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- import streamlit as st
- import matplotlib.pyplot as plt
- import numpy as np
- import sys
-
- ### don't do it this way!
- import os
- absolute_path = os.path.abspath(__file__)
- # print("Full path: " + absolute_path)
- # print("Directory Path: " + os.path.dirname(absolute_path))
- # adding /backend to use its functions here
- sys.path.append("/".join(os.path.dirname(absolute_path).split('/')[:-1]))
- # print("/".join(os.path.dirname(absolute_path).split('/')[:-1]))
- from backend.calc import *
- 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
- 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)
- # ../../resource/data/1_M450.MEA
- # with open("/".join(os.path.dirname(absolute_path).split('/')[:-2]) + "/resource/data/1_M450.MEA") as f:
- # row = f.readlines()
- # f, r, i = [], [], []
- # for x in row:
- # a, b, c = (float(y) for y in x.split())
- # f.append(a) # frequency
- # r.append(b) # Re of something
- # i.append(c) # Im of something
- # plot_data(r,i)
- ### move all that into to a 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',['","' ,'" "','";"'])
- def unpack_data(data):
- f, r, i = [], [], []
- for x in data:
- a, b, c = (float(y) for y in x.split())
- f.append(a) # frequency
- r.append(b) # Re of S11
- i.append(c) # Im of S11
- 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 =fl_fitting(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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