diff --git a/jupyter_frontend/src/components/Acquisition.tsx b/jupyter_frontend/src/components/Acquisition.tsx
index 58970de0..2bd290b7 100644
--- a/jupyter_frontend/src/components/Acquisition.tsx
+++ b/jupyter_frontend/src/components/Acquisition.tsx
@@ -111,8 +111,8 @@ const Acquisition: React.FC = () => {
size={"small"}
value={triggerJudgeWaitTime}
addonAfter={intl.formatMessage({id: "cracker.config.unit.second"})}
- min={0.05}
- step={0.01}
+ min={0.001}
+ step={0.001}
onChange={(v) => {
setTriggerJudgeWaitTime(Number(v));
}}
diff --git a/src/cracknuts/acquisition/acquisition.py b/src/cracknuts/acquisition/acquisition.py
index 0bf259fc..dd8ee069 100644
--- a/src/cracknuts/acquisition/acquisition.py
+++ b/src/cracknuts/acquisition/acquisition.py
@@ -14,7 +14,6 @@
import numpy as np
from cracknuts import logger
-from cracknuts.cracker.cracker_s1 import CrackerS1
from cracknuts.cracker.cracker_basic import CrackerBasic
from cracknuts.trace.trace import ZarrTraceDataset, NumpyTraceDataset
@@ -25,7 +24,8 @@ class AcquisitionConfig:
sample_length: int = 1024
sample_offset: int = 0
trigger_judge_timeout: float = 0.005
- trigger_judge_wait_time: float = 0.001
+ trigger_judge_wait_time: float = 0.05
+ # trigger_judge_wait_time: float = 0.001
do_error_max_count: int = 1
file_path: str = ""
file_format: str = "zarr"
@@ -56,22 +56,22 @@ class Acquisition(abc.ABC):
MAX_WAVE_LENGTH = 32_000_000
def __init__(
- self,
- cracker: CrackerBasic,
- trace_count: int = 1000,
- sample_length: int = -1,
- sample_offset: int = 0,
- data_plaintext_length: int | None = None,
- data_ciphertext_length: int | None = None,
- data_key_length: int | None = None,
- data_extended_length: int | None = None,
- trigger_judge_wait_time: float = 0.01,
- trigger_judge_timeout: float = 1.0,
- do_error_handler_strategy: int = DO_ERROR_HANDLER_STRATEGY_EXIT,
- do_error_max_count: int = -1,
- file_format: str = "zarr",
- file_path: str = "auto",
- trace_fetch_interval: float = 0,
+ self,
+ cracker: CrackerBasic,
+ trace_count: int = 1000,
+ sample_length: int = -1,
+ sample_offset: int = 0,
+ data_plaintext_length: int | None = None,
+ data_ciphertext_length: int | None = None,
+ data_key_length: int | None = None,
+ data_extended_length: int | None = None,
+ trigger_judge_wait_time: float = 0.01,
+ trigger_judge_timeout: float = 1.0,
+ do_error_handler_strategy: int = DO_ERROR_HANDLER_STRATEGY_EXIT,
+ do_error_max_count: int = -1,
+ file_format: str = "zarr",
+ file_path: str = "auto",
+ trace_fetch_interval: float = 0,
):
"""
:param cracker: The controlled Cracker object.
@@ -846,7 +846,7 @@ def _is_triggered(self):
return triggered
def _get_waves(self, offset: int, sample_length: int) -> dict[int, np.ndarray]:
- if sample_length == -1 or sample_length is None:
+ if sample_length == -1:
sample_length = self.cracker.get_current_config().osc_sample_length
config = self.cracker.get_current_config()
@@ -857,20 +857,35 @@ def _get_waves(self, offset: int, sample_length: int) -> dict[int, np.ndarray]:
enable_channels.append(1)
wave_dict = {}
for c in enable_channels:
- _count = sample_length // self.MAX_WAVE_LENGTH
- _left = sample_length % self.MAX_WAVE_LENGTH
- _offset = offset
- waves = []
- for _ in range(_count):
- _, _wave = self.cracker.osc_get_analog_wave(c, _offset, self.MAX_WAVE_LENGTH)
- waves.append(_wave)
- _offset += self.MAX_WAVE_LENGTH
- if _left > 0:
- _, _wave = self.cracker.osc_get_analog_wave(c, _offset, _left)
- waves.append(_wave)
- wave_dict[c] = np.concatenate(waves)
+ status, wave_dict[c] = self.cracker.osc_get_analog_wave(c, offset, sample_length)
return wave_dict
+ # def _get_waves(self, offset: int, sample_length: int) -> dict[int, np.ndarray]:
+ # if sample_length == -1 or sample_length is None:
+ # sample_length = self.cracker.get_current_config().osc_sample_length
+ # config = self.cracker.get_current_config()
+ #
+ # enable_channels = []
+ # if config.osc_channel_0_enable:
+ # enable_channels.append(0)
+ # if config.osc_channel_1_enable:
+ # enable_channels.append(1)
+ # wave_dict = {}
+ # for c in enable_channels:
+ # _count = sample_length // self.MAX_WAVE_LENGTH
+ # _left = sample_length % self.MAX_WAVE_LENGTH
+ # _offset = offset
+ # waves = []
+ # for _ in range(_count):
+ # _, _wave = self.cracker.osc_get_analog_wave(c, _offset, self.MAX_WAVE_LENGTH)
+ # waves.append(_wave)
+ # _offset += self.MAX_WAVE_LENGTH
+ # if _left > 0:
+ # _, _wave = self.cracker.osc_get_analog_wave(c, _offset, _left)
+ # waves.append(_wave)
+ # wave_dict[c] = np.concatenate(waves)
+ # return wave_dict
+
def _pre_finish(self): ...
def _post_finish(self): ...
diff --git a/src/cracknuts/cracker/cracker_s1.py b/src/cracknuts/cracker/cracker_s1.py
index 4d070b3c..2a364597 100644
--- a/src/cracknuts/cracker/cracker_s1.py
+++ b/src/cracknuts/cracker/cracker_s1.py
@@ -757,12 +757,12 @@ def _nut_set_clock_enable(self, enable: bool) -> tuple[int, None]:
return status, None
@connection_status_check
- def nut_clock_freq(self, clock: int | str) -> tuple[int, None]:
+ def nut_clock_freq(self, clock: float | int | str) -> tuple[int, None]:
"""
Set nut clock.
