text stringlengths 0 1.05M | meta dict |
|---|---|
import pinutils;
info = {
'name' : "Mini STM32 angled 7 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_mini_stm32_ve.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'USE_LCD_FSMC',
'USE_FILESYSTEM',
'USE_FILESYSTEM_SDIO'
]
}
};
chip ... | {
"repo_name": "muet/Espruino",
"path": "boards/MINISTM32_ANGLED_VE.py",
"copies": "6",
"size": "4378",
"license": "mpl-2.0",
"hash": -8006676139833648000,
"line_mean": 27.4285714286,
"line_max": 143,
"alpha_frac": 0.4412973961,
"autogenerated": false,
"ratio": 2.4945868945868948,
"config_test":... |
import pinutils;
info = {
'name' : "Mini STM32 angled 7 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_mini_stm32_ve.bin',
'build' : {
'optimizeflags' : '-Os',
'libraries' : [
'GRAPHICS',
'LCD_FSMC',
'FILESYSTEM',
'FILESYSTEM_SD... | {
"repo_name": "lancernet/Espruino",
"path": "boards/MINISTM32_ANGLED_VE.py",
"copies": "6",
"size": "4696",
"license": "mpl-2.0",
"hash": -3040074330807640600,
"line_mean": 28.1677018634,
"line_max": 143,
"alpha_frac": 0.4531516184,
"autogenerated": false,
"ratio": 2.515265131226567,
"config_te... |
import pinutils;
info = {
'name' : "Mini STM32 angled 7 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_mini_stm32_ve.bin',
};
chip = {
'part' : "STM32F103VE", #T6
'family' : "STM32F1",
'package' : "LQFP100",
'ram' : 64,
'flash' : 512,
'speed' : 72,
... | {
"repo_name": "tdautc19841202/Espruino",
"path": "boards/MINISTM32_ANGLED_VE.py",
"copies": "6",
"size": "4244",
"license": "mpl-2.0",
"hash": 996935010503384400,
"line_mean": 28.0684931507,
"line_max": 143,
"alpha_frac": 0.4403864279,
"autogenerated": false,
"ratio": 2.495002939447384,
"config... |
import pinutils;
info = {
'name' : "Mini STM32 angled 7 inch LCD Board (VGT6)",
#'variables' : 2800,
'variables' : 5376, # (96-12)*1024/16-1
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_mini_stm32_vg.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'USE_LCD_FSMC',
'USE_FILESYSTEM',
... | {
"repo_name": "jasonkajita/Espruino",
"path": "boards/MINISTM32_ANGLED_VG.py",
"copies": "6",
"size": "4419",
"license": "mpl-2.0",
"hash": -3757371124202079000,
"line_mean": 27.5096774194,
"line_max": 143,
"alpha_frac": 0.4424077846,
"autogenerated": false,
"ratio": 2.4937923250564333,
"config... |
import pinutils;
info = {
'name' : "Normal Linux Compile",
'default_console' : "EV_USBSERIAL",
'binary_name' : 'espruino',
'build' : {
'libraries' : [
'NET',
'GRAPHICS',
'FILESYSTEM',
'CRYPTO',
'TLS',
'HASHLIB',
'TELNET',
],
'makefile' : [
'LINUX=1',
]
}
};
chip... | {
"repo_name": "lancernet/Espruino",
"path": "boards/LINUX.py",
"copies": "4",
"size": "1473",
"license": "mpl-2.0",
"hash": -6698937705336763000,
"line_mean": 24.8421052632,
"line_max": 93,
"alpha_frac": 0.5397148676,
"autogenerated": false,
"ratio": 3.2806236080178173,
"config_test": false,
... |
import pinutils;
info = {
'name' : "Normal Linux Compile",
'default_console' : "EV_USBSERIAL",
'binary_name' : 'espruino_%v_linux',
};
chip = {
'part' : "LINUX",
'family' : "LINUX",
'package' : "",
'ram' : -1,
'flash' : -1,
'speed' : -1,
'usart' : 0,
'spi' : 1,
'i2c' : 0,
'adc' : 0,
'dac' : 0,... | {
"repo_name": "rwaldron/Espruino",
"path": "boards/LINUX.py",
"copies": "1",
"size": "1201",
"license": "mpl-2.0",
"hash": 4743886991800445000,
"line_mean": 25.6888888889,
"line_max": 91,
"alpha_frac": 0.5470441299,
"autogenerated": false,
"ratio": 3.31767955801105,
"config_test": false,
"has... |
import pinutils;
info = {
'name' : "Original Espruino Board rev 1.3/1.4",
'link' : [ "http://www.espruino.com/EspruinoBoard" ],
'espruino_page_link' : "EspruinoBoard",
'default_console' : "EV_SERIAL1",
'default_console_tx' : "A9",
'default_console_rx' : "A10",
'variables' : 2240,
'bootloader' : 1,
'serial_boo... | {
"repo_name": "wilberforce/Espruino",
"path": "boards/ESPRUINOBOARD.py",
"copies": "1",
"size": "4198",
"license": "mpl-2.0",
"hash": 78572988054197700,
"line_mean": 29.8676470588,
"line_max": 212,
"alpha_frac": 0.5385898047,
"autogenerated": false,
"ratio": 2.5442424242424244,
"config_test": f... |
import pinutils;
info = {
'name' : "Raspberry Pi",
'default_console' : "EV_USBSERIAL",
'binary_name' : 'espruino_%v_raspberrypi',
'build' : {
'defines' : [
'USE_NET',
'USE_GRAPHICS',
'USE_FILESYSTEM',
'USE_CRYPTO',
'USE_TLS'
]
}
};
chip = {
'part' : "RASPBERRYPI",
'family' : "LI... | {
"repo_name": "mjdietzx/Espruino",
"path": "boards/RASPBERRYPI.py",
"copies": "6",
"size": "1972",
"license": "mpl-2.0",
"hash": 5104667721245187000,
"line_mean": 31.8666666667,
"line_max": 91,
"alpha_frac": 0.5735294118,
"autogenerated": false,
"ratio": 2.9085545722713864,
"config_test": false... |
import pinutils;
info = {
'name' : "Raspberry Pi",
'default_console' : "EV_USBSERIAL",
'binary_name' : 'espruino_%v_raspberrypi',
'build' : {
'optimizeflags' : '-O3',
'libraries' : [
'NET',
'GRAPHICS',
'FILESYSTEM',
'CRYPTO',
'TLS',
'HASHLIB',
'TELNET',
],
'makefile' ... | {
"repo_name": "wilberforce/Espruino",
"path": "boards/RASPBERRYPI.py",
"copies": "4",
"size": "2085",
"license": "mpl-2.0",
"hash": -8609154723728374000,
"line_mean": 30.1194029851,
"line_max": 91,
"alpha_frac": 0.5654676259,
"autogenerated": false,
"ratio": 2.9201680672268906,
"config_test": f... |
import pinutils;
info = {
'name' : "Raspberry Pi",
'default_console' : "EV_USBSERIAL",
'binary_name' : 'espruino_%v_raspberrypi',
};
chip = {
'part' : "RASPBERRYPI",
'family' : "LINUX",
'package' : "",
'ram' : -1,
'flash' : -1,
'speed' : -1,
'usart' : 1,
'spi' : 1,
'i2c' : 1,
'adc' : 0,
'dac' ... | {
"repo_name": "vshymanskyy/Espruino",
"path": "boards/RASPBERRYPI.py",
"copies": "9",
"size": "1908",
"license": "mpl-2.0",
"hash": 1092706856002980000,
"line_mean": 33.0714285714,
"line_max": 91,
"alpha_frac": 0.5828092243,
"autogenerated": false,
"ratio": 2.9218989280245022,
"config_test": fa... |
import pinutils;
info = {
'name' : "Single Chip",
'link' : [ "http://www.st.com/stm32-discovery" ],
'variables' : 700,
'binary_name' : 'espruino_%v_stm32f103tb.bin',
};
chip = {
'part' : "STM32F103TBU6",
'family' : "STM32F1",
'package' : "VFQFPN36",
'ram' : 20,
'flash' : 128,
'speed' : 24,
'usart' :... | {
"repo_name": "femtoio/Espruino",
"path": "boards/TINYCHIP.py",
"copies": "10",
"size": "1493",
"license": "mpl-2.0",
"hash": -4284695172673174500,
"line_mean": 28.86,
"line_max": 91,
"alpha_frac": 0.5539182853,
"autogenerated": false,
"ratio": 2.9623015873015874,
"config_test": false,
"has_n... |
import pinutils;
info = {
'name' : "Sony Smartwatch",
'link' : [ "http://developer.sonymobile.com/services/open-smartwatch-project/smartwatch-hacker-guide/" ],
'variables' : 4000,
'binary_name' : 'espruino_%v_smartwatch.bin',
};
chip = {
'part' : "STM32F205RG",
'family' : "STM32F2",
'package' : "LQFP48", # F... | {
"repo_name": "0xPIT/Espruino",
"path": "boards/SMARTWATCH.py",
"copies": "10",
"size": "1842",
"license": "mpl-2.0",
"hash": 4551961515142608000,
"line_mean": 31.3157894737,
"line_max": 106,
"alpha_frac": 0.5781758958,
"autogenerated": false,
"ratio": 2.9854132901134522,
"config_test": false,
... |
import pinutils;
info = {
'name' : "STM32 2.4 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_24_ve.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'USE_LCD_FSMC',
