<jupyter_start><jupyter_text>Einfluss Herbizide auf ÜberlebensrateDie Messungen wurden von <NAME> et. al. durchgeführt.Die Software wurde als Notebook programmiert gemäss https://fslab.org/XPlot//chart/plotly-line-scatter-plots.html  Zuerst die Messdaten<jupyter_code>let Finalsan = [
    3.3, 9
    3.9, 10
    4.5, 9
    5.5, 2
    5.5, 1
]
let Duplosan = [
    2.7, 8
    3.3, 8
    3.6, 10
    3.9, 10
    4.9, 10
    6.9, 8
    8.9, 8
    10.9, 9
]
let Roundup = [
    0.3, 9
    0.9, 9
    1.5, 9
    2.1, 9
    2.7, 9
    3, 8
    3.2, 10
    //3.3, 0
    3.3, 10
    3.9, 10
    4.9, 9
    5.9, 4
    5.9, 10
    6.9, 1
    //6.9, 0
    7.9, 2
]<jupyter_output><empty_output><jupyter_text>Jetzt laden wir die Software, die die Plots macht.<jupyter_code>#r "nuget: XPlot.Plotly.Interactive"
open XPlot.Plotly<jupyter_output><empty_output><jupyter_text>Die Messdaten müssen je in die ``x`` und ``y`` Vektoren unterteilt werden.^<jupyter_code>let Finalsan_x = Finalsan |> List.map (fun (x, _) -> x) 
let Finalsan_y = Finalsan |> List.map (fun (_, y) -> y)
let Duplosan_x = Duplosan |> List.map (fun (x, _) -> x)
let Duplosan_y = Duplosan |> List.map (fun (_, y) -> y)
let Roundup_x = Roundup |> List.map (fun (x, _) -> x)
let Roundup_y = Roundup |> List.map (fun (_, y) -> y)<jupyter_output><empty_output><jupyter_text>Jetzt erstellen wir zuerst die drei Liniendiagramme, und fügen sie dann zu einem Chart zusammen.<jupyter_code>let finalsan_line =
    Scatter(x = Finalsan_x, y = Finalsan_y, name = "Finalsan")
let duplosan_line = 
    Scatter(x = Duplosan_x, y = Duplosan_y, name = "Duplosan")
let roundup_line =
    Scatter(x = Roundup_x, y = Roundup_y, name = "Roundup")

let chart = [finalsan_line; duplosan_line; roundup_line] |> Chart.Plot
chart.WithXTitle("Herbizid [µl]")
chart.WithYTitle("Lebend")
display(chart)<jupyter_output><empty_output><jupyter_text>Jetzt runterladen als interaktive HTML Datei.<jupyter_code>let htmlx = chart.GetHtml()
IO.File.WriteAllText("/Users/mmgreiner/Projects/Herbizid.html", htmlx)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13848396501457727, 'fraction_numerical': 0.04616132167152575, 'mean_word_length': 3.476086956521739, 'pattern_counts': {'":': 0, '<': 22, '<?xml version=': 0, '>': 35, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '162175', 'license': 'MIT', 'n_tokens_mistral': 951, 'n_tokens_neox': 896, 'n_words': 205, 'path': 'Herbizid.ipynb', 'repo_name': 'mmgreiner/Notebook', 'size': '2063'}