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 <p>Draw-Descriptions (Maxima)</p> <p>Draw-Descriptions (Maxima)</p>

Optionen

Options

[Maxima Draw] adapt_depth (=10): maximale Teilungstiefe der adaptive Kurvenabtastung

[Maxima Draw] adapt_depth (=10) maximum number of adaptive interval splits when drawing curves

 adapt_depth adapt_depth :

[Maxima Draw] axis_3d (=true): Achsen im 3D zeichnen, false: keine Achsen zeichnen

[Maxima Draw] axis_3d (=true): draw 3D axes, false: don't draw axes

 axis_3d axis_3d :

[Maxima Draw] axis_bottom (=true): untere Achse im 2D zeichnen, false: Achse nicht zeichnen

[Maxima Draw] axis_bottom (=true): draw bottom axis in 2D, false: don't draw axis

 axis_bottom axis_bottom :

[Maxima Draw] axis_top (=true): obere Achse im 2D zeichnen, false: Achse nicht zeichnen

[Maxima Draw] axis_top (=true): draw top axis in 2D, false: don't draw axis

 axis_top axis_top :

[Maxima Draw] axis_left (=true): linke Achse im 2D zeichnen, false: Achse nicht zeichnen

[Maxima Draw] axis_left (=true): draw left axis in 2D, false: don't draw axis

 axis_left axis_left :

[Maxima Draw] axis_right (=true): rechte Achse im 2D zeichnen, false: Achse nicht zeichnen

[Maxima Draw] axis_right (=true): draw right axis in 2D, false: don't draw axis

 axis_right axis_right :

[Maxima Draw] background_color (=white): Hintergrundfarbe des Diagramms

[Maxima Draw] background_color (=white): background color of the plot

 background_color background_color :

[Maxima Draw] border (=true): Ränder von polygon(), ellipse() oder rectangle() zeichnen

[Maxima Draw] border (=true): draw borders of polygon(), ellipse() or rectangle() objects

 border border :

[Maxima Draw] cbrange (=auto): Farbbereich (Liste min,max)

[Maxima Draw] capping (=false): indicates if extremes of the tube object remain open (false) or are closed (true). If only one end is to be closed, provide a list with two entries.

 capping capping :

[Maxima Draw] cbrange (=auto): Farbbereich (Liste min,max)

[Maxima Draw] cbrange (=auto): color bar range (list min,max)

 cbrange cbrange :

[Maxima Draw] cbtics (=auto): Marken an der Farblegende

[Maxima Draw] cbtics (=auto): color bar tick marks

 cbtics cbtics :

[Maxima Draw] color (=blue): Farbe für Linien, Punkte, Kanten und Text, als Namen oder hexadezimal in der Form "#rrggbb"

[Maxima Draw] color (=blue): color for lines, points, borders and text, given as name or as "#rrggbb"

 color color :

[Maxima Draw] colorbox (=true): Farblegende ohne Beschriftung zeichnen, false: keine Farblegende zeichnen, text: Farblegende mit text als Beschriftung zeichnen.

[Maxima Draw] colorbox (=true): draw color scale without label, false: no colorbar, string: draw colorbar with string as label.

 colorbox colorbox :

[Maxima Draw] contour (=none): Art der Höhenlinien. none: keine, base: auf der xy-Ebene, surface: auf der 3D-Fläche, both: auf xy-Ebene und Fläche, map: auf xy-Ebene und Blickrichtung senkrecht.

[Maxima Draw] contour (=none): contour lines. none: no contours, base: on xy plane, surface: on 3D surface, both: on xy plane and surface, map: on xy plane plus vertical view.

 contour contour :

[Maxima Draw] contour_levels (=5): Werte für die Höhenlinien. Anzahl oder Liste (min, Δ, max), oder set(L1, L2,...) mit Werten

[Maxima Draw] contour_levels (=5): contour levels. number oder list (min, Δ, max), or set(L1, L2,...) of values

 contour_levels contour_levels :

[Maxima Draw] data_file_name (="data.gnuplot"): Kurvendaten für Gnuplot

[Maxima Draw] data_file_name (="data.gnuplot"): internal data file name for gnuplot

 data_file_name data_file_name :

[Maxima Draw] delay (=5) Zeitschritt in animierten gif-Dateien

[Maxima Draw] delay (=5): time step in animted gif files

 delay delay :

[Maxima Draw] dimensions (= 600 x 500): Liste [Breite,Höhe]

[Maxima Draw] dimensions (= 600 x 500) list [width, height]

 dimensions dimensions :

[Maxima Draw] draw_realpart (=true) Realteil zur Darstellung komplexer Werte verwenden

[Maxima Draw] draw_realpart (=true) use real part for plotting complex values

 draw_realpart draw_realpart :

[Maxima Draw] enhanced3d (=none) Farbpalette, none: 3D Flächen als Gitter zeichnen (Steuerung mit color und surface_hide), true: Farbe anhand des z-Werts, Liste [f(x,y,z), x, y, z]: Farbe anhand der Funktion f, Liste [f(u,v),u,v]: Farbe anhand der Flächenparameter oder Liste [f(k), k ]: Farbe anhand der Punktnummer in points() Objekten