:param clock: The clock of the nut in kHz
- :type clock: int | str
+ :type clock: float | int | str
:return: The device response status
:rtype: tuple[int, None]
"""
@@ -781,6 +781,7 @@ def nut_clock_freq(self, clock: int | str) -> tuple[int, None]:
else:
self._logger.error(f"Unknown clock type: {clock}, 64M or 24M or 12M or 8M or 4M")
return protocol.STATUS_ERROR, None
+ clock = round(clock) # TODO 这里由于这些设置是在cracker中的server程序完成的，目前只支持这些整数值，后续优化
validate_nut_clock = (64000, 24000, 12000, 8000, 4000)
if clock not in validate_nut_clock:
self._logger.error(f"UnSupport osc clock, it should in {validate_nut_clock}")
diff --git a/src/cracknuts/firmware/bs-cracker_g1_v0.1-0.0.0-alpha.8.bit.bin b/src/cracknuts/firmware/bs-cracker_g1_v0.1-0.0.0-alpha.8.bit.bin
deleted file mode 100644
index 7c116fe8..00000000
--- a/src/cracknuts/firmware/bs-cracker_g1_v0.1-0.0.0-alpha.8.bit.bin
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:bfc1f2b6736852cacd251e8bd6bd4a87e921fad4577feb7ffab0122605e77bd3
-size 4045568
diff --git a/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.12.bit.bin b/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.12.bit.bin
deleted file mode 100644
index 2d4aabcf..00000000
--- a/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.12.bit.bin
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c789ef83242001b97059764e1d8868b987104f42d05574091c6d425579cf30e6
-size 4045568
diff --git a/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin b/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin
new file mode 100644
index 00000000..34f5ce66
--- /dev/null
+++ b/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa795d93db652a53a71df42df00c97f198c1ab9659a4bb0d4f7939f62413b990
+size 4045568
diff --git a/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin b/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin
deleted file mode 100644
index cbac49fa..00000000
--- a/src/cracknuts/firmware/bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:230adfd023946da7996cb5823d5a17cd63a76de681ef18d44c2666b05e652fe3
-size 4045568
diff --git a/src/cracknuts/firmware/map.json b/src/cracknuts/firmware/map.json
index b4cc2dbd..6fc29b21 100644
--- a/src/cracknuts/firmware/map.json
+++ b/src/cracknuts/firmware/map.json
@@ -1,30 +1,30 @@
{
"cracker_s1_beta1": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin"
+ "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin"
},
"cracker_s1_v0.1": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin"
+ "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin"
},
"cracker_s1_v0.2": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin"
+ "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin"
},
"cracker_s1_v1.0": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin"
+ "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin"
},
"cracker_s1d_v1.0": {
"server": "server-sd-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.15.bit.bin"
+ "bitstream": "bs-cracker_s1_v0.1-0.1.0-alpha.14.bit.bin"
},
"cracker_g1_v1.0": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_g1_v0.1-0.0.0-alpha.6.bit.bin"
+ "bitstream": "bs-cracker_g1_v0.1-0.0.0-alpha.9.bit.bin"
},
- "cracker_g1_v1.0": {
+ "cracker_g1d_v1_1": {
"server": "server-0.5.6-alpha.3.bin",
- "bitstream": "bs-cracker_g1_v0.1-0.0.0-alpha.6.bit.bin"
+ "bitstream": "bs-cracker_g1_v0.1-0.0.0-alpha.9.bit.bin"
}
}
\ No newline at end of file
diff --git a/src/cracknuts/firmware/server-0.5.6-alpha.2.bin b/src/cracknuts/firmware/server-0.5.6-alpha.2.bin
deleted file mode 100644
index 9f9ee59f..00000000
--- a/src/cracknuts/firmware/server-0.5.6-alpha.2.bin
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:02076c63ad854a7730e1d8de33b08d2de17795a9b10378b31525a24b8a452e63
-size 2254020
diff --git a/src/cracknuts/firmware/server-sd-0.5.6-alpha.2.bin b/src/cracknuts/firmware/server-sd-0.5.6-alpha.2.bin
deleted file mode 100644
index 50ba06cc..00000000
--- a/src/cracknuts/firmware/server-sd-0.5.6-alpha.2.bin
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cfac4a0bfb5d1983f963129d712310457e0bf0667df39e1c7978e995023729d4
-size 2272988
diff --git a/tests/jupyter/0.20/0.20_g1_startup.ipynb b/tests/jupyter/0.20/0.20_g1_startup.ipynb
new file mode 100644
index 00000000..af7b5f78
--- /dev/null
+++ b/tests/jupyter/0.20/0.20_g1_startup.ipynb
@@ -0,0 +1,144 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "1cb5a996-2f83-417b-9efb-fdc4fb35d980",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cracknuts as cn"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "ede7207d-0411-4fb2-aded-d1f4c5c82c4b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "g1 = cn.cracker_g1('192.168.0.10')\n",
+ "g1.connect(force_update_bin=True, force_write_default_config=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "442c29be-5fc3-4186-a704-e529e33b258d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "43863abee97146958540d18613b869f7",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "WorkbenchG1Panel(acq_run_progress={'finished': 0, 'total': -1}, connect_status=True, custom_y_range={'0': (0, …"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import random\n",
+ "import time\n",
+ "from cracknuts.cracker import serial\n",
+ "\n",
+ "\n",
+ "cmd_set_aes_enc_key = \"01 00 00 00 00 00 00 10\"\n",
+ "cmd_aes_enc = \"01 02 00 00 00 00 00 10\"\n",
+ "\n",
+ "aes_key = \"11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\"\n",
+ "aes_data_len = 16\n",
+ "\n",
+ "sample_length = 20000\n",
+ "\n",
+ "def init(cracker):\n",
+ " cracker.nut_voltage_enable()\n",
+ " cracker.nut_voltage(3.3)\n",
+ " cracker.nut_clock_enable()\n",
+ " cracker.nut_clock_freq('8M')\n",
+ " cracker.uart_io_enable()\n",
+ " cracker.osc_sample_clock('48m')\n",
+ " cracker.osc_sample_length(sample_length)\n",
+ " cracker.osc_trigger_source('N')\n",
+ " cracker.osc_analog_gain('B', 10)\n",
+ " cracker.osc_trigger_level(0)\n",
+ " cracker.osc_trigger_mode('E')\n",
+ " cracker.osc_trigger_edge('U')\n",
+ " cracker.uart_config(baudrate=serial.Baudrate.BAUDRATE_115200, bytesize=serial.Bytesize.EIGHTBITS, parity=serial.Parity.PARITY_NONE, stopbits=serial.Stopbits.STOPBITS_ONE)\n",
+ "\n",
+ " time.sleep(2)\n",
+ " cmd = cmd_set_aes_enc_key + aes_key\n",
+ " status, ret = cracker.uart_transmit_receive(cmd, timeout=1000, rx_count=6)\n",
+ "\n",
+ "# def do(cracker, count):\n",
+ "# plaintext_data = random.randbytes(aes_data_len)\n",
+ "# tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ "# status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " \n",
+ "# return {\n",
+ "# \"plaintext\": plaintext_data,\n",
+ "# \"ciphertext\": ret[-aes_data_len:],\n",
+ "# \"key\": bytes.fromhex(aes_key)\n",
+ "# }\n",
+ "\n",
+ "def do(cracker, count):\n",
+ " # plaintext_data = random.randbytes(aes_data_len)\n",
+ " plaintext_data = bytes.fromhex('AA BB CC DD EE FF 00 11 22 33 44 55 66 77 88 99')\n",
+ " tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ " status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " # print(ret.hex(' ') if ret else 'None')\n",
+ " return {\n",
+ " \"plaintext\": plaintext_data,\n",
+ " \"ciphertext\": ret[-aes_data_len:],\n",
+ " \"key\": bytes.fromhex(aes_key)\n",
+ " }\n",
+ "\n",
+ "\n",
+ "def finish(cracker):\n",
+ " ...\n",
+ " # print('optional behavior')\n",
+ "\n",
+ "\n",
+ "acq = cn.simple_glitch_acq(g1, init, do)\n",
+ "\n",
+ "p = cn.show_panel(acq)\n",
+ "p"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a0562d3d-745d-4a3b-9b24-ab1b03ea18ff",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/0.20/0.20_s1_startup.ipynb b/tests/jupyter/0.20/0.20_s1_startup.ipynb
new file mode 100644
index 00000000..32fcc4c2
--- /dev/null
+++ b/tests/jupyter/0.20/0.20_s1_startup.ipynb
@@ -0,0 +1,146 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "1cb5a996-2f83-417b-9efb-fdc4fb35d980",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cracknuts as cn"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "ede7207d-0411-4fb2-aded-d1f4c5c82c4b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s1 = cn.cracker_s1('192.168.0.15')\n",
