.4%
800 11.52 0.036 0.3%
820 11.73 0.029 0.2%
840 11.94 0.037 0.3%
860 12.06 0.04 0.3%
880 12.3 0.019 0.1%
900 12.46 0.045 0.3%
920 12.62 0.027 0.2%
940 12.91 0.022 0.1%
960 13.03 0.035 0.2%
980 13.17 0.044 0.3%
1000 13.38 0.024 0.1%

Quality and confidence:
param error
v 0

Model:
Time ~= 4.184
+ v 0.009
µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 82.37
+ s 3.982
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 74.73 0.103 0.1%
2 88.28 0.052 0.0%
4 97.28 0.107 0.1%
6 105.1 0.175 0.1%
8 113.3 0.208 0.1%
10 122 0.183 0.1%
12 129.9 0.232 0.1%
14 137.9 0.138 0.1%
16 146.9 0.396 0.2%
18 154.8 0.339 0.2%
20 161.5 0.178 0.1%
22 169.7 0.281 0.1%
24 178.2 0.24 0.1%
26 186.5 0.153 0.0%
28 194.6 0.196 0.1%
30 202.4 0.533 0.2%
32 211 0.369 0.1%
34 217.6 0.227 0.1%
36 225.8 0.28 0.1%
38 234.2 0.338 0.1%
40 242.3 0.315 0.1%
42 251 0.302 0.1%
44 258.2 0.562 0.2%
46 266.3 0.584 0.2%
48 273.8 0.32 0.1%
50 281.9 0.233 0.0%
52 289.7 0.449 0.1%
54 297.7 0.31 0.1%
56 304.7 0.293 0.0%
58 313.8 0.426 0.1%
60 321.3 0.432 0.1%
62 328.7 0.571 0.1%
64 337.9 0.656 0.1%
66 346.2 0.481 0.1%
68 354.4 0.409 0.1%
70 361.8 0.511 0.1%
72 367.8 0.392 0.1%
74 376.8 0.616 0.1%
76 383.8 0.615 0.1%
78 392 0.493 0.1%
80 400.8 0.633 0.1%
82 408.7 0.544 0.1%
84 414.4 0.747 0.1%
86 423.8 0.735 0.1%
88 432 0.643 0.1%
90 440.3 0.604 0.1%
92 446.4 0.575 0.1%
94 453.6 0.258 0.0%
96 461.8 0.587 0.1%
98 473.2 0.849 0.1%
100 482.3 0.583 0.1%

Quality and confidence:
param error
s 0.002

Model:
Time ~= 82.03
+ s 3.983
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 6463
+ s 34.99
µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 365.2 0.585 0.1%
20 1663 3.276 0.1%
39 2928 2.504 0.0%
58 4177 2.828 0.0%
77 5396 7.942 0.1%
96 6593 9.764 0.1%
115 7755 4.85 0.0%
134 8917 15.21 0.1%
153 10040 15.06 0.1%
172 11130 6.871 0.0%
191 12210 11.89 0.0%
210 13240 14.17 0.1%
229 14270 14.68 0.1%
248 15260 8.503 0.0%
267 16230 12.8 0.0%
286 17180 18.77 0.1%
305 18100 8.148 0.0%
324 19000 10.93 0.0%
343 19880 13.25 0.0%
362 20710 7.994 0.0%
381 21550 23.26 0.1%
400 22340 12.22 0.0%
419 23120 14.01 0.0%
438 23840 2.582 0.0%
457 24580 15.8 0.0%
476 25270 12.35 0.0%
495 25980 22.96 0.0%
514 26610 21.2 0.0%
533 27230 11.82 0.0%
552 27830 11.2 0.0%
571 29000 17.65 0.0%
590 28960 18.42 0.0%
609 29470 8.532 0.0%
628 29970 15.26 0.0%
647 30440 15.59 0.0%
666 30910 17.62 0.0%
685 31310 9.61 0.0%
704 31710 13.15 0.0%
723 32080 19.84 0.0%
742 32420 2.695 0.0%
761 32750 15.91 0.0%
780 33040 14.11 0.0%
799 33320 13.98 0.0%
818 33960 190.9 0.5%
837 33830 19.29 0.0%
856 34030 13.7 0.0%
875 34200 9.861 0.0%
894 34350 14.78 0.0%
913 34480 23.41 0.0%
932 34560 14.98 0.0%
951 34640 9.684 0.0%
970 34710 24.82 0.0%
989 34730 14.45 0.0%

Quality and confidence:
param error
s 0.391

Model:
Time ~= 5832
+ s 34.81
µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 146.9
+ n 61.01
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 198.2 0.326 0.1%
6 506.9 0.788 0.1%
11 812.5 0.8 0.0%
16 1123 0.954 0.0%
21 1429 3.063 0.2%
26 1731 8.635 0.4%
31 2034 1.247 0.0%
36 2351 3.626 0.1%
41 2651 7.378 0.2%
46 2953 8.804 0.2%
51 3263 4.778 0.1%
56 3551 3.267 0.0%
61 3861 7.127 0.1%
66 4171 6.511 0.1%
71 4518 10.82 0.2%
76 4805 15.42 0.3%
81 5115 8.362 0.1%
86 5421 18.94 0.3%
91 5704 14.13 0.2%
96 6006 12.39 0.2%
101 6317 10.03 0.1%
106 6603 16.61 0.2%
111 6905 12.71 0.1%
116 7227 14.82 0.2%
121 7513 12.55 0.1%
126 7819 16.29 0.2%
131 8144 18.24 0.2%
136 8401 11.78 0.1%
141 8712 13.61 0.1%
146 9063 18.06 0.1%
151 9368 10.01 0.1%
156 9709 23.6 0.2%
161 9973 16.48 0.1%
166 10290 16.27 0.1%
171 10620 11.8 0.1%
176 10870 11.93 0.1%
181 11190 15.01 0.1%
186 11530 23.34 0.2%
191 11810 9.918 0.0%
196 12160 17.34 0.1%
201 12410 23.22 0.1%
206 12730 12.81 0.1%
211 13020 18.26 0.1%
216 13390 81.28 0.6%
221 13640 23.32 0.1%
226 13930 15.97 0.1%
231 14240 24.25 0.1%
236 14490 19.18 0.1%
241 14880 19.07 0.1%
246 15210 127.2 0.8%
251 15400 29.81 0.1%
256 15730 15.23 0.0%

Quality and confidence:
param error
n 0.02

Model:
Time ~= 146.7
+ n 61.05
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 185.8
+ n 79.07
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 253.9 0.318 0.1%
6 652.6 0.68 0.1%
11 1052 2.376 0.2%
16 1453 2.493 0.1%
21 1856 2.775 0.1%
26 2244 4.915 0.2%
31 2645 10.93 0.4%
36 3020 5.958 0.1%
41 3434 8.417 0.2%
46 3836 8.206 0.2%
51 4223 6.696 0.1%
56 4602 10.09 0.2%
61 5002 12.1 0.2%
66 5412 12.59 0.2%
71 5789 7.645 0.1%
76 6181 8.462 0.1%
81 6555 7.898 0.1%
86 7006 14.08 0.2%
91 7451 20.05 0.2%
96 7805 14.77 0.1%
101 8157 23.62 0.2%
106 8608 9.896 0.1%
111 8991 13.45 0.1%
116 9341 24.55 0.2%
121 9741 14.2 0.1%
126 10160 46.41 0.4%
131 10530 25.58 0.2%
136 10930 17.34 0.1%
141 11320 17.57 0.1%
146 11680 19.57 0.1%
151 12030 17.54 0.1%
156 12450 21.5 0.1%
161 12910 28.49 0.2%
166 13220 24.62 0.1%
171 13640 35.04 0.2%
176 14150 21.27 0.1%
181 14600 30.82 0.2%
186 14910 15.09 0.1%
191 15300 19.85 0.1%
196 15690 24.04 0.1%
201 16110 14.15 0.0%
206 16570 77.89 0.4%
211 16900 21.61 0.1%
216 17230 28.52 0.1%
221 17650 30.08 0.1%
226 17980 28.57 0.1%
231 18450 58.24 0.3%
236 18870 49.23 0.2%
241 19280 34.46 0.1%
246 19670 19.57 0.0%
251 19970 26.91 0.1%
256 20410 47.11 0.2%

Quality and confidence:
param error
n 0.027

Model:
Time ~= 184
+ n 79.09
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 50.27
+ l 0.106
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
l mean µs sigma µs %
1 50.11 0.102 0.2%
2 49.81 0.138 0.2%
3 50.12 0.098 0.1%
4 50.24 0.125 0.2%
5 50.71 0.073 0.1%
6 50.65 0.117 0.2%
7 50.74 0.096 0.1%
8 50.96 0.086 0.1%
9 51.22 0.168 0.3%
10 51.48 0.067 0.1%
11 51.57 0.137 0.2%
12 51.99 0.095 0.1%
13 52.11 0.13 0.2%
14 51.95 0.042 0.0%
15 52.16 0.097 0.1%
16 52.09 0.128 0.2%
17 52.49 0.123 0.2%
18 52.86 0.09 0.1%
19 52.82 0.093 0.1%
20 52.94 0.127 0.2%
21 52.84 0.121 0.2%
22 52.8 0.08 0.1%
23 52.96 0.131 0.2%
24 52.86 0.068 0.1%
25 53.03 0.095 0.1%
26 52.94 0.08 0.1%
27 53.09 0.115 0.2%
28 52.72 0.048 0.0%
29 53.2 0.105 0.1%
30 52.95 0.222 0.4%
31 52.95 0.054 0.1%
32 53.01 0.092 0.1%