[Maxima Draw] enhanced3d (=none) don't use color palette, draw 3D surfaces as grid (control using color und surface_hide), true: coloring of surfaces by z-value, or list [f(x,y,z), x, y, z]: coloring according to function f or list [f(u,v),u,v] or list [f(k), k ] (k being the point counter in points() objects)

 enhanced3d enhanced3d :

[Maxima Draw] error_type (=y) Art der Fehlerbalken in errors(): x, y, xy oder boxes

[Maxima Draw] error_type (=y) type of error bars in errors(): x, y, xy or boxes

 error_type error_type :

[Maxima Draw] file_name (="maxima_out") Grafik-Ausgabedatei, Endung wird gemäß Ausgabeformat ergänzt

[Maxima Draw] file_name (="maxima_out") output file, extension is set according to format

 file_name file_name :

[Maxima Draw] fill_color (=red) Füllfarbe für Objejte polygon() und explicit() in 2D

[Maxima Draw] fill_color (=red) fill color for polygons and explicit functions y(x) in 2D

fill_color fill_color :

[Maxima Draw] fill_density (=0) Deckungsgrad der Füllfarbe in bars()-Objekten, zwischen 0 und 1

[Maxima Draw] fill_density (=0) opacity of the fill color in bars()-objects, 0..1

 fill_density fill_density :

[Maxima Draw] filled_func (=false): explizite Funktionen y(x) werden nicht gefüllt, true: Füllung bis zur Unterkante des Diagramms, g(x): Füllung zwischen g(x) und y(x)

[Maxima Draw] filled_func (=false): don't fill explicit functions y(x), true: fill between the next explicit() object and the bottom border of the diagram, g(x): fill between g(x) and the next explicit() object

 filled_func filled_func :

[Maxima Draw] gnuplot_file_name (="maxout.gnuplot"): Kommandodatei für Gnuplot

[Maxima Draw] gnuplot_file_name (="maxout.gnuplot"): name of the temporary gnuplot command file

 gnuplot_file_name gnuplot_file_name :

[Maxima Draw] gnuplot_term (): Ausgabe-Format-Spezifikation (Text nach "set terminal")

[Maxima Draw] gnuplot_term (): gnuplot terminal options (arguments of "set terminal")

 gnuplot_term gnuplot_term :

[Maxima Draw] gnuplot_out_file (=maxplot.xxx) Ausgabedateiname (xxx abhängig vom Format)

[Maxima Draw] gnuplot_out_file (=maxplot.xxx) output file name (xxx depends on terminal)

 gnuplot_out_file gnuplot_out_file :

[Maxima Draw] grid (=false): kein Gitterraster zeichnen, true: Gitter zeichnen

[Maxima Draw] grid (=false): don't draw xy grid, true: draw grid

 grid grid :

[Maxima Draw] head_angle (=45) Pfeilwinkel an vector()-Objekten (halber Öffnungswinkel in °)

[Maxima Draw] head_angle (=45): head angle of vector()-Objekten (angle between border and vector direction in °)

 head_angle head_angle :

[Maxima Draw] head_both (=false) oder true: ob bei vector()-Objekten zwei Pfeilspitzen gezeichnet werden.

[Maxima Draw] head_both (=false): don't draw a second head of vector() objects, true: draw a second head

 head_both head_both :

[Maxima Draw] head_length (=2) Länge der Pfeilspitze bei vector()-Objekten in Einheiten der x-Achse

[Maxima Draw] head_length (=2): head length of vector() objects in units of the x-axis

 head_length head_length :

[Maxima Draw] head_type (=filled) Spitzenform bei vector()-Objekten: filled, empty oder nonfilled

[Maxima Draw] head_type (=filled) head type of vector() objects: filled, empty or nonfilled

 head_type head_type :

[Maxima Draw] ip_grid (={50, 50): Primäres Gitter für die Darstellung impliziter Funktionen, als Liste angeben

[Maxima Draw] ip_grid (={50, 50): primary grid for sampling of implicit functions, two-element list

 ip_grid ip_grid :

[Maxima Draw] ip_grid_in (={5, 5 ): Sekundäres Gitter für die Darstellung impliziter Funktionen

[Maxima Draw] ip_grid_in (={5, 5 ): secondary grid for sampling of implicit functions

 ip_grid_in ip_grid_in :

[Maxima Draw] key (=""): Legendeneintrag für das nachfolgende Grafikobjekt.