'USE_FILESYSTEM',
'USE_FILESYSTEM_SDIO'
]
}
};
chip = {
'par... | {
"repo_name": "tve/Espruino",
"path": "boards/HYSTM32_24.py",
"copies": "6",
"size": "4386",
"license": "mpl-2.0",
"hash": 8698483539645064000,
"line_mean": 27.4805194805,
"line_max": 195,
"alpha_frac": 0.4414044688,
"autogenerated": false,
"ratio": 2.4205298013245033,
"config_test": false,
"... |
import pinutils;
info = {
'name' : "STM32 2.4 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_24_ve.bin',
'build' : {
'optimizeflags' : '-Os',
'libraries' : [
'GRAPHICS',
'LCD_FSMC',
'FILESYSTEM',
'FILESYSTEM_SDIO',
... | {
"repo_name": "luetgendorf/Espruino",
"path": "boards/HYSTM32_24.py",
"copies": "9",
"size": "4682",
"license": "mpl-2.0",
"hash": 3139798330964892700,
"line_mean": 28.2625,
"line_max": 195,
"alpha_frac": 0.4525843657,
"autogenerated": false,
"ratio": 2.4449086161879894,
"config_test": false,
... |
import pinutils;
info = {
'name' : "STM32 2.4 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_24_ve.bin',
};
chip = {
'part' : "STM32F103VE", #T6
'family' : "STM32F1",
'package' : "LQFP100",
'ram' : 64,
'flash' : 512,
'speed' : 72,
'usart' ... | {
"repo_name": "dptechnics/Espruino",
"path": "boards/HYSTM32_24.py",
"copies": "9",
"size": "4252",
"license": "mpl-2.0",
"hash": 5953821661754122000,
"line_mean": 28.1232876712,
"line_max": 195,
"alpha_frac": 0.4404985889,
"autogenerated": false,
"ratio": 2.4186575654152445,
"config_test": fal... |
import pinutils;
info = {
'name' : "STM32 2.8 inch LCD Board (RBT6)",
'variables' : 400, # FIXME we could get 700, but we don't have enough flash
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_28_rb.bin',
};
chip = {
'part' : "STM32F103RB", #T6
'family' : "STM32F1",
'package' : "LQFP64",
... | {
"repo_name": "oesterle/Espruino",
"path": "boards/HYSTM32_28.py",
"copies": "7",
"size": "3850",
"license": "mpl-2.0",
"hash": 2513137811410286000,
"line_mean": 26.5,
"line_max": 93,
"alpha_frac": 0.4464935065,
"autogenerated": false,
"ratio": 2.5245901639344264,
"config_test": false,
"has_n... |
import pinutils;
info = {
'name' : "STM32 2.8 inch LCD Board (RBT6)",
'variables' : 510, # FIXME we could get 700, but we don't have enough flash
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_28_rb.bin',
};
chip = {
'part' : "STM32F103RB", #T6
'family' : "STM32F1",
'package' : "LQFP64",
... | {
"repo_name": "rwaldron/Espruino",
"path": "boards/HYSTM32_28.py",
"copies": "1",
"size": "3746",
"license": "mpl-2.0",
"hash": -9087370755454216000,
"line_mean": 26.7481481481,
"line_max": 93,
"alpha_frac": 0.4514148425,
"autogenerated": false,
"ratio": 2.524258760107817,
"config_test": false,... |
import pinutils;
info = {
'name' : "STM32 2.8 inch LCD Board (RBT6)",
'variables' : 700,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_28_rb.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'USE_LCD_FSMC'
]
}
};
chip = {
'part' : "STM32F103RB", #T6
'family' : "STM32F1",
'p... | {
"repo_name": "mjdietzx/Espruino",
"path": "boards/HYSTM32_28.py",
"copies": "5",
"size": "4079",
"license": "mpl-2.0",
"hash": 7029094082194084000,
"line_mean": 26.0132450331,
"line_max": 93,
"alpha_frac": 0.4474135818,
"autogenerated": false,
"ratio": 2.5272614622057,
"config_test": false,
... |
import pinutils;
info = {
'name' : "STM32 2.8 inch LCD Board (RBT6)",
'variables' : 700,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_28_rb.bin',
'build' : {
'optimizeflags' : '-Os',
'libraries' : [
'GRAPHICS',
'LCD_FSMC',
'NEOPIXEL'
],
'makefile' : [
'S... | {
"repo_name": "wilberforce/Espruino",
"path": "boards/HYSTM32_28.py",
"copies": "4",
"size": "4380",
"license": "mpl-2.0",
"hash": 8076478558068656000,
"line_mean": 26.5471698113,
"line_max": 96,
"alpha_frac": 0.4593607306,
"autogenerated": false,
"ratio": 2.5450319581638583,
"config_test": fal... |
import pinutils;
info = {
'name' : "STM32 2.8 inch LCD Board (RBT6)",
'variables' : 700,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_hystm32_28_rb.bin',
};
chip = {
'part' : "STM32F103RB", #T6
'family' : "STM32F1",
'package' : "LQFP64",
'ram' : 20,
'flash' : 128,
'speed' : 72,
'usart' : ... | {
"repo_name": "AlexanderBrevig/Espruino",
"path": "boards/HYSTM32_28.py",
"copies": "1",
"size": "4000",
"license": "mpl-2.0",
"hash": 1038983778220845300,
"line_mean": 26.5862068966,
"line_max": 93,
"alpha_frac": 0.448,
"autogenerated": false,
"ratio": 2.5300442757748263,
"config_test": false,... |
import pinutils;
info = {
'name' : "STM32F401C Discovery",
'link' : [ "http://www.st.com/web/catalog/tools/FM116/SC959/SS1532/LN1848/PF259098" ],
'default_console' : "EV_SERIAL2",
'variables' : 3040,
'binary_name' : 'espruino_%v_stm32f401cdiscovery.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'US... | {
"repo_name": "tve/Espruino",
"path": "boards/STM32F401CDISCOVERY.py",
"copies": "6",
"size": "4168",
"license": "mpl-2.0",
"hash": 2367327365637102000,
"line_mean": 29.8740740741,
"line_max": 157,
"alpha_frac": 0.4748080614,
"autogenerated": false,
"ratio": 2.4973037747153985,
"config_test": f... |
import pinutils;
info = {
'name' : "STM32F401C Discovery",
'link' : [ "http://www.st.com/web/catalog/tools/FM116/SC959/SS1532/LN1848/PF259098" ],
'default_console' : "EV_SERIAL2",
'variables' : 3040,
'binary_name' : 'espruino_%v_stm32f401cdiscovery.bin',
};
chip = {
'part' : "STM32F401VCT6",
'family' : ... | {
"repo_name": "0xPIT/Espruino",
"path": "boards/STM32F401CDISCOVERY.py",
"copies": "1",
"size": "4088",
"license": "mpl-2.0",
"hash": -6266476011930594000,
"line_mean": 31.188976378,
"line_max": 157,
"alpha_frac": 0.4752935421,
"autogenerated": false,
"ratio": 2.511056511056511,
"config_test": ... |
import pinutils;
info = {
'name' : "STM32 F411 Discovery",
'link' : [ "http://www.st.com/content/st_com/en/products/evaluation-tools/product-evaluation-tools/mcu-eval-tools/stm32-mcu-eval-tools/stm32-mcu-discovery-kits/32f411ediscovery.html" ],
'default_console' : "EV_SERIAL2", # FIXME: This was S2 because of pin ... | {
"repo_name": "nkolban/Espruino",
"path": "boards/STM32F411DISCOVERY.py",
"copies": "4",
"size": "4699",
"license": "mpl-2.0",
"hash": -1295991559439365400,
"line_mean": 34.3308270677,
"line_max": 187,
"alpha_frac": 0.5201106618,
"autogenerated": false,
"ratio": 2.577619308831596,
"config_test"... |
import pinutils;
info = {
'name' : "STM32 F429 Discovery",
'link' : [ "http://www.st.com/web/catalog/tools/FM116/SC959/SS1532/LN1199/PF259090" ],
'default_console' : "EV_SERIAL1",
'variables' : 5450,
'binary_name' : 'espruino_%v_stm32f429idiscovery.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'US... | {
"repo_name": "nkolban/Espruino",
"path": "boards/STM32F429IDISCOVERY.py",
"copies": "6",
"size": "5414",
"license": "mpl-2.0",
"hash": 6289600820116494000,
"line_mean": 27.3455497382,
"line_max": 104,
"alpha_frac": 0.4117103805,
"autogenerated": false,
"ratio": 2.6243334949103247,
"config_test... |
import pinutils;
info = {
'name' : "STM32 F4 Discovery",
'link' : [ "http://www.st.com/web/catalog/tools/FM116/SC959/SS1532/LN1199/PF252419" ],
'default_console' : "EV_SERIAL2", # FIXME: This was S2 because of pin conflict. Not sure if it's really an issue?