+ "s1.connect(force_update_bin=True, force_write_default_config=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "442c29be-5fc3-4186-a704-e529e33b258d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "4eeb599b99854089a9540b55fb16e85f",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "CracknutsPanelWidget(acq_run_progress={'finished': 0, 'total': -1}, connect_status=True, custom_y_range={'0': …"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import random\n",
+ "import time\n",
+ "from cracknuts.cracker import serial\n",
+ "\n",
+ "\n",
+ "cmd_set_aes_enc_key = \"01 00 00 00 00 00 00 10\"\n",
+ "cmd_aes_enc = \"01 02 00 00 00 00 00 10\"\n",
+ "\n",
+ "aes_key = \"11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\"\n",
+ "aes_data_len = 16\n",
+ "\n",
+ "sample_length = 20000\n",
+ "\n",
+ "def init(cracker):\n",
+ " cracker.nut_voltage_enable()\n",
+ " cracker.nut_voltage(3.3)\n",
+ " cracker.nut_clock_enable()\n",
+ " cracker.nut_clock_freq('8M')\n",
+ " cracker.uart_io_enable()\n",
+ " cracker.osc_sample_clock('48m')\n",
+ " cracker.osc_sample_length(sample_length)\n",
+ " cracker.osc_trigger_source('N')\n",
+ " cracker.osc_analog_gain('B', 10)\n",
+ " cracker.osc_trigger_level(0)\n",
+ " cracker.osc_trigger_mode('E')\n",
+ " cracker.osc_trigger_edge('U')\n",
+ " cracker.uart_config(baudrate=serial.Baudrate.BAUDRATE_115200, bytesize=serial.Bytesize.EIGHTBITS, parity=serial.Parity.PARITY_NONE, stopbits=serial.Stopbits.STOPBITS_ONE)\n",
+ "\n",
+ " time.sleep(2)\n",
+ " cmd = cmd_set_aes_enc_key + aes_key\n",
+ " status, ret = cracker.uart_transmit_receive(cmd, timeout=1000, rx_count=6)\n",
+ "\n",
+ "# def do(cracker, count):\n",
+ "# plaintext_data = random.randbytes(aes_data_len)\n",
+ "# tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ "# status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " \n",
+ "# return {\n",
+ "# \"plaintext\": plaintext_data,\n",
+ "# \"ciphertext\": ret[-aes_data_len:],\n",
+ "# \"key\": bytes.fromhex(aes_key)\n",
+ "# }\n",
+ "\n",
+ "def do(cracker, count):\n",
+ " # plaintext_data = random.randbytes(aes_data_len)\n",
+ " plaintext_data = bytes.fromhex('AA BB CC DD EE FF 00 11 22 33 44 55 66 77 88 99')\n",
+ " tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ " status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " # print(ret.hex(' ') if ret else 'None')\n",
+ " return {\n",
+ " \"plaintext\": plaintext_data,\n",
+ " \"ciphertext\": ret[-aes_data_len:],\n",
+ " \"key\": bytes.fromhex(aes_key)\n",
+ " }\n",
+ "\n",
+ "\n",
+ "def finish(cracker):\n",
+ " ...\n",
+ " # print('optional behavior')\n",
+ "\n",
+ "\n",
+ "acq = cn.simple_acq(s1, init, do)\n",
+ "\n",
+ "p = cn.show_panel(acq)\n",
+ "p"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "973b2a5d-f6db-4281-949d-b679cf081109",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s1.get_firmware_info()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/fly_flip_power.ipynb b/tests/jupyter/archive/fly_flip_power.ipynb
new file mode 100644
index 00000000..21b1d872
--- /dev/null
+++ b/tests/jupyter/archive/fly_flip_power.ipynb
@@ -0,0 +1,561 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b80b27f2-791e-4736-81b9-3218810bb233",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1200 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251029153409_1200_power_8m_30.zarr')\n",
+ "\n",
+ "p1200 = zd1200.plot()\n",
+ "p1200.show_trace(0, slice(2,3))\n",
+ "f1200 = p1200.plot_line(width=2300)\n",
+ "f1200"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "cd3e8568-de19-47e7-90da-d7eb35d13ae9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1200.show_trace(0, slice(13,14))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8963fefd-37f4-4770-9b47-207499b8f2ed",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1200.zoom_x((7_000_000, 9_000_000))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "15e8e1f4-8447-43e8-803a-5c6c73f8df6f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1300 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251029153409_1300_power_8m_30.zarr')\n",
+ "\n",
+ "p1300 = zd1300.plot()\n",
+ "p1300.show_trace(0, slice(2,3))\n",
+ "f1300 = p1300.plot_line(width=2300)\n",
+ "f1300"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3f88234d-bbf3-4514-8e49-cfbce117eea3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1300.show_trace(0, slice(11, 12))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9150479b-3c9a-47ad-ace3-f3f8f2e1c18b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1300.zoom_x((7_000_000, 9_000_000))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "10b1568e-a75e-4bbc-a2cc-4138feb57b18",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1100 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251030110021_1100_power_8m_30.zarr')\n",
+ "\n",
+ "p1100 = zd1100.plot()\n",
+ "p1100.show_trace(0, slice(2,3))\n",
+ "f1100 = p1100.plot_line(width=2300)\n",
+ "f1100"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3f2330fb-a5bb-4c6c-93c2-e6ba330e4198",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1000 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251030112125_1000_power_8m_30.zarr')\n",
+ "\n",
+ "p1000 = zd1000.plot()\n",
+ "p1000.show_trace(0, slice(2,3))\n",
+ "f1000 = p1000.plot_line(width=2300)\n",
+ "f1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "373f5ed5-48db-475e-8e64-3602949611d2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1000 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251030112125_1000_power_8m_30.zarr')\n",
+ "\n",
+ "p1000 = zd1000.plot()\n",
+ "p1000.show_trace(0, slice(2,3))\n",
+ "f1000 = p1000.plot_line(width=2300)\n",
+ "f1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c2e1eeb5-77c4-4f7c-a93c-7b05e4534771",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1000.zoom_x((0, 8_000_0))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "43c677f0-ceed-414b-8560-d14b90f2d429",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1000.show_trace(0, slice(2, 6))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "90bfa8f3-50c0-47c2-bf56-13375dd55a23",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1000.shift(0, 3, -25)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b4739a53-e794-4910-aaf5-99f3f50d568d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1000 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251031144124_1000_power_8m_delay0m_2000m_30.zarr')\n",
+ "\n",
+ "p1000 = zd1000.plot()\n",
+ "p1000.show_trace(0, slice(1, 4))\n",
+ "f1000 = p1000.plot_line(width=2300)\n",
+ "f1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "555d18e1-e185-4fc5-ab41-e379f4e8b5f9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 1 2\n",
+ "p1000.shift(0, 2, -20)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "7b21a955-78ab-4f38-804a-7ac18e8b0869",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "1c3c369b74de4466b2d3711ad0481ceb",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "FigureWidgetResampler({\n",
+ " 'data': [{'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T2 ~16k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '4eb63cfc-57b6-48d0-b176-6082260a763d',\n",
+ " 'x': {'bdata': ('AAAAAH8JAABWRQAAIo0AAMfBAAAvEA' ... 'C4JPMAe2XzAJS38wA6APQA/yP0AA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('bP8ACDv+8QE//ssBZv7aASX+ygEl/q' ... 'sGuvzHBtL89gbT/FMH1fyMB6D8jv8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T3 ~16k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '18081a9c-b815-4738-a240-e527df415580',\n",
+ " 'x': {'bdata': ('AAAAAGwKAAClegAA334AAOzBAADDAw' ... 'BkQPMAwobzANeR8wAS3vMA/yP0AA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('HAUB+O8EXfyWAXb+owFE/qQBYv7AAS' ... 'n8oQbb/OoGrvwdB6D8MweK/JAHOwI='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T5 ~16k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '79230bbe-5703-4281-bcee-1dfa78246301',\n",
+ " 'x': {'bdata': ('AAAAABAAAACsUQAAsIwAAMTLAAAnDg' ... 'AzO/MAxV3zAMGm8wCxEfQA/yP0AA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('mP0ACCv+EwJh/pUBTv6tASz+pgFd/o' ... 'YGrvzsBqv8dAfR/HYHZ/yTB+8H7P4='),\n",
