plotters module of the psy-transect psyplot plugin

Formatoption classes:

`AlternativeTransectXCoord`(key[, plotter, ...])	Specify what to use for the x-axis
`Transect`(key[, plotter, index_in_list, ...])	Transect within a 2D plot
`TransectMethod`(key[, plotter, ...])	Specify the method how to select the transect.
`TransectResolution`(key[, plotter, ...])	Expand the transect to a minimum resolution.
`VTransform`(key[, plotter, index_in_list, ...])	Specify the coordinate system of the data
`VerticalTransectTranspose`(args, *kwargs)

Plotter classes:

`VerticalMapTransectPlotter`(args, *kwargs)
`VerticalTransectPlotter`(args, *kwargs)

class psy_transect.plotters.AlternativeTransectXCoord(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)

Bases: Formatoption

Specify what to use for the x-axis

Possible types

'index': Will use the index of the cell along the transect
'distance': Will use the euclidean distance of the start of the transect
'haversine': Will use the haversine distance in kilometers of the start of the transect. This can only be used if the x- and y-coordinates have units in 'degrees_east' and 'degrees_north', or 'radian' respectively.
'x': Will use the x-coordinate of the initial array
'y': Will use the y-coordinate of the initial array

Attributes:

`dependencies`	list of str.
`name`	`str`.
`priority`	`int`.
`transect`	transect Formatoption instance in the plotter

Methods:

update(value)

Method that is call to update the formatoption on the axes

dependencies = ['transect']: list of str. List of formatoptions that force an update of this formatoption if they are updated.

name = 'Select the x-coordinate': str. A bit more verbose name than the formatoption key to be included in the gui. If None, the key is used in the gui

priority = 30

int. Priority value of the the formatoption determining when the formatoption is updated.

10: at the end (for labels, etc.)
20: before the plotting (e.g. for colormaps, etc.)
30: before loading the data (e.g. for lonlatbox)

property transect: transect Formatoption instance in the plotter

update(value)

Method that is call to update the formatoption on the axes

Parameters:: value – Value to update

class psy_transect.plotters.Transect(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)

Bases: Formatoption

Transect within a 2D plot

This formatoption takes a list of x-y tuples, the so-called transect, and extracts the raw data along this path.

Possible types

list of x-y tuples: The point coordinates of the transect.
None: Uses up to the first 100 cells

Attributes:

`data_dependent`	`bool` or a callable.
`dependencies`	list of str.
`name`	`str`.
`priority`	`int`.
`transect_method`	transect_method Formatoption instance in the plotter
`transect_resolution`	transect_resolution Formatoption instance in the plotter

Methods:

`diff`(value)	Checks whether the given value differs from what is currently set
`update`(value)	Method that is call to update the formatoption on the axes

data_dependent = True: bool or a callable. This attribute indicates whether this Formatoption depends on the data and should be updated if the data changes. If it is a callable, it must accept one argument: the new data. (Note: This is automatically set to True for plot formatoptions)

dependencies = ['transect_method', 'transect_resolution']: list of str. List of formatoptions that force an update of this formatoption if they are updated.

diff(value)

Checks whether the given value differs from what is currently set

Parameters:: value – A possible value to set (make sure that it has been validate via the validate attribute before)
Returns:: True if the value differs from what is currently set
Return type:: bool

name = 'Transect within the raw data': str. A bit more verbose name than the formatoption key to be included in the gui. If None, the key is used in the gui

priority = 30

int. Priority value of the the formatoption determining when the formatoption is updated.

10: at the end (for labels, etc.)
20: before the plotting (e.g. for colormaps, etc.)
30: before loading the data (e.g. for lonlatbox)

property transect_method: transect_method Formatoption instance in the plotter

property transect_resolution: transect_resolution Formatoption instance in the plotter

update(value)

Method that is call to update the formatoption on the axes

Parameters:: value – Value to update

class psy_transect.plotters.TransectMethod(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)

Bases: Formatoption

Specify the method how to select the transect.

This formatoption specifies how the transect is selected.

Possible types

‘nearest’: Take the nearest grid point along the transect. This will not interpolate and return a unique list of grid points from the raw data.
‘nearest_exact’: Take the nearest grid point, one point from the raw data per point in the transect
‘inverse_distance_weighting’: Interpolation of the value at the requested position by inverse distance weighting method. See pyinterp.RTree.inverse_distance_weighting()
str: Any other method suitable for the rbf parameter of the pyinterp.RTree.radial_basis_function() method

Attributes:

`name`	`str`.
`priority`	`int`.

Methods:

update(value)

Method that is call to update the formatoption on the axes

name = 'Method for getting the data along the transect': str. A bit more verbose name than the formatoption key to be included in the gui. If None, the key is used in the gui

priority = 30

int. Priority value of the the formatoption determining when the formatoption is updated.

10: at the end (for labels, etc.)
20: before the plotting (e.g. for colormaps, etc.)
30: before loading the data (e.g. for lonlatbox)

update(value)

Method that is call to update the formatoption on the axes

Parameters:: value – Value to update

class psy_transect.plotters.TransectResolution(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)

Bases: Formatoption

Expand the transect to a minimum resolution.

This formatoption expands the segments of the transect to fullfil a minimum resolution. Everything but False will expand the segments of the transect to fullfil the minimum resolution.

This formatoption is of particular importance if you want to use the vertical transect plotter in combination with a map.

Possible types

False: Do not make any changes to the provided transect but take it as it is
True or 'auto': The default value estimates the resolution of the underlying spatial data and estimates it’s minimum resolution. This won’t not work for unstructured data!
float: Specify the spatial resolution directly

Attributes:

`estimated_resolution`	Estimate the resolution of the input data.
`name`	`str`.

Methods:

`expand_path`(path)	Expand the path segments to match the datas resolution.
`expand_path_to_resolution`(path, resolution)	Expand a given set of points to match the given resolution.
`update`(value)	Method that is call to update the formatoption on the axes

property estimated_resolution: float | None: Estimate the resolution of the input data.

expand_path(path: ndarray) → ndarray

Expand the path segments to match the datas resolution.

