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Commit 50d99f08 authored by Christian Klarhorst's avatar Christian Klarhorst
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Change dir structure

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.gitlab-ci.yml
+ 3
− 2
View file @ 50d99f08
......@@ -13,8 +13,9 @@ create-rebort-job:
- results/*
script:
- apt-get update
- git clone https://gitlab.ub.uni-bielefeld.de/ks-nano/tmu/ecosystem/storage-dut.git ../storage-dut/
- git clone https://gitlab.ub.uni-bielefeld.de/ks-nano/tmu/ecosystem/storage-response.git ../storage-response/
- ls -l ../
- git clone https://gitlab.ub.uni-bielefeld.de/ks-nano/tmu/ecosystem/storage-dut.git
- git clone https://gitlab.ub.uni-bielefeld.de/ks-nano/tmu/ecosystem/storage-response.git
- export PATH=$PATH:/ks/eda/riscv32-unknown-elf.gcc-12.1.0-stnolting/bin
- python3 -mvenv tmp/
- source tmp/bin/activate
......
compression.ipynb
+ 2
− 2
View file @ 50d99f08
%% Cell type:code id:04ceef79-87ab-4cd7-9476-6e3a80f225b0 tags:
``` python
import glob
import os
import pandas
import bitstring
from lib import *
pandas.set_option('display.width', 800)
```
%% Output
/tmp/ipykernel_3994518/2415918054.py:3: DeprecationWarning:
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
import pandas
%% Cell type:code id:806e7f99-94b1-4d37-8e7e-80bd611eb471 tags:
``` python
response_dir = '../storage-response'
storage_dut_dir = '../storage-dut'
response_dir = 'storage-response'
storage_dut_dir = 'storage-dut'
```
%% Cell type:code id:7cdea57a-6408-451e-9d1b-861fa7ee4274 tags:
``` python
soc_names = [name for name in os.listdir(response_dir) if os.path.isdir(f'{response_dir}/{name}') and not name.startswith('.')]
```
%% Cell type:code id:412e6417-f54c-4cda-a8aa-b16afeba0335 tags:
``` python
soc_names
```
%% Output
['airisc']
%% Cell type:code id:e9cad51b-b075-4254-ab6a-2020b784fb99 tags:
``` python
df = parse_all_socs(response_dir, soc_names)
```
%% Output
Did not parse all__int_array__tmu_ext__int_debug.elf.raw
Did not parse bs__int_array__tmu_ext__int_debug.elf.raw
Did not parse bs__sorted__tmu_ext__int_debug.elf.raw
Did not parse cs__int_array__tmu_ext__int_debug.elf.raw
Did not parse rs__int_array__tmu_ext__int_debug.elf.raw
%% Cell type:code id:cbe5c5b6-98b5-42aa-966f-6e73fe68b0e7 tags:
``` python
df
```
%% Cell type:code id:39fdc8af-da58-48fe-a001-9367712b318c tags:
``` python
tmu_dfs = {}
symbols = {}
for i in df.index:
row = df.iloc[i]
#print(row)
tmp = read_symbols_from_elf(storage_dut_dir, row['soc'], row['soc_config'], row['firmware'], row['raw-name'])
symbols[i] = post_process_symbols(tmp)
tmu_dfs[i] = parse_tmu_transactions(df['tmu_transmissions'][i], symbols[i])
if len(tmu_dfs[i])==0:
continue
try:
find_tmu_isr(tmu_dfs[i])
except AssertionError:
print("Potential missing data detected!!!!!!!!!!!!!!!!!!!!!!!!!!!")