'variables' : 5450,
'binary_name' : 'espruino_%v_stm32f... | {
"repo_name": "jasonkajita/Espruino",
"path": "boards/STM32F4DISCOVERY.py",
"copies": "1",
"size": "3767",
"license": "mpl-2.0",
"hash": -8762458686106632000,
"line_mean": 29.6260162602,
"line_max": 157,
"alpha_frac": 0.4669498274,
"autogenerated": false,
"ratio": 2.457273320287019,
"config_tes... |
import pinutils;
info = {
'name' : "STM32 VL Discovery",
'link' : [ "http://www.st.com/stm32-discovery" ],
'variables' : 254,
'binary_name' : 'espruino_%v_stm32vldiscovery.bin',
};
chip = {
'part' : "STM32F100RBT6",
'family' : "STM32F1",
'package' : "LQFP64",
'ram' : 8,
'flash' : 128,
'speed' : 24,
... | {
"repo_name": "rwaldron/Espruino",
"path": "boards/STM32VLDISCOVERY.py",
"copies": "1",
"size": "2340",
"license": "mpl-2.0",
"hash": -8153021543779825000,
"line_mean": 27.8888888889,
"line_max": 196,
"alpha_frac": 0.5141025641,
"autogenerated": false,
"ratio": 2.4788135593220337,
"config_test"... |
import pinutils;
info = {
'name' : "STM32 VL Discovery",
'link' : [ "http://www.st.com/stm32-discovery" ],
'variables' : 500,
'binary_name' : 'espruino_%v_stm32vldiscovery.bin',
'build' : {
'defines' : [
]
}
};
chip = {
'part' : "STM32F100RBT6",
'family' : "STM32F1",
'package' : "LQFP64",
'ram' : ... | {
"repo_name": "tve/Espruino",
"path": "boards/STM32VLDISCOVERY.py",
"copies": "6",
"size": "2483",
"license": "mpl-2.0",
"hash": 1564518836863301000,
"line_mean": 27.5402298851,
"line_max": 196,
"alpha_frac": 0.5006041079,
"autogenerated": false,
"ratio": 2.4805194805194803,
"config_test": fals... |
import pinutils;
info = {
'name' : "STM32 VL Discovery",
'link' : [ "http://www.st.com/stm32-discovery" ],
'variables' : 500,
'binary_name' : 'espruino_%v_stm32vldiscovery.bin',
'build' : {
'optimizeflags' : '-Os',
'libraries' : [
'NEOPIXEL'
],
'makefile' : [
'SAVE_ON_FLASH=1',
'STLIB=... | {
"repo_name": "luetgendorf/Espruino",
"path": "boards/STM32VLDISCOVERY.py",
"copies": "4",
"size": "2687",
"license": "mpl-2.0",
"hash": 4602776527317333500,
"line_mean": 27.585106383,
"line_max": 196,
"alpha_frac": 0.5083736509,
"autogenerated": false,
"ratio": 2.4674012855831036,
"config_test... |
import pinutils;
info = {
'name' : "STM32 VL Discovery",
'link' : [ "http://www.st.com/stm32-discovery" ],
'variables' : 500,
'binary_name' : 'espruino_%v_stm32vldiscovery.bin',
};
chip = {
'part' : "STM32F100RBT6",
'family' : "STM32F1",
'package' : "LQFP64",
'ram' : 8,
'flash' : 128,
'speed' : 24,
... | {
"repo_name": "AlexanderBrevig/Espruino",
"path": "boards/STM32VLDISCOVERY.py",
"copies": "1",
"size": "2446",
"license": "mpl-2.0",
"hash": 6468899245274227000,
"line_mean": 28.4698795181,
"line_max": 196,
"alpha_frac": 0.503270646,
"autogenerated": false,
"ratio": 2.483248730964467,
"config_t... |
import pinutils;
info = {
'name' : "STRIVE Mini STM32 2.4 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_strive_mini_stm32.bin',
'build' : {
'defines' : [
'USE_GRAPHICS',
'USE_LCD_FSMC',
'USE_FILESYSTEM',
'USE_FILESYSTEM_SDIO'
]
}
};... | {
"repo_name": "tve/Espruino",
"path": "boards/MINISTM32_STRIVE.py",
"copies": "6",
"size": "4396",
"license": "mpl-2.0",
"hash": -5652072548409625000,
"line_mean": 27.5454545455,
"line_max": 145,
"alpha_frac": 0.4433575978,
"autogenerated": false,
"ratio": 2.4794134235758603,
"config_test": fal... |
import pinutils;
info = {
'name' : "STRIVE Mini STM32 2.4 inch LCD Board (VET6)",
'variables' : 2800,
'serial_bootloader' : True,
'binary_name' : 'espruino_%v_strive_mini_stm32.bin',
};
chip = {
'part' : "STM32F103VE", #T6
'family' : "STM32F1",
'package' : "LQFP100",
'ram' : 64,
'flash' : 512,
'speed' ... | {
"repo_name": "koltegirish/Espruino",
"path": "boards/MINISTM32_STRIVE.py",
"copies": "6",
"size": "4262",
"license": "mpl-2.0",
"hash": 3101998220816216600,
"line_mean": 28.1917808219,
"line_max": 145,
"alpha_frac": 0.4425152511,
"autogenerated": false,
"ratio": 2.47934845840605,
"config_test"... |
import pinutils;
info = {
'name' : "nRF51 Development Kit",
'link' : [ "https://www.nordicsemi.com/Products/Bluetooth-Smart-Bluetooth-low-energy/nRF51822" ],
'default_console' : "EV_SERIAL1",
'variables' : 200, # How many variables are allocated for Espruino to use. RAM will be overflowed if this number is too h... | {
"repo_name": "vshymanskyy/Espruino",
"path": "boards/NRF51822DK.py",
"copies": "2",
"size": "3347",
"license": "mpl-2.0",
"hash": -5591275849444216000,
"line_mean": 40.3209876543,
"line_max": 200,
"alpha_frac": 0.5847027189,
"autogenerated": false,
"ratio": 2.796157059314954,
"config_test": fa... |
import pinutils;
info = {
'name' : "nRF51 Development Kit",
'link' : [ "https://www.nordicsemi.com/Products/Bluetooth-Smart-Bluetooth-low-energy/nRF51822" ],
# This is the PCA10028
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D9",
'default_console_rx' : "D11",
'default_console_baudrate' : "9600"... | {
"repo_name": "jasonkajita/Espruino",
"path": "boards/NRF51822DK.py",
"copies": "1",
"size": "4284",
"license": "mpl-2.0",
"hash": -3451903977877127700,
"line_mean": 39.4150943396,
"line_max": 200,
"alpha_frac": 0.5905695612,
"autogenerated": false,
"ratio": 2.7532133676092543,
"config_test": f... |
import pinutils;
info = {
'name' : "nRF51 Tag",
'link' : [ "" ],
'default_console' : "EV_BLUETOOTH",
# 'default_console_tx' : "D15",
# 'default_console_rx' : "D17",
# 'default_console_baudrate' : "9600",
'variables' : 350,
'binary_name' : 'espruino_%v_nrf51tag.bin',
'build' : {
'optimizeflags' : '-Os',
'... | {
"repo_name": "lancernet/Espruino",
"path": "boards/NRF51TAG.py",
"copies": "6",
"size": "2277",
"license": "mpl-2.0",
"hash": -4095528962199229000,
"line_mean": 30.1917808219,
"line_max": 156,
"alpha_frac": 0.5718050066,
"autogenerated": false,
"ratio": 2.976470588235294,
"config_test": false,... |
import pinutils;
info = {
'name' : "nRF51 Tag",
'link' : [ "" ],
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D15",
'default_console_rx' : "D17",
'default_console_baudrate' : "9600",
'variables' : 310,
'binary_name' : 'espruino_%v_nrf51tag.bin',
'build' : {
'defines' : [
'USE_BLUETOOTH'
... | {
"repo_name": "tve/Espruino",
"path": "boards/NRF51TAG.py",
"copies": "2",
"size": "2106",
"license": "mpl-2.0",
"hash": 2276441413656820500,
"line_mean": 30.4328358209,
"line_max": 156,
"alpha_frac": 0.5754985755,
"autogenerated": false,
"ratio": 2.991477272727273,
"config_test": false,
"has... |
import pinutils;
info = {
'name' : "nRF52 Preview Development Kit",
'link' : [ "https://www.nordicsemi.com/Products/Bluetooth-Smart-Bluetooth-low-energy/nRF52832" ],
'default_console' : "EV_SERIAL1",
'variables' : 750, # How many variables are allocated for Espruino to use. RAM will be overflowed if this number ... | {
"repo_name": "dptechnics/Espruino",
"path": "boards/NRF52832DK.py",
"copies": "1",
"size": "3722",
"license": "mpl-2.0",
"hash": 5111407994938024000,
"line_mean": 40.8202247191,
"line_max": 200,
"alpha_frac": 0.5875873186,
"autogenerated": false,
"ratio": 2.809056603773585,
"config_test": fals... |
import pinutils;
info = {
'name' : "nRF52 Preview Development Kit",
'link' : [ "https://www.nordicsemi.com/Products/Bluetooth-Smart-Bluetooth-low-energy/nRF52832" ],
# This is the PCA10036
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D6",
'default_console_rx' : "D8",
'default_console_baudrate' :... | {
"repo_name": "jasonkajita/Espruino",
"path": "boards/NRF52832DK.py",
"copies": "1",
"size": "3942",
"license": "mpl-2.0",
"hash": 4830879622792385000,
"line_mean": 39.2244897959,
"line_max": 200,
"alpha_frac": 0.5887874176,
"autogenerated": false,
"ratio": 2.803698435277383,
"config_test": fal... |
import pinutils;
info = {
'name' : "PuckJS",
'link' : [ "http://www.espruino.com/PuckJS" ],
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D28",
'default_console_rx' : "D29",
'default_console_baudrate' : "9600",
# Number of variables can be WAY higher on this board
'variables' : 2000, # How many v... | {
"repo_name": "wilberforce/Espruino",
"path": "boards/PUCKJS.py",
"copies": "1",
"size": "5107",
"license": "mpl-2.0",
"hash": -4286140541753800000,
"line_mean": 32.5986842105,
"line_max": 156,
"alpha_frac": 0.5925200705,
"autogenerated": false,
"ratio": 2.694986807387863,
"config_test": false,... |
import pinutils;
info = {
'name' : "PuckJS",
'link' : [ "" ],
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D28",
'default_console_rx' : "D29",
'default_console_baudrate' : "9600",
# Number of variables can be WAY higher on this board
'variables' : 1020, # How many variables are allocated for Esp... | {
"repo_name": "mjdietzx/Espruino",
"path": "boards/PUCKJS.py",
"copies": "2",
"size": "3062",
"license": "mpl-2.0",
"hash": -7018206239359297000,
"line_mean": 34.6046511628,
"line_max": 156,
"alpha_frac": 0.5891574135,
"autogenerated": false,
"ratio": 2.8404452690166977,
"config_test": false,
... |
import pinutils;
# placeholder
info = {
'name' : "MBed LPC1768",
'link' : [ "http://www.espruino.com/kick" ],
'variables' : 2000, #?