+ " 'dtype': 'i2'}}],\n",
+ " 'layout': {'height': 350,\n",
+ " 'margin': {'b': 40, 'l': 0, 't': 40},\n",
+ " 'paper_bgcolor': 'white',\n",
+ " 'plot_bgcolor': 'white',\n",
+ " 'template': '...',\n",
+ " 'width': 2300,\n",
+ " 'xaxis': {'gridcolor': '#dddddd',\n",
+ " 'gridwidth': 1,\n",
+ " 'linecolor': '#dddddd',\n",
+ " 'linewidth': 1,\n",
+ " 'mirror': True,\n",
+ " 'showline': True},\n",
+ " 'yaxis': {'gridcolor': '#dddddd',\n",
+ " 'gridwidth': 1,\n",
+ " 'linecolor': '#dddddd',\n",
+ " 'linewidth': 1,\n",
+ " 'mirror': True,\n",
+ " 'showline': True}}\n",
+ "})"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\n",
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1100_64 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251031144124_1000_power_8m_delay0m_2000m_30.zarr')\n",
+ "\n",
+ "p1100_64 = zd1100_64.plot()\n",
+ "p1100_64.show_trace(0, [slice(2,4), slice(5,6)])\n",
+ "f1100_64 = p1100_64.plot_line(width=2300)\n",
+ "f1100_64"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "02f6ce18-312d-4cc2-9d17-60b68bec9ee0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p1100_64.shift(0, 0, 4)\n",
+ "p1100_64.shift(0, 2, -20)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7482255b-67e7-4977-8d52-44032dd3c9a5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd1000_64 = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251030165220_1000_power_64m_delay59m_10m_10.zarr')\n",
+ "\n",
+ "p1000_64 = zd1000_64.plot()\n",
+ "p1000_64.show_trace(0, slice(2,4))\n",
+ "f1000_64 = p1000_64.plot_line(width=2300)\n",
+ "f1000_64"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "726d4945-c57d-4f40-9113-19dd6bb892f9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# p1000_64.shift(0, 0, 593200)\n",
+ "p1000_64.shift(0, 0, 0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "c68804dc-fa7c-4bcd-b50a-6090f063d8f9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "ea102d526afe4c7e8149704672abe43e",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "TracePanelWidget(chart_size={'width': 0, 'height': 0}, language='zh', overview_select_range=(0, 0), overview_t…"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from cracknuts.jupyter import TracePanelWidget\n",
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251102122308_1000_power_64m_delay0m_.192_00_k.zarr')\n",
+ "tp = TracePanelWidget()\n",
+ "tp.set_trace_dataset(zd)\n",
+ "\n",
+ "tp.show_trace[0, 2:4]\n",
+ "tp"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "bc2d469a-5256-4de0-9b61-479994188088",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "21db94daafc643599173782a3cb50fd6",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "TracePanelWidget(chart_size={'width': 0, 'height': 0}, language='zh', overview_select_range=(0, 0), overview_t…"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\n",
+ "from cracknuts.jupyter import TracePanelWidget\n",
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251031144124_1000_power_8m_delay0m_2000m_30.zarr')\n",
+ "tp = TracePanelWidget()\n",
+ "tp.set_trace_dataset(zd)\n",
+ "# tp.change_range(0, 80_000)\n",
+ "tp.show_trace[0, 2:4]\n",
+ "tp"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3eae92aa-61a7-4869-a4b3-52e9ed96f9a1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cracknuts as cn\n",
+ "from cracknuts.jupyter import TracePanelWidget\n",
+ "import zarr\n",
+ "\n",
+ "zd = zarr.open(r'D:\\work\\00.project\\cracknuts-show\\dataset\\smt32f103_aes_power_CPAAnalysis.zarr')\n",
+ "\n",
+ "data = zd[\"/0/0/correlation\"][:,0,:]\n",
+ "print(data.shape)\n",
+ "\n",
+ "pt = cn.panel_trace()\n",
+ "pt.set_numpy_like_data(data)\n",
+ "pt.show_all_trace()\n",
+ "pt.highlight(0x11)\n",
+ "pt"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b8360d51-4910-433b-862a-a13989c936be",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "def plot_correlation_peaks_plotly_to_matplotlib(correlation_data, bytes_index, the_key, sample_len=None):\n",
+ " \"\"\"\n",
+ " 将原来的 Plotly-Resampler 图转换为 Matplotlib 静态绘图版本。\n",
+ " correlation_data: ndarray, shape = (256, N_bytes, N_samples)\n",
+ " bytes_index: int, 指定第几个字节\n",
+ " the_key: int, 目标 key 的索引\n",
+ " sample_len: int or None, 指定绘制的采样长度\n",
+ " \"\"\"\n",
+ "\n",
+ " if sample_len is None:\n",
+ " sample_len = correlation_data.shape[2]\n",
+ "\n",
+ " x = np.arange(sample_len)\n",
+ "\n",
+ " # 创建画布\n",
+ " fig, ax = plt.subplots(figsize=(9, 3)) # 约等于 900x300 像素\n",
+ " fig.patch.set_facecolor(\"white\")\n",
+ "\n",
+ " # 绘制所有 key 曲线（非 target key 灰色）\n",
+ " for i in range(256):\n",
+ " if i == the_key:\n",
+ " continue\n",
+ " ax.plot(\n",
+ " x,\n",
+ " correlation_data[i, bytes_index, :sample_len],\n",
+ " color=\"gray\",\n",
+ " linewidth=0.5,\n",
+ " alpha=0.3\n",
+ " )\n",
+ "\n",
+ " # 绘制 target key（红色）\n",
+ " ax.plot(\n",
+ " x,\n",
+ " correlation_data[the_key, bytes_index, :sample_len],\n",
+ " color=\"red\",\n",
+ " linewidth=1.0,\n",
+ " label=f\"target key {the_key}\"\n",
+ " )\n",
+ "\n",
+ " # 样式与布局\n",
+ " ax.set_facecolor(\"white\")\n",
+ " ax.grid(True, linewidth=1, color=\"#dddddd\", linestyle=\"-\", alpha=0.6)\n",
+ " ax.set_xlabel(\"Sample index\")\n",
+ " ax.set_ylabel(\"Correlation\")\n",
+ " ax.set_title(f\"Correlation peaks for byte {bytes_index} (key {the_key})\", pad=10)\n",
+ " ax.legend(loc=\"upper right\", frameon=False)\n",
+ "\n",
+ " # 边框样式（类似 Plotly 的 mirror=True）\n",
+ " for spine in ax.spines.values():\n",
+ " spine.set_linewidth(1)\n",
+ " spine.set_color(\"#dddddd\")\n",
+ "\n",
+ " plt.tight_layout()\n",
+ " plt.show()\n",
+ "\n",
+ " return fig, ax\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7f75c2b7-583f-426d-b0ff-aad412326d55",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plot_correlation_peaks_plotly_to_matplotlib(zd[\"/0/0/correlation\"], 0, 0x11)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "cd5fbef3-f2bf-4e77-9a55-dbfa89b8a711",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import plotly.graph_objects as go\n",
+ "from plotly_resampler import FigureWidgetResampler\n",
+ "import zarr\n",
+ "\n",
+ "zd = zarr.open(r'D:\\work\\00.project\\cracknuts-show\\dataset\\smt32f103_aes_power_CPAAnalysis.zarr')\n",
+ "data = zd[\"/0/0/correlation\"][:,0,:]\n",
+ "\n",
+ "fig = FigureWidgetResampler(go.Figure())\n",
+ "\n",
+ "# ======== 3. 添加每条曲线 ========\n",
+ "for i in range(data.shape[0]):\n",
+ " if i == 0x11:\n",
+ " continue\n",
+ " fig.add_trace(\n",
+ " go.Scattergl(\n",
+ " y=data[i, :],\n",
+ " mode='lines',\n",
+ " name=f\"Signal {i+1}\",\n",
+ " line=dict(\n",
+ " color='gray', # 可以是颜色名 'red', 'blue', 'green' 或者十六进制 '#ff0000'\n",
+ " width=1 # 线宽，可选\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ "\n",
+ "fig.add_trace(\n",
+ " go.Scattergl(\n",
+ " y=data[0x11, :],\n",
+ " mode='lines',\n",
+ " name=f\"Signal {i+1}\",\n",
+ " line=dict(\n",
+ " color='red', # 可以是颜色名 'red', 'blue', 'green' 或者十六进制 '#ff0000'\n",
+ " width=1 # 线宽，可选\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ "\n",
+ "fig.update_layout(\n",
+ " title=\"二维 NumPy 数据示例\",\n",
+ " width=2000, # ← 指定画布宽度（像素）\n",
+ " height=500\n",
+ ")\n",
+ "\n",
+ "fig"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7f977745-3595-4eb5-85d9-1aa8e878e93e",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/new_plot.ipynb b/tests/jupyter/archive/new_plot.ipynb
new file mode 100644
index 00000000..8f2f8c4a
--- /dev/null
+++ b/tests/jupyter/archive/new_plot.ipynb
@@ -0,0 +1,331 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "b80b27f2-791e-4736-81b9-3218810bb233",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "3fdea9c64cfa419aa50b46fa4f2c4237",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "FigureWidgetResampler({\n",
+ " 'data': [{'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T2 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'd2071d28-bfd3-4e65-98e2-7090d1836e85',\n",