Quality and confidence:
param error
l 0.002

Model:
Time ~= 50.25
+ l 0.107
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ e 39.2
µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
e mean µs sigma µs %
1 49.95 0.047 0.0%
2 82.07 0.092 0.1%
3 111.5 0.203 0.1%
4 145.3 0.241 0.1%
5 174.6 0.276 0.1%
6 206.2 0.374 0.1%
7 235.8 0.577 0.2%
8 267.4 0.288 0.1%
9 298.7 0.489 0.1%
10 331.6 0.593 0.1%
11 364.8 0.623 0.1%
12 394.3 0.605 0.1%
13 428.8 0.844 0.1%
14 462.9 0.743 0.1%
15 496.7 1.201 0.2%
16 527.4 1.384 0.2%
17 562.9 0.715 0.1%
18 597.8 1.807 0.3%
19 628.2 1.139 0.1%
20 664.4 1.838 0.2%
21 696 1.305 0.1%
22 734.4 1.333 0.1%
23 768.8 0.768 0.0%
24 804.6 2.005 0.2%
25 836.1 1.056 0.1%
26 876.4 1.146 0.1%
27 913.9 1.954 0.2%
28 949.4 0.939 0.0%
29 980.7 1.586 0.1%
30 1022 1.344 0.1%
31 1059 1.592 0.1%
32 1095 2.411 0.2%
33 1124 2.915 0.2%
34 1163 2.813 0.2%
35 1205 2.034 0.1%
36 1243 2.101 0.1%
37 1273 1.994 0.1%
38 1305 2.648 0.2%
39 1331 2.186 0.1%
40 1383 1.789 0.1%
41 1405 1.907 0.1%
42 1461 2.464 0.1%
43 1492 2.069 0.1%
44 1535 2.298 0.1%
45 1563 2.74 0.1%
46 1616 3.909 0.2%
47 1653 6.142 0.3%
48 1687 3.744 0.2%
49 1737 4.086 0.2%
50 1773 4.155 0.2%
51 1820 5.267 0.2%
52 1860 5.34 0.2%
53 1890 3.849 0.2%
54 1928 5.076 0.2%
55 1975 4.652 0.2%
56 2012 3.533 0.1%
57 2043 3.49 0.1%
58 2091 3.216 0.1%
59 2134 3.797 0.1%
60 2176 2.11 0.0%
61 2204 6.225 0.2%
62 2252 4.769 0.2%
63 2281 6.978 0.3%
64 2346 5.618 0.2%
65 2365 4.146 0.1%
66 2413 3.137 0.1%
67 2464 3.399 0.1%
68 2477 5.532 0.2%
69 2529 6.051 0.2%
70 2583 3.165 0.1%
71 2606 4.427 0.1%
72 2653 5.033 0.1%
73 2709 5.106 0.1%
74 2750 6.889 0.2%
75 2813 5.05 0.1%
76 2858 4.157 0.1%
77 2894 9.22 0.3%
78 2940 5.941 0.2%
79 2956 8.288 0.2%
80 3025 6.236 0.2%
81 3041 9.416 0.3%
82 3096 4.758 0.1%
83 3162 3.834 0.1%
84 3224 6.555 0.2%
85 3271 9.556 0.2%
86 3282 6.038 0.1%
87 3358 8.732 0.2%
88 3388 6.402 0.1%
89 3438 5.966 0.1%
90 3486 5.346 0.1%
91 3531 9.149 0.2%
92 3573 5.593 0.1%
93 3634 5.489 0.1%
94 3672 2.978 0.0%
95 3720 7.093 0.1%
96 3743 5.311 0.1%
97 3765 5.641 0.1%
98 3864 12.27 0.3%
99 3912 7.798 0.1%
100 3972 16.7 0.4%

Quality and confidence:
param error
e 0.072

Model:
Time ~= 0
+ e 39.4
µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 102.4
+ s 3.975
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 103.4 0.125 0.1%
2 108.7 0.09 0.0%
3 112.8 0.145 0.1%
4 117 0.131 0.1%
5 121.3 0.22 0.1%
6 124.9 0.173 0.1%
7 128.9 0.184 0.1%
8 133.7 0.123 0.0%
9 137.8 0.117 0.0%
10 141.4 0.203 0.1%
11 145.4 0.148 0.1%
12 149.6 0.133 0.0%
13 154.5 0.251 0.1%
14 158.7 0.102 0.0%
15 162.2 0.226 0.1%
16 165.8 0.169 0.1%
17 170.1 0.186 0.1%
18 173.9 0.246 0.1%
19 177.5 0.068 0.0%
20 182.1 0.159 0.0%
21 185.7 0.312 0.1%
22 188.9 0.194 0.1%
23 193.6 0.227 0.1%
24 197.7 0.178 0.0%
25 202.9 0.503 0.2%
26 206.3 0.355 0.1%
27 210 0.264 0.1%
28 214.5 0.221 0.1%
29 218.8 0.158 0.0%
30 222.6 0.368 0.1%
31 226.6 0.289 0.1%
32 230.4 0.186 0.0%
33 233.7 0.27 0.1%
34 239 0.198 0.0%
35 241.6 0.128 0.0%
36 246.1 0.382 0.1%
37 249 0.328 0.1%
38 253.9 0.224 0.0%
39 257.2 0.281 0.1%
40 262 0.264 0.1%
41 266 0.34 0.1%
42 270.5 0.359 0.1%
43 273.4 0.198 0.0%
44 277.5 0.404 0.1%
45 281.6 0.277 0.0%
46 286.3 0.556 0.1%
47 289.7 0.121 0.0%
48 293 0.371 0.1%
49 297.7 0.452 0.1%
50 301.3 0.476 0.1%
51 305.7 0.36 0.1%
52 309.6 0.249 0.0%
53 313.3 0.212 0.0%
54 317.3 0.453 0.1%
55 321.3 0.431 0.1%
56 325.1 0.372 0.1%
57 329.3 0.36 0.1%
58 332.4 0.308 0.0%
59 364.2 19.28 5.2%
60 352.5 12.34 3.5%
61 350.2 4.027 1.1%
62 354.7 4.029 1.1%
63 359.3 4.358 1.2%
64 364 5.7 1.5%
65 367.8 3.948 1.0%
66 375.2 6.226 1.6%
67 373 5.244 1.4%
68 373.3 0.572 0.1%
69 377 0.6 0.1%
70 381.1 0.42 0.1%
71 384.9 0.572 0.1%
72 388.6 0.25 0.0%
73 391.6 0.514 0.1%
74 396.4 0.578 0.1%
75 400.2 0.568 0.1%
76 404 0.469 0.1%
77 407.3 0.497 0.1%
78 411.5 0.371 0.0%
79 416.1 0.712 0.1%
80 421.6 0.862 0.2%
81 423.7 0.504 0.1%
82 428.1 0.591 0.1%
83 431.8 1.001 0.2%
84 435.1 0.689 0.1%
85 439.9 0.424 0.0%
86 442.9 0.427 0.0%
87 445.5 1.154 0.2%
88 451.1 0.756 0.1%
89 455.5 0.723 0.1%
90 459.9 0.689 0.1%
91 463.1 0.466 0.1%
92 465.7 0.547 0.1%
93 469.7 0.545 0.1%
94 473.5 0.604 0.1%
95 478.1 0.495 0.1%
96 482.6 0.682 0.1%
97 489.5 2.395 0.4%
98 491.9 0.527 0.1%
99 495.6 1.009 0.2%
100 500.1 0.671 0.1%

Quality and confidence:
param error
s 0.004

Model:
Time ~= 102.7
+ s 3.982
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 898.1
+ n 118.5
µs