[Maxima Draw] key (=""): legend key for subsequent graphics object.

 key key :

[Maxima Draw] key_pos (="", entspricht top_right): Legendenposition. Gültige Werte: top_left, top_center, top_right, center_left, center, center_right, bottom_left, bottom_center, bottom_right

[Maxima Draw] key_pos (="", equivalent to top_right): position of the legend. Valid options: top_left, top_center, top_right, center_left, center, center_right, bottom_left, bottom_center, bottom_right

 key_pos key_pos :

[Maxima Draw] label_alignment (=center), left oder right: horizontale Ausrichtung von Beschriftungen

[Maxima Draw] label_alignment (=center), left or right: alignment of text labels

 label_alignment label_alignment :

[Maxima Draw] label_orientation (=horizontal) oder vertical: Ausrichtung von Texten

[Maxima Draw] label_orientation (=horizontal) or vertical: orientation of text labels

 label_orientation label_orientation :

[Maxima Draw] line_type (=solid) Linienart. Alternativen: dots (für alle Formate) oder wenn von Gnuplot unterstützt: dashes, short_dashes, short_long_dashes, short_short_long_dashes

[Maxima Draw] line_type (=solid) line type. Other options: dots (for all formats) or if supported by Gnuplot: dashes, short_dashes, short_long_dashes, short_short_long_dashes

line_type line_type :

[Maxima Draw] line_width (=1) , >0

line_width line_width :

[Maxima Draw] logcb (=false) oder true: logarithmische Farbskale

[Maxima Draw] logcb (=false) or true: log scale of the colorbar

 logcb logcb :

[Maxima Draw] logx (=false) oder true: logarithmische x-Achse

[Maxima Draw] logx (=false) or true: log scale of x-axis

 logx logx :

[Maxima Draw] logx_secondary (=false) oder true: logarithmische zweite x-Achse

[Maxima Draw] logx_secondary (=false) or true: log scale of secondary x-axis

 logx_secondary logx_secondary :

[Maxima Draw] logy (=false) oder true: logarithmische y-Achse

[Maxima Draw] logy (=false) or true: log scale of y-axis

 logy logy :

[Maxima Draw] logy_secondary (=false) oder true: logarithmische zweite y-Achse

[Maxima Draw] logy_secondary (=false) or true: log scale of secondary y-axis

 logy_secondary logy_secondary :

[Maxima Draw] logz (=false) oder true: logarithmische z-Achse

[Maxima Draw] logz (=false) or true: log scale of z-axis

 logz logz :

[Maxima Draw] nticks (=29): Punktezahl für die Kurvenabtastung

[Maxima Draw] nticks (=29): number of points for curve sampling (explicit and parametric)

 nticks nticks :

[Maxima Draw] palette (=color) Standard-Farbpalette, gray: Graustufen, Liste { Farbe1, Farbe2... oder false: Flächen nicht färben

[Maxima Draw] palette (=color) default color palette, gray: gray levels, list { color1, color2... or false: don't color 3D objects

palette palette :

[Maxima Draw] point_size (=1) Größe von points()-Symbolen

[Maxima Draw] point_size (=1) size of points()-symbols

 point_size point_size :

[Maxima Draw] point_type (=1) Symbol für points()-Objekte, Name oder Kennzahl: none -1, dot 0, plus 1, multiply 2, asterisk 3, square 4, filled_square 5, circle 6, filled_circle 7, up_triangle 8, filled_up_triangle 9, down_triangle 10, filled_dwn_triangle 11, diamant 12, filled_diamant 13

[Maxima Draw] point_type (=1) type of points() objects, name or key number: none -1, dot 0, plus 1, multiply 2, asterisk 3, square 4, filled_square 5, circle 6, filled_circle 7, up_triangle 8, filled_up_triangle 9, down_triangle 10, filled_down_triangle 11, diamant 12, filled_diamant 13

 point_type point_type :

[Maxima Draw] points_joined (=false), true oder impulses: Verbindungsart von points()-Objekten

[Maxima Draw] points_joined (=false), true or impulses: how to join points

 points_joined points_joined :

[Maxima Draw] proportional_axes (=none), xy oder xyz: Achsen mit gleicher Skalierung)

[Maxima Draw] proportional_axes (=none), xy or xyz: set axes of equal scaling)

 proportional_axes proportional_axes :

[Maxima Draw] surface_hide (=false) oder true: Ausblendung verdeckter Flächen bei Linienrasterdarstellung

[Maxima Draw] surface_hide (=false) or true: handling of hidden lines in surface grids

 surface_hide surface_hide :

[Maxima Draw] terminal (=screen) separate interactive terminal window, png, jpg, gif, eps, svg, pdf, animated_gif: gnuplot output format

terminal terminal :

[Maxima Draw] title (="") Überschrift für das Diagramm

[Maxima Draw] title (="") headline for the plot

 title title :

[Maxima Draw] transform (=none) Koordinatentransformation, für 2D als Liste {f1(x,y), f2(x,y), x, y, für 3D als Liste {f1(x,y), f2(x,y), f3(x, y, z), x, y, z

[Maxima Draw] transform (=none) co-ordinate transformation, for 2D as list {f1(x,y), f2(x,y), x, y, for 3D as list {f1(x,y), f2(x,y), f3(x, y, z), x, y, z

 transform transform :

[Maxima Draw] transparent (=false) oder true: ob Rechtecke, Polygone oder Ellipsen transparent sein sollen (bei false werden sie gefüllt)

[Maxima Draw] transparent (=false) fill objects with border, true: don't fill (make them transparent)

 transparent transparent :

[Maxima Draw] tube_extremes (=(open, open) ), open oder closed: Endscheiben von tube()-Objekten.