'binary_name' : 'espruino_%v_lpc1768.bin',
};
chip = {
'part' : "LPC1768",
'family' : "LPC1768",
# 'package' : "LQFP64",
'ram' : 32,
'flash' : 512,
'speed' : 96,
'usart'... | {
"repo_name": "dptechnics/Espruino",
"path": "boards/LPC1768.py",
"copies": "4",
"size": "1257",
"license": "mpl-2.0",
"hash": -8837635905924484000,
"line_mean": 25.7446808511,
"line_max": 91,
"alpha_frac": 0.5521081941,
"autogenerated": false,
"ratio": 3.1503759398496243,
"config_test": false,... |
import pinutils;
# placeholder
info = {
'name' : "RedBear Duo",
'link' : [ "http://www.RedBear.cc/Duo" ],
'default_console' : "EV_SERIAL1",
'variables' : 2250,
'bootloader' : 0,
'binary_name' : 'espruino_%v_redbearduo.bin',
'build' : {
'defines' : [
]
}
};
chip = {
'part' : "STM32F205RGT6",
'family' :... | {
"repo_name": "redbear/Espruino",
"path": "boards/REDBEARDUO.py",
"copies": "1",
"size": "1944",
"license": "mpl-2.0",
"hash": -5433255783521351000,
"line_mean": 29.375,
"line_max": 91,
"alpha_frac": 0.5596707819,
"autogenerated": false,
"ratio": 2.884272997032641,
"config_test": false,
"has_... |
# The ESP8266_OTA represents esp8266 modules with 1MB or more flash and using the OTA
# (over the air update) flash layout with two 512KB partitions in the first MB and the
# v1.4 or later bootloader at 0x0. Modules with >1MB flash will have a SPIFFS filesystem
# in the flash beyond the first 1MB.
import pinutils;
in... | {
"repo_name": "dptechnics/Espruino",
"path": "boards/ESP8266_OTA.py",
"copies": "1",
"size": "1949",
"license": "mpl-2.0",
"hash": 497478377671889800,
"line_mean": 31.4833333333,
"line_max": 93,
"alpha_frac": 0.5931246793,
"autogenerated": false,
"ratio": 3.2268211920529803,
"config_test": fals... |
import pinutils;
import json;
info = {
'name' : "LC Technology STM32F103RBT6 / ebay board",
'link' : [ "http://www.lctech-inc.com/Hardware/Detail.aspx?id=4ae8ef7e-9bfe-48a1-9540-fa66ad4645b4"],
'variables' : 715,
'binary_name' : 'espruino_%v_lctech_stm32f103rbt6.bin',
'build' : {
'defines' : [
]
}
};
chip... | {
"repo_name": "jasonkajita/Espruino",
"path": "boards/LCTECH_STM32F103RBT6.py",
"copies": "6",
"size": "2844",
"license": "mpl-2.0",
"hash": -313055820122350500,
"line_mean": 27.44,
"line_max": 110,
"alpha_frac": 0.5239099859,
"autogenerated": false,
"ratio": 2.4328485885372113,
"config_test": ... |
import pinutils;
info = {
'name' : "RuuviTag",
'link' : [ "https://ruuvitag.com" ],
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D4",
'default_console_rx' : "D5",
'default_console_baudrate' : "9600",
# Number of variables can be WAY higher on this board
'variables' : 2000, # How many variables a... | {
"repo_name": "wilberforce/Espruino",
"path": "boards/RUUVITAG.py",
"copies": "1",
"size": "4494",
"license": "mpl-2.0",
"hash": 5473398320755803000,
"line_mean": 37.4102564103,
"line_max": 200,
"alpha_frac": 0.5694259012,
"autogenerated": false,
"ratio": 2.713768115942029,
"config_test": false... |
import pinutils;
info = {
'name' : "RuuviTag",
'link' : [ "https://ruuvitag.com" ],
'espruino_page_link' : 'Ruuvitag',
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D4",
'default_console_rx' : "D5",
'default_console_baudrate' : "9600",
# Number of variables can be WAY higher on this board
'varia... | {
"repo_name": "luetgendorf/Espruino",
"path": "boards/RUUVITAG.py",
"copies": "2",
"size": "4552",
"license": "mpl-2.0",
"hash": -9173073306221544000,
"line_mean": 37.5762711864,
"line_max": 200,
"alpha_frac": 0.5705184534,
"autogenerated": false,
"ratio": 2.704693998811646,
"config_test": fals... |
import pinutils;
# placeholder
info = {
'name' : "BBC micro:bit",
'link' : [ "https://en.wikipedia.org/wiki/Micro_Bit" ],
'default_console' : "EV_SERIAL1",
'default_console_tx' : "H0", # pin 24
'default_console_rx' : "H1", # pin 25
'default_console_baudrate' : "9600",
'variables' : 145,
'binary_name' : 'espru... | {
"repo_name": "AlexanderBrevig/Espruino",
"path": "boards/MICROBIT.py",
"copies": "1",
"size": "3831",
"license": "mpl-2.0",
"hash": 8363764453148080000,
"line_mean": 46.2962962963,
"line_max": 119,
"alpha_frac": 0.5108326808,
"autogenerated": false,
"ratio": 2.6567267683772537,
"config_test": ... |
import pinutils;
# placeholder
info = {
'name' : "BBC micro:bit",
'link' : [ "https://en.wikipedia.org/wiki/Micro_Bit" ],
'espruino_page_link' : 'MicroBit',
'default_console' : "EV_SERIAL1",
'default_console_tx' : "H0", # pin 24
'default_console_rx' : "H1", # pin 25
'default_console_baudrate' : "9600",
'variab... | {
"repo_name": "nkolban/Espruino",
"path": "boards/MICROBIT.py",
"copies": "1",
"size": "5111",
"license": "mpl-2.0",
"hash": 3895080573413977000,
"line_mean": 39.5634920635,
"line_max": 119,
"alpha_frac": 0.5089023674,
"autogenerated": false,
"ratio": 2.6049949031600406,
"config_test": false,
... |
import pinutils;
# placeholder
info = {
'name' : "BBC micro:bit",
'link' : [ "" ],
'variables' : 145,
'binary_name' : 'espruino_%v_microbit.bin',
};
chip = {
'part' : "NRF51822",
'family' : "NRF51",
# 'package' : "LQFP64",
'ram' : 16,
'flash' : 256,
'speed' : 96,
'usart' : 1,
'spi' : 1,
'i2c' : 1... | {
"repo_name": "dptechnics/Espruino",
"path": "boards/MICROBIT.py",
"copies": "1",
"size": "3159",
"license": "mpl-2.0",
"hash": -7185730582049484000,
"line_mean": 44.1285714286,
"line_max": 107,
"alpha_frac": 0.4985754986,
"autogenerated": false,
"ratio": 2.775922671353251,
"config_test": false... |
import pinutils;
# placeholder
info = {
'name' : "BBC micro:bit",
'link' : [ "" ],
'variables' : 191,
'binary_name' : 'espruino_%v_microbit.bin',
};
chip = {
'part' : "NRF51822",
'family' : "NRF51",
# 'package' : "LQFP64",
'ram' : 16,
'flash' : 256,
'speed' : 96,
'usart' : 1,
'spi' : 1,
'i2c' : 1... | {
"repo_name": "vshymanskyy/Espruino",
"path": "boards/MICROBIT.py",
"copies": "1",
"size": "3159",
"license": "mpl-2.0",
"hash": 2214225750410552800,
"line_mean": 44.1285714286,
"line_max": 107,
"alpha_frac": 0.4985754986,
"autogenerated": false,
"ratio": 2.7734855136084287,
"config_test": fals... |
import pinutils;
# placeholder
info = {
'name' : "DO-003 watch",
'link' : [ "http://forum.espruino.com/conversations/280747" ],