Reads = 10 + (4 * v) + (3 * n)
Writes = 8 + (3 * v) + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n mean µs sigma µs %
1 100 4582 5.385 0.1%
2 100 5377 5.414 0.1%
3 100 6116 6.621 0.1%
4 100 6850 7.083 0.1%
5 100 7750 10.81 0.1%
6 100 8574 8.252 0.0%
7 100 9474 13.58 0.1%
8 100 10450 21.47 0.2%
9 100 11580 12.26 0.1%
10 1 898.3 1.233 0.1%
10 2 1025 0.936 0.0%
10 3 1154 1.049 0.0%
10 4 1281 0.904 0.0%
10 5 1394 0.999 0.0%
10 6 1512 2.063 0.1%
10 7 1641 3.724 0.2%
10 8 1765 1.16 0.0%
10 9 1886 1.825 0.0%
10 10 2051 2.801 0.1%
10 11 2173 1.463 0.0%
10 12 2296 2.023 0.0%
10 13 2444 14.19 0.5%
10 14 2615 9.81 0.3%
10 15 2709 16.82 0.6%
10 16 2798 2.048 0.0%
10 17 2922 3.543 0.1%
10 18 3046 1.359 0.0%
10 19 3166 3.695 0.1%
10 20 3304 8.282 0.2%
10 21 3424 11.45 0.3%
10 22 3530 3.973 0.1%
10 23 3702 7.486 0.2%
10 24 3789 9.292 0.2%
10 25 3906 11.74 0.3%
10 26 4059 4.697 0.1%
10 27 4176 2.142 0.0%
10 28 4276 2.544 0.0%
10 29 4405 2.954 0.0%
10 30 4522 7.447 0.1%
10 31 4640 4.375 0.0%
10 32 4776 7.621 0.1%
10 33 4914 11.38 0.2%
10 34 5022 5.267 0.1%
10 35 5147 5.161 0.1%
10 36 5257 4.783 0.0%
10 37 5393 16.17 0.2%
10 38 5483 6.912 0.1%
10 39 5612 7.19 0.1%
10 40 5743 7.967 0.1%
10 41 5867 10.85 0.1%
10 42 5967 13.67 0.2%
10 43 6101 13.34 0.2%
10 44 6207 11.66 0.1%
10 45 6299 6.236 0.0%
10 46 6427 11.77 0.1%
10 47 6516 6.544 0.1%
10 48 6625 9.821 0.1%
10 49 6779 11.17 0.1%
10 50 6900 14.81 0.2%
10 51 7015 12.54 0.1%
10 52 7111 7.068 0.0%
10 53 7253 8.283 0.1%
10 54 7395 9.442 0.1%
10 55 7517 7.998 0.1%
10 56 7635 8.956 0.1%
10 57 7734 10.33 0.1%
10 58 7883 9.608 0.1%
10 59 7951 11.49 0.1%
10 60 8107 9.558 0.1%
10 61 8213 8.126 0.0%
10 62 8309 11.49 0.1%
10 63 8444 8.885 0.1%
10 64 8601 9.904 0.1%
10 65 8709 6.464 0.0%
10 66 8823 12.68 0.1%
10 67 8918 14.37 0.1%
10 68 9051 19.45 0.2%
10 69 9142 13.45 0.1%
10 70 9266 7.359 0.0%
10 71 9377 7.248 0.0%
10 72 9490 5.868 0.0%
10 73 9616 11.87 0.1%
10 74 9743 16.2 0.1%
10 75 9846 14.71 0.1%
10 76 10000 58.33 0.5%
10 77 10090 39.32 0.3%
10 78 10160 10.22 0.1%
10 79 10300 12.95 0.1%
10 80 10410 13.86 0.1%
10 81 10530 22.84 0.2%
10 82 10640 10.58 0.0%
10 83 10760 10.63 0.0%
10 84 10880 15.91 0.1%
10 85 10950 24.02 0.2%
10 86 11100 19.74 0.1%
10 87 11200 14.81 0.1%
10 88 11310 11.29 0.0%
10 89 11460 14.76 0.1%
10 90 11560 12.06 0.1%
10 91 11820 122.3 1.0%
10 92 11760 14.59 0.1%
10 93 11850 16.15 0.1%
10 94 11990 14.85 0.1%
10 95 12060 14.59 0.1%
10 96 12180 16.67 0.1%
10 97 12320 12.85 0.1%
10 98 12400 16.12 0.1%
10 99 12520 12.84 0.1%
10 100 12660 9.61 0.0%

Quality and confidence:
param error
v 2.329
n 0.117

Model:
Time ~= 0
+ v 952.4
+ n 117.9
µs

Reads = 10 + (4 * v) + (3 * n)
Writes = 8 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "submit_solution_better", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 1.164
+ n 0.456
+ a 99.28
+ w 9.453
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n a w mean µs sigma µs %
200 1000 400 100 40780 69.68 0.1%
204 1000 400 100 40800 51.13 0.1%
208 1000 400 100 41030 49.85 0.1%
212 1000 400 100 40760 31.61 0.0%
216 1000 400 100 40780 49.74 0.1%
220 1000 400 100 40890 33.02 0.0%
224 1000 400 100 40780 42.25 0.1%
228 1000 400 100 40960 45.32 0.1%
232 1000 400 100 40840 78.04 0.1%
236 1000 400 100 40790 40.14 0.0%
240 1000 400 100 41000 16.77 0.0%
244 1000 400 100 41050 29.76 0.0%
248 1000 400 100 40880 33.76 0.0%
252 1000 400 100 40840 54.31 0.1%
256 1000 400 100 40850 48.07 0.1%
260 1000 400 100 40910 74.98 0.1%
264 1000 400 100 40850 54.78 0.1%
268 1000 400 100 40790 36.68 0.0%
272 1000 400 100 40930 54.23 0.1%
276 1000 400 100 40920 58.03 0.1%
280 1000 400 100 40880 49.1 0.1%
284 1000 400 100 40780 56.02 0.1%
288 1000 400 100 40990 63.93 0.1%
292 1000 400 100 40850 51.98 0.1%
296 1000 400 100 40960 57.65 0.1%
300 1000 400 100 40850 47.8 0.1%
304 1000 400 100 40910 33.37 0.0%
308 1000 400 100 40920 54.54 0.1%
312 1000 400 100 40930 53.08 0.1%
316 1000 400 100 40960 37.41 0.0%
320 1000 400 100 41080 33.67 0.0%
324 1000 400 100 40980 33.03 0.0%
328 1000 400 100 40990 21.61 0.0%
332 1000 400 100 40870 79.66 0.1%
336 1000 400 100 40960 43.63 0.1%
340 1000 400 100 40880 46.1 0.1%
344 1000 400 100 40990 48.51 0.1%
348 1000 400 100 41130 39.69 0.0%
352 1000 400 100 40940 55.62 0.1%
356 1000 400 100 41160 40.56 0.0%
360 1000 400 100 40890 60.16 0.1%
364 1000 400 100 40930 56.02 0.1%
368 1000 400 100 41080 14.47 0.0%
372 1000 400 100 41150 57.27 0.1%
376 1000 400 100 41090 33.11 0.0%
380 1000 400 100 40970 56.54 0.1%
384 1000 400 100 41050 25.68 0.0%
388 1000 400 100 41140 43.42 0.1%
392 1000 400 100 41070 53.39 0.1%
396 1000 400 100 41110 23.59 0.0%
400 500 400 100 40830 55.11 0.1%
400 510 400 100 40890 36.85 0.0%
400 520 400 100 40820 47.6 0.1%
400 530 400 100 40790 86.81 0.2%
400 540 400 100 40650 44.86 0.1%
400 550 400 100 40760 77.44 0.1%
400 560 400 100 40760 46.88 0.1%
400 570 400 100 40870 38.77 0.0%
400 580 400 100 40730 67.05 0.1%
400 590 400 100 40850 54.99 0.1%
400 600 400 100 40890 59.61 0.1%
400 610 400 100 40780 35.36 0.0%
400 620 400 100 40980 27.42 0.0%
400 630 400 100 40990 44.21 0.1%
400 640 400 100 40840 44.26 0.1%
400 650 400 100 40810 36.11 0.0%
400 660 400 100 40950 44.94 0.1%
400 670 400 100 40930 44.12 0.1%
400 680 400 100 40770 36.65 0.0%
400 690 400 100 40800 47.47 0.1%
400 700 400 100 41050 38.5 0.0%
400 710 400 100 40890 35.44 0.0%
400 720 400 100 40870 26.31 0.0%
400 730 400 100 41020 37.24 0.0%
400 740 400 100 41050 42.03 0.1%
400 750 400 100 40850 48.39 0.1%
400 760 400 100 40920 75.94 0.1%
400 770 400 100 40910 52.81 0.1%
400 780 400 100 40850 42.33 0.1%
400 790 400 100 40950 49.17 0.1%
400 800 400 100 40920 35.08 0.0%
400 810 400 100 41100 43.37 0.1%
400 820 400 100 40950 49.19 0.1%
400 830 400 100 41130 38.81 0.0%
400 840 400 100 40880 40.76 0.0%
400 850 400 100 41110 63.35 0.1%
400 860 400 100 40880 37.71 0.0%
400 870 400 100 40940 49.11 0.1%
400 880 400 100 40900 42.61 0.1%
400 890 400 100 40950 61.83 0.1%
400 900 400 100 41040 69.46 0.1%
400 910 400 100 40980 48.23 0.1%
400 920 400 100 41130 58 0.1%
400 930 400 100 41060 37.82 0.0%
400 940 400 100 40960 60.23 0.1%
400 950 400 100 41130 38.76 0.0%
400 960 400 100 40930 50.55 0.1%
400 970 400 100 40910 34.6 0.0%
400 980 400 100 41100 41.95 0.1%
400 990 400 100 40870 29.23 0.0%
400 1000 200 100 20990 36.62 0.1%
400 1000 204 100 21380 26.97 0.1%
400 1000 208 100 21790 27.1 0.1%
400 1000 212 100 22320 33.08 0.1%
400 1000 216 100 22680 21.75 0.0%
400 1000 220 100 23090 34.71 0.1%
400 1000 224 100 23510 27.44 0.1%
400 1000 228 100 23900 31.5 0.1%
400 1000 232 100 24320 22.89 0.0%
400 1000 236 100 24720 39.86 0.1%
400 1000 240 100 25130 24.24 0.0%
400 1000 244 100 25530 41.45 0.1%
400 1000 248 100 25910 44.85 0.1%
400 1000 252 100 26320 28.92 0.1%
400 1000 256 100 26720 22.11 0.0%
400 1000 260 100 27120 36.88 0.1%
400 1000 264 100 27520 34.39 0.1%
400 1000 268 100 27950 52.9 0.1%
400 1000 272 100 28260 60.45 0.2%
400 1000 276 100 28690 101.4 0.3%
400 1000 280 100 29110 59.21 0.2%
400 1000 284 100 29490 34.47 0.1%
400 1000 288 100 29870 48.27 0.1%
400 1000 292 100 30220 32.44 0.1%
400 1000 296 100 30620 36.42 0.1%
400 1000 300 100 30990 55.09 0.1%
400 1000 304 100 31400 26.74 0.0%
400 1000 308 100 31780 41.5 0.1%
400 1000 312 100 32180 26.53 0.0%
400 1000 316 100 32650 60.07 0.1%
400 1000 320 100 32960 26.37 0.0%
400 1000 324 100 33450 65.94 0.1%
400 1000 328 100 33800 39.85 0.1%
400 1000 332 100 34200 58.36 0.1%
400 1000 336 100 34570 42.27 0.1%
400 1000 340 100 34970 53.88 0.1%
400 1000 344 100 35350 40.05 0.1%
400 1000 348 100 35780 13.69 0.0%
400 1000 352 100 36150 54.44 0.1%
400 1000 356 100 36570 41.34 0.1%
400 1000 360 100 36980 39.23 0.1%
400 1000 364 100 37350 28.05 0.0%
400 1000 368 100 37760 24.05 0.0%
400 1000 372 100 38160 38.62 0.1%
400 1000 376 100 38610 94.42 0.2%
400 1000 380 100 38990 70.49 0.1%
400 1000 384 100 39360 59.16 0.1%
400 1000 388 100 39710 56.96 0.1%
400 1000 392 100 40200 27.22 0.0%
400 1000 396 100 40600 25.7 0.0%
400 1000 400 16 40260 30.83 0.0%
400 1000 400 17 40150 65.99 0.1%
400 1000 400 18 40360 18.37 0.0%
400 1000 400 19 40390 57.86 0.1%
400 1000 400 20 40260 26.7 0.0%
400 1000 400 21 40490 59.57 0.1%
400 1000 400 22 40390 59.66 0.1%
400 1000 400 23 40510 48.76 0.1%
400 1000 400 24 40560 25.74 0.0%
400 1000 400 25 40520 35.04 0.0%
400 1000 400 26 40320 54.7 0.1%
400 1000 400 27 40350 47.09 0.1%
400 1000 400 28 40310 41.59 0.1%
400 1000 400 29 40570 30.88 0.0%
400 1000 400 30 40590 31.56 0.0%
400 1000 400 31 40430 37.45 0.0%
400 1000 400 32 40530 60.78 0.1%
400 1000 400 33 40510 29.79 0.0%
400 1000 400 34 40480 53.31 0.1%
400 1000 400 35 40530 62.93 0.1%
400 1000 400 36 40340 22.49 0.0%
400 1000 400 37 40470 40.01 0.0%
400 1000 400 38 40670 61.7 0.1%
400 1000 400 39 40640 24.77 0.0%
400 1000 400 40 40710 45.73 0.1%
400 1000 400 41 40530 29.7 0.0%
400 1000 400 42 40810 83.53 0.2%
400 1000 400 43 40550 45.96 0.1%
400 1000 400 44 40910 36.73 0.0%
400 1000 400 45 40890 43.14 0.1%
400 1000 400 46 40840 73.52 0.1%
400 1000 400 47 40730 73.51 0.1%
400 1000 400 48 40850 38.7 0.0%
400 1000 400 49 40920 37.48 0.0%
400 1000 400 50 40850 52.86 0.1%
400 1000 400 51 40600 28.35 0.0%
400 1000 400 52 40670 73.48 0.1%
400 1000 400 53 40570 47.25 0.1%
400 1000 400 54 40640 49.87 0.1%
400 1000 400 55 40670 45.14 0.1%
400 1000 400 56 40490 46.41 0.1%
400 1000 400 57 40770 42.81 0.1%
400 1000 400 58 40820 64.37 0.1%
400 1000 400 59 40670 37.26 0.0%
400 1000 400 60 40650 72.74 0.1%
400 1000 400 61 40720 35.85 0.0%
400 1000 400 62 40730 52.74 0.1%
400 1000 400 63 40930 45.13 0.1%
400 1000 400 64 40760 52.49 0.1%
400 1000 400 65 40760 44.01 0.1%
400 1000 400 66 40800 86.87 0.2%
400 1000 400 67 40710 40.76 0.1%
400 1000 400 68 40840 40.45 0.0%
400 1000 400 69 40970 40.01 0.0%
400 1000 400 70 40850 61.02 0.1%
400 1000 400 71 40980 43.5 0.1%
400 1000 400 72 40970 37.4 0.0%
400 1000 400 73 40860 47.58 0.1%
400 1000 400 74 40760 52.43 0.1%
400 1000 400 75 41090 79.21 0.1%
400 1000 400 76 40830 35.99 0.0%
400 1000 400 77 41020 32.7 0.0%
400 1000 400 78 40960 41.89 0.1%
400 1000 400 79 41100 52.21 0.1%
400 1000 400 80 40970 31.67 0.0%
400 1000 400 81 41160 64.45 0.1%
400 1000 400 82 40920 35.33 0.0%
400 1000 400 83 41140 50.4 0.1%
400 1000 400 84 41070 45.04 0.1%
400 1000 400 85 40950 59.75 0.1%
400 1000 400 86 41020 73.51 0.1%
400 1000 400 87 41230 44.71 0.1%
400 1000 400 88 41010 49.23 0.1%
400 1000 400 89 41050 63.42 0.1%
400 1000 400 90 41030 35.21 0.0%
400 1000 400 91 41230 34.33 0.0%
400 1000 400 92 41070 56.55 0.1%
400 1000 400 93 40970 46.17 0.1%
400 1000 400 94 41100 52.38 0.1%
400 1000 400 95 41060 48.71 0.1%
400 1000 400 96 41100 58.75 0.1%
400 1000 400 97 41170 56.13 0.1%
400 1000 400 98 41210 36.4 0.0%
400 1000 400 99 41220 56.15 0.1%
400 1000 400 100 41000 56.3 0.1%