+ " 'x': {'bdata': ('AAAAAOAJAAANawEAUiEDALbZAwBvSA' ... 'SXx78EPy/BBBqywgRDVcQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('AgDSAdb/LQDX/yoA0f8rANT/LgDV/y' ... '0Az/8wANH/MwDM/zIA0P80ADAA9v8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T3 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'a00908dd-19b2-4542-8e50-d2be8e3dffa9',\n",
+ " 'x': {'bdata': ('AAAAANQJAADYWwEADXMCAMTxAwAv8A' ... 'THy78EqkPBBMHbwQQ4ecME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('DwC7AtT/KwDW/ysA1f8sANf/LQDV/y' ... 'P/MgDR/zIAzP88ANP/NgDT/zMACAA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T4 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'ce57a7cf-31b1-4324-a0d9-aa86cfde91fd',\n",
+ " 'x': {'bdata': ('AAAAAM8JAABZsAEAsfwCAJfAAwC3FA' ... 'Qigr8EE67ABNbVwgSRE8ME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('+P+uAdb/LQDW/ysA1/8sANX/LgDX/y' ... 'H/LgDS/zUA0f85ANL/NADS/zQAAwA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T5 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'cb10bb05-a6a7-49e4-8cd4-654f9975207c',\n",
+ " 'x': {'bdata': ('AAAAANIJAACOhAEAudgCAFz/AwCbTg' ... 'QH+r8EyQXCBC8jwgQktsME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('EAAAA9X/KwDV/ywA1v8sANj/LQDY/y' ... 'IAzv8xANH/MgDN/zcANQDQ/zQABwA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T6 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'd3aafb41-bc86-48c0-b5ba-a1b5b59383ed',\n",
+ " 'x': {'bdata': ('AAAAAAEKAAB+pAEAggoDAL4mBAAu8g' ... 'ThpL8E3LPABDRSwgQwMcQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('//8XAdX/LgDT/ywA0/8sANb/KwDW/y' ... 'L/NQDQ/y4AMgDT/zAAz/8zAC8ABwA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T7 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'e0338ae5-8732-4d47-a6fd-21b72572703d',\n",
+ " 'x': {'bdata': ('AAAAAO4JAABPfAEA76sCAEYCBACM/Q' ... 'Tahb8Ef5jABAkMwgQSVMQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('/f+sAc//LADX/y4A1P8sANb/LgDW/y' ... 'MA0f8vANL/MQDN/zQA0v8yAC4A4P8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T8 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '248a8fe2-844b-4bde-81d6-786c4d308a6d',\n",
+ " 'x': {'bdata': ('AAAAAMgJAACnbgEAeowCACvuAwD+Sw' ... 'Szi78EzRHBBFJiwgQ9OcQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('FAByAtb/LwDQ/y4A1/8vANX/KwDW/y' ... 'P/MADU/y8A0/8xAM7/LgDV/9H/CAA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T9 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'bcb78ae7-9e0d-476b-b701-08747c18922a',\n",
+ " 'x': {'bdata': ('AAAAAMkJAADlYgEAFrcCADTeAwCxJA' ... 'Sper8Ekv/ABI4twgSqG8QE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('5v9sAtb/KwDW/y8A0f8rANP/KwDX/y' ... 'D/MADR/zEA0/82ANP/LwDU/8//FgA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T10 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '2f10a7fe-8c51-4258-8799-952a90511dc9',\n",
+ " 'x': {'bdata': ('AAAAAOwJAABEPQEALJICAGXbAwDH7A' ... 'THxb8EtRzBBMBqwgT8fMQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('+v+SAtT/LADX/ywA1/8sANP/KgDV/y' ... 'L/LQDU/zQA0f8yAM//LADQ/87/GQA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T11 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '0a2d8929-d357-4d56-9141-98f6d0f4930c',\n",
+ " 'x': {'bdata': ('AAAAAM0JAADOfgEAlL4CALHHAwCzAg' ... 'RKor8ESOTABNs/wgSYCcME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('9f/MA9b/KwDX/ysA1P8rANX/LADX/y' ... 'YA0f8wAM//MwAzANP/NgDQ/zIA+f8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T12 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '552f1464-3805-4cdf-93be-b0b851fc7b97',\n",
+ " 'x': {'bdata': ('AAAAANMJAAAgmAEAn+MCAE7FAwBSWg' ... 'Q7zb8EZgHBBKoBwgTl38ME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('+f9/A9f/KwDX/ysA2P8rANX/KwDW/y' ... 'MAzv8yAM//NgDO/zAA0/81ANX/8P8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T13 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '9c0b1bdb-e88e-44b3-9a8d-41d14ee38c8c',\n",
+ " 'x': {'bdata': ('AAAAAM0JAADXYwEAyfACAEjRAwA/OQ' ... 'S4vL8ELITBBLB9wgS2McME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('DQAJBNf/LwDY/ysA1f8qANj/LQDY/y' ... 'IA0P83ANH/LQDR/y8A0P8wANT/BAA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T14 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'bfb31c76-df78-4b52-8e4c-23c0cb10bd25',\n",
+ " 'x': {'bdata': ('AAAAAMIJAADZSgEAtYICAOYaBADO7A' ... 'TPKcAEFmzBBCItwgRpMcQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('AQC9A9X/LwDV/ywA0v8rANf/KgDX/y' ... '7/MwDR/y4A0P8uANT/OgDS/9D/BAA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T15 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'c031fdc6-fded-4aa8-99ac-14b6bf864417',\n",
+ " 'x': {'bdata': ('AAAAANcJAABvfAEArYACAMDPAwAXNA' ... 'T9rb8EI3zBBCyMwgQlbMME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('9/8LBNT/LADT/ysA1P8uANb/KgDY/y' ... 'X/LwDQ/zYA0P8zANH/LwDV/y4AAAA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T16 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'ea429b81-ea7d-4d4a-bb55-d2d877078ab1',\n",
+ " 'x': {'bdata': ('AAAAAMwJAACUSwEAurQCALLLAwB+6Q' ... 'S1nL8EwL7ABL5cwgR6U8ME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('BABMBdf/MADY/ywA1v8qANf/NADR/y' ... '//MQDS/y0A0P/R/zUA0f8xANL/DwA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T17 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'bf3b43e6-586a-476e-a7e6-e89400558d7b',\n",
+ " 'x': {'bdata': ('AAAAALgJAAAOUwEAIt8CAJirAwA9MQ' ... 'QtEMAES5HBBE1DwgSUesME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('+P+tBdf/LQDX/y0A1v8rANj/LQDX/y' ... '8A0P8zANP/MADS/ywA0v8yANL/DwA='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T18 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': '322169dd-a50a-4c3e-b2f0-32b7fec1f518',\n",
+ " 'x': {'bdata': ('AAAAAKsJAAAAdwEAs/wCADK3AwDJXg' ... 'Sd078EySnBBOITwgTVHsME/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('5/+6BNb/LADO/y0A1f8yANT/MQDW/y' ... '8A0f86AM//MwDP/zYA0/8vANH//P8='),\n",
+ " 'dtype': 'i2'}},\n",
+ " {'line': {'width': 1},\n",
+ " 'mode': 'lines',\n",
+ " 'name': '[R] T19 ~80k',\n",
+ " 'showlegend': True,\n",
+ " 'type': 'scattergl',\n",
+ " 'uid': 'eea0f842-1d25-4f60-aa06-04a3a95e7406',\n",
+ " 'x': {'bdata': ('AAAAAKwJAAByagEAXpQCAEGyAwAufQ' ... 'QnxL8Eot3ABLFMwgSqNsQE/7PEBA=='),\n",
+ " 'dtype': 'i4'},\n",
+ " 'y': {'bdata': ('/P/uA9T/LgDW/y0A1f8uANP/LgDT/y' ... 'T/MQDV/8//NADQ/zcA0f8sAC0ABQA='),\n",
+ " 'dtype': 'i2'}}],\n",
+ " 'layout': {'height': 350,\n",
+ " 'margin': {'b': 40, 'l': 0, 't': 40},\n",
+ " 'paper_bgcolor': 'white',\n",
+ " 'plot_bgcolor': 'white',\n",
+ " 'template': '...',\n",
+ " 'xaxis': {'gridcolor': '#dddddd',\n",
+ " 'gridwidth': 1,\n",
+ " 'linecolor': '#dddddd',\n",
+ " 'linewidth': 1,\n",
+ " 'mirror': True,\n",
+ " 'showline': True},\n",
+ " 'yaxis': {'gridcolor': '#dddddd',\n",
+ " 'gridwidth': 1,\n",
+ " 'linecolor': '#dddddd',\n",
+ " 'linewidth': 1,\n",
+ " 'mirror': True,\n",
+ " 'showline': True}}\n",
+ "})"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251029153409_1200_power_8m_30.zarr')\n",
+ "\n",
+ "p = zd.plot()\n",
+ "p.show_trace(0, slice(2,20))\n",
+ "f = p.plot_line()\n",
+ "f"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "682a189c-c0ed-4958-9e3f-433cb21b191d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p.zoom(x=(10000, 20000), y=(0, 200))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "bca1f8e0-3622-4dc0-a3a9-6a170b630ef1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "r = 9000000\n",
+ "start = 3000\n",
+ "f.layout.xaxis.range = [start, start+r] # X 轴显示 20~50"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "8483d41d-622b-4796-b138-1a9cadf35e09",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 执行后 会自动宽度\n",
+ "f.layout.autosize=False\n",
+ "f.layout.autosize=True"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "11e4d84f-59ca-4a1d-86ba-dee8546de76b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "f.layout.autosize"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "32a1c788-e40e-425f-ba2b-98dfb2990b58",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cracknuts.trace import ZarrTraceDataset\n",
+ "\n",
+ "zd = ZarrTraceDataset.load(r'D:\\work\\01.testing\\02.fly(gpio02)\\cracknuts\\tests\\jupyter\\dataset\\20251029153409_1200_power_8m_30.zarr')\n",
+ "\n",
+ "p = zd.plot()\n",