Parameters:: path (np.ndarray of shape (N, 2)) – The x-y-coordinates of the path segments
Returns:: An array with M>=N where each segment in the path is smaller. than the minimum resolution.
Return type:: np.ndarray of shape (M, 2)

static expand_path_to_resolution(path: ndarray, resolution: float) → ndarray

Expand a given set of points to match the given resolution.

Parameters:

path (np.ndarray of shape (N, 2)) – The x-y-coordinates of the path segments
resolution (float) – The minimum resolution that shall be used to expand the path

Returns:

An array with M>=N where each segment in the path is smaller. than the minimum resolution.

Return type:

np.ndarray of shape (M, 2)

name = 'Minimum resolution of the transect': str. A bit more verbose name than the formatoption key to be included in the gui. If None, the key is used in the gui

update(value)

Method that is call to update the formatoption on the axes

Parameters:: value – Value to update

class psy_transect.plotters.VTransform(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)

Bases: Transform

Specify the coordinate system of the data

This formatoption defines the coordinate system of the data (usually we expect a simple latitude longitude coordinate system)

Possible types

cartopy.crs.CRS

A cartopy projection instance (e.g. cartopy.crs.PlateCarree)

str

A string specifies the projection instance to use. The centered longitude and latitude are determined by the clon and clat formatoptions. Possible strings are (each standing for the specified projection)

cf	try to decode the CF-conventions
cyl	`cartopy.crs.PlateCarree`
robin	`cartopy.crs.Robinson`
moll	`cartopy.crs.Mollweide`
geo	`cartopy.crs.Geostationary`
northpole	`cartopy.crs.NorthPolarStereo`
southpole	`cartopy.crs.SouthPolarStereo`
ortho	`cartopy.crs.Orthographic`
stereo	`cartopy.crs.Stereographic`
near	`cartopy.crs.NearsidePerspective`
rotated	`cartopy.crs.RotatedPole`

The special case 'cf' tries to decode the CF-conventions in the data. If this is not possible, we assume a standard lat-lon projection ('cyl')

See also

Grid-mappings of cf-conventions

Attributes:

connections

list of str.

connections: List[str] = []: list of str. Connections to other formatoptions that are (different from dependencies and children) not important for the update process

class psy_transect.plotters.VerticalMapTransectPlotter(*args, **kwargs)

Bases: VerticalTransectPlotter

Axes formatoptions:

`axiscolor`	Color the x- and y-axes
`background`	The background color for the matplotlib axes.
`grid`	Display the grid
`tight`	Automatically adjust the plots.
`transpose`
`xlim`	Set the x-axis limits
`ylim`	Set the y-axis limits

Color coding formatoptions:

`bounds`	Specify the boundaries of the colorbar
`cbar`	Specify the position of the colorbars
`cbarspacing`	Specify the spacing of the bounds in the colorbar
`cmap`	Specify the color map
`ctickprops`	Specify the font properties of the colorbar ticklabels
`cticksize`	Specify the font size of the colorbar ticklabels
`ctickweight`	Specify the fontweight of the colorbar ticklabels
`extend`	Draw arrows at the side of the colorbar
`levels`	The levels for the contour plot
`miss_color`	Set the color for missing values

Label formatoptions:

`clabel`	Show the colorbar label
`clabelprops`	Properties of the Colorbar label
`clabelsize`	Set the size of the Colorbar label
`clabelweight`	Set the fontweight of the Colorbar label
`figtitle`	Plot a figure title
`figtitleprops`	Properties of the figure title
`figtitlesize`	Set the size of the figure title
`figtitleweight`	Set the fontweight of the figure title
`labelprops`	Set the font properties of both, x- and y-label
`labelsize`	Set the size of both, x- and y-label
`labelweight`	Set the font size of both, x- and y-label
`text`	Add text anywhere on the plot
`title`	Show the title
`titleprops`	Properties of the title
`titlesize`	Set the size of the title
`titleweight`	Set the fontweight of the title
`xlabel`	Set the x-axis label
`ylabel`	Set the y-axis label

Miscallaneous formatoptions:

`coord`	Specify what to use for the x-axis
`datagrid`	Show the grid of the data
`interp_bounds`	Interpolate grid cell boundaries for 2D plots
`mask_datagrid`	Mask the datagrid where the array is NaN
`sym_lims`	Make x- and y-axis symmetric
`ticksize`	Change the ticksize of the ticklabels
`tickweight`	Change the fontweight of the ticks
`transect`	Transect within a 2D plot
`transect_method`	Specify the method how to select the transect.
`transect_resolution`	Expand the transect to a minimum resolution.
`transform`	Specify the coordinate system of the data

Axis tick formatoptions:

`cticklabels`	Specify the colorbar ticklabels
`cticks`	Specify the tick locations of the colorbar
`xrotation`	Rotate the x-axis ticks
`xticklabels`	Modify the x-axis ticklabels
`xtickprops`	Specify the x-axis tick parameters
`xticks`	Modify the x-axis ticks
`yrotation`	Rotate the y-axis ticks
`yticklabels`	Modify the y-axis ticklabels
`ytickprops`	Specify the y-axis tick parameters
`yticks`	Modify the y-axis ticks

Masking formatoptions:

`mask`	Mask the data where a certain condition is True
`maskbetween`	Mask data points between two numbers
`maskgeq`	Mask data points greater than or equal to a number
`maskgreater`	Mask data points greater than a number
`maskleq`	Mask data points smaller than or equal to a number
`maskless`	Mask data points smaller than a number

Plot formatoptions:

plot

Specify the plotting method

Post processing formatoptions:

`post`	Apply your own postprocessing script
`post_timing`	Determine when to run the `post` formatoption

Attributes:

selectors

axiscolor

Color the x- and y-axes

This formatoption colors the left, right, bottom and top axis bar.

Possible types

dict: Keys may be one of {‘right’, ‘left’, ‘bottom’, ‘top’}, the values can be any valid color or None.

Notes

The following color abbreviations are supported:

character	color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

In addition, you can specify colors in many weird and wonderful ways, including full names ('green'), hex strings ('#008000'), RGB or RGBA tuples ((0,1,0,1)) or grayscale intensities as a string ('0.8').

background

The background color for the matplotlib axes.