Quality and confidence:
param error
v 0.054
n 0.021
a 0.054
w 0.112

Model:
Time ~= 0
+ v 1.327
+ n 0.584
+ a 100.1
+ w 7.994
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)

[kianenigma]

The benchmarking happening above ^^ was actually done with #[compact].. and it still drastically reduced its weight. Lets see what we get next without it.

[kianenigma]

/benchmark runtime pallet pallet_staking

[parity-benchapp]

Finished benchmark for branch: kiz-remove-compact

Benchmark: Runtime Benchmarks Pallet

cargo run --release --features runtime-benchmarks --manifest-path bin/node/cli/Cargo.toml -- benchmark --chain dev --steps 50 --repeat 20 --extrinsic "*" --execution=wasm --wasm-execution=compiled --output ./bin/node/runtime/src/weights --header ./HEADER --pallet pallet_staking

Results

Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 100.6
µs

Reads = 5
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 100.6
µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 79.13
µs

Reads = 4
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 79.13
µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 71.69
µs

Reads = 5
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 71.69
µs

Reads = 5
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 72.62
+ s 0.074
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 70.96 0.1 0.1%
2 71.9 0.198 0.2%
4 72.04 0.109 0.1%
6 72.35 0.11 0.1%
8 72.78 0.109 0.1%
10 72.98 0.13 0.1%
12 73.25 0.146 0.1%
14 73.23 0.121 0.1%
16 74.09 0.128 0.1%
18 73.66 0.09 0.1%
20 74.23 0.133 0.1%
22 74.42 0.134 0.1%
24 74.82 0.151 0.2%
26 75.33 0.198 0.2%
28 74.62 0.159 0.2%
30 75.11 0.151 0.2%
32 75.27 0.074 0.0%
34 75.48 0.133 0.1%
36 75.77 0.08 0.1%
38 75.72 0.153 0.2%
40 75.98 0.174 0.2%
42 75.98 0.113 0.1%
44 76.31 0.185 0.2%
46 76.65 0.136 0.1%
48 75.87 0.691 0.9%
50 74.78 1.069 1.4%
52 76.53 0.779 1.0%
54 76.37 0.66 0.8%
56 76.73 0.148 0.1%
58 77.16 0.211 0.2%
60 76.27 0.84 1.1%
62 77.53 0.123 0.1%
64 75.91 0.857 1.1%
66 78.05 0.214 0.2%
68 78.05 0.201 0.2%
70 77.93 0.158 0.2%
72 75.52 0.196 0.2%
74 78.04 0.216 0.2%
76 78.43 0.145 0.1%
78 78.43 0.172 0.2%
80 79.1 0.14 0.1%
82 78.96 0.112 0.1%
84 79.28 0.198 0.2%
86 79.4 0.156 0.1%
88 79.05 0.167 0.2%
90 78.93 0.106 0.1%
92 78.9 0.188 0.2%
94 78.88 1.059 1.3%
96 76.54 0.265 0.3%
98 76.51 0.18 0.2%
100 76.79 0.209 0.2%

Quality and confidence:
param error
s 0.001

Model:
Time ~= 72.72
+ s 0.066
µs

Reads = 5 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 119
+ s 3.967
µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 111.2 0.142 0.1%
2 125.3 0.104 0.0%
4 133.6 0.136 0.1%
6 141.2 0.238 0.1%
8 150 0.186 0.1%
10 157.6 0.155 0.0%
12 165.8 0.154 0.0%
14 175 0.228 0.1%
16 182.5 0.14 0.0%
18 190.4 0.329 0.1%
20 198 0.157 0.0%
22 206.4 0.155 0.0%
24 214.7 0.303 0.1%
26 222.7 0.233 0.1%
28 231 0.218 0.0%
30 238.7 0.187 0.0%
32 246.7 0.401 0.1%
34 254.8 0.317 0.1%
36 262.6 0.161 0.0%
38 270.8 0.399 0.1%
40 279.3 0.202 0.0%
42 286.4 0.295 0.1%
44 293.7 0.243 0.0%
46 302.2 0.446 0.1%
48 309.3 0.376 0.1%
50 317.7 0.323 0.1%
52 326.1 0.168 0.0%
54 333 0.497 0.1%
56 341 0.254 0.0%
58 348.6 0.247 0.0%
60 357.3 0.388 0.1%
62 365.4 0.397 0.1%
64 374 0.428 0.1%
66 382.1 0.329 0.0%
68 390.5 0.382 0.0%
70 397.5 0.498 0.1%
72 402.7 1.016 0.2%
74 411.6 0.681 0.1%
76 419.2 1.092 0.2%
78 426.3 1.043 0.2%
80 436.4 0.445 0.1%
82 444.4 0.346 0.0%
84 451.9 0.479 0.1%
86 459.9 0.79 0.1%
88 468 0.535 0.1%
90 477 1.708 0.3%
92 482.9 0.31 0.0%
94 490.5 0.312 0.0%
96 496.7 1.049 0.2%
98 505 0.472 0.0%
100 513.1 0.391 0.0%