+ "p.show_trace(0, slice(2,20))\n",
+ "f = p.plot_line()\n",
+ "f\n",
+ "# 执行后 会自动宽度\n",
+ "f.layout.autosize=False\n",
+ "f.layout.autosize=True"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/new_trace_monitor.ipynb b/tests/jupyter/archive/new_trace_monitor.ipynb
new file mode 100644
index 00000000..324b2c05
--- /dev/null
+++ b/tests/jupyter/archive/new_trace_monitor.ipynb
@@ -0,0 +1,33 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1c83ebe8-fb6b-41d6-866c-347d03bf07a7",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/pl_io_test1.ipynb b/tests/jupyter/archive/pl_io_test1.ipynb
new file mode 100644
index 00000000..e23ab2dd
--- /dev/null
+++ b/tests/jupyter/archive/pl_io_test1.ipynb
@@ -0,0 +1,216 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "8f23a5fd-1412-4abd-ae70-7b6de6f9960f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cracknuts as cn"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "b96151cb-ef3e-4f75-b38a-133a5ff89a0d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s1 = cn.new_cracker('192.168.0.15')\n",
+ "s1.connect(force_update_bin=True, force_write_default_config=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "5ada5d09-1c38-4681-bcdc-203586ee21c3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0,\n",
+ " \"operator_version: 0.3.0-alpha.3, server_version: 0.5.6-alpha.2, bitstream_version: b'S1-0.1.0-alpha.15'\")"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s1.get_firmware_version()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "51db0764-5363-43da-9c9c-c8bf914456f1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 复位 PL IO\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x300, data=0x01)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "15590cd5-26bc-41a0-ab50-7355cfe50116",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 30,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 使能 PL IO\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x304, data=0b0000_0000_0000_0000_0000_0000_0000_0000)\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x304, data=0b0000_0000_0000_0000_0000_0000_0001_1111)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "id": "bcca88b2-b262-4111-9f92-2695a7416357",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 31,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 输入输出控制\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x308, data=0b0000_0000_0000_0000_0000_0000_0000_0000) # 输出\n",
+ "# s1.register_write(base_address=0x43c10000, offset=0x308, data=0b0000_0000_0000_0000_0000_0000_0000_1111) # 输入"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "id": "821ae232-5641-4fdb-9782-a5eb73954bca",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 32,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 波形控制\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x318, data=0b0000_0000_0000_0000_0000_0000_0000_1010) # 波形\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x32c, data=0x0000_0200) # 1000 10ns 10μs\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x330, data=0x0000_0200) # 1000 10ns 10μs\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x334, data=0x0000_0200) # 1000 10ns 10μs\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x338, data=0x0000_0200) # 1000 10ns 10μs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "id": "09c3077d-3c11-4856-949e-8bd5bdbaf1d8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 33,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 设置波形开始\n",
+ "s1.register_write(base_address=0x43c10000, offset=0x30c, data=0b0000_0000_0000_0000_0000_0000_0001_1111)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "id": "ddde216e-319c-4bd1-a120-41388fa52cba",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'00000000 00000000 00000010 00000000'"
+ ]
+ },
+ "execution_count": 41,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bytes_bin(s1.register_read(base_address=0x43c10000, offset=0x32c)[1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "id": "6c498891-110f-40e2-be97-c75b1818999e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def bytes_bin(b: bytes, sep: str = ' ') -> str:\n",
+ " return sep.join(f'{byte:08b}' for byte in b)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/scope_optimization.ipynb b/tests/jupyter/archive/scope_optimization.ipynb
new file mode 100644
index 00000000..3cda03d1
--- /dev/null
+++ b/tests/jupyter/archive/scope_optimization.ipynb
@@ -0,0 +1,226 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "f5c99cb1-5585-4460-b0c1-9a87d854b3d0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 引入依赖\n",
+ "import cracknuts as cn\n",
+ "from cracknuts.acquisition import Acquisition\n",
+ "\n",
+ "# 创建 cracker \n",
+ "cracker = cn.new_cracker('192.168.0.15')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "6d734bcc-74e8-49eb-a5cf-89c881b89aa8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cracker.connect(force_update_bin=True, force_write_default_config=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "80cb363b-8504-42fa-894e-1e9408f46206",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "6e04b89227674ef395f4e30f1b7e7084",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "CracknutsPanelWidget(acq_run_progress={'finished': 0, 'total': -1}, connect_status=True, custom_y_range={'0': …"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\Dingzb\\AppData\\Local\\Temp\\ipykernel_7472\\3407830264.py:19: DeprecationWarning: uart_enable() 已弃用，将在未来版本中移除，请使用 uart_io_enable() 替代。\n",
+ " cracker.uart_enable()\n",
+ "Exception in thread Thread-12 (_monitor):\n",
+ "Traceback (most recent call last):\n",
+ " File \"C:\\Users\\Dingzb\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\threading.py\", line 1075, in _bootstrap_inner\n",
+ "Exception in thread Thread-11 (_monitor):\n",
+ "Traceback (most recent call last):\n",
+ " File \"C:\\Users\\Dingzb\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\threading.py\", line 1075, in _bootstrap_inner\n",
+ " self.run()\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\ipykernel\\ipkernel.py\", line 772, in run_closure\n",
+ " self.run()\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\ipykernel\\ipkernel.py\", line 772, in run_closure\n",
+ " _threading_Thread_run(self)\n",
+ " File \"C:\\Users\\Dingzb\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\threading.py\", line 1012, in run\n",
+ " _threading_Thread_run(self)\n",
+ " File \"C:\\Users\\Dingzb\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\threading.py\", line 1012, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"D:\\work\\00.project\\cracknuts\\src\\cracknuts\\jupyter\\scope_panel.py\", line 127, in _monitor\n",
+ " self.update(wave)\n",
+ " File \"D:\\work\\00.project\\cracknuts\\src\\cracknuts\\jupyter\\scope_panel.py\", line 90, in update\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"D:\\work\\00.project\\cracknuts\\src\\cracknuts\\jupyter\\scope_panel.py\", line 127, in _monitor\n",
+ " self.overview_series = {k: minmax(v, 0, v.shape[0], 1920) for k, v in series_data.items()}\n",
+ " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\numba\\core\\dispatcher.py\", line 424, in _compile_for_args\n",
+ " error_rewrite(e, 'typing')\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\numba\\core\\dispatcher.py\", line 365, in error_rewrite\n",
+ " self.update(wave)\n",
+ " File \"D:\\work\\00.project\\cracknuts\\src\\cracknuts\\jupyter\\scope_panel.py\", line 90, in update\n",
+ " raise e.with_traceback(None)\n",
+ "numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)\n",
+ "\u001b[1m\u001b[1mCan't unify return type from the following types: Tuple(array(int32, 1d, C), array(float64, 1d, C)), Tuple(array(int32, 1d, C), array(int16, 1d, C))\n",
+ "\u001b[1mReturn of: IR name '$234return_value.17', type 'Tuple(array(int32, 1d, C), array(float64, 1d, C))', location: \u001b[1m\n",
+ "File \"..\\..\\src\\cracknuts\\trace\\downsample.py\", line 14:\u001b[0m\n",
+ "\u001b[1mdef minmax(value: NDArray[np.int16], mn: int, mx: int, down_count: int) -> tuple[NDArray[np.int32], NDArray[np.int16]]:\n",