Possible types

‘rc’: to use matplotlibs rc params
None: to use a transparent color
color: Any possible matplotlib color

bounds

Specify the boundaries of the colorbar

Possible types

None

make no normalization

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten

int

Specifies how many ticks to use with the 'rounded' option. I.e. if integer i, then this is the same as ['rounded', i].

matplotlib.colors.Normalize

A matplotlib normalization instance

Examples

Plot 11 bounds over the whole data range:

>>> plotter.update(bounds='rounded')

which is equivalent to:

>>> plotter.update(bounds={'method': 'rounded'})

Plot 7 ticks over the whole data range where the maximal and minimal tick matches the data maximum and minimum:
```
>>> plotter.update(bounds=['minmax', 7])
```
which is equivaluent to:
```
>>> plotter.update(bounds={'method': 'minmax', 'N': 7})
```

chop the first and last five percentiles:

>>> plotter.update(bounds=['rounded', None, 5, 95])

which is equivalent to:

>>> plotter.update(bounds={'method': 'rounded', 'percmin': 5,
...                        'percmax': 95})

Plot 3 bounds per power of ten:
```
>>> plotter.update(bounds=['log', 3])
```

Plot continuous logarithmic bounds:

>>> from matplotlib.colors import LogNorm
>>> plotter.update(bounds=LogNorm())

See also

cmap: Specifies the colormap

cbar

Specify the position of the colorbars

Possible types

bool

True: defaults to ‘b’ False: Don’t draw any colorbar

str

The string can be a combination of one of the following strings: {‘fr’, ‘fb’, ‘fl’, ‘ft’, ‘b’, ‘r’, ‘sv’, ‘sh’}

‘b’, ‘r’ stand for bottom and right of the axes
‘fr’, ‘fb’, ‘fl’, ‘ft’ stand for bottom, right, left and top of the figure
‘sv’ and ‘sh’ stand for a vertical or horizontal colorbar in a separate figure

list

A containing one of the above positions

Examples

Draw a colorbar at the bottom and left of the axes:

>>> plotter.update(cbar='bl')

cbarspacing

Specify the spacing of the bounds in the colorbar

Possible types

str {‘uniform’, ‘proportional’}: if 'uniform', every color has exactly the same width in the colorbar, if 'proportional', the size is chosen according to the data

clabel

Show the colorbar label

Set the label of the colorbar. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the set_label() method.

clabelprops

Properties of the Colorbar label

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

See also

clabel, clabelsize, clabelweight

clabelsize

Set the size of the Colorbar label

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

clabel, clabelweight, clabelprops

clabelweight

Set the fontweight of the Colorbar label

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

clabel, clabelsize, clabelprops

cmap

Specify the color map

This formatoption specifies the color coding of the data via a matplotlib.colors.Colormap

Possible types

str

Strings may be any valid colormap name suitable for the matplotlib.cm.get_cmap() function or one of the color lists defined in the ‘colors.cmaps’ key of the psyplot.rcParams dictionary (including their reversed color maps given via the ‘_r’ extension).

matplotlib.colors.Colormap: The colormap instance to use

See also

bounds: specifies the boundaries of the colormap

coord

Specify what to use for the x-axis

Possible types

'index': Will use the index of the cell along the transect
'distance': Will use the euclidean distance of the start of the transect
'haversine': Will use the haversine distance in kilometers of the start of the transect. This can only be used if the x- and y-coordinates have units in 'degrees_east' and 'degrees_north', or 'radian' respectively.
'x': Will use the x-coordinate of the initial array
'y': Will use the y-coordinate of the initial array

cticklabels

Specify the colorbar ticklabels

Possible types

str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

See also

cticks, cticksize, ctickweight, ctickprops, vcticks, vcticksize, vctickweight, vctickprops

ctickprops

Specify the font properties of the colorbar ticklabels

Possible types

dict: Items may be anything of the matplotlib.pyplot.tick_params() function

See also

cticksize, ctickweight, cticklabels, cticks, vcticksize, vctickweight, vcticklabels, vcticks

cticks

Specify the tick locations of the colorbar

Possible types

None

use the default ticks

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
bounds: let the bounds keyword determine the ticks. An additional integer i may be specified to only use every i-th bound as a tick (see also int below)
midbounds: Same as bounds but in the middle between two bounds

int

Specifies how many ticks to use with the 'bounds' option. I.e. if integer i, then this is the same as ['bounds', i].

See also

cticklabels

cticksize

Specify the font size of the colorbar ticklabels

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

ctickweight, ctickprops, cticklabels, cticks, vctickweight, vctickprops, vcticklabels, vcticks

ctickweight

Specify the fontweight of the colorbar ticklabels

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

cticksize, ctickprops, cticklabels, cticks, vcticksize, vctickprops, vcticklabels, vcticks

datagrid

Show the grid of the data

This formatoption shows the grid of the data (without labels)

Possible types

None: Don’t show the data grid
str: A linestyle in the form 'k-', where 'k' is the color and '-' the linestyle.
dict: any keyword arguments that are passed to the plotting function ( matplotlib.pyplot.triplot() for unstructured grids and matplotlib.pyplot.hlines() for rectilinear grids)

See also

mask_datagrid: To display cells with NaN

extend

Draw arrows at the side of the colorbar

Possible types

str {‘neither’, ‘both’, ‘min’ or ‘max’}: If not ‘neither’, make pointed end(s) for out-of-range values

figtitle

Plot a figure title

Set the title of the figure. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the suptitle() function

Notes

If the plotter is part of a psyplot.project.Project and multiple plotters of this project are on the same figure, the replacement attributes (see above) are joined by a delimiter. If the delimiter attribute of this Figtitle instance is not None, it will be used. Otherwise the rcParams[‘texts.delimiter’] item is used.
This is the title of the whole figure! For the title of this specific subplot, see the title formatoption.

figtitleprops

Properties of the figure title

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

figtitlesize

Set the size of the figure title

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

figtitleweight

Set the fontweight of the figure title

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

grid

Display the grid

Show the grid on the plot with the specified color.

Possible types

None: If the grid is currently shown, it will not be displayed any longer. If the grid is not shown, it will be drawn
bool: If True, the grid is displayed with the automatic settings (usually black)
string, tuple.: Defines the color of the grid.

Notes

The following color abbreviations are supported:

character	color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

In addition, you can specify colors in many weird and wonderful ways, including full names ('green'), hex strings ('#008000'), RGB or RGBA tuples ((0,1,0,1)) or grayscale intensities as a string ('0.8').

interp_bounds

Interpolate grid cell boundaries for 2D plots

This formatoption can be used to tell enable and disable the interpolation of grid cell boundaries. Usually, netCDF files only contain the centered coordinates. In this case, we interpolate the boundaries between the grid cell centers.

Possible types

None: Interpolate the boundaries, except for circumpolar grids
bool: If True (the default), the grid cell boundaries are inter- and extrapolated. Otherwise, if False, the coordinate centers are used and the default behaviour of matplotlib cuts of the most outer row and column of the 2D-data. Note that this results in a slight shift of the data

labelprops

Set the font properties of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
dict: Items may be any valid text property

labelsize

Set the size of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

labelweight

Set the font size of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

levels

The levels for the contour plot

This formatoption sets the levels for the filled contour plot and only has an effect if the plot Formatoption is set to 'contourf'

Possible types

None

Use the settings from the bounds formatoption and if this does not specify boundaries, use 11

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten

int

Specifies how many ticks to use with the 'rounded' option. I.e. if integer i, then this is the same as ['rounded', i].

mask

Mask the data where a certain condition is True

This formatoption can be used to mask the plotting data based on another array. This array can be the name of a variable in the base dataset, or it can be a numeric array. Note that the data needs to be on exactly the same coordinates as the data shown here

Possible types

None

Apply no mask

str

The name of a variable in the base dataset to use.

dimensions that are in the given mask but not in the visualized base variable will be aggregated using numpy.any()
if the given mask misses dimensions that are in the visualized data (i.e. the data of this plotter), we broadcast the mask to match the shape of the data
dimensions that are in mask and the base variable, but not in the visualized data will be matched against each other

str

The path to a netCDF file that shall be loaded

xr.DataArray or np.ndarray

An array that can be broadcasted to the shape of the data

mask_datagrid

Mask the datagrid where the array is NaN

This boolean formatoption enables to mask the grid of the datagrid formatoption where the data is NaN

Possible types

bool: Either True, to not display the data grid for cells with NaN, or False

See also

datagrid

maskbetween

Mask data points between two numbers

Possible types

float: The floating number to mask above

maskgeq

Mask data points greater than or equal to a number

Possible types

float: The floating number to mask above

maskgreater

Mask data points greater than a number

Possible types

float: The floating number to mask above

maskleq

Mask data points smaller than or equal to a number

Possible types

float: The floating number to mask below

maskless

Mask data points smaller than a number

Possible types

float: The floating number to mask below

miss_color

Set the color for missing values

Possible types

None: Use the default from the colormap
string, tuple.: Defines the color of the grid.

plot

Specify the plotting method

Possible types

None: Don’t make any plotting
‘mesh’: Use the matplotlib.pyplot.pcolormesh() function to make the plot

post

Apply your own postprocessing script

This formatoption let’s you apply your own post processing script. Just enter the script as a string and it will be executed. The formatoption will be made available via the self variable

Possible types

None: Don’t do anything
str: The post processing script as string

Note

This formatoption uses the built-in exec() function to compile the script. Since this poses a security risk when loading psyplot projects, it is by default disabled through the Plotter.enable_post attribute. If you are sure that you can trust the script in this formatoption, set this attribute of the corresponding Plotter to True

Examples

Assume, you want to manually add the mean of the data to the title of the matplotlib axes. You can simply do this via

from psyplot.plotter import Plotter
from xarray import DataArray

plotter = Plotter(DataArray([1, 2, 3]))
# enable the post formatoption
plotter.enable_post = True
plotter.update(post="self.ax.set_title(str(self.data.mean()))")
plotter.ax.get_title()
"2.0"

By default, the post formatoption is only ran, when it is explicitly updated. However, you can use the post_timing formatoption, to run it automatically. E.g. for running it after every update of the plotter, you can set

plotter.update(post_timing="always")

See also

post_timing: Determine the timing of this formatoption

post_timing

Determine when to run the post formatoption

This formatoption determines, whether the post formatoption should be run never, after replot or after every update.

Possible types

‘never’: Never run post processing scripts
‘always’: Always run post processing scripts
‘replot’: Only run post processing scripts when the data changes or a replot is necessary

See also

post: The post processing formatoption

selectors: Dict[Axes, widgets.LassoSelector]

sym_lims

Make x- and y-axis symmetric

Possible types

None: No symmetric type
‘min’: Use the minimum of x- and y-limits
‘max’: Use the maximum of x- and y-limits
[str, str]: A combination, None, 'min' and 'max' specific for minimum and maximum limit

text

Add text anywhere on the plot

This formatoption draws a text on the specified position on the figure. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: If string s: this will be used as (1., 1., s, {‘ha’: ‘right’}) (i.e. a string in the upper right corner of the axes).
tuple or list of tuples (x,y,s[,coord.-system][,options]]): Each tuple defines a text instance on the plot. 0<=x, y<=1 are the coordinates. The coord.-system can be either the data coordinates (default, 'data') or the axes coordinates ('axes') or the figure coordinates (‘fig’). The string s finally is the text. options may be a dictionary to specify format the appearence (e.g. 'color', 'fontweight', 'fontsize', etc., see matplotlib.text.Text for possible keys). To remove one single text from the plot, set (x,y,’’[, coord.-system]) for the text at position (x,y)
empty list: remove all texts from the plot

See also

title, figtitle

ticksize

Change the ticksize of the ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

tickweight

Change the fontweight of the ticks

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

ticksize, xtickprops, ytickprops

tight

Automatically adjust the plots.

If set to True, the plots are automatically adjusted to fit to the figure limitations via the matplotlib.pyplot.tight_layout() function.

Possible types

bool: True for automatic adjustment

Warning

There is no update method to undo what happend after this formatoption is set to True!

title

Show the title

Set the title of the plot. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the title() function.

Notes

This is the title of this specific subplot! For the title of the whole figure, see the figtitle formatoption.

titleprops

Properties of the title

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

See also

title, titlesize, titleweight

titlesize

Set the size of the title

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

title, titleweight, titleprops

titleweight

Set the fontweight of the title

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

title, titlesize, titleprops

transect

Transect within a 2D plot

This formatoption takes a list of x-y tuples, the so-called transect, and extracts the raw data along this path.

Possible types

list of x-y tuples: The point coordinates of the transect.
None: Uses up to the first 100 cells

transect_method

Specify the method how to select the transect.

This formatoption specifies how the transect is selected.

Possible types

‘nearest’: Take the nearest grid point along the transect. This will not interpolate and return a unique list of grid points from the raw data.
‘nearest_exact’: Take the nearest grid point, one point from the raw data per point in the transect
‘inverse_distance_weighting’: Interpolation of the value at the requested position by inverse distance weighting method. See pyinterp.RTree.inverse_distance_weighting()
str: Any other method suitable for the rbf parameter of the pyinterp.RTree.radial_basis_function() method

transect_resolution

Expand the transect to a minimum resolution.

This formatoption expands the segments of the transect to fullfil a minimum resolution. Everything but False will expand the segments of the transect to fullfil the minimum resolution.

This formatoption is of particular importance if you want to use the vertical transect plotter in combination with a map.

Possible types

False: Do not make any changes to the provided transect but take it as it is
True or 'auto': The default value estimates the resolution of the underlying spatial data and estimates it’s minimum resolution. This won’t not work for unstructured data!
float: Specify the spatial resolution directly

transform

Specify the coordinate system of the data

This formatoption defines the coordinate system of the data (usually we expect a simple latitude longitude coordinate system)

Possible types

cartopy.crs.CRS

A cartopy projection instance (e.g. cartopy.crs.PlateCarree)

str

A string specifies the projection instance to use. The centered longitude and latitude are determined by the clon and clat formatoptions. Possible strings are (each standing for the specified projection)

cf	try to decode the CF-conventions
cyl	`cartopy.crs.PlateCarree`
robin	`cartopy.crs.Robinson`
moll	`cartopy.crs.Mollweide`
geo	`cartopy.crs.Geostationary`
northpole	`cartopy.crs.NorthPolarStereo`
southpole	`cartopy.crs.SouthPolarStereo`
ortho	`cartopy.crs.Orthographic`
stereo	`cartopy.crs.Stereographic`
near	`cartopy.crs.NearsidePerspective`
rotated	`cartopy.crs.RotatedPole`

The special case 'cf' tries to decode the CF-conventions in the data. If this is not possible, we assume a standard lat-lon projection ('cyl')

See also

Grid-mappings of cf-conventions

transpose

xlabel

Set the x-axis label

Set the label for the x-axis. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The text for the xlabel() function.

See also

xlabelsize, xlabelweight, xlabelprops

xlim

Set the x-axis limits

Possible types

None

To not change the current limits

str or list [str, str] or [[str, float], [str, float]]

Automatically determine the ticks corresponding to the data. The given string determines how the limits are calculated. The float determines the percentile to use A string can be one of the following:

rounded: Sets the minimum and maximum of the limits to the rounded data minimum or maximum. Limits are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimum will always be lower or equal than the data minimum, the maximum will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the limits are chosen such that they are symmetric around zero
minmax: Uses the minimum and maximum
sym: Same as minmax but symmetric around zero

tuple (xmin, xmax)

xmin is the smaller value, xmax the larger. Any of those values can be None or one of the strings (or lists) above to use the corresponding value here

See also

ylim

xrotation

Rotate the x-axis ticks

Possible types

float: The rotation angle in degrees

See also

yrotation

xticklabels

Modify the x-axis ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

xtickprops

Specify the x-axis tick parameters

This formatoption can be used to make a detailed change of the ticks parameters on the x-axis.

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
dict: Items may be anything of the matplotlib.pyplot.tick_params() function

xticks

Modify the x-axis ticks

Possible types

dict

A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.

None

use the default ticks

int

for an integer i, only every i-th tick of the default ticks are used

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
hour: draw ticks every hour
day: draw ticks every day
week: draw ticks every week
month, monthend, monthbegin: draw ticks in the middle, at the end or at the beginning of each month
year, yearend, yearbegin: draw ticks in the middle, at the end or at the beginning of each year

For data, mid, hour, day, week, month, etc., the optional second value can be an integer i determining that every i-th data point shall be used (by default, it is set to 1). For rounded, roundedsym, minmax and sym, the second value determines the total number of ticks (defaults to 11).

Examples

Plot 11 ticks over the whole data range:

>>> plotter.update(xticks='rounded')

Plot 7 ticks over the whole data range where the maximal and minimal tick matches the data maximum and minimum:

>>> plotter.update(xticks=['minmax', 7])

Plot ticks every year and minor ticks every month:

>>> plotter.update(xticks={'major': 'year', 'minor': 'month'})

ylabel

Set the y-axis label

Set the label for the y-axis. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The text for the ylabel() function.

See also

ylabelsize, ylabelweight, ylabelprops

ylim

Set the y-axis limits

Possible types

None

To not change the current limits

str or list [str, str] or [[str, float], [str, float]]

Automatically determine the ticks corresponding to the data. The given string determines how the limits are calculated. The float determines the percentile to use A string can be one of the following:

rounded: Sets the minimum and maximum of the limits to the rounded data minimum or maximum. Limits are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimum will always be lower or equal than the data minimum, the maximum will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the limits are chosen such that they are symmetric around zero
minmax: Uses the minimum and maximum
sym: Same as minmax but symmetric around zero

tuple (xmin, xmax)

xmin is the smaller value, xmax the larger. Any of those values can be None or one of the strings (or lists) above to use the corresponding value here

See also

xlim

yrotation

Rotate the y-axis ticks

Possible types

float: The rotation angle in degrees

See also

xrotation

yticklabels

Modify the y-axis ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

ytickprops

Specify the y-axis tick parameters

This formatoption can be used to make a detailed change of the ticks parameters of the y-axis.