Quality and confidence:
param error
s 0.002

Model:
Time ~= 118.7
+ s 3.967
µs

Reads = 7 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 25.42
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 25.42
µs

Reads = 2
Writes = 2
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.71
+ n 0.231
µs

Reads = 3 + (0 * n)
Writes = 2 + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 32.44 0.059 0.1%
2 33.88 0.062 0.1%
3 35.16 0.119 0.3%
4 36.25 0.153 0.4%
5 38.83 0.115 0.2%
6 39.38 0.099 0.2%
7 39.74 0.094 0.2%
8 35.9 0.103 0.2%
9 36.98 0.114 0.3%
10 36.86 0.075 0.2%
11 37.48 0.085 0.2%
12 37.63 0.096 0.2%
13 37.7 0.051 0.1%
14 37.88 0.123 0.3%
15 37.92 0.125 0.3%
16 37.67 0.099 0.2%

Quality and confidence:
param error
n 0.027

Model:
Time ~= 35.13
+ n 0.218
µs

Reads = 3 + (0 * n)
Writes = 2 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.98
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.98
µs

Reads = 2
Writes = 2
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 17.45
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 17.45
µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 37.17
µs

Reads = 3
Writes = 3
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 37.17
µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.526
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.526
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.91
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.91
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.933
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.933
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 3.926
µs

Reads = 0
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 3.926
µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 4.082
+ v 0.008
µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v mean µs sigma µs %
0 3.955 0.031 0.7%
20 4.321 0.018 0.4%
40 4.553 0.016 0.3%
60 4.712 0.019 0.4%
80 4.894 0.025 0.5%
100 5.051 0.019 0.3%
120 5.206 0.021 0.4%
140 5.386 0.024 0.4%
160 5.537 0.046 0.8%
180 5.661 0.018 0.3%
200 5.798 0.037 0.6%
220 5.978 0.016 0.2%
240 6.19 0.043 0.6%
260 6.324 0.018 0.2%
280 6.531 0.029 0.4%
300 6.683 0.015 0.2%
320 6.851 0.039 0.5%
340 7.029 0.018 0.2%
360 7.222 0.036 0.4%
380 7.386 0.026 0.3%
400 7.536 0.027 0.3%
420 7.695 0.009 0.1%
440 7.874 0.016 0.2%
460 8.096 0.035 0.4%
480 8.253 0.029 0.3%
500 8.398 0.027 0.3%
520 8.557 0.031 0.3%
540 8.702 0.031 0.3%
560 8.87 0.033 0.3%
580 9.092 0.021 0.2%
600 9.259 0.033 0.3%
620 9.431 0.029 0.3%
640 9.625 0.02 0.2%
660 9.833 0.022 0.2%
680 10 0.022 0.2%
700 10.22 0.03 0.2%
720 10.36 0.036 0.3%
740 10.57 0.034 0.3%
760 10.81 0.055 0.5%
780 10.95 0.039 0.3%
800 11.14 0.02 0.1%
820 11.29 0.02 0.1%
840 11.47 0.05 0.4%
860 11.65 0.033 0.2%
880 11.78 0.037 0.3%
900 11.99 0.037 0.3%
920 12.19 0.026 0.2%
940 12.38 0.038 0.3%
960 12.55 0.048 0.3%
980 12.75 0.037 0.2%
1000 12.88 0.022 0.1%

Quality and confidence:
param error
v 0

Model:
Time ~= 4.08
+ v 0.009
µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 82.19
+ s 3.977
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
0 74.84 0.119 0.1%
2 88.09 0.109 0.1%
4 96.96 0.069 0.0%
6 105.2 0.11 0.1%
8 113 0.118 0.1%
10 121.5 0.144 0.1%
12 129.5 0.196 0.1%
14 137.7 0.159 0.1%
16 146.3 0.138 0.0%
18 154.3 0.216 0.1%
20 161.5 0.268 0.1%
22 169.9 0.206 0.1%
24 177.8 0.163 0.0%
26 186.2 0.231 0.1%
28 194.1 0.205 0.1%
30 201.9 0.249 0.1%
32 210.2 0.192 0.0%
34 217.4 0.172 0.0%
36 225.8 0.291 0.1%
38 234.1 0.286 0.1%
40 241.3 0.164 0.0%
42 250.3 0.218 0.0%
44 257.4 0.232 0.0%
46 265.8 0.2 0.0%
48 272.7 0.193 0.0%
50 281.7 0.288 0.1%
52 289.5 0.181 0.0%
54 297.3 0.706 0.2%
56 304.7 0.49 0.1%
58 312.5 0.357 0.1%
60 320.8 0.183 0.0%
62 329 0.18 0.0%
64 337.2 0.237 0.0%
66 345.5 0.306 0.0%
68 353.1 0.166 0.0%
70 361.1 0.117 0.0%
72 366.3 0.436 0.1%
74 375.9 0.223 0.0%
76 383.1 0.67 0.1%
78 391.7 0.399 0.1%
80 399.9 0.357 0.0%
82 407 0.497 0.1%
84 414.9 0.442 0.1%
86 422.8 0.423 0.1%
88 431.7 0.39 0.0%
90 439 0.323 0.0%
92 444.8 0.636 0.1%
94 452.5 0.372 0.0%
96 463.6 8.683 1.8%
98 486.8 5.222 1.0%
100 489.1 5.586 1.1%

Quality and confidence:
param error
s 0.004

Model:
Time ~= 81.03
+ s 4.002
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 6618
+ s 34.69
µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 375.1 3.613 0.9%
20 1699 12.45 0.7%
39 2992 6.082 0.2%
58 4259 8.436 0.1%
77 5501 4.704 0.0%
96 6731 8.264 0.1%
115 7773 10.6 0.1%
134 8891 14.75 0.1%
153 10010 14.72 0.1%
172 11100 11.5 0.1%
191 12170 16.39 0.1%
210 13220 13.71 0.1%
229 14240 7.312 0.0%
248 15230 13.08 0.0%
267 16200 5.702 0.0%
286 17150 10.16 0.0%
305 18070 16.86 0.0%
324 18960 13.88 0.0%
343 19830 13 0.0%
362 20680 13.87 0.0%
381 21490 13.21 0.0%
400 22300 12.86 0.0%
419 23070 22.44 0.0%
438 23820 10.39 0.0%
457 24530 14.69 0.0%
476 25220 15.81 0.0%
495 25910 18.53 0.0%
514 26950 63.4 0.2%
533 27150 12.91 0.0%
552 27770 21.19 0.0%
571 28340 12.48 0.0%
590 28880 14.33 0.0%
609 29410 18.32 0.0%
628 29900 12.66 0.0%
647 30370 11.64 0.0%
666 30830 22.82 0.0%
685 31250 14.92 0.0%
704 31650 18.02 0.0%
723 32020 11.8 0.0%
742 32380 20.06 0.0%
761 32690 17.28 0.0%
780 33000 16.57 0.0%
799 33260 11.29 0.0%
818 33510 10.55 0.0%
837 33750 22 0.0%
856 33940 10.61 0.0%
875 34110 14.23 0.0%
894 34270 19.2 0.0%
913 34400 18.54 0.0%
932 34500 18.68 0.0%
951 34560 11.68 0.0%
970 34620 36.03 0.1%
989 34650 10.68 0.0%

Quality and confidence:
param error
s 0.388

Model:
Time ~= 5861
+ s 34.65
µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 147.9
+ n 60.2
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 197.8 0.311 0.1%
6 501.7 0.584 0.1%
11 804.5 1.087 0.1%
16 1115 1.608 0.1%
21 1408 1.283 0.0%
26 1733 16.29 0.9%
31 2012 3.405 0.1%
36 2309 3.969 0.1%
41 2612 2.252 0.0%
46 2922 6.867 0.2%
51 3229 3.197 0.0%
56 3506 5.421 0.1%
61 3819 5.87 0.1%
66 4112 7.102 0.1%
71 4452 5.929 0.1%
76 4749 31.27 0.6%
81 5040 8.821 0.1%
86 5350 9.097 0.1%
91 5651 9.29 0.1%
96 5922 9.918 0.1%
101 6197 11.3 0.1%
106 6503 8.57 0.1%
111 6830 15.09 0.2%
116 7126 11.53 0.1%
121 7396 12.15 0.1%
126 7739 11.91 0.1%
131 8014 9.268 0.1%
136 8318 11.55 0.1%
141 8629 15.17 0.1%
146 8951 11.55 0.1%
151 9258 10.97 0.1%
156 9534 15.23 0.1%
161 9896 14.53 0.1%
166 10120 21.08 0.2%
171 10430 12.96 0.1%
176 10760 19.18 0.1%
181 11080 15.52 0.1%
186 11350 16.05 0.1%
191 11670 15.69 0.1%
196 11920 15.23 0.1%
201 12230 17.17 0.1%
206 12550 12.81 0.1%
211 12860 17.1 0.1%
216 13140 19.43 0.1%
221 13430 11.32 0.0%
226 13790 16.19 0.1%
231 14070 11.31 0.0%
236 14400 17.98 0.1%
241 14700 19.97 0.1%
246 14980 24.8 0.1%
251 15180 16.78 0.1%
256 15470 15.54 0.1%

