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@@ -11,23 +11,34 @@ from .data_parsing_utils import parse_snp_header, read_data, count_columns, prep
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def plot_smith(r, i, g, r_cut, i_cut):
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def plot_smith(r, i, g, r_cut, i_cut):
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- show_excluded_points = True
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- show_Abs_S_gridlines = False
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- show_Re_Z_gridlines = False
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- show_Im_Z_gridlines = False
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- show_grid = True
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+ # maintaining state again (remember options for this session)
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+ if 'smith_options' not in st.session_state:
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+ st.session_state.smith_options = (True, True, False, False, False)
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with st.expander("Smith chart options"):
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with st.expander("Smith chart options"):
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- show_excluded_points = st.checkbox("Show excluded points",
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- value=show_excluded_points)
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- show_grid = st.checkbox("Show grid", value=show_grid)
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-
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- show_Abs_S_gridlines = st.checkbox("Show |S| gridlines",
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- value=show_Abs_S_gridlines)
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- show_Re_Z_gridlines = st.checkbox("Show Re(Z) gridlines",
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- value=show_Re_Z_gridlines)
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- show_Im_Z_gridlines = st.checkbox("Show Im(Z) gridlines",
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- value=show_Im_Z_gridlines)
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+ smith_options_input = (st.checkbox(
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+ "Show excluded points",
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+ value=st.session_state.smith_options[0]),
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+ st.checkbox("Show grid",
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+ st.session_state.smith_options[1]),
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+ st.checkbox(
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+ "Show |S| gridlines",
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+ value=st.session_state.smith_options[2],
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+ ),
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+ st.checkbox(
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+ "Show Re(Z) gridlines",
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+ value=st.session_state.smith_options[3],
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+ ),
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+ st.checkbox(
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+ "Show Im(Z) gridlines",
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+ value=st.session_state.smith_options[4],
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+ ))
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+ if st.session_state.smith_options != smith_options_input:
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+ st.session_state.smith_options = smith_options_input
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+ st.experimental_rerun()
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+
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+ (show_excluded_points, show_grid, show_Abs_S_gridlines,
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+ show_Re_Z_gridlines, show_Im_Z_gridlines) = st.session_state.smith_options
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fig = plt.figure(figsize=(10, 10))
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fig = plt.figure(figsize=(10, 10))
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ax = fig.add_subplot()
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ax = fig.add_subplot()
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ax.axis('equal')
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ax.axis('equal')
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@@ -81,23 +92,18 @@ 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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fig = plt.figure(figsize=(10, 10))
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s = np.abs(np.array(r) + 1j * np.array(i))
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s = np.abs(np.array(r) + 1j * np.array(i))
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if st.session_state.legendselection == '|S| (dB)':
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if st.session_state.legendselection == '|S| (dB)':
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- m = np.min(np.where(s==0, np.inf, s))
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- s = list(20*np.where(s==0, np.log10(m), np.log10(s)))
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- m = np.min(np.where(s==0, np.inf, fitted_mag_s))
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- fitted_mag_s = list(20*np.where(s==0, np.log10(m), np.log10(fitted_mag_s)))
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+ m = np.min(np.where(s == 0, np.inf, s))
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+ s = list(20 * np.where(s == 0, np.log10(m), np.log10(s)))
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+ m = np.min(np.where(s == 0, np.inf, fitted_mag_s))
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+ fitted_mag_s = list(
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+ 20 * np.where(s == 0, np.log10(m), np.log10(fitted_mag_s)))
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s = list(s)
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s = list(s)
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min_f = min(f)
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min_f = min(f)
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max_f = max(f)
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max_f = max(f)
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- xlim = [
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- min_f - abs(max_f - min_f) * 0.1,
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- max_f + abs(max_f - min_f) * 0.1
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- ]
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+ xlim = [min_f - abs(max_f - min_f) * 0.1, max_f + abs(max_f - min_f) * 0.1]
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min_s = min(s)
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min_s = min(s)
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max_s = max(s)
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max_s = max(s)
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- ylim = [
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- min_s - abs(max_s - min_s) * 0.5,
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- max_s + abs(max_s - min_s) * 0.5
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- ]
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+ ylim = [min_s - abs(max_s - min_s) * 0.5, max_s + abs(max_s - min_s) * 0.5]
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ax = fig.add_subplot()
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ax = fig.add_subplot()
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ax.set_xlim(xlim)
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ax.set_xlim(xlim)
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ax.set_ylim(ylim)
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ax.set_ylim(ylim)
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@@ -366,4 +372,3 @@ def run(calc_function):
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plot_abs_vs_f(f_cut, r_cut, i_cut, fitted_mag_s)
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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)
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plot_smith(r, i, circle_params, r_cut, i_cut)
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-
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