calc-q-factor-for-vna/source/frontend/front.py

import streamlit as st
import matplotlib.pyplot as plt
import numpy as np
import math

def plot_data(r,i, g):
    # unit circle
    unit_circle_x = []
    unit_circle_y = []
    for x in np.arange(-1, 1, 0.01):
        unit_circle_x.append(x)
        unit_circle_y.append((1-x**2)**0.5)

    unit_circle_x.append(1)
    unit_circle_y.append(0)

    for x in np.arange(-1, 1, 0.01)[::-1]:
        unit_circle_x.append(x)
        unit_circle_y.append(-(1-x**2)**0.5)

    fig, ax = plt.subplots()
    ax.plot(unit_circle_x, unit_circle_y)
    #

    # data
    ax.plot(r, i, 'b+')
    #
    #cirlce approximation
    # g_c = (np.conj(g[2])*g[1]-g[0])/(np.conj(g[2])-g[2])
    # g_d = g[0]/g[2]
    # radius = abs(g_c-g_d)
    # p=[[],[]]
    # for alpha in range(0,360):
    #     p[0].append(g_c.real+radius*math.cos(math.radians(alpha)))
    #     p[1].append(g_c.imag+radius*math.sin(math.radians(alpha)))
    # ax.plot(p[0],p[1])
    #

    ax.grid(True)
    ax.axis('square')
    ax.set_yticks(np.arange(-1, 1.2, 0.2))
    ax.set_yticks(np.arange(-1, 1.2, 0.2))
    st.pyplot(fig)


def run(calc_function):
    data = []
    uploaded_file = st.file_uploader('Upload a csv')
    if uploaded_file is not None:
        data = uploaded_file.readlines()


    col1, col2 = st.columns(2)

    select_data_format = col1.selectbox('Choose data format from a list',['Frequency, Re(S11), Im(S11)','Frequency, Re(Zin), Im(Zin)'])

    select_separator = col2.selectbox('Choose separator',['" "' ,'","','";"'])
    select_coupling_losses = st.checkbox('I want to apply corrections for coupling losses (lossy coupling)')
    
    def is_float(element) -> bool:
        try:
            float(element)
            val = float(element)
            if math.isnan(val) or math.isinf(val):
                raise ValueError
            return True
        except ValueError:
            return False

    def unpack_data(data):
        nonlocal select_separator
        nonlocal select_data_format
        f, r, i = [], [], []
        if select_data_format == 'Frequency, Re(S11), Im(S11)':
            for x in range(len(data)):
                # print(select_separator)
                select_separator=select_separator.replace('\"','')
                if select_separator==" ":
                    tru = data[x].split()
                else:
                    data[x]=data[x].replace(select_separator,' ')
                    tru = data[x].split()


                if len(tru)!=3:
                    return f, r, i, 'Bad line in your file. №:' + str(x)
                a, b, c = (y for y in tru)
                if not ((is_float(a)) or (is_float(b)) or (is_float(c))):
                    return f, r, i, 'Bad data. Your data isnt numerical type. Number of bad line:' + str(x)
                f.append(float(a))  # frequency
                r.append(float(b))  # Re of S11
                i.append(float(c))  # Im of S11
        else:
            return f, r, i, 'Bad data format'
        return f, r, i, 'very nice'


    validator_status = 'nice'
    # calculate
    circle_params=[]
    if len(data) > 0:
        f,r,i,validator_status = unpack_data(data)

        Q0,sigmaQ0,QL,sigmaQl, circle_params =calc_function(f,r,i)
        st.write("Cable attenuation")
        st.write(f"Q0 = {Q0} +- {sigmaQ0}, epsilon Q0 ={sigmaQ0/Q0}")
        st.write(f"QL = {QL} +- {sigmaQl}, epsilon QL ={sigmaQl/QL}")


    st.write("Status: " +validator_status)

    if len(data) > 0:
        f,r,i,validator_status = unpack_data(data)
        if validator_status == 'very nice':
            plot_data(r,i,circle_params)