Quality and confidence:
param error
n 0.017

Model:
Time ~= 149.2
+ n 60.2
µs

Reads = 11 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 188.8
+ n 79.16
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n mean µs sigma µs %
1 252.3 0.425 0.1%
6 654.8 1.143 0.1%
11 1057 1.401 0.1%
16 1453 2.867 0.1%
21 1859 4.477 0.2%
26 2247 4.936 0.2%
31 2640 2.958 0.1%
36 3034 5.037 0.1%
41 3442 23.36 0.6%
46 3849 12.54 0.3%
51 4229 8.583 0.2%
56 4607 8.504 0.1%
61 5020 5.474 0.1%
66 5429 10.85 0.1%
71 5814 9.215 0.1%
76 6189 12.31 0.1%
81 6562 12.91 0.1%
86 7069 57.69 0.8%
91 7447 16.68 0.2%
96 7847 14.69 0.1%
101 8220 10.1 0.1%
106 8554 8.491 0.0%
111 9004 14.17 0.1%
116 9386 14.33 0.1%
121 9768 25.19 0.2%
126 10150 26.45 0.2%
131 10580 9.968 0.0%
136 10890 7.389 0.0%
141 11290 7.49 0.0%
146 11720 30.32 0.2%
151 12130 18.22 0.1%
156 12480 16.07 0.1%
161 12930 7.525 0.0%
166 13290 22.61 0.1%
171 13720 79.62 0.5%
176 14190 28.06 0.1%
181 14500 27.37 0.1%
186 14890 17.09 0.1%
191 15340 25.43 0.1%
196 15710 19.74 0.1%
201 16120 93.51 0.5%
206 16510 33.04 0.2%
211 16900 13.37 0.0%
216 17330 16.88 0.0%
221 17700 25.33 0.1%
226 18020 16.89 0.0%
231 18480 27.25 0.1%
236 18920 18.89 0.0%
241 19230 34.84 0.1%
246 19680 18.65 0.0%
251 20050 33.07 0.1%
256 20400 20.54 0.1%

Quality and confidence:
param error
n 0.023

Model:
Time ~= 191.4
+ n 79.16
µs

Reads = 12 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 50.15
+ l 0.105
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
l mean µs sigma µs %
1 50.15 0.196 0.3%
2 49.85 0.1 0.2%
3 49.87 0.092 0.1%
4 49.95 0.055 0.1%
5 50.65 0.102 0.2%
6 50.67 0.108 0.2%
7 50.77 0.071 0.1%
8 50.74 0.112 0.2%
9 51.42 0.089 0.1%
10 51.46 0.087 0.1%
11 51.26 0.036 0.0%
12 51.68 0.087 0.1%
13 51.9 0.098 0.1%
14 51.79 0.083 0.1%
15 51.79 0.144 0.2%
16 51.84 0.102 0.1%
17 52.57 0.067 0.1%
18 52.53 0.119 0.2%
19 52.84 0.1 0.1%
20 52.68 0.116 0.2%
21 52.52 0.073 0.1%
22 52.87 0.112 0.2%
23 52.87 0.062 0.1%
24 52.93 0.131 0.2%
25 52.83 0.069 0.1%
26 52.84 0.089 0.1%
27 52.74 0.092 0.1%
28 52.97 0.142 0.2%
29 52.85 0.092 0.1%
30 52.82 0.069 0.1%
31 52.75 0.065 0.1%
32 53.03 0.096 0.1%

Quality and confidence:
param error
l 0.002

Model:
Time ~= 50.14
+ l 0.106
µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ e 39.07
µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
e mean µs sigma µs %
1 49.51 0.142 0.2%
2 81.56 0.119 0.1%
3 111.3 0.202 0.1%
4 144.3 0.373 0.2%
5 174.4 0.333 0.1%
6 204.2 0.173 0.0%
7 237 0.44 0.1%
8 266.9 0.414 0.1%
9 298.2 0.865 0.2%
10 331.5 0.651 0.1%
11 362.6 0.598 0.1%
12 394.8 0.596 0.1%
13 424.1 0.67 0.1%
14 459.5 0.549 0.1%
15 491.7 0.475 0.0%
16 526.4 0.866 0.1%
17 559.3 0.791 0.1%
18 589.8 0.829 0.1%
19 627.9 0.885 0.1%
20 661.1 1.067 0.1%
21 692.9 1.205 0.1%
22 727.5 1.036 0.1%
23 762 1.312 0.1%
24 796.9 1.702 0.2%
25 834.9 1.068 0.1%
26 873.7 1.409 0.1%
27 909 1.406 0.1%
28 944.3 1.785 0.1%
29 980.1 2.672 0.2%
30 1019 2.592 0.2%
31 1053 2.33 0.2%
32 1085 1.139 0.1%
33 1124 2.134 0.1%
34 1157 1.095 0.0%
35 1197 1.999 0.1%
36 1228 2.925 0.2%
37 1255 1.971 0.1%
38 1294 2.324 0.1%
39 1340 1.751 0.1%
40 1368 1.712 0.1%
41 1407 3.463 0.2%
42 1446 2.121 0.1%
43 1478 3.209 0.2%
44 1531 2.242 0.1%
45 1623 13.27 0.8%
46 1639 4.057 0.2%
47 1671 3.514 0.2%
48 1709 12.47 0.7%
49 1715 2.598 0.1%
50 1754 2.199 0.1%
51 1792 4.285 0.2%
52 1850 4.495 0.2%
53 1886 6.305 0.3%
54 1924 3.372 0.1%
55 1972 5.473 0.2%
56 1998 4.528 0.2%
57 2029 1.758 0.0%
58 2077 5.736 0.2%
59 2120 2.187 0.1%
60 2159 2.734 0.1%
61 2202 4.796 0.2%
62 2240 3.355 0.1%
63 2284 7.211 0.3%
64 2330 4.559 0.1%
65 2372 9.251 0.3%
66 2399 5.715 0.2%
67 2448 3.773 0.1%
68 2498 5.779 0.2%
69 2521 3.489 0.1%
70 2577 4.949 0.1%
71 2608 3.911 0.1%
72 2675 4.968 0.1%
73 2704 5.53 0.2%
74 2737 3.926 0.1%
75 2794 6.326 0.2%
76 2835 7.174 0.2%
77 2864 4.296 0.1%
78 2923 5.39 0.1%
79 2939 5.109 0.1%
80 3004 7.114 0.2%
81 3045 4.369 0.1%
82 3097 4.41 0.1%
83 3135 5.597 0.1%
84 3183 5.811 0.1%
85 3239 4.393 0.1%
86 3291 6.204 0.1%
87 3324 8.485 0.2%
88 3369 5.51 0.1%
89 3420 10.28 0.3%
90 3477 4.342 0.1%
91 3496 4.14 0.1%
92 3543 10.9 0.3%
93 3593 9.834 0.2%
94 3629 6.873 0.1%
95 3688 7.91 0.2%
96 3732 8.759 0.2%
97 3759 5.288 0.1%
98 3938 19.13 0.4%
99 3925 29.41 0.7%
100 3918 3.64 0.0%

Quality and confidence:
param error
e 0.072

Model:
Time ~= 0
+ e 39.23
µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 101.7
+ s 3.961
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
s mean µs sigma µs %
1 103.4 0.132 0.1%
2 108.5 0.151 0.1%
3 112.8 0.119 0.1%
4 116.5 0.168 0.1%
5 120.9 0.185 0.1%
6 124.4 0.085 0.0%
7 128.4 0.123 0.0%
8 133.3 0.184 0.1%
9 137.1 0.205 0.1%
10 140.8 0.175 0.1%
11 144.6 0.212 0.1%
12 148.7 0.089 0.0%
13 153.7 0.237 0.1%
14 157.6 0.164 0.1%
15 161.4 0.15 0.0%
16 165.1 0.16 0.0%
17 169.8 0.146 0.0%
18 173 0.119 0.0%
19 177.2 0.317 0.1%
20 180.8 0.22 0.1%
21 184.6 0.145 0.0%
22 188.2 0.282 0.1%
23 192.1 0.259 0.1%
24 196.3 0.155 0.0%
25 200.8 0.178 0.0%
26 204.6 0.314 0.1%
27 209 0.197 0.0%
28 212.3 0.214 0.1%
29 217.3 0.224 0.1%
30 221.3 0.239 0.1%
31 225.1 0.179 0.0%
32 228.8 0.169 0.0%
33 232.5 0.184 0.0%
34 237.1 0.244 0.1%
35 241.2 0.34 0.1%
36 244.7 0.299 0.1%
37 248.3 0.233 0.0%
38 252.4 0.235 0.0%
39 256.9 0.237 0.0%
40 261.4 0.242 0.0%
41 265.1 0.185 0.0%
42 268.7 0.326 0.1%
43 272 0.282 0.1%
44 275.7 0.157 0.0%
45 280.2 0.256 0.0%
46 285 0.17 0.0%
47 288.5 0.293 0.1%
48 292 0.097 0.0%
49 296.7 0.198 0.0%
50 300.6 0.123 0.0%
51 304.8 0.263 0.0%
52 308.2 0.239 0.0%
53 312.3 0.257 0.0%
54 315.7 0.252 0.0%
55 319.9 0.253 0.0%
56 323.1 0.352 0.1%
57 328 0.382 0.1%
58 330.9 0.309 0.0%
59 334.6 0.406 0.1%
60 339.3 0.477 0.1%
61 343.6 0.282 0.0%
62 347.3 0.375 0.1%
63 351.7 0.442 0.1%
64 355.3 0.421 0.1%
65 359.5 0.47 0.1%
66 364.1 0.312 0.0%
67 367.7 0.278 0.0%
68 371.6 0.478 0.1%
69 375.5 0.407 0.1%
70 379.7 0.387 0.1%
71 383.2 0.377 0.0%
72 386.4 0.309 0.0%
73 390.1 0.36 0.0%
74 395 0.385 0.0%
75 398.8 0.262 0.0%
76 402.7 0.229 0.0%
77 405.4 0.294 0.0%
78 409.8 0.482 0.1%
79 414.3 0.368 0.0%
80 418.4 0.292 0.0%
81 421.7 0.477 0.1%
82 426 0.241 0.0%
83 430 0.475 0.1%
84 433.7 0.44 0.1%
85 437.5 0.254 0.0%
86 440.7 0.402 0.0%
87 444 0.309 0.0%
88 449.8 0.289 0.0%
89 453.7 0.381 0.0%
90 457.7 0.45 0.0%
91 461.3 0.319 0.0%
92 464.2 0.276 0.0%
93 469.7 1.073 0.2%
94 473.8 1.538 0.3%
95 477.8 1.281 0.2%
96 480.6 0.279 0.0%
97 486.5 0.547 0.1%
98 490.5 0.253 0.0%
99 493.9 0.577 0.1%
100 498.3 0.241 0.0%