[Maxima Draw] tube_extremes (=(open, open) ), open or closed: how tube() objects are terminated.

 tube_extremes tube_extremes :

[Maxima Draw] unit_vectors (=false) oder true: Vektoren in originaler Länge oder als Einheitsvektoren zeichnen.

[Maxima Draw] unit_vectors (=false) draw vectors in original length, true: draw unit vectors.

 unit_vectors unit_vectors :

[Maxima Draw] user_preamble (="") Zeichenkette oder Liste von Zeichenketten, die unmittelbar vor dem eigentlichen Diagrammbefehl an Gnuplot übergeben werden.

[Maxima Draw] user_preamble (="") string or list of strings, gnuplot commands placed immediately before the plot commands

 user_preamble user_preamble :

[Maxima Draw] view (=(60,30)) view direction

view view :

[Maxima Draw] wired_surface (=false) oder true: Gitternetz auf eingefärbten Flächen anzeigen oder nicht.

[Maxima Draw] wired_surface (=false) no grid on colored surfaces, true: draw grid on surfaces

 wired_surface wired_surface :

[Maxima Draw] x_voxel (=10) x-Bereichsteilung für den Marching-Cubes-Algorithmus bei implizit gegebenen Flächen

[Maxima Draw] x_voxel (=10) number of x steps for the Marching Cube algorithm (for implicit 3D functions)

 x_voxel x_voxel :

[Maxima Draw] y_voxel (=10) y-Bereichsteilung für den Marching-Cubes-Algorithmus bei implizit gegebenen Flächen

[Maxima Draw] y_voxel (=10) number of y steps for the Marching Cube algorithm (for implicit 3D functions)

 y_voxel y_voxel :

[Maxima Draw] z_voxel (=10) z-Bereichsteilung für den Marching-Cubes-Algorithmus bei implizit gegebenen Flächen

[Maxima Draw] z_voxel (=10) number of z steps for the Marching Cube algorithm (for implicit 3D functions)

 z_voxel z_voxel :

[Maxima Draw] xaxis (=false) oder true: Anzeige der x-Achse

[Maxima Draw] xaxis (=false) or true: draw x-axis

 xaxis xaxis :

[Maxima Draw] yaxis (=false) oder true: Anzeige der y-Achse

[Maxima Draw] yaxis (=false) or true: draw y-axis

 yaxis yaxis :

[Maxima Draw] zaxis (=false) oder true: Anzeige der z-Achse

[Maxima Draw] zaxis (=false) or true: draw z-axis

 zaxis zaxis :

[Maxima Draw] xaxis_color (=black) Farbe x-Achse

[Maxima Draw] xaxis_color (=black) color of the x-axis

 xaxis_color xaxis_color :

[Maxima Draw] yaxis_color (=black) Farbe y-Achse

[Maxima Draw] yaxis_color (=black) color of the y-axis

 yaxis_color yaxis_color :

[Maxima Draw] zaxis_color (=black) Farbe z-Achse

[Maxima Draw] zaxis_color (=black) color of the z-axis

 zaxis_color zaxis_color :

[Maxima Draw] xaxis_secondary (=false) oder true: Nutzung einer zweiten x-Achse (oben) für die nachfolgenden Objekte

[Maxima Draw] xaxis_secondary (=false) or true: use the secondary x-axis (top) for subsequent objects

 xaxis_secondary xaxis_secondary :

[Maxima Draw] yaxis_secondary (=false) oder true: Nutzung einer zweiten y-Achse (rechts) für die nachfolgenden Objekte

[Maxima Draw] yaxis_secondary (=false) or true: use the secondary y-axis (right) for subsequent objects

 yaxis_secondary yaxis_secondary :

[Maxima Draw] xaxis_type (=dots) oder solid: Linienart der x-Achse

[Maxima Draw] xaxis_type (=dots) or solid

 xaxis_type xaxis_type :

[Maxima Draw] yaxis_type (=dots) oder solid: Linienart der y-Achse

[Maxima Draw] yaxis_type (=dots) or solid

 yaxis_type yaxis_type :

[Maxima Draw] zaxis_type (=dots) oder solid: Linienart der z-Achse

[Maxima Draw] zaxis_type (=dots) or solid

 zaxis_type zaxis_type :

[Maxima Draw] xaxis_width (=1) Linienbreite der x-Achse

[Maxima Draw] xaxis_width (=1)

 xaxis_width xaxis_width :

[Maxima Draw] yaxis_width (=1) Linienbreite der y-Achse

[Maxima Draw] yaxis_width (=1)

 yaxis_width yaxis_width :

[Maxima Draw] zaxis_width (=1) Linienbreite der z-Achse

[Maxima Draw] zaxis_width (=1)

 zaxis_width zaxis_width :

[Maxima Draw] xlabel (="") x-Achsenbeschriftung

[Maxima Draw] xlabel (="") label of the x-axis

 xlabel xlabel :

[Maxima Draw] ylabel(="") y-Achsenbeschriftung

[Maxima Draw] ylabel (="") label of the y-axis

 ylabel ylabel :