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
dict: Items may be anything of the matplotlib.pyplot.tick_params() function

yticks

Modify the y-axis ticks

Possible types

dict

A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.

None

use the default ticks

int

for an integer i, only every i-th tick of the default ticks are used

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
hour: draw ticks every hour
day: draw ticks every day
week: draw ticks every week
month, monthend, monthbegin: draw ticks in the middle, at the end or at the beginning of each month
year, yearend, yearbegin: draw ticks in the middle, at the end or at the beginning of each year

For data, mid, hour, day, week, month, etc., the optional second value can be an integer i determining that every i-th data point shall be used (by default, it is set to 1). For rounded, roundedsym, minmax and sym, the second value determines the total number of ticks (defaults to 11).

xticks: for possible examples

class psy_transect.plotters.VerticalTransectPlotter(*args, **kwargs)

Bases: Simple2DPlotter

Attributes:

`allowed_dims`	The number of allowed dimensions in the for the visualization.
`selectors`

Axes formatoptions:

`axiscolor`	Color the x- and y-axes
`background`	The background color for the matplotlib axes.
`grid`	Display the grid
`tight`	Automatically adjust the plots.
`transpose`
`xlim`	Set the x-axis limits
`ylim`	Set the y-axis limits

Color coding formatoptions:

`bounds`	Specify the boundaries of the colorbar
`cbar`	Specify the position of the colorbars
`cbarspacing`	Specify the spacing of the bounds in the colorbar
`cmap`	Specify the color map
`ctickprops`	Specify the font properties of the colorbar ticklabels
`cticksize`	Specify the font size of the colorbar ticklabels
`ctickweight`	Specify the fontweight of the colorbar ticklabels
`extend`	Draw arrows at the side of the colorbar
`levels`	The levels for the contour plot
`miss_color`	Set the color for missing values

Label formatoptions:

`clabel`	Show the colorbar label
`clabelprops`	Properties of the Colorbar label
`clabelsize`	Set the size of the Colorbar label
`clabelweight`	Set the fontweight of the Colorbar label
`figtitle`	Plot a figure title
`figtitleprops`	Properties of the figure title
`figtitlesize`	Set the size of the figure title
`figtitleweight`	Set the fontweight of the figure title
`labelprops`	Set the font properties of both, x- and y-label
`labelsize`	Set the size of both, x- and y-label
`labelweight`	Set the font size of both, x- and y-label
`text`	Add text anywhere on the plot
`title`	Show the title
`titleprops`	Properties of the title
`titlesize`	Set the size of the title
`titleweight`	Set the fontweight of the title
`xlabel`	Set the x-axis label
`ylabel`	Set the y-axis label

Methods:

`connect_ax`(plotter_or_ax, **kwargs)	Connect to a matplotlib axes via lasso.
`disconnect_ax`(ax)	Disconnect this plotter from an axes and remove the selector.
`get_enhanced_attrs`(arr, args, *kwargs)

Miscallaneous formatoptions:

`coord`	Specify what to use for the x-axis
`datagrid`	Show the grid of the data
`interp_bounds`	Interpolate grid cell boundaries for 2D plots
`mask_datagrid`	Mask the datagrid where the array is NaN
`sym_lims`	Make x- and y-axis symmetric
`ticksize`	Change the ticksize of the ticklabels
`tickweight`	Change the fontweight of the ticks
`transect`	Transect within a 2D plot
`transect_method`	Specify the method how to select the transect.
`transect_resolution`	Expand the transect to a minimum resolution.

Axis tick formatoptions:

`cticklabels`	Specify the colorbar ticklabels
`cticks`	Specify the tick locations of the colorbar
`xrotation`	Rotate the x-axis ticks
`xticklabels`	Modify the x-axis ticklabels
`xtickprops`	Specify the x-axis tick parameters
`xticks`	Modify the x-axis ticks
`yrotation`	Rotate the y-axis ticks
`yticklabels`	Modify the y-axis ticklabels
`ytickprops`	Specify the y-axis tick parameters
`yticks`	Modify the y-axis ticks

Masking formatoptions:

`mask`	Mask the data where a certain condition is True
`maskbetween`	Mask data points between two numbers
`maskgeq`	Mask data points greater than or equal to a number
`maskgreater`	Mask data points greater than a number
`maskleq`	Mask data points smaller than or equal to a number
`maskless`	Mask data points smaller than a number

Plot formatoptions:

plot

Specify the plotting method

Post processing formatoptions:

`post`	Apply your own postprocessing script
`post_timing`	Determine when to run the `post` formatoption

allowed_dims = 3: The number of allowed dimensions in the for the visualization. If the array is unstructured, one dimension will be subtracted

axiscolor

Color the x- and y-axes

This formatoption colors the left, right, bottom and top axis bar.

Possible types

dict: Keys may be one of {‘right’, ‘left’, ‘bottom’, ‘top’}, the values can be any valid color or None.

Notes

The following color abbreviations are supported:

character	color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

In addition, you can specify colors in many weird and wonderful ways, including full names ('green'), hex strings ('#008000'), RGB or RGBA tuples ((0,1,0,1)) or grayscale intensities as a string ('0.8').

background

The background color for the matplotlib axes.