+ " \n",
+ " _index = np.arange(mn, mx, dtype=np.int32)\n",
+ "\u001b[1m return _index, _value\n",
+ "\u001b[0m \u001b[1m^\u001b[0m\u001b[0m\u001b[0m\n",
+ "\u001b[1mReturn of: IR name '$618return_value.5', type 'Tuple(array(int32, 1d, C), array(int16, 1d, C))', location: \u001b[1m\n",
+ "File \"..\\..\\src\\cracknuts\\trace\\downsample.py\", line 28:\u001b[0m\n",
+ "\u001b[1mdef minmax(value: NDArray[np.int16], mn: int, mx: int, down_count: int) -> tuple[NDArray[np.int32], NDArray[np.int16]]:\n",
+ " \n",
+ " down_value[2 * i + 1] = block.min()\n",
+ "\u001b[1m return down_index, down_value\n",
+ "\u001b[0m \u001b[1m^\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n",
+ "\u001b[0m\u001b[1mDuring: Pass nopython_type_inference\u001b[0m\n",
+ " self.overview_series = {k: minmax(v, 0, v.shape[0], 1920) for k, v in series_data.items()}\n",
+ " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\numba\\core\\dispatcher.py\", line 424, in _compile_for_args\n",
+ " error_rewrite(e, 'typing')\n",
+ " File \"D:\\work\\00.project\\cracknuts\\.venv\\Lib\\site-packages\\numba\\core\\dispatcher.py\", line 365, in error_rewrite\n",
+ " raise e.with_traceback(None)\n",
+ "numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)\n",
+ "\u001b[1m\u001b[1mCan't unify return type from the following types: Tuple(array(int32, 1d, C), array(float64, 1d, C)), Tuple(array(int32, 1d, C), array(int16, 1d, C))\n",
+ "\u001b[1mReturn of: IR name '$234return_value.17', type 'Tuple(array(int32, 1d, C), array(float64, 1d, C))', location: \u001b[1m\n",
+ "File \"..\\..\\src\\cracknuts\\trace\\downsample.py\", line 14:\u001b[0m\n",
+ "\u001b[1mdef minmax(value: NDArray[np.int16], mn: int, mx: int, down_count: int) -> tuple[NDArray[np.int32], NDArray[np.int16]]:\n",
+ " \n",
+ " _index = np.arange(mn, mx, dtype=np.int32)\n",
+ "\u001b[1m return _index, _value\n",
+ "\u001b[0m \u001b[1m^\u001b[0m\u001b[0m\u001b[0m\n",
+ "\u001b[1mReturn of: IR name '$618return_value.5', type 'Tuple(array(int32, 1d, C), array(int16, 1d, C))', location: \u001b[1m\n",
+ "File \"..\\..\\src\\cracknuts\\trace\\downsample.py\", line 28:\u001b[0m\n",
+ "\u001b[1mdef minmax(value: NDArray[np.int16], mn: int, mx: int, down_count: int) -> tuple[NDArray[np.int32], NDArray[np.int16]]:\n",
+ " \n",
+ " down_value[2 * i + 1] = block.min()\n",
+ "\u001b[1m return down_index, down_value\n",
+ "\u001b[0m \u001b[1m^\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n",
+ "\u001b[0m\u001b[1mDuring: Pass nopython_type_inference\u001b[0m\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0\n",
+ "1\n",
+ "2\n",
+ "3\n",
+ "4\n",
+ "5\n",
+ "6\n",
+ "7\n",
+ "8\n"
+ ]
+ }
+ ],
+ "source": [
+ "import random\n",
+ "import time\n",
+ "from cracknuts.cracker import serial\n",
+ "\n",
+ "\n",
+ "cmd_set_aes_enc_key = \"01 00 00 00 00 00 00 10\"\n",
+ "cmd_aes_enc = \"01 02 00 00 00 00 00 10\"\n",
+ "\n",
+ "aes_key = \"11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\"\n",
+ "aes_data_len = 16\n",
+ "\n",
+ "sample_length = 20000\n",
+ "\n",
+ "def init(c):\n",
+ " cracker.nut_voltage_enable()\n",
+ " cracker.nut_voltage(3.3)\n",
+ " cracker.nut_clock_enable()\n",
+ " cracker.nut_clock_freq('8M')\n",
+ " cracker.uart_enable()\n",
+ " cracker.osc_sample_clock('48m')\n",
+ " cracker.osc_sample_length(sample_length)\n",
+ " cracker.osc_trigger_source('N')\n",
+ " cracker.osc_analog_gain('B', 10)\n",
+ " cracker.osc_trigger_level(0)\n",
+ " cracker.osc_trigger_mode('E')\n",
+ " cracker.osc_trigger_edge('U')\n",
+ " cracker.uart_config(baudrate=serial.Baudrate.BAUDRATE_115200, bytesize=serial.Bytesize.EIGHTBITS, parity=serial.Parity.PARITY_NONE, stopbits=serial.Stopbits.STOPBITS_ONE)\n",
+ "\n",
+ " time.sleep(2)\n",
+ " cmd = cmd_set_aes_enc_key + aes_key\n",
+ " status, ret = cracker.uart_transmit_receive(cmd, timeout=1000, rx_count=6)\n",
+ "\n",
+ "def do(cracer, count):\n",
+ " print(count)\n",
+ " plaintext_data = random.randbytes(aes_data_len)\n",
+ " tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ " status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " \n",
+ " return {\n",
+ " \"plaintext\": plaintext_data,\n",
+ " \"ciphertext\": ret[-aes_data_len:],\n",
+ " \"key\": bytes.fromhex(aes_key)\n",
+ " }\n",
+ "\n",
+ "\n",
+ "def finish(c):\n",
+ " ...\n",
+ " # print('optional behavior')\n",
+ "\n",
+ "\n",
+ "acq = cn.new_acquisition(cracker, init=init, do=do, finish=finish)\n",
+ "cn.panel(acq)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "edad4468-9cb3-4ec4-b3d3-9b562db283b7",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/trigger_reset_analysis.ipynb b/tests/jupyter/archive/trigger_reset_analysis.ipynb
new file mode 100644
index 00000000..ae3085a1
--- /dev/null
+++ b/tests/jupyter/archive/trigger_reset_analysis.ipynb
@@ -0,0 +1,100 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "dbacfa1e-7cb7-44f1-9571-3aa8fa789d0b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cracknuts as cn\n",
+ "from cracknuts.trace import ZarrTraceDataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "304aea6b-de65-4f9d-8476-f0f50cf1dd9b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Channel: ['0']\n",
+ "Trace: 30, 19200000\n",
+ "Data: 30 plaintext: 0 ciphertext: 0 key: 0 extended: None"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "trace_path = \"dataset/20251102122308.zarr/\"\n",
+ "\n",
+ "d = ZarrTraceDataset.load(trace_path)\n",
+ "\n",
+ "d.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "aee8758a-6044-4dfe-8a0a-72db46d03d96",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "a231c459da204a2cb1f6545fde00e81e",
+ "version_major": 2,
+ "version_minor": 1
+ },
+ "text/plain": [
+ "TracePanelWidget(chart_size={'width': 0, 'height': 0}, language='zh', overview_select_range=(0, 0), overview_t…"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "tp = cn.panel_trace()\n",
+ "tp.set_trace_dataset(d)\n",
+ "tp.show_trace[0, :30]\n",
+ "tp"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c77ba3fe-9f24-4510-9095-addf160c0af2",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/archive/uart_receive.ipynb b/tests/jupyter/archive/uart_receive.ipynb
new file mode 100644
index 00000000..0fe8b13c
--- /dev/null
+++ b/tests/jupyter/archive/uart_receive.ipynb
@@ -0,0 +1,329 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 引入依赖\n",
+ "import cracknuts as cn\n",
+ "\n",
+ "# 创建 cracker \n",
+ "cracker = cn.new_cracker('192.168.0.15')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cracker.connect(force_update_bin=True, force_write_default_config=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "c2eabcc4-a583-4b97-bd58-66582a602c67",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import random"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "591ed9ce-7592-4c1e-978d-7c13815c4767",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\n",
+ "cracker.nut_voltage_enable()\n",
+ "cracker.nut_voltage(3.3)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "adb0121b-b742-444e-962f-2656c4464a21",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, None)"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cracker.uart_io_enable()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "a8d99263-86fd-4747-98f2-22d4965654a7",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "01 00 00 00 00 00 00 10 11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\n",
+ "0\n",
+ "00 00 00 00 00 00\n"
+ ]
+ }
+ ],
+ "source": [
+ "cmd_set_aes_enc_key = \"01 00 00 00 00 00 00 10\"\n",
+ "aes_key = \"11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\"\n",
+ "aes_data_len = 16\n",
+ "\n",
+ "# plaintext_data = random.randbytes(aes_data_len)\n",
+ "# tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ "cmd = cmd_set_aes_enc_key + ' ' + aes_key\n",
+ "status, ret = cracker.uart_transmit_receive(cmd, timeout=1000, rx_count=6)\n",
+ "\n",
+ "print(cmd)\n",
+ "print(status)\n",
+ "print(ret.hex(' ') if ret else 'None')\n",
+ "\n",