df.at[i, 'raw_hil_status'] = 'Potential missing data'
continue
df.at[i,"tmu_transactions"] = len(tmu_dfs[i]['tid'])
df.at[i,"tmu_interrupts"] = tmu_dfs[i]['tid'].max()+1
curr_tmu = tmu_dfs[i]
df.at[i,"tmu_compression_total_cycles_max"] = curr_tmu['cont'].max()+1
df.at[i,"tmu_compression_total_cycles_mean"] = curr_tmu['cont'].mean()+1
df.at[i,"tmu_compression_total_cycles_min"] = curr_tmu['cont'].min()+1
df.at[i,"tmu_compression_stack_cycles_max"] = curr_tmu[curr_tmu['symbol']=='stack']['cont'].max()+1
df.at[i,"tmu_compression_stack_cycles_mean"] = curr_tmu[curr_tmu['symbol']=='stack']['cont'].mean()+1
df.at[i,"tmu_compression_stack_cycles_min"] = curr_tmu[curr_tmu['symbol']=='stack']['cont'].min()+1
df.at[i,"tmu_compression_no_stack_cycles_max"] = curr_tmu[curr_tmu['symbol']!='stack']['cont'].max()+1
df.at[i,"tmu_compression_no_stack_cycles_mean"] = curr_tmu[curr_tmu['symbol']!='stack']['cont'].mean()+1
df.at[i,"tmu_compression_no_stack_cycles_min"] = curr_tmu[curr_tmu['symbol']!='stack']['cont'].min()+1
df.at[i,"tmu_compression_isr_cycles_max"] = curr_tmu[curr_tmu['isr']==True]['cont'].max()+1
df.at[i,"tmu_compression_isr_cycles_mean"] = curr_tmu[curr_tmu['isr']==True]['cont'].mean()+1
df.at[i,"tmu_compression_isr_cycles_min"] = curr_tmu[curr_tmu['isr']==True]['cont'].min()+1
df.at[i,"tmu_compression_no_isr_cycles_max"] = curr_tmu[curr_tmu['isr']==False]['cont'].max()+1
df.at[i,"tmu_compression_no_isr_cycles_mean"] = curr_tmu[curr_tmu['isr']==False]['cont'].mean()+1
df.at[i,"tmu_compression_no_isr_cycles_min"] = curr_tmu[curr_tmu['isr']==False]['cont'].min()+1
```
%% Output
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 4 with ['stack' 'storage' nan 'marker_func_done'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 3 with ['storage' 'marker_func_done' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 3 with ['storage' 'stack' nan] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 3 with ['storage' 'stack' nan] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 3 with ['storage' 'stack' nan] and therefore may not belong to isr
Potential missing data detected!!!!!!!!!!!!!!!!!!!!!!!!!!!
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 4 with ['stack' 'storage' nan 'marker_func_done'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 5 with ['stack' 'storage' 'uptime' nan 'marker_func_done'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 4 with ['storage' 'stack' '_bss_start' 'marker_func_done'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 5 with ['storage' 'stack' '_bss_start' 'uptime' nan] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
Potential missing data detected!!!!!!!!!!!!!!!!!!!!!!!!!!!
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['storage' 'stack'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 1 with ['storage'] and therefore may not belong to isr
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
Check qid: 1 -> belongs to ISR
Check qid: 2 -> belongs to ISR
Check qid: 3 -> belongs to ISR
qid: 4 has 2 with ['stack' 'storage'] and therefore may not belong to isr
/homes/cklarhor/git/diva/240215/reports/lib.py:264: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
tmu_data.fillna({'isr': False}, inplace=True)
%% Cell type:code id:86e8fe68-f0f5-4396-a5b1-fa5b9080f97c tags:
``` python
df.loc[5]
```
%% Output
soc airisc
soc_config 32mhz
firmware mfs-hil
raw-name all__int_array__tmu_ext__tmu_5.elf.raw
raw_hil_config_start_pos 1056
raw_hil_config_end_pos 1709
raw_hil_start_pos 1740
raw_hil_end_pos 207642
raw_hil_dead_pos -1
raw_size 207653
raw_hil_status ok
total_tmu_transmitted_bytes 205902
total_tmu_payload_bytes 194832
total_tmu_transactions 24354
tmu_transmissions [b'\x00\x00\x00\x00 \x00\x00\x00x\xff\x01\x80\...
tmu_transactions 24354.0