Possible types

‘rc’: to use matplotlibs rc params
None: to use a transparent color
color: Any possible matplotlib color

bounds

Specify the boundaries of the colorbar

Possible types

None

make no normalization

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten

int

Specifies how many ticks to use with the 'rounded' option. I.e. if integer i, then this is the same as ['rounded', i].

matplotlib.colors.Normalize

A matplotlib normalization instance

Examples

Plot 11 bounds over the whole data range:

>>> plotter.update(bounds='rounded')

which is equivalent to:

>>> plotter.update(bounds={'method': 'rounded'})

Plot 7 ticks over the whole data range where the maximal and minimal tick matches the data maximum and minimum:
```
>>> plotter.update(bounds=['minmax', 7])
```
which is equivaluent to:
```
>>> plotter.update(bounds={'method': 'minmax', 'N': 7})
```

chop the first and last five percentiles:

>>> plotter.update(bounds=['rounded', None, 5, 95])

which is equivalent to:

>>> plotter.update(bounds={'method': 'rounded', 'percmin': 5,
...                        'percmax': 95})

Plot 3 bounds per power of ten:
```
>>> plotter.update(bounds=['log', 3])
```

Plot continuous logarithmic bounds:

>>> from matplotlib.colors import LogNorm
>>> plotter.update(bounds=LogNorm())

See also

cmap: Specifies the colormap

cbar

Specify the position of the colorbars

Possible types

bool

True: defaults to ‘b’ False: Don’t draw any colorbar

str

The string can be a combination of one of the following strings: {‘fr’, ‘fb’, ‘fl’, ‘ft’, ‘b’, ‘r’, ‘sv’, ‘sh’}

‘b’, ‘r’ stand for bottom and right of the axes
‘fr’, ‘fb’, ‘fl’, ‘ft’ stand for bottom, right, left and top of the figure
‘sv’ and ‘sh’ stand for a vertical or horizontal colorbar in a separate figure

list

A containing one of the above positions

Examples

Draw a colorbar at the bottom and left of the axes:

>>> plotter.update(cbar='bl')

cbarspacing

Specify the spacing of the bounds in the colorbar

Possible types

str {‘uniform’, ‘proportional’}: if 'uniform', every color has exactly the same width in the colorbar, if 'proportional', the size is chosen according to the data

clabel

Show the colorbar label

Set the label of the colorbar. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the set_label() method.

clabelprops

Properties of the Colorbar label

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

See also

clabel, clabelsize, clabelweight

clabelsize

Set the size of the Colorbar label

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

clabel, clabelweight, clabelprops

clabelweight

Set the fontweight of the Colorbar label

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

clabel, clabelsize, clabelprops

cmap

Specify the color map

This formatoption specifies the color coding of the data via a matplotlib.colors.Colormap

Possible types

str

Strings may be any valid colormap name suitable for the matplotlib.cm.get_cmap() function or one of the color lists defined in the ‘colors.cmaps’ key of the psyplot.rcParams dictionary (including their reversed color maps given via the ‘_r’ extension).

matplotlib.colors.Colormap: The colormap instance to use

See also

bounds: specifies the boundaries of the colormap

connect_ax(plotter_or_ax: HorizontalTransectPlotterMixin | Axes, **kwargs)

Connect to a matplotlib axes via lasso.

This creates a lasso to be used

Parameters:: plotter_or_ax (VerticalTransectPlotter or matplotlib.axes.Axes) – The plotter whose axes to draw on, or an matplotlib axes. If you pass in the plotter, we make sure that lasso selectors of the plotter still work after an update.

coord

Specify what to use for the x-axis

Possible types

'index': Will use the index of the cell along the transect
'distance': Will use the euclidean distance of the start of the transect
'haversine': Will use the haversine distance in kilometers of the start of the transect. This can only be used if the x- and y-coordinates have units in 'degrees_east' and 'degrees_north', or 'radian' respectively.
'x': Will use the x-coordinate of the initial array
'y': Will use the y-coordinate of the initial array

cticklabels

Specify the colorbar ticklabels

Possible types

str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

See also

cticks, cticksize, ctickweight, ctickprops, vcticks, vcticksize, vctickweight, vctickprops

ctickprops

Specify the font properties of the colorbar ticklabels

Possible types

dict: Items may be anything of the matplotlib.pyplot.tick_params() function

See also

cticksize, ctickweight, cticklabels, cticks, vcticksize, vctickweight, vcticklabels, vcticks

cticks

Specify the tick locations of the colorbar

Possible types

None

use the default ticks

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
bounds: let the bounds keyword determine the ticks. An additional integer i may be specified to only use every i-th bound as a tick (see also int below)
midbounds: Same as bounds but in the middle between two bounds

int

Specifies how many ticks to use with the 'bounds' option. I.e. if integer i, then this is the same as ['bounds', i].

See also

cticklabels

cticksize

Specify the font size of the colorbar ticklabels

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

ctickweight, ctickprops, cticklabels, cticks, vctickweight, vctickprops, vcticklabels, vcticks

ctickweight

Specify the fontweight of the colorbar ticklabels

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

cticksize, ctickprops, cticklabels, cticks, vcticksize, vctickprops, vcticklabels, vcticks

datagrid

Show the grid of the data

This formatoption shows the grid of the data (without labels)

Possible types

None: Don’t show the data grid
str: A linestyle in the form 'k-', where 'k' is the color and '-' the linestyle.
dict: any keyword arguments that are passed to the plotting function ( matplotlib.pyplot.triplot() for unstructured grids and matplotlib.pyplot.hlines() for rectilinear grids)

See also

mask_datagrid: To display cells with NaN

disconnect_ax(ax: Axes): Disconnect this plotter from an axes and remove the selector.

extend

Draw arrows at the side of the colorbar

Possible types

str {‘neither’, ‘both’, ‘min’ or ‘max’}: If not ‘neither’, make pointed end(s) for out-of-range values

figtitle

Plot a figure title

Set the title of the figure. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the suptitle() function

Notes

If the plotter is part of a psyplot.project.Project and multiple plotters of this project are on the same figure, the replacement attributes (see above) are joined by a delimiter. If the delimiter attribute of this Figtitle instance is not None, it will be used. Otherwise the rcParams[‘texts.delimiter’] item is used.
This is the title of the whole figure! For the title of this specific subplot, see the title formatoption.

figtitleprops

Properties of the figure title

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

figtitlesize

Set the size of the figure title

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

figtitleweight

Set the fontweight of the figure title

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

get_enhanced_attrs(arr, *args, **kwargs)

grid

Display the grid

Show the grid on the plot with the specified color.

Possible types

None: If the grid is currently shown, it will not be displayed any longer. If the grid is not shown, it will be drawn
bool: If True, the grid is displayed with the automatic settings (usually black)
string, tuple.: Defines the color of the grid.