# Very experimental firmware for DO 003 fitness watch
'espruino_page_link' : '',
'default_console' : "EV_SERIAL1",
'default_console_tx' : "D18", # pin 24
'default_console_rx' : "D17",... | {
"repo_name": "mjdietzx/Espruino",
"path": "boards/DO-003.py",
"copies": "6",
"size": "2312",
"license": "mpl-2.0",
"hash": 3293554083189132300,
"line_mean": 27.9,
"line_max": 91,
"alpha_frac": 0.5415224913,
"autogenerated": false,
"ratio": 2.937738246505718,
"config_test": false,
"has_no_key... |
BIN_FILE_DESTINATION = r""
COMPILE_TARGET = "lpc1768"
COMPILE_TOOLCHAIN = "GCC_ARM"
import os
from subprocess import call
from shutil import copy
from os.path import join
def Get_bin_file_path():
search_path = join("..", "BUILD", COMPILE_TARGET, COMPILE_TOOLCHAIN)
for item in os.listdir(search_path):
... | {
"repo_name": "SamuelMartens/Embed_scripts",
"path": "compile_project.py",
"copies": "1",
"size": "1134",
"license": "mit",
"hash": -1493697600506334000,
"line_mean": 26.6585365854,
"line_max": 94,
"alpha_frac": 0.6349206349,
"autogenerated": false,
"ratio": 3.532710280373832,
"config_test": fa... |
#-------------bin_frogs.py-----------------------------------------------------#
#
# Purpose: To place frogs of all different ages into bins according to their
# age. This is a homework assignment for our python class
#
# Method: I will use a for loop to gra 100 frogs, call frog_found.py to
# generat... | {
"repo_name": "leios/OIST.CSC",
"path": "homework/tadpole_pool/bin_frogs.py",
"copies": "1",
"size": "1789",
"license": "mit",
"hash": 7109900761542703000,
"line_mean": 30.9464285714,
"line_max": 80,
"alpha_frac": 0.5768585802,
"autogenerated": false,
"ratio": 3.3564727954971856,
"config_test":... |
# bin_from_bedscore
import pandas
import argparse
import os
import yaml
def bins_from_data(data, n_bins):
try:
bins = pandas.qcut(data, n_bins, retbins=True)[1].tolist()
return bins
except:
# If we can't cut into n_bins without error, cut into n_bins-1, and then divide the largest bin
... | {
"repo_name": "Duke-GCB/TrackHubGenerator",
"path": "cwl/bin/bins_from_bedfile.py",
"copies": "1",
"size": "2302",
"license": "mit",
"hash": -1953296681886271700,
"line_mean": 45.04,
"line_max": 122,
"alpha_frac": 0.6559513467,
"autogenerated": false,
"ratio": 3.2376933895921236,
"config_test":... |
#bing_connect.py
import requests
import json
import ast
import time
import urllib2
key = '5lr03uc8ED3BKCehrM4s~UeZYhEuwi5E-XmN3wnP7Ew~AuVG-mN8njenB8rQfdOR28vfuFYqAm7BB56b6l5MNKAld_cYwrkD32bjSvPa4yV2'
#URL Format: 'http://dev.virtualearth.net/REST/v1/Traffic/Incidents/37,-105,45,-94?key=YourBingMapsKey'
def query_incid... | {
"repo_name": "anivk/riceai-traffic",
"path": "traffic/bing_connect.py",
"copies": "1",
"size": "1260",
"license": "mit",
"hash": -5273632942771515000,
"line_mean": 29.7317073171,
"line_max": 129,
"alpha_frac": 0.6761904762,
"autogenerated": false,
"ratio": 2.5301204819277108,
"config_test": fa... |
# Bingo
# Calculate the probability of winning at Bingo
# Programming Praxis Exercise 3
# http://programmingpraxis.com/2009/02/19/bingo/
from random import sample, shuffle
class BingoCard:
def __init__(self):
self.card = [sample(xrange(a,b), 5) for a,b in \
[(1,16), (16,31), (31,... | {
"repo_name": "gosub/programming-praxis-python",
"path": "003-bingo/bingo.py",
"copies": "1",
"size": "2633",
"license": "mit",
"hash": 6787071454768266000,
"line_mean": 28.9204545455,
"line_max": 77,
"alpha_frac": 0.5567793392,
"autogenerated": false,
"ratio": 3.4328552803129075,
"config_test"... |
# Bingo Square Generator
# n! / (n - r)!; 24! = 620,448,401,733,239,439,360,000 = 6.2 x 10^23
import random
import sys
try:
filename = sys.argv[1]
sheets = sys.argv[2]
title = sys.argv[3:]
except IndexError:
print "Parameters for bingo.py: filename, number of sheets to create, title."
sys.exit(1)
... | {
"repo_name": "shannonturner/bingo-sheets",
"path": "bingo.py",
"copies": "1",
"size": "2262",
"license": "mit",
"hash": 6310142930122840000,
"line_mean": 33.8,
"line_max": 273,
"alpha_frac": 0.5968169761,
"autogenerated": false,
"ratio": 3.181434599156118,
"config_test": false,
"has_no_keywo... |
import sys, os, time, argparse
import re
import pprint
import math
import cPickle
import ged, lcs
class Chooser(idaapi.Choose2):
def __init__(self, title, items, embedded=False):
idaapi.Choose2.__init__(self, title, [["Rank", 3], ["Function", 30], ["GED", 3], ["LCS", 3], ["Vector", 10]])
self.item... | {
"repo_name": "hada2/bingrep",
"path": "bingrep_search.py",
"copies": "1",
"size": "10243",
"license": "bsd-3-clause",
"hash": 2452611431897322500,
"line_mean": 35.4519572954,
"line_max": 202,
"alpha_frac": 0.5914282925,
"autogenerated": false,
"ratio": 3.2109717868338556,
"config_test": false,... |
import sys, os, time, argparse
import re
import pprint
#import pydot
import math
import cPickle
import ged_node
from idautils import *
from idc import *
import idaapi
def idascript_exit(code=0):
idc.Exit(code)
def get_short_function_name(function):
return function.replace("?", "")[:100]
def mkdir(dirname):
... | {
"repo_name": "hada2/bingrep",
"path": "bingrep_dump.py",
"copies": "1",
"size": "8471",
"license": "bsd-3-clause",
"hash": 8805099356239254000,
"line_mean": 30.6082089552,
"line_max": 163,
"alpha_frac": 0.5466887026,
"autogenerated": false,
"ratio": 3.25682429834679,
"config_test": false,
"h... |
"""Binheap data structure."""
class Binheap(object):
"""Binheap class for min heap."""
def __init__(self, iterable=None):
"""Will init a new instance of the min heap."""
self.size = 0
self.list = [None]
def push(self, data):
"""Will push a value into the Binheap class."""... | {
"repo_name": "han8909227/data-structures",
"path": "src/binheap.py",
"copies": "1",
"size": "1788",
"license": "mit",
"hash": -7827926202790168000,
"line_mean": 28.8,
"line_max": 72,
"alpha_frac": 0.4742729306,
"autogenerated": false,
"ratio": 3.5617529880478087,
"config_test": false,
"has_n... |
"""Binheap Data Structure."""
class Binheap(object):
"""
Binheap data structure.
.pop: Removes lowest value and reorders heap.
.push: Adds a value to the end and reorders heap.