tmu_interrupts 2214.0
tmu_compression_total_cycles_max 81.0
tmu_compression_total_cycles_mean 10.468753
tmu_compression_total_cycles_min 1.0
tmu_compression_stack_cycles_max 81.0
tmu_compression_stack_cycles_mean 6.888927
tmu_compression_stack_cycles_min 1.0
tmu_compression_no_stack_cycles_max 63.0
tmu_compression_no_stack_cycles_mean 19.208139
tmu_compression_no_stack_cycles_min 1.0
tmu_compression_isr_cycles_max 63.0
tmu_compression_isr_cycles_mean 12.631471
tmu_compression_isr_cycles_min 1.0
tmu_compression_no_isr_cycles_max 81.0
tmu_compression_no_isr_cycles_mean 1.628577
tmu_compression_no_isr_cycles_min 1.0
Name: 5, dtype: object
%% Cell type:code id:fdf398cf-f0fb-42f8-9dc1-83f258c70ac5 tags:
``` python
hex(3221228068)
```
%% Output
'0xc0000a24'
%% Cell type:code id:f2221cfa-d738-48ae-b18f-f64760febb01 tags:
``` python
tmu_dfs[5][0:50]
```
%% Output
address write size error cont cont_mode idle waitstate tid qid symbol isr
0 0 False 0 0 1 0 0 0 0 0 __airisc_xmem_size False
1 2147614584 True 2 0 5 2 4 0 0 1 stack False
2 2147492904 True 2 0 1 2 3 0 0 2 marker_data_gen_done False
3 2147492888 True 2 0 19 1 63 0 0 3 storage False
4 2147492896 True 2 0 1 2 14 0 0 4 marker_func_done False
5 2147614556 True 2 0 3 2 5 0 0 5 stack False
6 2147614572 True 2 0 0 3 1 0 0 6 stack False
7 2147614448 True 2 0 23 2 9 0 0 7 stack True
8 2147614436 True 2 0 1 2 21 0 0 8 stack True
9 2147614444 True 2 0 0 3 1 0 0 9 stack True
10 3221226000 False 2 0 44 0 63 0 0 10 NaN True
11 3221228068 True 2 0 0 3 9 0 1 0 NaN True
12 2147614524 False 2 0 0 3 63 0 1 1 stack True
13 2147614528 False 2 0 3 2 0 0 1 2 stack True
14 2147614448 False 2 0 18 2 0 0 1 3 stack True
15 2147614572 True 2 0 0 3 6 0 1 4 stack False
16 2147492812 False 2 0 0 3 8 0 1 5 _bss_start False
17 2147614448 True 2 0 23 2 16 0 1 6 stack True
18 2147614436 True 2 0 1 2 21 0 1 7 stack True
19 2147614444 True 2 0 0 3 1 0 1 8 stack True
20 3221226000 False 2 0 62 0 63 0 1 9 NaN True
21 3221225984 True 2 0 0 3 8 0 1 10 NaN True
22 3221228068 True 2 0 0 3 9 0 2 0 NaN True
23 2147614524 False 2 0 0 3 63 0 2 1 stack True
24 2147614528 False 2 0 3 2 0 0 2 2 stack True
25 2147614448 False 2 0 18 2 0 0 2 3 stack True
26 2147492888 False 2 0 18 1 63 0 2 4 storage False
27 2147614476 True 2 0 3 1 48 0 2 5 stack False
28 2147614368 True 2 0 23 2 10 0 2 6 stack True
29 2147614356 True 2 0 1 2 21 0 2 7 stack True
30 2147614364 True 2 0 0 3 1 0 2 8 stack True
31 3221226000 False 2 0 41 0 63 0 2 9 NaN True
32 3221225984 True 2 0 0 3 8 0 2 10 NaN True
33 3221228068 True 2 0 0 3 9 0 3 0 NaN True
34 2147614444 False 2 0 0 3 63 0 3 1 stack True
35 2147614448 False 2 0 3 2 0 0 3 2 stack True
36 2147614368 False 2 0 18 2 0 0 3 3 stack True
37 2147614540 True 2 0 15 1 30 0 3 4 stack False
38 2147492812 False 2 0 0 3 16 0 3 5 _bss_start False
39 2147614540 False 2 0 0 3 2 0 3 6 stack False
40 2147614540 True 2 0 0 3 2 0 3 7 stack False
41 2147614368 True 2 0 23 2 9 0 3 8 stack True
42 2147614356 True 2 0 1 2 21 0 3 9 stack True
43 2147614364 True 2 0 0 3 1 0 3 10 stack True
44 3221228068 True 2 0 0 3 9 0 4 0 NaN True
45 2147614444 False 2 0 0 3 63 0 4 1 stack True
46 2147614448 False 2 0 3 2 0 0 4 2 stack True
47 2147614368 False 2 0 18 2 0 0 4 3 stack True
48 2147614540 True 2 0 0 3 6 0 4 4 stack False
49 2147492816 False 2 0 0 3 11 0 4 5 storage False
%% Cell type:code id:11b61f2d-a3ab-4d2e-8816-b16f900f67a4 tags:
``` python
df
```
%% Cell type:code id:a61099ea-ac2f-4343-bc12-09ae4d6c37b5 tags:
``` python
df[df['raw_hil_status'] == 'Potential missing data']
```
%% Output