Quality and confidence:
param error
s 0

Model:
Time ~= 101.7
+ s 3.959
µs

Reads = 4 + (0 * s)
Writes = 8 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 902.6
+ n 118.6
µs

Reads = 10 + (4 * v) + (3 * n)
Writes = 8 + (3 * v) + (0 * n)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n mean µs sigma µs %
1 100 4560 8.344 0.1%
2 100 5404 9.166 0.1%
3 100 6083 11.7 0.1%
4 100 6801 6.14 0.0%
5 100 7754 10.37 0.1%
6 100 8600 12.25 0.1%
7 100 9485 10.53 0.1%
8 100 10450 15.25 0.1%
9 100 11620 9.28 0.0%
10 1 896.6 1.027 0.1%
10 2 1028 1.067 0.1%
10 3 1154 0.862 0.0%
10 4 1281 1.152 0.0%
10 5 1391 2.027 0.1%
10 6 1508 1.171 0.0%
10 7 1636 1.115 0.0%
10 8 1765 2.209 0.1%
10 9 1879 1.711 0.0%
10 10 2051 2.107 0.1%
10 11 2170 2.263 0.1%
10 12 2294 2.69 0.1%
10 13 2423 1.588 0.0%
10 14 2553 3.289 0.1%
10 15 2674 1.938 0.0%
10 16 2794 4.082 0.1%
10 17 2922 1.752 0.0%
10 18 3047 7.165 0.2%
10 19 3170 4.847 0.1%
10 20 3293 6.53 0.1%
10 21 3420 9.842 0.2%
10 22 3528 3.541 0.1%
10 23 3651 2.137 0.0%
10 24 3770 5.544 0.1%
10 25 3898 2.284 0.0%
10 26 4049 7.039 0.1%
10 27 4161 7.2 0.1%
10 28 4272 3.645 0.0%
10 29 4403 1.681 0.0%
10 30 4519 8.116 0.1%
10 31 4633 6.592 0.1%
10 32 4762 8.205 0.1%
10 33 4894 7.371 0.1%
10 34 5021 14.78 0.2%
10 35 5147 11.84 0.2%
10 36 5263 8.981 0.1%
10 37 5368 9.025 0.1%
10 38 5478 4.77 0.0%
10 39 5616 9.518 0.1%
10 40 5713 5.045 0.0%
10 41 5838 12.22 0.2%
10 42 5962 11.26 0.1%
10 43 6110 11.85 0.1%
10 44 6221 6.936 0.1%
10 45 6300 12.67 0.2%
10 46 6414 6.76 0.1%
10 47 6507 9.806 0.1%
10 48 6639 10.96 0.1%
10 49 6765 11.91 0.1%
10 50 6887 7.767 0.1%
10 51 7021 14.2 0.2%
10 52 7118 6.311 0.0%
10 53 7307 11.16 0.1%
10 54 7479 40.41 0.5%
10 55 7540 31.16 0.4%
10 56 7659 8.719 0.1%
10 57 7734 7.736 0.1%
10 58 7883 12.03 0.1%
10 59 7991 13.6 0.1%
10 60 8119 12.11 0.1%
10 61 8220 14.27 0.1%
10 62 8328 11.91 0.1%
10 63 8434 14.35 0.1%
10 64 8574 9.995 0.1%
10 65 8697 13.86 0.1%
10 66 8794 14.61 0.1%
10 67 8942 10.88 0.1%
10 68 9024 9.641 0.1%
10 69 9130 14.05 0.1%
10 70 9234 12.45 0.1%
10 71 9377 12.28 0.1%
10 72 9531 13.48 0.1%
10 73 9825 21.87 0.2%
10 74 9750 13.03 0.1%
10 75 9850 8.656 0.0%
10 76 9931 11.39 0.1%
10 77 10030 15.32 0.1%
10 78 10180 10.07 0.0%
10 79 10280 7.831 0.0%
10 80 10440 13.54 0.1%
10 81 10530 17.04 0.1%
10 82 10650 5.737 0.0%
10 83 10790 14.97 0.1%
10 84 10880 12.09 0.1%
10 85 10940 12.21 0.1%
10 86 11030 13.44 0.1%
10 87 11180 10.5 0.0%
10 88 11310 9.174 0.0%
10 89 11410 14.23 0.1%
10 90 11530 18.68 0.1%
10 91 11620 7.212 0.0%
10 92 11730 11.82 0.1%
10 93 11850 17.82 0.1%
10 94 11950 14.7 0.1%
10 95 12060 6.978 0.0%
10 96 12150 22.41 0.1%
10 97 12270 19.21 0.1%
10 98 12390 16.08 0.1%
10 99 12530 8.278 0.0%
10 100 12650 18.97 0.1%