+ "# cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "3fda7c7b-11a4-4bef-96d5-23fb764824a0",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "01 02 00 00 00 00 00 10 df b2 f7 6a 62 53 38 f7 07 67 e8 fb 8d 0d 67 25\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "cmd_aes_enc = \"01 02 00 00 00 00 00 10\"\n",
+ "plaintext_data = random.randbytes(aes_data_len)\n",
+ "tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ "print(tx_data.hex(' '))\n",
+ "# s, r = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ "# s, r = cracker.uart_transmit_receive(tx_data, rx_count=6, is_trigger=True)\n",
+ "s, r = cracker.uart_transmit(tx_data, is_trigger=True)\n",
+ "\n",
+ "print(r.hex(' ') if r else 'None')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "eca717c6-019e-4832-80a8-e994e9780d6f",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "bdcec7ce-4654-4356-b5b6-9d76ff9c9ae0",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "00 00 00 00 00 10 20 7a c1 bc 35 25 f8 10 7d 9a e3 78 ad 31 bc a9\n"
+ ]
+ }
+ ],
+ "source": [
+ "s, r = cracker.uart_receive_fifo_dump()\n",
+ "print(r.hex(' ') if r else 'None')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "10239b57-b49e-418c-b7de-d7edc4bcb544",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "00 00 00 00 00 10 dc a1 a0 de 51 7a 46 71 40 68 27 bd 49 f4 74 ea\n"
+ ]
+ }
+ ],
+ "source": [
+ "s, r = cracker.uart_receive(rx_count=22)\n",
+ "print(r.hex(' ') if r else 'None')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "cc1e8740-01d1-4584-b29b-3df82d0e5ad1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(cracker.register_read(base_address=0x43c10000, offset=0x54))\n",
+ "print(cracker.register_read(base_address=0x43c10000, offset=0x58))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "723228e6-012c-4707-b038-acddabb4433e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(cracker.register_read(base_address=0x43c10000, offset=0x40))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cracker.get_id() # 获取设备ID"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import random\n",
+ "import time\n",
+ "from cracknuts.cracker import serial\n",
+ "\n",
+ "\n",
+ "cmd_set_aes_enc_key = \"01 00 00 00 00 00 00 10\"\n",
+ "cmd_aes_enc = \"01 02 00 00 00 00 00 10\"\n",
+ "\n",
+ "aes_key = \"11 22 33 44 55 66 77 88 99 00 aa bb cc dd ee ff\"\n",
+ "aes_data_len = 16\n",
+ "\n",
+ "sample_length = 20000\n",
+ "\n",
+ "def init(c):\n",
+ " cracker.nut_voltage_enable()\n",
+ " cracker.nut_voltage(3.3)\n",
+ " cracker.nut_clock_enable()\n",
+ " cracker.nut_clock_freq('8M')\n",
+ " cracker.uart_io_enable()\n",
+ " cracker.osc_sample_clock('48m')\n",
+ " cracker.osc_sample_length(sample_length)\n",
+ " cracker.osc_trigger_source('N')\n",
+ " cracker.osc_analog_gain('B', 10)\n",
+ " cracker.osc_trigger_level(0)\n",
+ " cracker.osc_trigger_mode('E')\n",
+ " cracker.osc_trigger_edge('U')\n",
+ " cracker.uart_config(baudrate=serial.Baudrate.BAUDRATE_115200, bytesize=serial.Bytesize.EIGHTBITS, parity=serial.Parity.PARITY_NONE, stopbits=serial.Stopbits.STOPBITS_ONE)\n",
+ "\n",
+ " time.sleep(2)\n",
+ " cmd = cmd_set_aes_enc_key + aes_key\n",
+ " status, ret = cracker.uart_transmit_receive(cmd, timeout=1000, rx_count=6)\n",
+ "\n",
+ "def do(cracer, count):\n",
+ " plaintext_data = random.randbytes(aes_data_len)\n",
+ " tx_data = bytes.fromhex(cmd_aes_enc.replace(' ', '')) + plaintext_data\n",
+ " status, ret = cracker.uart_transmit_receive(tx_data, rx_count= 6 + aes_data_len, is_trigger=True)\n",
+ " \n",
+ " return {\n",
+ " \"plaintext\": plaintext_data,\n",
+ " \"ciphertext\": ret[-aes_data_len:],\n",
+ " \"key\": bytes.fromhex(aes_key)\n",
+ " }\n",
+ "\n",
+ "\n",
+ "def finish(c):\n",
+ " ...\n",
+ " # print('optional behavior')\n",
+ "\n",
+ "\n",
+ "acq = cn.new_acquisition(cracker, init=init, do=do, finish=finish)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cn.panel(acq)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e8f3e5e2-f235-4b9e-9795-c5b1a5823542",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cracker.set_logging_level('debug')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a5a65297-d6bf-41cf-acb3-6de66922a702",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cracker.get_firmware_version()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/jupyter/test_cracknuts_panel.py b/tests/jupyter/test_cracknuts_panel.py
deleted file mode 100644
index 8705ba67..00000000
--- a/tests/jupyter/test_cracknuts_panel.py
+++ /dev/null
@@ -1,112 +0,0 @@
-import logging
-import os.path
-import socket
-import struct
-import threading
-import time
-import subprocess
-import sys
-import pytest
-from pathlib import Path
-from playwright.sync_api import sync_playwright
-import cracknuts.mock as mock
-from cracknuts import CrackerS1
-from cracknuts.cracker.protocol import Command
-
-
-@pytest.fixture(scope='module')
-def mock_cracker():
- def start_mock_cracker():
- # mock.start(logging_level=logging.WARNING)
- mock.start(logging_level=logging.INFO)
-
- mock_thread = threading.Thread(target=start_mock_cracker)
- mock_thread.daemon = True
- mock_thread.start()
- time.sleep(1)
- yield
-
-
-def wait_for_jupyter(port=8888, timeout=10):
- start_time = time.time()
- while time.time() - start_time < timeout:
- with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
- if s.connect_ex(("localhost", port)) == 0:
- return True
- time.sleep(0.5)
- return False
-
-
-@pytest.fixture(scope="module", autouse=True)
-def start_jupyter_lab(request):
- jupyter_process = subprocess.Popen(
- [str(Path(sys.executable)), "-m", "jupyter", "lab", "--no-browser", "--ServerApp.token=''",
- f"{os.path.dirname(request.fspath)}/test_cracknuts_panel.ipynb"],
- stdout=subprocess.PIPE, stderr=subprocess.PIPE
- )
-
- if not wait_for_jupyter():
- raise RuntimeError("Jupyter Lab 启动失败")
-
- yield
-
- jupyter_process.terminate()
- jupyter_process.wait()
-
-
-@pytest.fixture(scope="module")
-def browser(start_jupyter_lab):
- with sync_playwright() as p:
- browser = p.chromium.launch(headless=False)
- # browser = p.chromium.launch()
- yield browser
- browser.close()
-
-
-@pytest.fixture(scope="module")
-def jupyter_page(browser):
- context = browser.new_context()
- page = context.new_page()
- # page.set_viewport_size(viewport_size={"width": 1920, "height": 1080})
- yield page
- page.close()
-
-
-@pytest.fixture(scope="module")
-def assert_cracker(mock_cracker):
- cracker = CrackerS1("localhost")
- cracker.connect(update_bin=False)
- yield cracker
-
-
-def get_result_by_command(device, command):
- _, r = device.send_with_command(0xFFFF, payload=struct.pack('>I', command))
- return r
-
-
-@pytest.fixture(scope="module")
-def run_cell(mock_cracker, jupyter_page):
- jupyter_page.goto('http://localhost:8888/lab/workspaces/auto-0/tree/test_cracknuts_panel.ipynb')
-
- jupyter_page.click("div.jp-Cell:first-of-type", timeout=15000)
-
- jupyter_page.click(
- 'jp-button[title="Run this cell and advance (Shift+Enter)"][data-command="notebook:run-cell-and-select-next"]', timeout=15000)
-
- jupyter_page.wait_for_selector("#cracknuts_widget", timeout=15000, state="attached")
-
-
-def test_uart_enable_disable(run_cell, assert_cracker, jupyter_page):
- jupyter_page.click("#cracker_config_uart_enable", timeout=5000)
- assert struct.unpack('?', get_result_by_command(assert_cracker, Command.CRACKER_UART_ENABLE))[0]
-
- # jupyter_page.click("#cracker_config_uart_enable", timeout=5000)
- # assert not struct.unpack('?', get_result_by_command(assert_cracker, Command.CRACKER_UART_ENABLE))[0]
-
- jupyter_page.query_selector('.ant-select:has(#cracker_config_uart_baudrate)').click()
- jupyter_page.click('.ant-select-item.ant-select-item-option[title="57600"]', timeout=5000)
- assert struct.unpack('>BBBI', get_result_by_command(assert_cracker, Command.CRACKER_UART_CONFIG))[3] == 57600
-
- jupyter_page.query_selector('.ant-select:has(#cracker_config_uart_baudrate)').click()
- jupyter_page.click('.ant-select-item.ant-select-item-option[title="9600"]', timeout=5000)
- assert struct.unpack('>BBBI', get_result_by_command(assert_cracker, Command.CRACKER_UART_CONFIG))[3] == 9600
\ No newline at end of file