根据要求添加的代码

Question

我在混乱的中间继承了一个项目，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内容相同。 [z = numpy.polyfit（x，y，5）]

但是，我想知道如何修改程序，以便我可以插入一个y的已知值的输入来查找x。

换句话说。我有x和y数组，其中： - 数组x保存已知公斤重量的值（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，它读取一个重量和由phidget创建的张力，并生成该程序使用的数组。

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。

有办法做到这一点吗？我觉得我只缺少一行代码，但我不知道如何从公式中实现返回值的结果。（z）的

提前致谢。

根据要求添加的代码

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()

Answer 1

来自校准的线性转换函数由numpy.polyfit作为系数数组返回。由于你为polyfit的度数参数传递了5，你将得到一个包含六个系数的数组：

f（x）= ax ⁵ + bx ⁴ + cx ³ + dx ² + ex + ˚F

其中a，b，c，d，e和f是z返回的nonlinear_regression数组的元素。

要实施线性转化公式，只需使用幂算子**，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))

使用Python

根据要求添加的代码

1 个答案: