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# projections

## `matplotlib.projections`

class `matplotlib.projections.``ProjectionRegistry`

  Bases: `object`

  Manages the set of projections available to the system.

  `get_projection_class`(name)

    Get a projection class from its name.

  `get_projection_names`()

    Get a list of the names of all projections currently registered.

  `register`(*projections)

    Register a new set of projection(s).

`matplotlib.projections.``get_projection_class`(projection=None)

  Get a projection class from its name.

  If projection is None, a standard rectilinear projection is returned.

`matplotlib.projections.``get_projection_names`()

  Get a list of acceptable projection names.

`matplotlib.projections.``process_projection_requirements`(figure, *args, **kwargs)

  Handle the args/kwargs to for add_axes/add_subplot/gca, returning:

      (axes_proj_class, proj_class_kwargs, proj_stack_key)

  Which can be used for new axes initialization/identification.

  Note

  kwargs is modified in place.

## `matplotlib.projections.polar`

class `matplotlib.projections.polar.``InvertedPolarTransform`(axis=None, use_rmin=True)

  Bases: `matplotlib.transforms.Transform`

  The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.

  `inverted`()

    Return the corresponding inverse transformation.

    The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

    `x === self.inverted().transform(self.transform(x))`

  `transform_non_affine`(xy)

    Performs only the non-affine part of the transformation.

    `transform(values)` is always equivalent to `transform_affine(transform_non_affine(values))`.

    In non-affine transformations, this is generally equivalent to `transform(values)`. In affine transformations, this is always a no-op.

    Accepts a numpy array of shape (N x `input_dims`) and returns a numpy array of shape (N x `output_dims`).

    Alternatively, accepts a numpy array of length `input_dims` and returns a numpy array of length `output_dims`.

class `matplotlib.projections.polar.``PolarAffine`(scale_transform, limits)

  Bases: `matplotlib.transforms.Affine2DBase`

  The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle.

  limits is the view limit of the data. The only part of its bounds that is used is ymax (for the radius maximum). The theta range is always fixed to (0, 2pi).

  `get_matrix`()

    Get the Affine transformation array for the affine part of this transform.

class `matplotlib.projections.polar.``PolarAxes`(*args, **kwargs)

  Bases: `matplotlib.axes._axes.Axes`

  A polar graph projection, where the input dimensions are theta, r.

  Theta starts pointing east and goes anti-clockwise.

  class `InvertedPolarTransform`(axis=None, use_rmin=True)

    Bases: `matplotlib.transforms.Transform`

    The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.

    `inverted`()

      Return the corresponding inverse transformation.

      The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

      `x === self.inverted().transform(self.transform(x))`

    `transform_non_affine`(xy)

      Performs only the non-affine part of the transformation.

      `transform(values)` is always equivalent to `transform_affine(transform_non_affine(values))`.

      In non-affine transformations, this is generally equivalent to `transform(values)`. In affine transformations, this is always a no-op.

      Accepts a numpy array of shape (N x `input_dims`) and returns a numpy array of shape (N x `output_dims`).

      Alternatively, accepts a numpy array of length `input_dims` and returns a numpy array of length `output_dims`.

  class `PolarAffine`(scale_transform, limits)

    Bases: `matplotlib.transforms.Affine2DBase`

    The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle.

    limits is the view limit of the data. The only part of its bounds that is used is ymax (for the radius maximum). The theta range is always fixed to (0, 2pi).

    `get_matrix`()

      Get the Affine transformation array for the affine part of this transform.

  class `PolarTransform`(axis=None, use_rmin=True)

    Bases: `matplotlib.transforms.Transform`

    The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position.

    `inverted`()

      Return the corresponding inverse transformation.

      The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

      `x === self.inverted().transform(self.transform(x))`

    `transform_non_affine`(tr)

      Performs only the non-affine part of the transformation.

      `transform(values)` is always equivalent to `transform_affine(transform_non_affine(values))`.

      In non-affine transformations, this is generally equivalent to `transform(values)`. In affine transformations, this is always a no-op.

      Accepts a numpy array of shape (N x `input_dims`) and returns a numpy array of shape (N x `output_dims`).

      Alternatively, accepts a numpy array of length `input_dims` and returns a numpy array of length `output_dims`.

    `transform_path_non_affine`(path)

      Returns a path, transformed only by the non-affine part of this transform.

      path: a `Path` instance.

      `transform_path(path)` is equivalent to `transform_path_affine(transform_path_non_affine(values))`.

  class `RadialLocator`(base)

    Bases: `matplotlib.ticker.Locator`

    Used to locate radius ticks.

    Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base `Locator` (which may be different depending on the scale of the r-axis.

  class `ThetaFormatter`

    Bases: `matplotlib.ticker.Formatter`

    Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.

  `can_pan`()

    Return True if this axes supports the pan/zoom button functionality.

    For polar axes, this is slightly misleading. Both panning and zooming are performed by the same button. Panning is performed in azimuth while zooming is done along the radial.

  `can_zoom`()

    Return True if this axes supports the zoom box button functionality.

    Polar axes do not support zoom boxes.

  `format_coord`(theta, r)

    Return a format string formatting the coordinate using Unicode characters.

  `get_data_ratio`()

    Return the aspect ratio of the data itself. For a polar plot, this should always be 1.0

  `get_rlabel_position`()

    Returns: | float The theta position of the radius labels in degrees.

  `get_theta_direction`()

    Get the direction in which theta increases.

    -1:
      Theta increases in the clockwise direction
    1:
      Theta increases in the counterclockwise direction
  `get_theta_offset`()

    Get the offset for the location of 0 in radians.

  `set_rgrids`(radii, labels=None, angle=None, fmt=None, **kwargs)

    Set the radial locations and labels of the r grids.

    The labels will appear at radial distances radii at the given angle in degrees.

    labels, if not None, is a `len(radii)` list of strings of the labels to use at each radius.

    If labels is None, the built-in formatter will be used.

    Return value is a list of tuples (line, label), where line is `Line2D` instances and the label is `Text` instances.

    kwargs are optional text properties for the labels:

    > Property | Description
    > --- | ---
    > `agg_filter` | unknown
    > `alpha` | float (0.0 transparent through 1.0 opaque)
    > `animated` | [True | False]
    > `axes` | an `Axes` instance
    > `backgroundcolor` | any matplotlib color
    > `bbox` | FancyBboxPatch prop dict
    > `clip_box` | a `matplotlib.transforms.Bbox` instance
    > `clip_on` | [True | False]
    > `clip_path` | [ (`Path`, `Transform`) | `Patch` | None ]
    > `color` | any matplotlib color
    > `contains` | a callable function
    > `family` or fontfamily or fontname or name | [FONTNAME | ‘serif’ | ‘sans-serif’ | ‘cursive’ | ‘fantasy’ | ‘monospace’ ]
    > `figure` | a `matplotlib.figure.Figure` instance
    > `fontproperties` or font_properties | a `matplotlib.font_manager.FontProperties` instance
    > `gid` | an id string
    > `horizontalalignment` or ha | [ ‘center’ | ‘right’ | ‘left’ ]
    > `label` | string or anything printable with ‘%s’ conversion.
    > `linespacing` | float (multiple of font size)
    > `multialignment` | [‘left’ | ‘right’ | ‘center’ ]
    > `path_effects` | unknown
    > `picker` | [None|float|boolean|callable]
    > `position` | (x,y)
    > `rasterized` | [True | False | None]
    > `rotation` | [ angle in degrees | ‘vertical’ | ‘horizontal’ ]
    > `rotation_mode` | unknown
    > `size` or fontsize | [size in points | ‘xx-small’ | ‘x-small’ | ‘small’ | ‘medium’ | ‘large’ | ‘x-large’ | ‘xx-large’ ]
    > `sketch_params` | unknown
    > `snap` | unknown
    > `stretch` or fontstretch | [a numeric value in range 0-1000 | ‘ultra-condensed’ | ‘extra-condensed’ | ‘condensed’ | ‘semi-condensed’ | ‘normal’ | ‘semi-expanded’ | ‘expanded’ | ‘extra-expanded’ | ‘ultra-expanded’ ]
    > `style` or fontstyle | [ ‘normal’ | ‘italic’ | ‘oblique’]
    > `text` | string or anything printable with ‘%s’ conversion.
    > `transform` | `Transform` instance
    > `url` | a url string
    > `usetex` | unknown
    > `variant` or fontvariant | [ ‘normal’ | ‘small-caps’ ]
    > `verticalalignment` or ma or va | [ ‘center’ | ‘top’ | ‘bottom’ | ‘baseline’ ]
    > `visible` | [True | False]
    > `weight` or fontweight | [a numeric value in range 0-1000 | ‘ultralight’ | ‘light’ | ‘normal’ | ‘regular’ | ‘book’ | ‘medium’ | ‘roman’ | ‘semibold’ | ‘demibold’ | ‘demi’ | ‘bold’ | ‘heavy’ | ‘extra bold’ | ‘black’ ]
    > `wrap` | unknown
    > `x` | float
    > `y` | float
    > `zorder` | any number

    ACCEPTS: sequence of floats

  `set_rlabel_position`(value)

    Updates the theta position of the radius labels.

    Parameters: | value : number The angular position of the radius labels in degrees.

  `set_theta_direction`(direction)

    Set the direction in which theta increases.

    clockwise, -1:
      Theta increases in the clockwise direction
    counterclockwise, anticlockwise, 1:
      Theta increases in the counterclockwise direction
  `set_theta_offset`(offset)

    Set the offset for the location of 0 in radians.

  `set_theta_zero_location`(loc)

    Sets the location of theta’s zero. (Calls set_theta_offset with the correct value in radians under the hood.)

    May be one of “N”, “NW”, “W”, “SW”, “S”, “SE”, “E”, or “NE”.

  `set_thetagrids`(angles, labels=None, frac=None, fmt=None, **kwargs)

    Set the angles at which to place the theta grids (these gridlines are equal along the theta dimension). angles is in degrees.

    labels, if not None, is a `len(angles)` list of strings of the labels to use at each angle.

    If labels is None, the labels will be `fmt % angle`

    frac is the fraction of the polar axes radius at which to place the label (1 is the edge). e.g., 1.05 is outside the axes and 0.95 is inside the axes.

    Return value is a list of tuples (line, label), where line is `Line2D` instances and the label is `Text` instances.

    kwargs are optional text properties for the labels:

    > Property | Description
    > --- | ---
    > `agg_filter` | unknown
    > `alpha` | float (0.0 transparent through 1.0 opaque)
    > `animated` | [True | False]
    > `axes` | an `Axes` instance
    > `backgroundcolor` | any matplotlib color
    > `bbox` | FancyBboxPatch prop dict
    > `clip_box` | a `matplotlib.transforms.Bbox` instance
    > `clip_on` | [True | False]
    > `clip_path` | [ (`Path`, `Transform`) | `Patch` | None ]
    > `color` | any matplotlib color
    > `contains` | a callable function
    > `family` or fontfamily or fontname or name | [FONTNAME | ‘serif’ | ‘sans-serif’ | ‘cursive’ | ‘fantasy’ | ‘monospace’ ]
    > `figure` | a `matplotlib.figure.Figure` instance
    > `fontproperties` or font_properties | a `matplotlib.font_manager.FontProperties` instance
    > `gid` | an id string
    > `horizontalalignment` or ha | [ ‘center’ | ‘right’ | ‘left’ ]
    > `label` | string or anything printable with ‘%s’ conversion.
    > `linespacing` | float (multiple of font size)
    > `multialignment` | [‘left’ | ‘right’ | ‘center’ ]
    > `path_effects` | unknown
    > `picker` | [None|float|boolean|callable]
    > `position` | (x,y)
    > `rasterized` | [True | False | None]
    > `rotation` | [ angle in degrees | ‘vertical’ | ‘horizontal’ ]
    > `rotation_mode` | unknown
    > `size` or fontsize | [size in points | ‘xx-small’ | ‘x-small’ | ‘small’ | ‘medium’ | ‘large’ | ‘x-large’ | ‘xx-large’ ]
    > `sketch_params` | unknown
    > `snap` | unknown
    > `stretch` or fontstretch | [a numeric value in range 0-1000 | ‘ultra-condensed’ | ‘extra-condensed’ | ‘condensed’ | ‘semi-condensed’ | ‘normal’ | ‘semi-expanded’ | ‘expanded’ | ‘extra-expanded’ | ‘ultra-expanded’ ]
    > `style` or fontstyle | [ ‘normal’ | ‘italic’ | ‘oblique’]
    > `text` | string or anything printable with ‘%s’ conversion.
    > `transform` | `Transform` instance
    > `url` | a url string
    > `usetex` | unknown
    > `variant` or fontvariant | [ ‘normal’ | ‘small-caps’ ]
    > `verticalalignment` or ma or va | [ ‘center’ | ‘top’ | ‘bottom’ | ‘baseline’ ]
    > `visible` | [True | False]
    > `weight` or fontweight | [a numeric value in range 0-1000 | ‘ultralight’ | ‘light’ | ‘normal’ | ‘regular’ | ‘book’ | ‘medium’ | ‘roman’ | ‘semibold’ | ‘demibold’ | ‘demi’ | ‘bold’ | ‘heavy’ | ‘extra bold’ | ‘black’ ]
    > `wrap` | unknown
    > `x` | float
    > `y` | float
    > `zorder` | any number

    ACCEPTS: sequence of floats

class `matplotlib.projections.polar.``PolarTransform`(axis=None, use_rmin=True)

  Bases: `matplotlib.transforms.Transform`

  The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position.

  `inverted`()

    Return the corresponding inverse transformation.

    The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

    `x === self.inverted().transform(self.transform(x))`

  `transform_non_affine`(tr)

    Performs only the non-affine part of the transformation.

    `transform(values)` is always equivalent to `transform_affine(transform_non_affine(values))`.

    In non-affine transformations, this is generally equivalent to `transform(values)`. In affine transformations, this is always a no-op.

    Accepts a numpy array of shape (N x `input_dims`) and returns a numpy array of shape (N x `output_dims`).

    Alternatively, accepts a numpy array of length `input_dims` and returns a numpy array of length `output_dims`.

  `transform_path_non_affine`(path)

    Returns a path, transformed only by the non-affine part of this transform.

    path: a `Path` instance.

    `transform_path(path)` is equivalent to `transform_path_affine(transform_path_non_affine(values))`.

class `matplotlib.projections.polar.``RadialLocator`(base)

  Bases: `matplotlib.ticker.Locator`

  Used to locate radius ticks.

  Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base `Locator` (which may be different depending on the scale of the r-axis.

class `matplotlib.projections.polar.``ThetaFormatter`

  Bases: `matplotlib.ticker.Formatter`

  Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.