soc soc_config firmware raw-name raw_hil_config_start_pos raw_hil_config_end_pos raw_hil_start_pos raw_hil_end_pos raw_hil_dead_pos raw_size ... tmu_compression_stack_cycles_min tmu_compression_no_stack_cycles_max tmu_compression_no_stack_cycles_mean tmu_compression_no_stack_cycles_min tmu_compression_isr_cycles_max tmu_compression_isr_cycles_mean tmu_compression_isr_cycles_min tmu_compression_no_isr_cycles_max tmu_compression_no_isr_cycles_mean tmu_compression_no_isr_cycles_min
23 airisc 32mhz mfs-hil bs__int_array__tmu_ext__tmu_9.elf.raw 1056 1518 1549 16894 -1 16905 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
62 airisc 32mhz mfs-hil rs__int_array__tmu_ext__tmu_9.elf.raw 1056 1515 1546 13078 -1 13089 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
[2 rows x 32 columns]
%% Cell type:code id:061a9b5a-2b0c-48e1-b2c3-777eae43120f tags:
``` python
tmu = df.dropna(subset=['tmu_compression_no_isr_cycles_mean'])
```
%% Cell type:code id:24c399af-93be-407b-8b63-9fccc1d77629 tags:
``` python
tmu.groupby(by=['soc','soc_config','firmware']).plot(kind='bar', x='raw-name', y='tmu_compression_no_isr_cycles_mean')
```
%% Output
soc soc_config firmware
airisc 32mhz mfs-hil Axes(0.125,0.11;0.775x0.77)
dtype: object
%% Cell type:code id:dc95642b-3042-451b-ae5e-c650d1ee3cea tags:
``` python
tmu.groupby(by=['soc','soc_config','firmware']).plot(kind='bar', x='raw-name', y='tmu_decoded_compression_cycles_mean')
```
%% Output
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[11], line 1
----> 1 tmu.groupby(by=['soc','soc_config','firmware']).plot(kind='bar', x='raw-name', y='tmu_decoded_compression_cycles_mean')
NameError: name 'tmu' is not defined
%% Cell type:code id:54722489-9c77-4b74-957a-09671ea284a4 tags:
``` python
# best compression scatter
best_idx = tmu['tmu_decoded_compression_cycles_mean'].idxmax()
tmu_dfs[best_idx]['cont'].plot(kind='hist',bins=range(0,22),logy=True)
```
%% Cell type:code id:ee178362-eaeb-4733-a902-6c2a08e6a1eb tags:
``` python
# worst compression scatter
best_idx = tmu['tmu_decoded_compression_cycles_mean'].idxmin()
tmu_dfs[best_idx]['cont'].plot(kind='hist',bins=range(0,22), logy=True)
```
%% Cell type:code id:41f4cb6c-5085-4473-844d-c74c3d8b65f0 tags:
``` python
df
```
%% Cell type:code id:d86cb52e-1159-4003-b8ab-b27829a98395 tags:
``` python
df[df['raw-name'].str.contains("post")]
```
%% Cell type:code id:b75b1147-ba24-4e8d-83aa-bc1b23497aec tags:
``` python
df.iloc[2]
```
%% Cell type:code id:8b7d510c-a4f3-4d81-b6d8-2cb0e3cdc2e8 tags:
``` python
tmp = tmu_dfs[df.index[72]] #2
```
%% Cell type:markdown id:1b55d2d6-f915-44ae-900a-ede0316bed6e tags:
tmp
%% Cell type:code id:1a101ef7-feae-46ec-87bb-0bd84e8c2ede tags:
``` python
hex(tmp[tmp["tid"]<=2]['address'][2])
```
%% Cell type:code id:1801d564-eddc-4107-ac9e-7806c82984de tags:
``` python
tmp["addr_hex"] = [hex(x) for x in tmp["address"]]
```
%% Cell type:code id:c22bf4fc-2c1e-4548-8856-f9ce5417df1e tags:
``` python
tmp[tmp["tid"]<=4]
```
%% Cell type:code id:ad44e9da-c559-4c98-bf7e-838026ea1475 tags:
``` python
tmp[tmp["qid"]<=2]
```
%% Cell type:code id:c737168f-d406-4284-967b-165db3fd7bfc tags:
``` python
tmp[tmp["qid"]<=3].groupby(by=['qid', 'address']).count()
```
%% Cell type:code id:dadd88b1-65ee-4bd0-bc5f-e5217c470619 tags:
``` python
df.iloc[5] #5
```
%% Cell type:code id:2a3a299e-f681-4d33-b203-4040dafb4f19 tags:
``` python
#find_tmu_isr(tmu_dfs[df.index[5]])
tmp = tmu_dfs[df.index[5]] #70
tmp[tmp['isr']==True]
```
%% Cell type:code id:91fd0531-ee78-4721-ad27-112b3245a1ae tags:
``` python
tmp
```
%% Cell type:code id:429853c9-f185-40ec-8418-3979761be061 tags:
``` python
tmp[tmp["qid"]==6]
```
%% Cell type:code id:96afc080-fb78-45e4-aba4-087cb3665ffc tags:
``` python
tmp
```
%% Cell type:code id:c16ece83-fa80-4ce8-81fa-737450483a20 tags:
``` python
# check all ilocs -.-
```
%% Cell type:code id:c5f2fe27-b350-4e0b-9a98-df4474256050 tags:
``` python
```
......
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