Support existing test types with ASTF

+ Add UDP_CPS, TCP_CPS, UDP_PPS and TCP_PPS suites.
 + Update existing cps traffic profiles.
 + Add missing traffic profiles.
 + UDP:
  + Single burst of 32 packets was confirmed as safe enough for TRex.
  + Maybe 64 could work, but not enough testing for that.
  + Multiple bursts have lead to reduced TRex performance,
    as overlaping bursts (from different client instances)
    tend to fill up the buffers.
 + TCP:
  + Data size set to 11111 bytes, completely arbitrarily.
  + Results look reasonable, so I have kept that.
  - MSS not set at all
 - No tested support for frame size other than 64B.
  - Frame size does not even factor into TCP profiles.
 + So other frame sizes are skipped in autogen.
+ Update tags in related suites.
 - HOSTS_{n} and SRC_USER_{n} should be unified.
 - Questionable clarification on difference between IP4BASE and SCALE.
+ Add NAT state resetters to tests that need them.
 + Resetter is called (if set) before each measurement.
 + If ramp-up is detected, resetter is not set.
+ Rename "mult" argument to "multiplier".
+ Abstracted from packets to transactions.
 + Transaction corresponds to profile.
 + TRex multiplier argument sets target rate in transactions per second.
 + The familiar STL traffic:
  + Bidirectional is considered to be 2 packets per transaction.
  + Unidirectional is considered to be 1 packet per transaction.
 + The newer ASTF traffic:
  + 4 subtypes, each has different number of packets per transaction.
 + For max rate computation:
  + Packets in the more numerous direction are considered.
+ Rely on TRex reported traffic duration for ASTF:
 + Use the server side value.
  - Client side value is higher by an overhead.
  - TRex is not sending traffic during that time.
 + Remove delays from traffic profiles.
  - Those delays would increase the reprted traffic time.
+ Support for scale lmited trials.
 + Only for ASTF profiles, each ASTF profile has limited scale.
 + Scale defined in suite variables.
 + For TRex to send all transactions provided duration value is ignored.
  + The appropriate value is computed in TrafficGenerator.
  + An ad-hoc time constant is added to match the TRex client side time overhead.
  + The profile driver receives the computed duration.
  + Measurement for PLRsearch add a sleep if the computed duration is smaller.
 + Alternative argument for search algos if scale is limited.
  + Both need higher timeout to accomodate big scales.
  + MLRsearch can afford fewer phases.
 + Added a parameter to optionally shorten the duration.
  + Use short duration for runtime stats trial and failure stats trial.
+ Use very large keepalive values in udp profiles to avoid ka packets.
+ No polling in ASTF profile driver.
 - Polling could eliminate the time overhead value.
 + But polling proved to introduce some loss, affecting the results.
+ Handle duration stretching in ASTF by stopping traffic.
 + The stop has several steps so that:
  + The traffic is really stopped entirely.
  + Late packets do not count (maybe as errors).
  + Stats are preserved to read for results (and cleared afterwards).
 + Several quantities added to ReceiveRateMeasurement:
  + Original target duration is preserved (algos need that).
  + Input estimate (tps) for early search iterations.
  + Output estimate (maybe pps) for MRR output.
  + Strict result (unsent counts as loss) for NDR.
+ Use L2 counters (opackets, ipackets) where possible.
 - TRex has trouble processing packets for the L7 ones at high loads.
+ Remove warmup from profile drivers and keywords.
 + Suites should call "Send ramp-up traffic" explicitly if needed.
+ Added parsing for few more counters.
 + Both to use in formulas or just for debug purposes.
- Only 64B cases in autogen, framesize support to be added later.
+ Latency streams during search can be enabled via PERF_USE_LATENCY env var.
+ MLRsearch improvments:
 + Rename argument names to min_rate and max_rate.
 + Use relative receive rate in initial phase.
+ PLRsearch improvements:
 + Careful computation when output (pps) does not match input (tps).
 + Use geometric distribution (instead of Poisson).
  + Helps agains math errors.
  + This should improve estimate stability.
  - But in practice big losses still lead to significant jumps.
+ Traffic generator improvements:
 + send_traffic_on_tg now calls the full set_rate_provider_defaults.
 + _send_traffic_on_tg_internal for the logic without provider defaults.
  + As the internal function is re-used by measure() without affecting defaults.
 + Move _parse_traffic_results just before get_measurement_result.
  + As the latter uses fields set bu the former, it is now easier to read.
 + Multiple sources for approximate duration.
  + Tried from more precise to more available.
 + Includes logic for _pps tests (added in later change).
 + Move explicit type conversions to earlier occurences.
+ Profile driver output field uses semicolons to simplify parsing.
+ Performance Robot lib file split to several smaller ones.
 + performance_actions.robot:
  + Hosts Additional Statistics Action For * keywords.
 + performance_display.robot:
  + Hosts keyword for displaying and verifying results.
  + Change test message to use the correct unit (pps or cps).
 + performance_limits.robot renamed to performance_vars.robot
  + Added many keywords, mostly for accessing test variables.
   + Moved variables for Policer into a new keyword there.
  + Some keywords need sophisticated logic.
  - Other are basically Get Variable Value.
   + But in future more logic can be added, without editing callers.
  + Documentation for the new keywords acts as a documentation for test variables.
 + performance_utils.robot has the rest.
  + Eliminated arguments if the value is in test variable.
  + Small improvements to documentation.
  - Still not enough cleanup with respect to arguments and test variables.
 + Keywords are sorted alphabetically now in each one.
+ Suites:
 + Unified variables table:
  + No colons in comments.
  + ${n_hosts}, ${n_ports} and use them instead hardcoded numbers.
 + Add -cps to existing cps suite names.
  + Remove "trial data overwrite".
  + Compute max rate as in STL suites.
 + Each NAT suite has ip4base suite to compare results to.
  - Those act as indirect TRex calibration.
  - VPP does not lose packets in those.
 + Latency in ASTF suites is disabled hard.
  - As we do not support latency in ASTF profiles yet.
 + Unidirectional tests governed by suite variable, not an argument.
+ Write long argument lists vertically.
 + Prefer to use argument names.
 + In Python, also the last argument is followed by comma.
 + It makes renaming and reordering easier.
 + Similarly applies to prints with long lists of values.
+ A TODO to update api crc file comments.