[Maxima Draw] zlabel (="") z-Achsenbeschriftung

[Maxima Draw] zlabel (="") label of the z-axis

 zlabel zlabel :

[Maxima Draw] xrange (=auto) oder Liste {min,max: x-Achsenbereich

[Maxima Draw] xrange (=auto) or list {min,max: range of the x-axis

 xrange xrange :

[Maxima Draw] yrange (=auto) oder Liste {min,max: y-Achsenbereich

[Maxima Draw] yrange (=auto) or list {min,max: range of the y-axis

 yrange yrange :

[Maxima Draw] zrange (=auto) oder Liste {min,max: z-Achsenbereich

[Maxima Draw] zrange (=auto) or list {min,max: range of the z-axis

 zrange zrange :

[Maxima Draw] xrange_secondary (=auto) oder Liste {min,max: Bereich der zweiten (oberen) x-Achse

[Maxima Draw] xrange_secondary (=auto) or list {min,max: range of the secondary (top) x-axis

 xrange_secondary xrange_secondary :

[Maxima Draw] yrange_secondary (=auto) oder Liste {min,max: Bereich der zweiten (rechten) y-Achse

[Maxima Draw] yrange_secondary (=auto) or list {min,max: range of the secondary (right) y-axis

 yrange_secondary yrange_secondary :

[Maxima Draw] xtics (=auto): automatische x-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit {min, Schritt, max, oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ("text",pos) mit Vorgabe von Beschriftung und Position.

[Maxima Draw] xtics (=auto): automatic x ticks, none: no x ticks, number: tick interval, list of {min, step, max, or set() of numbers: explicit tick values, or set() of lists ("text",pos) for spec of position and text.

 xtics xtics :

[Maxima Draw] ytics (=auto): automatische y-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit {min, Schritt, max, oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen {"text",pos mit Vorgabe von Beschriftung und Position.

[Maxima Draw] ytics (=auto): automatic y ticks, none: no y ticks, number: tick interval, list of {min, step, max, or set() of numbers: explicit tick values, or set() of lists ("text",pos) for spec of position and text.

 ytics ytics :

[Maxima Draw] ztics (=auto): automatische z-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit {min, Schritt, max, oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen {"text",pos mit Vorgabe von Beschriftung und Position.

[Maxima Draw] ztics (=auto): automatic z ticks, none: no x ticks, number: tick interval, list of {min, step, max, or set() of numbers: explicit tick values, or set() of lists ("text",pos) for spec of position and text.

 ztics ztics :

[Maxima Draw] xtics_secondary (=auto): automatische Marken an der sekundären (oberen) x-Achse, none: keine, Zahl: Schrittweite, Liste mit {min, Schritt, max, oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen {"text",pos mit Vorgabe von Beschriftung und Position.

[Maxima Draw] xtics_secondary (=auto): automatic ticks on the secondary (top) x-axis, none: no ticks, number: tick interval, list of {min, step, max, or set() of numbers: explicit tick values, or set() of lists ("text",pos) for spec of position and text.

 xtics_secondary xtics_secondary :

[Maxima Draw] ytics_secondary (=auto): automatische Marken an der sekundären (rechten) y-Achse, none: keine, Zahl: Schrittweite, Liste mit {min, Schritt, max, oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen {"text",pos mit Vorgabe von Beschriftung und Position.

[Maxima Draw] ytics_secondary (=auto): automatic ticks on the secondary (right) y-axis, none: no ticks, number: tick interval, list of {min, step, max, or set() of numbers: explicit tick values, or set() of lists ("text",pos) for spec of position and text.

 ytics_secondary ytics_secondary :

[Maxima Draw] xtics_axis (=false): x-Achsmarken am Rand, true: an der Achse

[Maxima Draw] xtics_axis (=false): ticks on the boundary, true: ticks on the axis

 xtics_axis xtics_axis :

[Maxima Draw] ytics_axis (=false): y-Achsmarken am Rand, true: an der Achse

[Maxima Draw] ytics_axis (=false): ticks on the boundary, true: ticks on the axis

 ytics_axis ytics_axis :

[Maxima Draw] ztics_axis (=false): z-Achsmarken am Rand, true: an der Achse

[Maxima Draw] ztics_axis (=false): ticks on the boundary, true: ticks on the axis

 ztics_axis ztics_axis :

[Maxima Draw] xtics_secondary_axis (=false): Marken an der sekundaren (oberen) x-Achse am Rand, true: an der Achse

[Maxima Draw] xtics_secondary_axis (=false): ticks on the secondary (top) boundary, true: ticks on the axis

 xtics_secondary_axis xtics_secondary_axis :

[Maxima Draw] ytics_secondary_axis (=false): Marken an der sekundaren (rechten) y-Achse am Rand, true: an der Achse

[Maxima Draw] ytics_secondary_axis (=false): ticks on the secondary (right) boundary, true: ticks on the axis

 ytics_secondary_axis ytics_secondary_axis :

[Maxima Draw] xtics_rotate (=false): x-Achsmarken nicht drehen, true: um 90° drehen