"""
def __init__(self, iterable=None, style='min'):
"""Create the Binheap."""
self.style = style
... | {
"repo_name": "julienawilson/data-structures",
"path": "src/binheap.py",
"copies": "1",
"size": "2351",
"license": "mit",
"hash": -1080536326936497700,
"line_mean": 35.1692307692,
"line_max": 111,
"alpha_frac": 0.4385367929,
"autogenerated": false,
"ratio": 3.8227642276422764,
"config_test": fa... |
#Binh Le Chi - RBVH
#Auto Rename utility
import sys, re, os, stat
#match and fit the string with template
def write_vartofile(file,line_to_write,list_vardetected,component):
line_to_write=line_to_write.replace(r'(',r' ')
line_to_write=line_to_write.replace(r')',r' ')
line_to_write=line_to_write.replace(r'}... | {
"repo_name": "chibinh8/python-tool",
"path": "AutoDefineShortname.py",
"copies": "1",
"size": "18490",
"license": "apache-2.0",
"hash": 7312488784646503000,
"line_mean": 44.2078239609,
"line_max": 258,
"alpha_frac": 0.5679826933,
"autogenerated": false,
"ratio": 2.9788947961978414,
"config_tes... |
"""Binned"""
import datetime
import calendar
from pandas.io.sql import read_sql
from pyiem.plot.use_agg import plt
from pyiem.util import get_autoplot_context, get_dbconn
from pyiem.exceptions import NoDataFound
PDICT = {"tmpf": "Air Temperature", "dwpf": "Dew Point Temperature"}
def get_description():
""" Retu... | {
"repo_name": "akrherz/iem",
"path": "htdocs/plotting/auto/scripts/p53.py",
"copies": "1",
"size": "6097",
"license": "mit",
"hash": -3092771297836869600,
"line_mean": 27.0967741935,
"line_max": 79,
"alpha_frac": 0.4858126948,
"autogenerated": false,
"ratio": 3.205573080967403,
"config_test": f... |
"""Binning/histogramming classes for scientific computing
YAML interface
==============
All classes defined in `binning` can be stored as and read from YAML files
using the ``binning.yaml`` module::
with open("filename.yml", 'w') as f:
binning.yaml.dump(some_binning, f)
with open("filename.yml", 'r'... | {
"repo_name": "ast0815/remu",
"path": "remu/binning.py",
"copies": "2",
"size": "84740",
"license": "mit",
"hash": 4112196118320959000,
"line_mean": 31.9599377674,
"line_max": 194,
"alpha_frac": 0.5786051451,
"autogenerated": false,
"ratio": 4.053187927488401,
"config_test": false,
"has_no_ke... |
#Binning
import pysal
import numpy as np
# delta to get buckets right
DELTA = 0.000001
QUEEN = 1
ROOK = 2
# constants for bucket sizes
BUCK_SM = 8
BUCK_LG = 80
SHP_SMALL = 1000
def bbcommon(bb, bbother):
"""
Checks for overlaps of bounding boxes. First, east-west, then north-south.
Element 0 is west, e... | {
"repo_name": "pysal/pPysal",
"path": "weights/binning.py",
"copies": "1",
"size": "3885",
"license": "bsd-3-clause",
"hash": -2120056800459796000,
"line_mean": 27.9925373134,
"line_max": 78,
"alpha_frac": 0.5737451737,
"autogenerated": false,
"ratio": 3.360726643598616,
"config_test": false,
... |
#Binning
import multiprocessing as mp
import time
from collections import defaultdict
import sys
import copy
sys.path.append('/Users/Jay/github/pysal/pysal')
import pysal
# delta to get buckets right
DELTA = 0.000001
QUEEN = 1
ROOK = 2
# constants for bucket sizes
BUCK_SM = 8
BUCK_LG = 80
SHP_SMALL = 1000
class Shp... | {
"repo_name": "pysal/pPysal",
"path": "weights/pbinning.py",
"copies": "1",
"size": "7571",
"license": "bsd-3-clause",
"hash": 4236415686570248700,
"line_mean": 27.678030303,
"line_max": 127,
"alpha_frac": 0.5810328887,
"autogenerated": false,
"ratio": 3.3293755496921724,
"config_test": false,
... |
"""Bin
.. moduleauthor:: Stéphane Vialette <vialette@gmail.com>
"""
from .binexception import BinException
from .snapshot import Snapshot
class Bin(object):
def __init__(self, capacity, name = None):
self._items = []
self._capacity = capacity
self._name = name
if self._name is None:
self._name =... | {
"repo_name": "vialette/binreconfiguration",
"path": "binreconfiguration/bin/bin.py",
"copies": "1",
"size": "2240",
"license": "mit",
"hash": 396819493860489600,
"line_mean": 19.1711711712,
"line_max": 77,
"alpha_frac": 0.6422510049,
"autogenerated": false,
"ratio": 3.254360465116279,
"config_... |
"""bin_noise_maps_agave.py
This version of the script has hard-coding to facilitate
parallelization on Agave cluster.
"""
import os
import itertools
import argparse
from datetime import datetime
import numpy as np
import xarray as xr
import dask
from dask.distributed import Client, LocalCluster
FILTER_TRIM_PIX = {... | {
"repo_name": "piyanatk/sim",
"path": "scripts/fg1p/bin_noise_maps_agave.py",
"copies": "1",
"size": "5181",
"license": "mit",
"hash": -5973605215128144000,
"line_mean": 33.0855263158,
"line_max": 80,
"alpha_frac": 0.6008492569,
"autogenerated": false,
"ratio": 3.319026265214606,
"config_test":... |
bin_num = 0b10
oct_num = 0o10
hex_num = 0x10
print(bin_num)
print(oct_num)
print(hex_num)
# 2
# 8
# 16
Bin_num = 0B10
Oct_num = 0O10
Hex_num = 0X10
print(Bin_num)
print(Oct_num)
print(Hex_num)
# 2
# 8
# 16
print(type(bin_num))
print(type(oct_num))
print(type(hex_num))
# <class 'int'>
# <class 'int'>
# <class 'int'>... | {
"repo_name": "nkmk/python-snippets",
"path": "notebook/numeric_types.py",
"copies": "1",
"size": "2740",
"license": "mit",
"hash": 5072283014840140000,
"line_mean": 12.9086294416,
"line_max": 59,
"alpha_frac": 0.602919708,
"autogenerated": false,
"ratio": 2.138953942232631,
"config_test": fals... |
"""binny URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.9/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-based... | {
"repo_name": "bath-hacker/binny",
"path": "binny/binny/urls.py",
"copies": "1",
"size": "1384",
"license": "mit",
"hash": 3827423440131098000,
"line_mean": 37.4444444444,
"line_max": 79,
"alpha_frac": 0.6806358382,
"autogenerated": false,
"ratio": 3.392156862745098,
"config_test": false,
"ha... |
"""Binomial cofficients
Binomial coefficient of m chooses k:
C(m, k) = m!/[(m - k)! * k!]
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
def binomial_cofficient(m, k):
"""Binomial coefficien of m taking k.
Note there is a recursion relations... | {
"repo_name": "bowen0701/algorithms_data_structures",
"path": "alg_binomial_cofficients.py",
"copies": "1",
"size": "1668",
"license": "bsd-2-clause",
"hash": -4982421058168434000,
"line_mean": 21.5405405405,
"line_max": 73,
"alpha_frac": 0.528177458,
"autogenerated": false,
"ratio": 2.7524752475... |
"""Binomial probability distribution."""
from functools import wraps
import numpy
from scipy import special
import chaospy
from ..baseclass import SimpleDistribution
from ..operators import J
class binomial(SimpleDistribution):
"""Binomial probability distribution."""