Change-Id: I84729355edbec051298a9de1162107f88ff5737d
Signed-off-by: Vratko Polak <vrpolak@cisco.com>

1 files changed, 14 insertions, 13 deletions

diff --git a/resources/libraries/python/PLRsearch/PLRsearch.py b/resources/libraries/python/PLRsearch/PLRsearch.py
index ec58fbd10f..226b482d76 100644
--- a/resources/libraries/python/PLRsearch/PLRsearch.py
+++ b/resources/libraries/python/PLRsearch/PLRsearch.py
@@ -54,7 +54,7 @@ class PLRsearch:
 
     def __init__(
             self, measurer, trial_duration_per_trial, packet_loss_ratio_target,
-            trial_number_offset=0, timeout=1800.0, trace_enabled=False):
+            trial_number_offset=0, timeout=7200.0, trace_enabled=False):
         """Store rate measurer and additional parameters.
 
         The measurer must never report negative loss count.
@@ -205,7 +205,7 @@ class PLRsearch:
             if (trial_number - self.trial_number_offset) <= 1:
                 next_load = max_rate
             elif (trial_number - self.trial_number_offset) <= 3:
-                next_load = (measurement.receive_rate / (
+                next_load = (measurement.relative_receive_rate / (
                     1.0 - self.packet_loss_ratio_target))
             else:
                 next_load = (avg1 + avg2) / 2.0
@@ -439,7 +439,7 @@ class PLRsearch:
         :param lfit_func: Fitting function, typically lfit_spread or lfit_erf.
         :param trial_result_list: List of trial measurement results.
         :param mrr: The mrr parameter for the fitting function.
-        :param spread: The spread parameter for the fittinmg function.
+        :param spread: The spread parameter for the fitting function.
         :type trace: function (str, object) -> None
         :type lfit_func: Function from 3 floats to float.
         :type trial_result_list: list of MLRsearch.ReceiveRateMeasurement
@@ -455,20 +455,21 @@ class PLRsearch:
             trace(u"for tr", result.target_tr)
             trace(u"lc", result.loss_count)
             trace(u"d", result.duration)
-            log_avg_loss_per_second = lfit_func(
+            # _rel_ values use units of target_tr (transactions per second).
+            log_avg_rel_loss_per_second = lfit_func(
                 trace, result.target_tr, mrr, spread
             )
-            log_avg_loss_per_trial = (
-                log_avg_loss_per_second + math.log(result.duration)
+            # _abs_ values use units of loss count (maybe packets).
+            # There can be multiple packets per transaction.
+            log_avg_abs_loss_per_trial = log_avg_rel_loss_per_second + math.log(
+                result.transmit_count / result.target_tr
             )
-            # Poisson probability computation works nice for logarithms.
-            log_trial_likelihood = (
-                result.loss_count * log_avg_loss_per_trial
-                - math.exp(log_avg_loss_per_trial)
-            )
-            log_trial_likelihood -= math.lgamma(1 + result.loss_count)
+            # Geometric probability computation for logarithms.
+            log_trial_likelihood = log_plus(0.0, -log_avg_abs_loss_per_trial)
+            log_trial_likelihood *= -result.loss_count
+            log_trial_likelihood -= log_plus(0.0, +log_avg_abs_loss_per_trial)
             log_likelihood += log_trial_likelihood
-            trace(u"avg_loss_per_trial", math.exp(log_avg_loss_per_trial))
+            trace(u"avg_loss_per_trial", math.exp(log_avg_abs_loss_per_trial))
             trace(u"log_trial_likelihood", log_trial_likelihood)
         return log_likelihood