[Maxima Draw] xtics_rotate (=false): horizontal tick labels, true: vertical tick labels

 xtics_rotate xtics_rotate :

[Maxima Draw] ytics_rotate (=false): y-Achsmarken nicht drehen, true: um 90° drehen

[Maxima Draw] ytics_rotate (=false): horizontal tick labels, true: vertical tick labels

 ytics_rotate ytics_rotate :

[Maxima Draw] ztics_rotate (=false): z-Achsmarken nicht drehen, true: um 90° drehen

[Maxima Draw] ztics_rotate (=false): horizontal tick labels, true: vertical tick labels

 ztics_rotate ztics_rotate :

[Maxima Draw] xtics_rotate_secondary (=false): Marken an der sekundären (oberen) x-Achse nicht drehen, true: um 90° drehen

[Maxima Draw] xtics_rotate_secondary (=false): don't rotate ticks of the secondary (top) x-axis, true: rotate about 90°

 xtics_rotate_secondary xtics_rotate_secondary :

[Maxima Draw] ytics_rotate_secondary (=false): Marken an der sekundären (rechten) y-Achse nicht drehen, true: um 90° drehen

[Maxima Draw] ytics_rotate_secondary (=false): don't rotate ticks of the secondary (right) y-axis, true: rotate about 90°

 ytics_rotate_secondary ytics_rotate_secondary :

[Maxima Draw] xu_grid (=30) Abtastpunkte in x- oder u-Richtung

[Maxima Draw] xu_grid (=30) sampling points in x- or u-direction

xu_grid xu_grid :

[Maxima Draw] yv_grid (=30) Abtastpunkte in y- oder v-Richtung

[Maxima Draw] yv_grid (=30) sampling points in y- or v-direction

yv_grid yv_grid :

[Maxima Draw] xyplane (=false): xy-Koordinatenebene automatisch anordnen, Zahl: z-Koordinate

[Maxima Draw3D] xyplane (=false): automatic allocation of the xy-plane, reak number: xy-plane intersects the z-axis at this level

 xyplane xyplane :

Objekte

[Maxima Draw2D] bars(b1,b2...) Säulendiagramm, Säulen gegeben durch Listen (x,h,w). Optionen: key, color, fill_color, fill_density and line_

[Maxima Draw2D] bars(b1,b2...) vertical bars, given as lists (x,h,w). Options: key, color, fill_color, fill_density and line_width

 _ bars _ bars :

[Maxima Draw3D] elevation_grid(Matrix,x0,y0,w,h) Stellt eine Matrix in 3D dar. M_11 bei x=x0,y=y0+h, M_mn bei x=x0+w,y=y0. Optionem: xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d and color

[Maxima Draw3D] elevation_grid(Matrix,x0,y0,w,h) Draws a m x n-matrix in 3D. M_11 at x=x0,y=y0+h, M_mn at x=x0+w,y=y0. Options: xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d and color

 _1 _2 _3 _4 _5 elevation_grid _1 _2 _3 _4 _5 elevation_grid :

[Maxima Draw2D] ellipse(xc,yc,a,b,φ1,φ2) Ellipse, zentriert bei xc, yc mit den Halbachsen a und b, von Winkel φ1 bis Winkel φ2. Optionen nticks, transparent, fill_color, border, line_width, line_type, key and color.

[Maxima Draw2D] ellipse(xc,yc,a,b,φ1,φ2) plots an ellipse centered at [xc, yc] with horizontal and vertical semi axis a and b, respectively, starting at angle ang1 with an amplitude equal to angle ang2. Options: nticks, transparent, fill_color, border, line_width, line_type, key and color.

#1 #2 #3 #4 #5 #6 ellipse #1 #2 #3 #4 #5 #6 ellipse :

[Maxima Draw2D] errors(e1,e2...) Punkte mit Fehlerbalken, horizontal, vertical oder beide, abhängig von der Option error_type. Argumente für error_type = x: Listen [x, y, xdelta] oder [x, y, xlow, xhigh]. Argumente für error_type = y; Listen [x, y, ydelta] oder [x, y, ylow, yhigh]. Argumente für error_type = xy oder error_type = boxes: Listen [x, y, xdelta, ydelta] oder [x, y, xlow, xhigh, ylow, yhigh]. Optionen: error_type, points_joined, line_width, key, line_type, color, fill_density, xaxis_secondary, and yaxis_secondary

[Maxima Draw2D] errors(e1,e2...) Draws points with error bars, horizontally, vertically or both, depending on the value of option error_type. If error_type = x, arguments are lists [x, y, xdelta] or [x, y, xlow, xhigh]. If error_type = y, arguments are lists [x, y, ydelta] or [x, y, ylow, yhigh]. If error_type = xy or error_type = boxes, arguments are lists [x, y, xdelta, ydelta] or [x, y, xlow, xhigh, ylow, yhigh]. Options: error_type, points_joined, line_width, key, line_type, color, fill_density, xaxis_secondary, and yaxis_secondary

 _ errors _ errors :

[Maxima Draw2D] explicit(f,x,xmin,xmax) zeichnet eine Funktion f von x von xmin bis xmax. Optionen: nticks, adapt_depth, draw_realpart, line_width, line_type, key, filled_func, fill_color und color

[Maxima Draw2D] explicit(f,x,xmin,xmax) plots explicit function f, with variable x taking values from xmin to xmax. Options: nticks, adapt_depth, draw_realpart, line_width, line_type, key, filled_func, fill_color and color

 _1 _2 _3 _4 explicit _1 _2 _3 _4 explicit :

[Maxima Draw3D] explicit(f,x,xmin,xmax,y,ymin,ymax) zeichnet eine Funktion f von x und y im Bereich xmin bis xmax und ymin bis ymax Optionen: draw_realpart, xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d und color.

