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- 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+')
- #
- ax.xlabel("x")
- ax.ylabel("y")
- #cirlce approximation
- t=np.linspace(0,1,100)
- z = (g[0]*t+g[1])/(g[2]+1)
- ax.plot(z.real,z.imag)
- #
- 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):
- f, r, i = [], [], []
- if select_data_format == 'Frequency, Re(S11), Im(S11)':
- for x in range(len(data)):
- tru = data[x].split(select_separator)
- 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(a) # frequency
- r.append(b) # Re of S11
- i.append(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)
- plot_data(r,i,circle_params)
-
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