输入多项式回归公式 Python
Input into a polynomial regression formula with Python
我在一片混乱中接手了一个项目，更糟糕的是，我只是在学习 python。
我设法在我的代码和结果中实现了一个多项式函数
与本网页示例中发布的相同。
[z = numpy.polyfit(x, y, 5)]
但是，我想知道如何修改程序，以便我可以插入 y 的已知值之一的输入来找到 x。
也就是说。我有 x 和 y 数组，其中：
- 数组 x 保存已知千克重量的值 (0.0, 0.5, 1.0, 1.5, 2.0)
- 数组 y (0.074581967, 0.088474754, 0.106797419, 0.124461935, 0.133726833)
我有一个程序可以读取由 phidget 产生的重量和张力，并生成该程序要使用的数组。
我需要完成的是从 phidget 读取下一个值，并能够从提供的数组中将读数转换为千克。
有办法吗？我觉得我只是缺少一行代码，但我不知道如何实现公式返回值的结果。 (z)
提前致谢。
代码已按要求添加
from Phidgets.PhidgetException import PhidgetException
from Phidgets.Devices.Bridge import Bridge, BridgeGain
import datetime
import os
import re
import sys
import time
import numpy
wgh = list()
avg = list()
buf = list()
x = []
y = []
def nonlinear_regression(): # reads the calibration mapping and generates the conversion coefficients
fd = open("calibration.csv", "r")
for line in fd:
[v0, v1] = line.split(",")
x.append(float(v0))
y.append(float(v1[:len(v1) - 1]))
xdata = numpy.array(x)
ydata = numpy.array(y)
z = numpy.polyfit(x, y, 5)
return z
def create_data_directory(): # create the data directory
if not os.path.exists("data"):
os.makedirs("data")
def parse_config(): # get config-file value
v = int()
config = open("config.properties", "r")
for line in config:
toks = re.split(r"[\n= ]+", line)
if toks[0] == "record_interval":
v = int(toks[1])
return v
def read_bridge_data(event): # read the data
buf.append(event.value)
def record_data(f_name, date, rms):
if not os.path.isfile(f_name):
fd = open(f_name, "w")
fd.write("time,weight\n")
fd.write(datetime.datetime.strftime(date, "%H:%M"))
fd.write(",")
fd.write(str(rms) + "\n")
fd.close()
else:
fd = open(f_name, "a")
fd.write(datetime.datetime.strftime(date, "%H:%M"))
fd.write(",")
fd.write(str(rms) + "\n")
fd.close()
print("Data recorded.")
def release_bridge(event): # release the phidget device
try:
event.device.closePhidget()
except:
print("Phidget bridge could not be released properly.")
sys.exit(1)
def main():
create_data_directory()
RECORD_INTERVAL = parse_config() # get the config-file value
calibrate = nonlinear_regression() # get calibration function; use like: calibrate(some_input)
bridge = Bridge()
try:
bridge.setOnBridgeDataHandler(read_bridge_data)
bridge.setOnDetachHandler(release_bridge) # when the phidget gets physically detached
bridge.setOnErrorhandler(release_bridge) # asynchronous exception (i.e. keyboard interrupt)
except:
print("Phidget bridge event binding failed.")
sys.exit(1)
try:
bridge.openPhidget()
bridge.waitForAttach(3000)
except:
print("Phidget bridge opening failed.")
sys.exit(1)
last_record = int()
while (True):
date = datetime.datetime.now()
f_name = "data\" + datetime.datetime.strftime(date, "%B_%d_%Y") + ".csv"
curr = time.time() * 1000
if (curr - last_record) > (RECORD_INTERVAL * 1000):
try:
bridge.setDataRate(10)
last = time.time() * 1000
bridge.setEnabled(0, True)
while (time.time() * 1000 - last) < 1000: # collects over 1 sec
pass
bridge.setEnabled(0, False)
except:
print("Phidget bridge data reading error.")
