<jupyter_start><jupyter_text>Get the data  data for Gordon09 extinction curve sightlines<jupyter_code>data = get_merged_table()
# add comments for certain stars here
data.add_column(Column(['no'] * len(data), dtype='<U16', name='comment'))
def set_comment(name, s):
    data['comment'][data['Name'] == name] = s

for name in ["HD200775", "HD164906", "HD045314", "HD206773"]:
    set_comment(name, "lo_h_av")

set_comment("HD096675", "hi_h_av")
data['d']<jupyter_output><empty_output><jupyter_text>data for Gordon09 comparision star sightlines<jupyter_code>data_comp = get_merged_table(comp=True)<jupyter_output><empty_output><jupyter_text>data for Bohlin 78 Copernicus sightlines<jupyter_code>data_bohlin78 = get_bohlin78()
print(sorted(data.colnames))<jupyter_output><empty_output><jupyter_text>FM90 params versus fraction H2  Specific wavelength extinctionfh2 vs 1000 (or 1100) shows some structure.fh2 vs 1300 none at allfh2 vs 4000 looks like fh2 vs AV (as expected)<jupyter_code>_ = plot_results2(data, '1_RV', 'A1000', mark_comments=['lo_h_av'])
_ = plot_results2(data, "A1000_AV", 'fh2', mark_comments=['lo_h_av'])
_ = plot_results2(data, 'CAV1', 'fh2', mark_comments=['lo_h_av'])
_ = plot_results2(data, 'CAV2', 'fh2', mark_comments=['lo_h_av'])
_ = plot_results2(data, 'CAV3', 'fh2', ignore_comments=['lo_h_av'])
_ = plot_results2(data, 'CAV4', 'fh2', ignore_comments=['lo_h_av'])
_ = plot_results2(data[data['CAV4']<0.25], 'CAV4', 'fh2', ignore_comments=['lo_h_av'])
_ = plot_results2(data, 'x_o', 'fh2', mark_comments=['lo_h_av'])
_ = plot_results2(data, 'gamma', 'fh2', ignore_comments=['lo_h_av'])
_ = plot_results2(data, 'bump_area', 'fh2', mark_comments=['lo_h_av'])<jupyter_output><empty_output><jupyter_text>Some FM90 parameters versus Gas to dust<jupyter_code>fig, ax = plt.subplots()
_ = plot_results_scatter(ax, data[data['Name'] != 'HD062542'], 'CAV4', 'NH_AV', mark_comments=['lo_h_av'], ignore_comments=['hi_h_av'])
data['Name', 'CAV4'][data['CAV4'] > .3]
_ = plot_results2(data,'bump_area', 'NH_AV', ignore_comments=['lo_h_av'])
fig, ax = plt.subplots()
_ = plot_results_scatter(ax, data,'CAV3', 'NH_AV', ignore_comments=['hi_h_av'])
fig, ax = plt.subplots()
_ = plot_results_scatter(ax, data,'nhi', 'NH_AV', ignore_comments=['hi_h_av'])
fig, ax = plt.subplots()
_ = plot_results_scatter(ax, data,'denhtot', 'NH_AV', ignore_comments=['hi_h_av'])
_ = plot_results2(data, 'AV', 'A1000', ignore_comments=['hi_h_av'], mark_comments=['lo_h_av'])
_ = plot_results2(data, 'A1000_AV', 'AV_NH', ignore_comments=['hi_h_av'], mark_comments=['lo_h_av'])
_ = plot_results2(data, 'A1000_NH', 'AV_NH', ignore_comments=['hi_h_av'], mark_comments=['lo_h_av'])
_ = plot_results2(data, 'A1000_AV', 'A1000_NH', ignore_comments=['hi_h_av'], mark_comments=['lo_h_av'])
_ = plot_results2(data, 'A1000_AV', 'AV_NH', ignore_comments=['hi_h_av'], mark_comments=['lo_h_av'])<jupyter_output><empty_output><jupyter_text>FM90 parameters in native form (E(lambda - V)/E(B-V)) versus R(V)<jupyter_code>_ = plot_results2(data, '1_RV', 'C2')
_ = plot_results2(data, '1_RV', 'C3')
_ = plot_results2(data, '1_RV', 'C4')
_ = plot_results2(data, '1_RV', 'gamma')
_ = plot_results2(data, '1_RV', 'x_o')<jupyter_output><empty_output>
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