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@@ -130,7 +130,7 @@ def plot_smith(r, i, g, r_cut, i_cut, show_excluded):
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# plot (abs(S))(f) chart with pyplot
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-def plot_abs_vs_f(f, r, i):
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+def plot_abs_vs_f(f, r, i, fitted_mag_s):
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fig = plt.figure(figsize=(10, 10))
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abs_S = list((r[n] ** 2 + i[n] ** 2)**0.5 for n in range(len(r)))
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xlim = [min(f) - abs(max(f) - min(f)) * 0.1,
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@@ -149,6 +149,8 @@ def plot_abs_vs_f(f, r, i):
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ax.plot(f, abs_S, '+', ms=8, mew=2, color='#1946BA')
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+ ax.plot(f, fitted_mag_s, '-',ms=8, mew=8, color='#FF8400')
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+
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# radius = abs(g[1] - g[0] / g[2]) / 2
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# x = ((g[1] + g[0] / g[2]) / 2).real
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# y = ((g[1] + g[0] / g[2]) / 2).imag
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@@ -340,12 +342,13 @@ def run(calc_function):
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i.pop()
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f.pop()
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- if len(f) < 3 or len(f) != len(r) or len(f) != len(i):
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- return_status = 'Choosen data range is too small, add more points'
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- elif max(abs(np.array(r)+ 1j* np.array(i))) > 2:
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- return_status = 'Your data points have an abnormality:\
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- they are too far outside the unit cirlce.\
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- Make sure the format is correct'
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+ if return_status == 'data parsed':
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+ if len(f) < 3 or len(f) != len(r) or len(f) != len(i):
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+ return_status = 'Choosen data range is too small, add more points'
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+ elif max(abs(np.array(r)+ 1j* np.array(i))) > 2:
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+ return_status = 'Your data points have an abnormality:\
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+ they are too far outside the unit cirlce.\
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+ Make sure the format is correct'
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return f, r, i, return_status
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@@ -364,7 +367,7 @@ def run(calc_function):
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# file upload button
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uploaded_file = st.file_uploader('Upload a file from your vector analizer. \
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- Make sure the file format is .snp or it has a similar inner structure.' )
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+ Make sure the file format is .snp or it has a similar inner structure.' )
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# check .snp
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data_format_snp = False
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@@ -381,7 +384,7 @@ def run(calc_function):
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data =['# Hz S MA R 50\n\
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11415403125 0.37010744 92.47802\n\
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11416090625 0.33831283 92.906929\n\
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- 11416778125 0.3069371 94.03318']
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+ 11416778125 0.3069371 94.03318' ]
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else:
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data = uploaded_file.readlines()
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if uploaded_file.name[-4:-2]=='.s' and uploaded_file.name[-1]== 'p':
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@@ -402,6 +405,7 @@ def run(calc_function):
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col1, col2 = st.columns([1,2])
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+ ace_text_value = ''.join(data).strip()
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with col1.expander("Processing options"):
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select_measurement_parameter = st.selectbox('Measurement parameter',
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['S', 'Z'],
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@@ -456,7 +460,6 @@ def run(calc_function):
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"type": "text"
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})
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- ace_text_value = ''.join(data).strip()
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st_ace(value=ace_text_value,
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readonly=True,
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auto_update=True,
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@@ -475,19 +478,21 @@ def run(calc_function):
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input_ports_pair = 1
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if column_count > 3:
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pair_count = (column_count - 1) // 2
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- input_ports_pair_id = st.number_input(
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+ input_ports_pair = st.number_input(
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"Choosen pair of ports with network parameters:",
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- min_value = 1,
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- max_value = pair_count,
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- value = 1) - 1
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- ports_count = round(pair_count **0.5)
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+ min_value=1,
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+ max_value=pair_count,
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+ value=1)
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+ input_ports_pair_id = input_ports_pair - 1
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+ ports_count = round(pair_count**0.5)
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st.write(select_measurement_parameter +
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str(input_ports_pair_id // ports_count + 1) +
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str(input_ports_pair_id % ports_count + 1))
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-
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- f, r, i, validator_status = unpack_data(
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- data,(input_ports_pair - 1) * 2 + 1, column_count, input_ref_resistance,
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- ace_preview_markers)
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+ f, r, i, validator_status = unpack_data(data,
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+ (input_ports_pair - 1) * 2 + 1,
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+ column_count,
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+ input_ref_resistance,
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+ ace_preview_markers)
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f = [x * hz for x in f] # to hz
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st.write("Use range slider to choose best suitable data interval")
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@@ -528,7 +533,7 @@ def run(calc_function):
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precision = col2.slider("Precision", min_value=0, max_value=7, value = 4)
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precision = '0.'+str(precision)+'f'
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- Q0, sigmaQ0, QL, sigmaQL, circle_params = calc_function(
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+ Q0, sigmaQ0, QL, sigmaQL, circle_params, fl, fitted_mag_s = calc_function(
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f_cut, r_cut, i_cut, check_coupling_loss)
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if Q0 <= 0 or QL <= 0:
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@@ -556,8 +561,8 @@ def run(calc_function):
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f'{format(QL, precision)} \pm ' + f'{format(sigmaQL, precision)}, '
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+ r'\;\;\varepsilon_{Q_L} =' +
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f'{format(sigmaQL / QL, precision)}')
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-
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+ st.latex(r'f_L ='+f'{fl}'+'Hz')
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with st.expander("Show static abs(S) plot"):
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- plot_abs_vs_f(f_cut, r_cut, i_cut)
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+ plot_abs_vs_f(f_cut, r_cut, i_cut, fitted_mag_s)
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plot_smith(r, i, circle_params, r_cut, i_cut, st.checkbox("Show excluded points", value=True))
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