[Maxima Draw3D] explicit(f,x,xmin,xmax,y,ymin,ymax) plots the explicit function f, with variable x taking values from xmin to xmax and variable y taking values from yminto ymax. Options: draw_realpart, xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, and color.

#1 #2 #3 #4 #5 #6 #7 explicit #1 #2 #3 #4 #5 #6 #7 explicit :

[Maxima Draw2D] image(Matrix,x0,y0,w,h) Farbdarstellung einer m x n Matrix entsprechend der Option palette

[Maxima Draw2D] image(matrix,x0,y0,w,h) plots matrix in the rectangular region from vertex (x0,y0) to (x0+w,y0+h) according to option palette.

 #1 #2 #3 #4 #5 image #1 #2 #3 #4 #5 image :

[Maxima Draw2D] implicit(f,x,xmin,xmax,y,ymin,ymax) 2D Darstellung einer implizit gegebenen Funktion im angegebenen Variablenbereich (marching squares Algorithmus). Optionen: ip_grid, ip_grid_in, line_width, line_type, key, color

[Maxima Draw2D] implicit(f,x,xmin,xmax,y,ymin,ymax) plots the implicit function defined by f, with variable x taking values from xmin to xmax, and variable y taking values from ymin to ymax. Options: ip_grid, ip_grid_in, line_width, line_type, key, color

 #1 #2 #3 #4 #5 #6 #7 implicit #1 #2 #3 #4 #5 #6 #7 implicit :

[Maxima Draw3D] implicit(f,x,xmin,xmax,y,ymin,ymax,z,zmin,zmax) 3D Darstellung einer implizit gegebenen Funktion im angegebenen Variablenbereich (Marching Cubes Algorithmus). Optionen: x_voxel, y_voxel, z_voxel, ip_grid_in, line_width, line_type, wired_surface, enhanced3D, color [Maxima Draw]

[Maxima Draw3D] implicit(f,x,xmin,xmax,y,ymin,ymax,z,zmin,zmax) plots the implicit surface defined by f, with variable x taking values from xmin to xmax, variable y taking values from ymin to ymax and variable z taking values from zmin to zmax. This object implements the marching cubes algorithm. Options: x_voxel, y_voxel, z_voxel, line_width, line_type, key, wired_surface, enhanced3d,and color

 #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 implicit #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 implicit :

[Maxima Draw2D and 3D] label(list) Beschriftung, im 2D gegeben als Liste (text,x,y), im 3D als Liste (text,x,y,z), spezielle Optionen: color, label_alignment, label_orientation

[Maxima Draw2D and 3D] label(list) text label specified in 2D as list [text,x,y], in 3D as list [text,x,y,z], Options: color, label_alignment, label_orientation

 _ label _ label :

[Maxima Draw2D] parametric(fx,fy,p,pmin,pmax) parametrisch gegebenen Funktion. Optionen: nticks, line_width, line_type, key, color, enhanced3d

[Maxima Draw2D] parametric(fx,fy,p,pmin,pmax) plots the parametric function fx, fy with parameter p taking values from pmin to pmax. Options nticks, line_width, line_type, key, color, enhanced3d

 #1 #2 #3 #4 #5 parametric #1 #2 #3 #4 #5 parametric :

[Maxima Draw3D] parametric(fx,fy,fz,p,pmin,pmax) parametrisch gegebene Kurve. Optionen: nticks, line_width, line_type, key, color, enhanced3d

#1 #2 #3 #4 #5 #6 parametric #1 #2 #3 #4 #5 #6 parametric :

points(matrix) Punkte, zeilenweise gegeben als n x 2 (2D) oder n x 3 (3D)-Matrix. Spezielle Optionen: points_joined, point_type, point_size [Maxima Draw2D/3D]

[Maxima Draw2D and 3D] points(matrix) 2D: n x 2, 3D: n x 3, plots points, given as the rows in a matrix. special options: points_joined, point_type, point_size

 #1 points #1 points :

points(vx,vy) Punkte, gegeben durch Vektoren der x- und y-Koordinaten. Spezielle Optionen: points_joined, point_type, point_size [Maxima Draw2D]

[Maxima Draw2D] points(vx,vy) points given by two vectors, special options: points_joined, point_type, point_size

 #1 #2 points #1 #2 points :

[Maxima Draw3D] points(vx,vy,vz) zeichnet Punkte, gegeben durch drei Vektoren, spezielle Optionen: points_joined, point_type, point_size