bridge.setEnabled(0, False)
bridge.closePhidget()
sys.exit(1)
vol = sum(buf) / len(buf)
del buf[:]
last_record = curr
record_data(f_name, date, vol) # replace curr with calibrated data
#THIS IS WHERE I WILL LIKE TO INCORPORATE THE CHANGES TO SAVE THE WEIGHT
#record_data(f_name, date, conversion[0] * vol + conversion[1]) # using the linear conversion function
else:
time.sleep(RECORD_INTERVAL - 1) # to reduce the CPU's busy-waiting
if __name__ == "__main__":
main()
来自校准的线性转换函数由 numpy.polyfit 作为系数数组返回。由于您为 polyfit 的度参数传递了 5，您将得到一个包含六个系数的数组：
f(x) = ax5 + bx4 + cx3 + dx 2 + ex + f
其中 a、b、c、d、e 和 f 是 nonlinear_regression 返回的 z 数组的元素。
要实现线性转换公式，只需使用幂运算符**、z的元素和vol的值：
vol_calibrated = vol**5 * z[0] + vol**4 * z[1] + vol**3 * z[2] + vol**2 * z[3] + vol * z[4] + z[5]
或更一般地说：
degree = len(z) - 1
vol_calibrated = sum(vol**(degree-i) * coeff for i, coeff in enumerate(z))
我在一片混乱中接手了一个项目，更糟糕的是，我只是在学习 python。
我设法在我的代码和结果中实现了一个多项式函数 与本网页示例中发布的相同。 [z = numpy.polyfit(x, y, 5)]
但是，我想知道如何修改程序，以便我可以插入 y 的已知值之一的输入来找到 x。
也就是说。我有 x 和 y 数组，其中： - 数组 x 保存已知千克重量的值 (0.0, 0.5, 1.0, 1.5, 2.0) - 数组 y (0.074581967, 0.088474754, 0.106797419, 0.124461935, 0.133726833)
我有一个程序可以读取由 phidget 产生的重量和张力，并生成该程序要使用的数组。
我需要完成的是从 phidget 读取下一个值，并能够从提供的数组中将读数转换为千克。
有办法吗？我觉得我只是缺少一行代码，但我不知道如何实现公式返回值的结果。 (z)
提前致谢。
代码已按要求添加
from Phidgets.PhidgetException import PhidgetException
from Phidgets.Devices.Bridge import Bridge, BridgeGain
import datetime
import os
import re
import sys
import time
import numpy
wgh = list()
avg = list()
buf = list()
x = []
y = []
def nonlinear_regression(): # reads the calibration mapping and generates the conversion coefficients
fd = open("calibration.csv", "r")
for line in fd:
[v0, v1] = line.split(",")
x.append(float(v0))
y.append(float(v1[:len(v1) - 1]))
xdata = numpy.array(x)
ydata = numpy.array(y)
z = numpy.polyfit(x, y, 5)
return z
def create_data_directory(): # create the data directory
if not os.path.exists("data"):
os.makedirs("data")
def parse_config(): # get config-file value
v = int()
config = open("config.properties", "r")
for line in config:
toks = re.split(r"[\n= ]+", line)
if toks[0] == "record_interval":
v = int(toks[1])
return v
def read_bridge_data(event): # read the data
buf.append(event.value)
def record_data(f_name, date, rms):
if not os.path.isfile(f_name):
fd = open(f_name, "w")
fd.write("time,weight\n")
fd.write(datetime.datetime.strftime(date, "%H:%M"))
fd.write(",")
fd.write(str(rms) + "\n")
fd.close()
else:
fd = open(f_name, "a")
fd.write(datetime.datetime.strftime(date, "%H:%M"))
fd.write(",")
fd.write(str(rms) + "\n")
fd.close()
print("Data recorded.")
def release_bridge(event): # release the phidget device
try:
event.device.closePhidget()
except:
print("Phidget bridge could not be released properly.")
sys.exit(1)
def main():
create_data_directory()
RECORD_INTERVAL = parse_config() # get the config-file value
calibrate = nonlinear_regression() # get calibration function; use like: calibrate(some_input)
bridge = Bridge()
try:
bridge.setOnBridgeDataHandler(read_bridge_data)
bridge.setOnDetachHandler(release_bridge) # when the phidget gets physically detached
bridge.setOnErrorhandler(release_bridge) # asynchronous exception (i.e. keyboard interrupt)
except:
print("Phidget bridge event binding failed.")
sys.exit(1)
try:
bridge.openPhidget()
bridge.waitForAttach(3000)
except:
print("Phidget bridge opening failed.")
sys.exit(1)
last_record = int()
while (True):
date = datetime.datetime.now()
f_name = "data\" + datetime.datetime.strftime(date, "%B_%d_%Y") + ".csv"
curr = time.time() * 1000
if (curr - last_record) > (RECORD_INTERVAL * 1000):
try:
bridge.setDataRate(10)
last = time.time() * 1000
bridge.setEnabled(0, True)
while (time.time() * 1000 - last) < 1000: # collects over 1 sec
pass
bridge.setEnabled(0, False)
except:
print("Phidget bridge data reading error.")
bridge.setEnabled(0, False)
bridge.closePhidget()
sys.exit(1)
vol = sum(buf) / len(buf)
del buf[:]
last_record = curr
record_data(f_name, date, vol) # replace curr with calibrated data
#THIS IS WHERE I WILL LIKE TO INCORPORATE THE CHANGES TO SAVE THE WEIGHT
#record_data(f_name, date, conversion[0] * vol + conversion[1]) # using the linear conversion function
else:
time.sleep(RECORD_INTERVAL - 1) # to reduce the CPU's busy-waiting
if __name__ == "__main__":
main()
来自校准的线性转换函数由 numpy.polyfit 作为系数数组返回。由于您为 polyfit 的度参数传递了 5，您将得到一个包含六个系数的数组：
f(x) = ax5 + bx4 + cx3 + dx 2 + ex + f
其中 a、b、c、d、e 和 f 是 nonlinear_regression 返回的 z 数组的元素。
要实现线性转换公式，只需使用幂运算符**、z的元素和vol的值：
vol_calibrated = vol**5 * z[0] + vol**4 * z[1] + vol**3 * z[2] + vol**2 * z[3] + vol * z[4] + z[5]
或更一般地说：
degree = len(z) - 1
vol_calibrated = sum(vol**(degree-i) * coeff for i, coeff in enumerate(z))