Quality and confidence:
param error
v 2.375
n 0.119

Model:
Time ~= 0
+ v 952.1
+ n 117.9
µs

Reads = 10 + (4 * v) + (3 * n)
Writes = 8 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "submit_solution_better", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ v 0.415
+ n 0.37
+ a 99.49
+ w 8.323
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
v n a w mean µs sigma µs %
200 1000 400 100 41090 52.14 0.1%
204 1000 400 100 41060 33.04 0.0%
208 1000 400 100 41020 63.42 0.1%
212 1000 400 100 40980 64.63 0.1%
216 1000 400 100 41100 36.5 0.0%
220 1000 400 100 40910 65.99 0.1%
224 1000 400 100 40880 56.83 0.1%
228 1000 400 100 40960 51.29 0.1%
232 1000 400 100 40920 46.29 0.1%
236 1000 400 100 40970 41.8 0.1%
240 1000 400 100 40980 35.63 0.0%
244 1000 400 100 40990 50.49 0.1%
248 1000 400 100 40980 41.64 0.1%
252 1000 400 100 40960 92.19 0.2%
256 1000 400 100 40940 64.28 0.1%
260 1000 400 100 41120 62.65 0.1%
264 1000 400 100 40960 41.51 0.1%
268 1000 400 100 40890 30.97 0.0%
272 1000 400 100 41190 20.21 0.0%
276 1000 400 100 41190 68.01 0.1%
280 1000 400 100 41090 56.79 0.1%
284 1000 400 100 41010 32.68 0.0%
288 1000 400 100 41060 46.64 0.1%
292 1000 400 100 41020 54.4 0.1%
296 1000 400 100 41010 57.16 0.1%
300 1000 400 100 40920 49.94 0.1%
304 1000 400 100 41050 60.55 0.1%
308 1000 400 100 41100 44.02 0.1%
312 1000 400 100 41010 57.37 0.1%
316 1000 400 100 41150 25.85 0.0%
320 1000 400 100 41130 37.1 0.0%
324 1000 400 100 41040 55.04 0.1%
328 1000 400 100 41070 46.54 0.1%
332 1000 400 100 40980 27.67 0.0%
336 1000 400 100 41260 45.35 0.1%
340 1000 400 100 41070 44.13 0.1%
344 1000 400 100 41040 41.13 0.1%
348 1000 400 100 41240 28.14 0.0%
352 1000 400 100 40970 69.45 0.1%
356 1000 400 100 41080 55.82 0.1%
360 1000 400 100 41090 47.91 0.1%
364 1000 400 100 41010 18.57 0.0%
368 1000 400 100 41010 33.13 0.0%
372 1000 400 100 41080 41.4 0.1%
376 1000 400 100 40960 24.08 0.0%
380 1000 400 100 41190 43.3 0.1%
384 1000 400 100 40900 67.02 0.1%
388 1000 400 100 41220 43.78 0.1%
392 1000 400 100 41160 26.47 0.0%
396 1000 400 100 41180 52.32 0.1%
400 500 400 100 40820 48.32 0.1%
400 510 400 100 40720 30.76 0.0%
400 520 400 100 40870 39.74 0.0%
400 530 400 100 41010 48.77 0.1%
400 540 400 100 40980 29.05 0.0%
400 550 400 100 40810 46.96 0.1%
400 560 400 100 40910 56.66 0.1%
400 570 400 100 40960 59.36 0.1%
400 580 400 100 40980 59.94 0.1%
400 590 400 100 40960 37.07 0.0%
400 600 400 100 40880 61.86 0.1%
400 610 400 100 41000 35.17 0.0%
400 620 400 100 40890 40.9 0.1%
400 630 400 100 41050 37.56 0.0%
400 640 400 100 40960 37.38 0.0%
400 650 400 100 41060 45.5 0.1%
400 660 400 100 40940 46.95 0.1%
400 670 400 100 41050 47.43 0.1%
400 680 400 100 41060 41.53 0.1%
400 690 400 100 40930 49.77 0.1%
400 700 400 100 41020 25.13 0.0%
400 710 400 100 40980 27.59 0.0%
400 720 400 100 41010 36.44 0.0%
400 730 400 100 40940 59.05 0.1%
400 740 400 100 40960 42.37 0.1%
400 750 400 100 41210 23.05 0.0%
400 760 400 100 41070 39.86 0.0%
400 770 400 100 41060 43 0.1%
400 780 400 100 41130 61.47 0.1%
400 790 400 100 41190 38.32 0.0%
400 800 400 100 41180 32.35 0.0%
400 810 400 100 41000 34 0.0%
400 820 400 100 41170 69.52 0.1%
400 830 400 100 41090 70.7 0.1%
400 840 400 100 41070 38.33 0.0%
400 850 400 100 41110 57.75 0.1%
400 860 400 100 41230 70.32 0.1%
400 870 400 100 41130 45.23 0.1%
400 880 400 100 41110 32.39 0.0%
400 890 400 100 41170 21.85 0.0%
400 900 400 100 41030 50.46 0.1%
400 910 400 100 41000 37.57 0.0%
400 920 400 100 41100 66.81 0.1%
400 930 400 100 40880 49.73 0.1%
400 940 400 100 41020 53.5 0.1%
400 950 400 100 41110 50.26 0.1%
400 960 400 100 41080 44.88 0.1%
400 970 400 100 41030 62.05 0.1%
400 980 400 100 41250 35.92 0.0%
400 990 400 100 41070 37.6 0.0%
400 1000 200 100 20980 31.14 0.1%
400 1000 204 100 21400 29.61 0.1%
400 1000 208 100 21790 11.14 0.0%
400 1000 212 100 22310 23.65 0.1%
400 1000 216 100 22690 26.86 0.1%
400 1000 220 100 23120 12.73 0.0%
400 1000 224 100 23480 18.91 0.0%
400 1000 228 100 23900 22.67 0.0%
400 1000 232 100 24300 30.45 0.1%
400 1000 236 100 24700 13.03 0.0%
400 1000 240 100 25140 30.2 0.1%
400 1000 244 100 25510 21.08 0.0%
400 1000 248 100 25870 19.52 0.0%
400 1000 252 100 26280 26.69 0.1%
400 1000 256 100 26680 22.7 0.0%
400 1000 260 100 27060 27.33 0.1%
400 1000 264 100 27510 25.98 0.0%
400 1000 268 100 27870 26.39 0.0%
400 1000 272 100 28270 29.71 0.1%
400 1000 276 100 28730 48.74 0.1%
400 1000 280 100 29100 42.79 0.1%
400 1000 284 100 29490 16.95 0.0%
400 1000 288 100 29900 22.76 0.0%
400 1000 292 100 30300 38.34 0.1%
400 1000 296 100 30650 32.71 0.1%
400 1000 300 100 31020 21.67 0.0%
400 1000 304 100 31390 25.48 0.0%
400 1000 308 100 31830 36.55 0.1%
400 1000 312 100 32270 47.8 0.1%
400 1000 316 100 32680 26.23 0.0%
400 1000 320 100 33020 31.25 0.0%
400 1000 324 100 33420 36.76 0.1%
400 1000 328 100 33880 61.96 0.1%
400 1000 332 100 34270 27.14 0.0%
400 1000 336 100 34620 46 0.1%
400 1000 340 100 34970 37.18 0.1%
400 1000 344 100 35360 38.57 0.1%
400 1000 348 100 35780 27.69 0.0%
400 1000 352 100 36130 39.95 0.1%
400 1000 356 100 36610 54.12 0.1%
400 1000 360 100 37030 43.92 0.1%
400 1000 364 100 37410 49.12 0.1%
400 1000 368 100 37820 44.03 0.1%
400 1000 372 100 38200 36.23 0.0%
400 1000 376 100 38580 56.7 0.1%
400 1000 380 100 38960 32.32 0.0%
400 1000 384 100 39420 52.87 0.1%
400 1000 388 100 39780 43.8 0.1%
400 1000 392 100 40230 28.67 0.0%
400 1000 396 100 40630 31.99 0.0%
400 1000 400 16 40600 71.1 0.1%
400 1000 400 17 40390 36.48 0.0%
400 1000 400 18 40510 92.04 0.2%
400 1000 400 19 40370 29.68 0.0%
400 1000 400 20 40600 50.2 0.1%
400 1000 400 21 40570 34.78 0.0%
400 1000 400 22 40580 58.81 0.1%
400 1000 400 23 40590 56.15 0.1%
400 1000 400 24 40620 42.92 0.1%
400 1000 400 25 40500 27.42 0.0%
400 1000 400 26 40490 64.74 0.1%
400 1000 400 27 40390 26.6 0.0%
400 1000 400 28 40670 51.07 0.1%
400 1000 400 29 40490 60.24 0.1%
400 1000 400 30 40490 43.47 0.1%
400 1000 400 31 40410 38.81 0.0%
400 1000 400 32 40490 37.57 0.0%
400 1000 400 33 40570 52.2 0.1%
400 1000 400 34 40630 22.26 0.0%
400 1000 400 35 40640 30.27 0.0%
400 1000 400 36 40580 70.29 0.1%
400 1000 400 37 40650 55.43 0.1%
400 1000 400 38 40610 47.89 0.1%
400 1000 400 39 40800 50.21 0.1%
400 1000 400 40 40860 28.54 0.0%
400 1000 400 41 40710 44.62 0.1%
400 1000 400 42 40770 40.28 0.0%
400 1000 400 43 40600 58.92 0.1%
400 1000 400 44 40960 44.16 0.1%
400 1000 400 45 40760 32.99 0.0%
400 1000 400 46 40960 45.9 0.1%
400 1000 400 47 40860 62.81 0.1%
400 1000 400 48 40910 50.85 0.1%
400 1000 400 49 40830 53.96 0.1%
400 1000 400 50 40860 32.46 0.0%
400 1000 400 51 40820 45.59 0.1%
400 1000 400 52 40660 44.36 0.1%
400 1000 400 53 40650 23.04 0.0%
400 1000 400 54 40690 62.86 0.1%
400 1000 400 55 40720 32.38 0.0%
400 1000 400 56 40690 32.58 0.0%
400 1000 400 57 40740 54.14 0.1%
400 1000 400 58 40780 41.17 0.1%
400 1000 400 59 40890 34.15 0.0%
400 1000 400 60 40810 27.43 0.0%
400 1000 400 61 40790 62.97 0.1%
400 1000 400 62 40860 57.39 0.1%
400 1000 400 63 40790 25.87 0.0%
400 1000 400 64 40830 34.35 0.0%
400 1000 400 65 40900 82.66 0.2%
400 1000 400 66 40970 44.64 0.1%
400 1000 400 67 40900 37.59 0.0%
400 1000 400 68 41030 35.76 0.0%
400 1000 400 69 40940 42.35 0.1%
400 1000 400 70 40870 45.19 0.1%
400 1000 400 71 40840 57.6 0.1%
400 1000 400 72 41080 35.5 0.0%
400 1000 400 73 41000 67.95 0.1%
400 1000 400 74 40990 35.83 0.0%
400 1000 400 75 40820 56.98 0.1%
400 1000 400 76 40870 49.71 0.1%
400 1000 400 77 41080 21.59 0.0%
400 1000 400 78 41060 52.22 0.1%
400 1000 400 79 41160 42.81 0.1%
400 1000 400 80 40990 29.62 0.0%
400 1000 400 81 41000 28.66 0.0%
400 1000 400 82 41040 78.42 0.1%
400 1000 400 83 41060 45.97 0.1%
400 1000 400 84 41000 39.39 0.0%
400 1000 400 85 41120 29.98 0.0%
400 1000 400 86 41110 88.96 0.2%
400 1000 400 87 41270 35.23 0.0%
400 1000 400 88 41160 52.69 0.1%
400 1000 400 89 41290 44.64 0.1%
400 1000 400 90 41130 50.86 0.1%
400 1000 400 91 41210 39.22 0.0%
400 1000 400 92 41130 49.11 0.1%
400 1000 400 93 41150 50.75 0.1%
400 1000 400 94 41050 34.79 0.0%
400 1000 400 95 41070 35.99 0.0%
400 1000 400 96 41090 19.86 0.0%
400 1000 400 97 41180 52.95 0.1%
400 1000 400 98 41270 61.42 0.1%
400 1000 400 99 41150 60.3 0.1%
400 1000 400 100 40990 47.93 0.1%

Quality and confidence:
param error
v 0.05
n 0.02
a 0.05
w 0.103

Model:
Time ~= 0
+ v 0.733
+ n 0.405
+ a 100.4
+ w 7.279
µs

Reads = 6 + (0 * v) + (0 * n) + (4 * a) + (1 * w)
Writes = 2 + (0 * v) + (0 * n) + (0 * a) + (0 * w)

[tomusdrw]

lgtm, I'm not super knowledgable about staking though.

[kianenigma]

I actually realised that this is not useful because currently we don't decoding time into account.

[kianenigma]

Okay, leaving open to investigate integrating decode time in the benchmark tool @shawntabrizi @thiolliere

[kianenigma]

For now, I will made a new PR to make the important change to polkadot, namely reducing the on_initialize a bit. I will leave this PR open for a playground of investigating encode/decode affect on weights.

paritytech/polkadot#1838

[kianenigma]

Not needed for now. Sometime soon and somehow we should consider measuring encode decode time in benchmarks. The approach of this PR is a good starting point. Nonetheless, closing to de-clutter my ever growing todo list.