[Maxima Draw3D] points(vx,vy,vz) points given by three vectors, special options: points_joined, point_type, point_size

 #1 #2 #3 points #1 #2 #3 points :

[Maxima Draw2D] polar(r,φ,φmin,φmax) zeichnet Funktionen, die in Polarkoordinaten gegeben sind (Radius r als Funktion des Winkels φ). Spezielle Optionen: key, nticks, line_width, line_type, color

[Maxima Draw2D] polar(r,φ,φmin,φmax) draws functions given in polar co-ordinates (radius r as function of angle φ). Special options: key, nticks, line_width, line_type, color

 #1 #2 #3 #4 polar #1 #2 #3 #4 polar :

[Maxima Draw2D] polygon(matrix) Polygon durch die als n x 2 Matrix gegebenen Punkte. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type color

[Maxima Draw2D] polygon(matrix) polygon defined by matrix (each row one point). Special options: transparent, fill_color, border, line_width, key, line_type color

#1 polygon #1 polygon :

[Maxima Draw2D] polygon(vx,vy) Zeichnet ein Polygon durch die als x- und y-Vektoren gegebenen Punkte. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type color

[Maxima Draw2D] polygon(vx,vy) polygon defined by two vectors. Special options: transparent, fill_color, border, line_width, key, line_type color

#1 #2 polygon #1 #2 polygon :

[Maxima Draw2D/3D] quadrilateral(l1,l2,l3,l4) Viereck, gegeben durch Listen der Eckkoordinaten 2D: (x,y) oder 3D: (x,y,z). Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color, enhanced3D (nur 3D)

[Maxima Draw2D/3D] quadrilateral(l1,l2,l3,l4) quadrilateral given by lists of vertex coordinates: [x,y] in 2D or [x,y,z] in 3D. Special options: transparent, fill_color, border, line_width, key, line_type, color, enhanced3D (3D only)

 #1 #2 #3 #4 quadrilateral #1 #2 #3 #4 quadrilateral :

[Maxima Draw2D] rectangle(l1,l2) Rechteck gegeben durch Koordinatenlisten (x,y) gegenüberliegender Ecken. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color

[Maxima Draw2D] rectangle(l1,l2) specified by lists (x,y) of opposite corners. Special options: transparent, fill_color, border, line_width, key, line_type, color

#1 #2 rectangle #1 #2 rectangle :

[Maxima Draw2D] region(expr,x,xmin,xmax,y,ymin,ymax) Füllt das Gebiet wo expr wahr (true) ist im Bereich von xmin, xmax, ymin, ymax. Optionen: fill_color, key, x_voxel, y_voxel

[Maxima Draw2D] region(expr,x,xmin,xmax,y,ymin,ymax) Fills the region where expr is true in the domain given by xmin, xmax, ymin, ymax. Options: fill_color, key, x_voxel, y_voxel

 #1 #2 #3 #4 #5 #6 #7 region #1 #2 #3 #4 #5 #6 #7 region :

spherical() funktioniert nicht

[Maxima Draw2D/3D] triangle(l1,l2,l3) Dreieck, gegeben durch Koordinatenlisten (x,y) (2D) oder (x,y,z) (3D) der Ecken. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color

[Maxima Draw2D/3D] triangle(l1,l2,l3) given by co-ordinate lists (x,y) (2D) or (x,y,z) (3D) of the corners Special options: transparent, fill_color, border, line_width, key, line_type, color

#1 #2 #3 triangle #1 #2 #3 triangle :

[Maxima Draw3D] tube(fx,fy,fz,fr,p,pmin,pmax) Röhre, gegeben durch Mittellinie mit fx,fy,fz und den Radius fr als Funktionen des Parameters p. Spezielle Optionen: xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, color,tube_extremes.

[Maxima Draw3D] tube(fx,fy,fz,fr,p,pmin,pmax) tube, given by functions fx,fy,fz of the centerline and radius function fr pf parameters p. Special options: xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, color,tube_extremes.

 #1 #2 #3 #4 #5 #6 #7 tube #1 #2 #3 #4 #5 #6 #7 tube :

[Maxima Draw2D/3D] vector(l1,l2) Pfeil, gegeben durch Koordinatenlisten (x,y) (2D) oder (x,y,z) (3D) der Endpunkte. Spezielle Optionen: head_both, head_length, head_angle, head_type, line_width, line_type, key color.

[Maxima Draw2D/3D] vector(l1,l2) given by co-ordinate lists (x,y) (2D) or (x,y,z) (3D) of the end points. Spezielle Optionen: head_both, head_length, head_angle, head_type, line_width, line_type, key color.

 #1 #2 vector #1 #2 vector :

[Maxima] set(e1, e2,...) Maxima set (Liste in geschweiften Klammern)

[Maxima] set(e1, e2,...) Maxima set (in Maxima this is a list in curly braces)

 _ set _ set :

[Maxima] args(expr) Liste der Argumente von expr

[Maxima] args(expr) list of the top level arguments of expr

 _ args _ args :

Sonstige

[Maxima]

true true :

[Maxima]

false false : 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