interpret_as_integer = True
def __... | {
"repo_name": "jonathf/chaospy",
"path": "chaospy/distributions/collection/binomial.py",
"copies": "1",
"size": "2730",
"license": "mit",
"hash": -8172076974416207000,
"line_mean": 30.0227272727,
"line_max": 79,
"alpha_frac": 0.5483516484,
"autogenerated": false,
"ratio": 3.053691275167785,
"co... |
# binpacking.py
# This file contains a heuristic to translate a given combination of items
# into a bin packing mapping. Function ed performs the necessary encoding
# and decoding based on Dahmani (2014).
# Author: Kristina Spencer
# Date: March 11, 2016
from __future__ import print_function
import constrain... | {
"repo_name": "kyspencer/2D-bin-packing-heuristic",
"path": "binpacking.py",
"copies": "1",
"size": "10271",
"license": "mit",
"hash": 797881343343264600,
"line_mean": 33.0099337748,
"line_max": 93,
"alpha_frac": 0.5728750852,
"autogenerated": false,
"ratio": 3.2804215905461516,
"config_test": ... |
#!/bin/perl
# $Id$
# Run this from the support directory, and specify the path of a source directory
# to walk.
import sys, os
from stat import *
import re
updateCount = 0;
packageRe = re.compile(r'^\s*package\s+');
def walktree(dir, callback):
'''recursively descend the directory rooted at dir,
calling... | {
"repo_name": "apache/tapestry3",
"path": "support/update-copyrights.py",
"copies": "2",
"size": "2992",
"license": "apache-2.0",
"hash": -1544882873325386800,
"line_mean": 18.0573248408,
"line_max": 88,
"alpha_frac": 0.6323529412,
"autogenerated": false,
"ratio": 3.3961407491486946,
"config_te... |
#!/bin/perl
# This I hope to form a quick basis for my simple Python projects to us a geneic API
# We have yet to see what use it will actually be
# docker run --net host --name py --rm -it --device /dev/mem --cap-add SYS_RAWIO -v /sys:/sys $IMAGE python
# This nice little script works with the rocket-server to deter... | {
"repo_name": "lymbada/CHIPlearner",
"path": "gadget_projects/rocket/rocket-buttons/rocket-buttons.py",
"copies": "1",
"size": "3939",
"license": "bsd-3-clause",
"hash": 7602387386930942000,
"line_mean": 30.2619047619,
"line_max": 119,
"alpha_frac": 0.7154100025,
"autogenerated": false,
"ratio": ... |
#!/bin/prython3
# python3 preprocesamiento.py all_videos_features_clases.npz "coso_procesado" 'z_score+min_max'
import numpy as np
import sys
def iter_loadtxt(filename, delimiter=' ', skiprows=0, dtype=float):
def iter_func():
with open(filename, 'r') as infile:
for _ in range(skiprows):
... | {
"repo_name": "lerker/cupydle",
"path": "cupydle/test/kml/csv2npz.py",
"copies": "1",
"size": "1585",
"license": "apache-2.0",
"hash": -991117529218076000,
"line_mean": 30.0784313725,
"line_max": 95,
"alpha_frac": 0.6668769716,
"autogenerated": false,
"ratio": 2.8354203935599283,
"config_test":... |
#!/bin/prython
# python pca.py all_videos_features_clases.npz 70 all_videos_pca_70
import numpy as np
import sys
import matplotlib.pyplot as plt
from sklearn import decomposition
archivo_entrada = str(sys.argv[1])
cantidad_componentes = int(sys.argv[2])
archivo_salida = str(sys.argv[3])
print("Archivo en... | {
"repo_name": "lerker/cupydle",
"path": "cupydle/test/kml/pca.py",
"copies": "1",
"size": "1907",
"license": "apache-2.0",
"hash": -3789216708376582000,
"line_mean": 33.0535714286,
"line_max": 115,
"alpha_frac": 0.6680650236,
"autogenerated": false,
"ratio": 2.9611801242236027,
"config_test": f... |
#bin .ptxt data into desired time intervals
#ptxt files from the UTC code are in UTC
#final conversion to correct timezone from UTC happens here
import sys
import os
import datetime
from datetime import timedelta
from datetime import datetime
import calendar
import numpy as np
import matplotlib.pyplot as plt
from ppri... | {
"repo_name": "annahs/atmos_research",
"path": "SP2B_time_binning_UTC.py",
"copies": "1",
"size": "11430",
"license": "mit",
"hash": -1391822185472799000,
"line_mean": 51.1917808219,
"line_max": 263,
"alpha_frac": 0.5631671041,
"autogenerated": false,
"ratio": 4.174579985390796,
"config_test": ... |
#!/bin/pyhon
import subprocess
import os
core_branch = "develop"
mgr_branch = "develop"
mgr_name = "bill-manager"
git_host = "git.ispsystem.net"
core_build_dir = "/build"
discc_gen_hosts_dir = "distcc-gen-hosts"
need_core_rpm = False
thread_count = "20"
mgr_dir = "/usr/local/mgr5"
def RunShellCommand(command, check_... | {
"repo_name": "DimaKirk/fetchup-docker",
"path": "makefetchup.py",
"copies": "1",
"size": "3105",
"license": "mit",
"hash": -8539418700942922000,
"line_mean": 32.3870967742,
"line_max": 136,
"alpha_frac": 0.7120772947,
"autogenerated": false,
"ratio": 2.7972972972972974,
"config_test": false,
... |
#!/bin/py
# Atlassian Total Automation tool (ATAT)
# Written by Alex Merenyi for The Advisory Board Company
# Script title has nothing at all to do with the Imperial Walkers of the same name. (...or does it.)
# Version 0.1 started March 25, 2014
# Matches version 3.8 of the CLI package. Updates to that package WILL r... | {
"repo_name": "alexvirital/atlassian_utilities",
"path": "atat.py",
"copies": "1",
"size": "4365",
"license": "apache-2.0",
"hash": 4293308743843730400,
"line_mean": 36.3076923077,
"line_max": 170,
"alpha_frac": 0.7211912944,
"autogenerated": false,
"ratio": 3.2001466275659824,
"config_test": f... |
#!/bin/py
# check_vms.py - Lists all VirtualBox's Virtual Machines and checks their status
#
# TODO: separate vms listing and vms stats
import argparse
import re
import subprocess
import sys
parser = argparse.ArgumentParser()
parser.add_argument("list", help="list all virtual machines")
parser.add_argument("state", n... | {
"repo_name": "zatosource/zato-build",
"path": "ansible/files/check_vms.py",
"copies": "1",
"size": "3738",
"license": "mit",
"hash": 2534229708596374000,
"line_mean": 28.4330708661,
"line_max": 80,
"alpha_frac": 0.5524344569,
"autogenerated": false,
"ratio": 3.355475763016158,
"config_test": f... |
#!/bin/py
# From calculation, we expect that the local minimum occurs at (x,y) = (0,0)
#
# min f(x,y) = -cos(x)cos(y/10)
#
import numpy as np
import matplotlib.pylab as plt
x_old = np.array([0, 0])
eps = 0.01 # step size
thresh = 0.00001
x_guess = np.pi/4.
y_guess = -np.pi
x_new = np.array([x_guess... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "inv_prob/ps2/newton.py",
"copies": "2",
"size": "1338",
"license": "mit",
"hash": -794060053911503100,
"line_mean": 21.3,
"line_max": 85,
"alpha_frac": 0.5455904335,
"autogenerated": false,
"ratio": 2.3229166666666665,
"config_test": false,
... |
#!/bin/py
#
# Combustion Theory Final Exam: Turbulent Diffusion Flames
#
import sys
import numpy as np
import pylab
import scipy.special as ss
def beta(a, b, mew):
e1 = ss.gamma(a + b)
e2 = ss.gamma(a)
e3 = ss.gamma(b)
e4 = mew ** (a - 1)
e5 = (1 - mew) ** (b - 1)
return (e1/(e2*e3)) * e4 * e5
... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "combustion/final/flow.py",
"copies": "2",
"size": "5810",
"license": "mit",
"hash": -4915979162989245000,
"line_mean": 20.2820512821,
"line_max": 89,
"alpha_frac": 0.4457831325,
"autogenerated": false,
"ratio": 2.8355295265983407,
"config_test": ... |
#!/bin/py
'''
Create summary visualization for a dataset
'''
import glob
import os.path
import sys
import getopt
import numpy as np
import commands
import urllib2
from BeautifulSoup import BeautifulSoup
vizdir = '/home/mhughes/git/NPBayesHMM/figs/SkelVisBIG/'
MAXbID=33
SubjInfoMap = dict()
TrialInfoMap = dict()
def... | {
"repo_name": "michaelchughes/NPBayesHMM",
"path": "code/viz/mocap/buildHTMLForSkelViz.py",
"copies": "1",
"size": "2862",
"license": "bsd-3-clause",
"hash": -3379499366295835000,
"line_mean": 30.8,
"line_max": 104,
"alpha_frac": 0.643955276,
"autogenerated": false,
"ratio": 2.7813411078717203,
... |
#!/bin/py
#
# determine optimal energy from flow
#
#
def cl(phi):
if(phi>180):
cl = -1.75
else:
cl = 1.75
return cl
def cd(phi):
if(270>phi>180):
cd = 0
else:
cd = 2.0
return cd
#
# Radius VT Vz
# m m/s m/s
#
#
import numpy as np
import matplotlib.pyplot a... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "disputatio/causa/opt_turb/opt_turb.py",
"copies": "2",
"size": "2314",
"license": "mit",
"hash": -3252193563449374000,
"line_mean": 16.9379844961,
"line_max": 93,
"alpha_frac": 0.5639585134,
"autogenerated": false,
"ratio": 2.156570363466915,
... |
#!/bin/py
#
# global settings for the inference routines
#
#
# Use scipy to integrate:
#
# dy^2 / dt^2 = -g + r (dh/dt)^2 (object falling with drag)
#
from scipy.linalg import det, solve
from scipy.integrate import odeint
import numpy as np
from Data.read_data import read_data
def deriv(h,t,param):
"""retur... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "uq/ps2/settings_infer.py",
"copies": "2",
"size": "3090",
"license": "mit",
"hash": -3810011988293447700,
"line_mean": 24.9663865546,
"line_max": 92,
"alpha_frac": 0.6634304207,
"autogenerated": false,
"ratio": 2.6660914581535806,
"config_test": ... |
#!/bin/py
#
# inexact Newton-conjugate gradient method
#
# solve:
# min f(x) = 1/2 x.t (I + mu * A) x + sigma/4 (x.t A x)^2
#
import numpy as np
def mycg(A,b,maxiter,tol,x):
""" Conjugate Gradient Method. """
""" MYCG(A,B,maxiter,tol,x0) solves the system of linear equations A*X=B """
""" for X. Th... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "inv_prob/ps2/in-cg.py",
"copies": "2",
"size": "1347",
"license": "mit",
"hash": 5090238573561576000,
"line_mean": 21.45,
"line_max": 81,
"alpha_frac": 0.5337787676,
"autogenerated": false,
"ratio": 2.5903846153846155,
"config_test": false,
... |
#!/bin/py
#
# Integrate exodus II file in space
#
import sys
import glob
#
# need vtk environment to read EXOII
#
try:
import vtk
except ImportError:
sys.stderr.write("Error: Can't find the file 'vtk.py'...\n")
sys.stderr.write("Did you invoke with pvpython?\n")
sys.stderr.write("Is the paraview modu... | {
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"path": "disputatio/routines/file.py",
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#!/bin/py
#
# Integrate exodus II file in space
#
import sys
import numpy as np
import glob
import vtk
# -----------------------------------------------#
# Perform Radial Integration #
# -----------------------------------------------#
def integrate(name, var):
""" given filename and var, gen... | {
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#!/bin/py
#
# interpolate over data field for bottom vanes
#
#
#
import numpy as np
import matplotlib
matplotlib.use('Agg')
import itertools
import matplotlib.pyplot as plt
from scipy import integrate
from scipy.integrate import ode
radprime=3.0
radmin=0.6
def vf(t,x):
#
# Vector field function
#
the... | {
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"path": "disputatio/routines/vanes/bottom.py",
"copies": "2",
"size": "4039",
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"hash": -622915876783050900,
"line_mean": 22.899408284,
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"autogenerated": false,
"ratio": 2.8107167710508003,
"confi... |
#!/bin/py
#
# interpolate over data field with 2d polynomial fit
#
# fit a 2D, 3rd order polynomial to data
# estimate the 16 coefficients using all of your data points.
#
# http://stackoverflow.com/questions/18832763/drawing-directions-fields
#
#
import numpy as np
import matplotlib
matplotlib.use('Agg')
import iter... | {
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"size": "6595",
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"hash": -7464673951240500000,
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"autogenerated": false,
"ratio": 2.6233094669848844,
"config... |
# k_means_on_fpfh.py
# voxels-at-lems
#
# Created by Maria Isabel Restrepo on 11/14/11.
# Copyright (c) 2011 Brown University. All rights reserved.
import dbrec3d_batch;
import os;
import optparse;
dbrec3d_batch.register_processes();
dbrec3d_batch.register_datatypes();
class dbvalue:
def __init__(self, index... | {
"repo_name": "mirestrepo/voxels-at-lems",
"path": "dbrec3d/pcl/k_means_on_fpfh.py",
"copies": "1",
"size": "1345",
"license": "bsd-2-clause",
"hash": 3581253772429139500,
"line_mean": 27.6170212766,
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"alpha_frac": 0.7167286245,
"autogenerated": false,
"ratio": 2.458866544789762,
... |
#!/bin/py
#
#
#
import sys
import numpy as np
# no twist
flux = 1.35* np.array([0.99,1.02,1.1,1.12,1.12,1.11,1.112,1.123,1.1159,1.101,1.042])
it = [35,40,43,45,47,50,53,55,57,60,65]
#
# duane (top)
#
fluxd = 1.45*np.array([0.99,1.02,1.06,1.1,1.09,1.11,1.117,1.12,1.115,1.10,1.04])
itd = [35,40,43,45,47,50,53,55,57,60... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "disputatio/routines/collective_duane.py",
"copies": "2",
"size": "1665",
"license": "mit",
"hash": 5909022650821573000,
"line_mean": 19.8125,
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"alpha_frac": 0.6486486486,
"autogenerated": false,
"ratio": 2.032967032967033,
"conf... |
#!/bin/py
#
#
#
import sys
import numpy as np
#r = np.array([1.7,1.45,1.2,1.0])
#r = (r-r.min())/(r.max()-r.min())
#f = [0.54,0.32,0.20,0.28]
r = np.arange(1,0,-0.05)
f = [ 0.61405439, 0.53689096, 0.49637325, 0.46769237, 0.43770222, 0.39899252,
0.35569226, 0.31518384, 0.29326381, 0.26199337, 0.25785942, 0.2... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "disputatio/routines/annealing/anneal.py",
"copies": "2",
"size": "1728",
"license": "mit",
"hash": -6053540374605452000,
"line_mean": 17.7826086957,
"line_max": 83,
"alpha_frac": 0.6215277778,
"autogenerated": false,
"ratio": 2.1202453987730063,... |
#!/bin/py
#
#
#
import sys
#
# list of our fluxes
# 686 august field test simulations
# 796 optimized axisymmetric vanes
# 803 watts is back cylinder
# 930 is cylinder back with optimized linear vanes
# 1102 elliptic vanes
# 1380 optimized elliptic vanes
# 2203 horizontal partitions
flux = [180,435,688,705,843,940,1... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "disputatio/routines/turbine_opt.py",
"copies": "2",
"size": "1960",
"license": "mit",
"hash": 5159944689207675000,
"line_mean": 20.3043478261,
"line_max": 157,
"alpha_frac": 0.6244897959,
"autogenerated": false,
"ratio": 2.7489481065918655,
"c... |
#!/bin/py
#
#
#
import sys
# no twist
flux = [0.99,1.02,1.06,1.1,1.09,1.11,1.117,1.12,1.115,1.10,1.04]
it = [35,40,43,45,47,50,53,55,57,60,65]
# twist
flux2 = [1.13,1.25,1.32,1.33,1.34,1.33,1.31,1.25]
it2 = [35,40,43,45,47,49,50,55]
#
# iteration number (should be same as flux, above)
#
#it = range(len(flux))
#
# n... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "disputatio/routines/collective.py",
"copies": "2",
"size": "1120",
"license": "mit",
"hash": -1214188703819883300,
"line_mean": 17.3606557377,
"line_max": 68,
"alpha_frac": 0.6526785714,
"autogenerated": false,
"ratio": 2.1538461538461537,
"confi... |
#!/bin/py
#
#
# power law scaling thermal layer
#
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
#
# read in data
#
def read_dat():
x = []
t = []
f = open('data.dat', 'r')
for line in f:
values = line.split("\t")
values = line.split("\t")
x.append(float(va... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "disputatio/routines/thermal_boundary_layer/zoom.py",
"copies": "2",
"size": "2132",
"license": "mit",
"hash": 3512184231086853600,
"line_mean": 19.5,
"line_max": 128,
"alpha_frac": 0.558630394,
"autogenerated": false,
"ratio": 2.66167290886392,
"... |
#!/bin/py
#
# open file
# read contents
# (re)start when third column found
#
import sys
import numpy as np
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
import matplotlib.pyplot as plt
#
# open and read file
#
path = "vmean_5.txt"
file = open(path, "r+")
defect1 = []
f... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "exp/ldv/code/vmean.py",
"copies": "2",
"size": "1072",
"license": "mit",
"hash": 2888223538974757000,
"line_mean": 17.1694915254,
"line_max": 76,
"alpha_frac": 0.6604477612,
"autogenerated": false,
"ratio": 2.5046728971962615,
"config_test": f... |
#!/bin/py
#
# open file
# read contents
# (re)start when third column found
#
import sys
import numpy as np
def autocorr(x):
result = np.correlate(x, x, mode = 'full')
maxcorr = np.argmax(result)
#print 'maximum = ', result[maxcorr]
result = result / result[maxcorr] # <=== normalization
return... | {
"repo_name": "nicholasmalaya/paleologos",
"path": "exp/oriface/measurement/code/raw.py",
"copies": "2",
"size": "2663",
"license": "mit",
"hash": 6644659619978550000,
"line_mean": 19.3282442748,
"line_max": 93,
"alpha_frac": 0.5745399925,
"autogenerated": false,
"ratio": 2.913566739606127,
"co... |
#!/bin/py
#
# open file
# read contents
# (re)start when third column found
#
import sys
def read_set(path):
#
# data
#
set_names = []
orm = []
lfe = []
file = open(path, "r+")
for line in file:
#
# sep by whitespace
#
line_list = line.... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "exp/oriface/measurement/code/cd.py",
"copies": "2",
"size": "4185",
"license": "mit",
"hash": -502722121610253300,
"line_mean": 24.8333333333,
"line_max": 86,
"alpha_frac": 0.4697729988,
"autogenerated": false,
"ratio": 3.1656580937972767,
"confi... |
#!/bin/py
#
# open file
# read contents
# (re)start when third column found
#
import sys
#
# open and read file
#
path="../data/statistics_incl.lvm"
file = open(path, "r+")
#
# data objects
#
set_names = []
voltage = []
std = []
height = []
voltage2 = []
std2 = []
height2 = []
for line in file:
... | {
"repo_name": "nicholasmalaya/arcanus",
"path": "exp/press_trans/code/read_incline_stats.py",
"copies": "2",
"size": "2086",
"license": "mit",
"hash": -7202503301723789000,
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"line_max": 157,
"alpha_frac": 0.6447746884,
"autogenerated": false,
"ratio": 2.889196675900277,... |
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