Notes

The following color abbreviations are supported:

character	color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

In addition, you can specify colors in many weird and wonderful ways, including full names ('green'), hex strings ('#008000'), RGB or RGBA tuples ((0,1,0,1)) or grayscale intensities as a string ('0.8').

interp_bounds

Interpolate grid cell boundaries for 2D plots

This formatoption can be used to tell enable and disable the interpolation of grid cell boundaries. Usually, netCDF files only contain the centered coordinates. In this case, we interpolate the boundaries between the grid cell centers.

Possible types

None: Interpolate the boundaries, except for circumpolar grids
bool: If True (the default), the grid cell boundaries are inter- and extrapolated. Otherwise, if False, the coordinate centers are used and the default behaviour of matplotlib cuts of the most outer row and column of the 2D-data. Note that this results in a slight shift of the data

labelprops

Set the font properties of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
dict: Items may be any valid text property

labelsize

Set the size of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

labelweight

Set the font size of both, x- and y-label

Possible types

dict: A dictionary with the keys 'x' and (or) 'y' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is used for the x- and y-axis. The values in the dictionary can be one types below.
float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

levels

The levels for the contour plot

This formatoption sets the levels for the filled contour plot and only has an effect if the plot Formatoption is set to 'contourf'

Possible types

None

Use the settings from the bounds formatoption and if this does not specify boundaries, use 11

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten

int

Specifies how many ticks to use with the 'rounded' option. I.e. if integer i, then this is the same as ['rounded', i].

mask

Mask the data where a certain condition is True

This formatoption can be used to mask the plotting data based on another array. This array can be the name of a variable in the base dataset, or it can be a numeric array. Note that the data needs to be on exactly the same coordinates as the data shown here

Possible types

None

Apply no mask

str

The name of a variable in the base dataset to use.

dimensions that are in the given mask but not in the visualized base variable will be aggregated using numpy.any()
if the given mask misses dimensions that are in the visualized data (i.e. the data of this plotter), we broadcast the mask to match the shape of the data
dimensions that are in mask and the base variable, but not in the visualized data will be matched against each other

str

The path to a netCDF file that shall be loaded

xr.DataArray or np.ndarray

An array that can be broadcasted to the shape of the data

mask_datagrid

Mask the datagrid where the array is NaN

This boolean formatoption enables to mask the grid of the datagrid formatoption where the data is NaN

Possible types

bool: Either True, to not display the data grid for cells with NaN, or False

See also

datagrid

maskbetween

Mask data points between two numbers

Possible types

float: The floating number to mask above

maskgeq

Mask data points greater than or equal to a number

Possible types

float: The floating number to mask above

maskgreater

Mask data points greater than a number

Possible types

float: The floating number to mask above

maskleq

Mask data points smaller than or equal to a number

Possible types

float: The floating number to mask below

maskless

Mask data points smaller than a number

Possible types

float: The floating number to mask below

miss_color

Set the color for missing values

Possible types

None: Use the default from the colormap
string, tuple.: Defines the color of the grid.

plot

Specify the plotting method

Possible types

None: Don’t make any plotting
‘mesh’: Use the matplotlib.pyplot.pcolormesh() function to make the plot

post

Apply your own postprocessing script

This formatoption let’s you apply your own post processing script. Just enter the script as a string and it will be executed. The formatoption will be made available via the self variable

Possible types

None: Don’t do anything
str: The post processing script as string

Note

This formatoption uses the built-in exec() function to compile the script. Since this poses a security risk when loading psyplot projects, it is by default disabled through the Plotter.enable_post attribute. If you are sure that you can trust the script in this formatoption, set this attribute of the corresponding Plotter to True

Examples

Assume, you want to manually add the mean of the data to the title of the matplotlib axes. You can simply do this via

from psyplot.plotter import Plotter
from xarray import DataArray

plotter = Plotter(DataArray([1, 2, 3]))
# enable the post formatoption
plotter.enable_post = True
plotter.update(post="self.ax.set_title(str(self.data.mean()))")
plotter.ax.get_title()
"2.0"

By default, the post formatoption is only ran, when it is explicitly updated. However, you can use the post_timing formatoption, to run it automatically. E.g. for running it after every update of the plotter, you can set

plotter.update(post_timing="always")

See also

post_timing: Determine the timing of this formatoption

post_timing

Determine when to run the post formatoption

This formatoption determines, whether the post formatoption should be run never, after replot or after every update.

Possible types

‘never’: Never run post processing scripts
‘always’: Always run post processing scripts
‘replot’: Only run post processing scripts when the data changes or a replot is necessary

See also

post: The post processing formatoption

selectors: Dict[Axes, widgets.LassoSelector]

sym_lims

Make x- and y-axis symmetric

Possible types

None: No symmetric type
‘min’: Use the minimum of x- and y-limits
‘max’: Use the maximum of x- and y-limits
[str, str]: A combination, None, 'min' and 'max' specific for minimum and maximum limit

text

Add text anywhere on the plot

This formatoption draws a text on the specified position on the figure. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: If string s: this will be used as (1., 1., s, {‘ha’: ‘right’}) (i.e. a string in the upper right corner of the axes).
tuple or list of tuples (x,y,s[,coord.-system][,options]]): Each tuple defines a text instance on the plot. 0<=x, y<=1 are the coordinates. The coord.-system can be either the data coordinates (default, 'data') or the axes coordinates ('axes') or the figure coordinates (‘fig’). The string s finally is the text. options may be a dictionary to specify format the appearence (e.g. 'color', 'fontweight', 'fontsize', etc., see matplotlib.text.Text for possible keys). To remove one single text from the plot, set (x,y,’’[, coord.-system]) for the text at position (x,y)
empty list: remove all texts from the plot

See also

title, figtitle

ticksize

Change the ticksize of the ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

tickweight

Change the fontweight of the ticks

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

ticksize, xtickprops, ytickprops

tight

Automatically adjust the plots.

If set to True, the plots are automatically adjusted to fit to the figure limitations via the matplotlib.pyplot.tight_layout() function.

Possible types

bool: True for automatic adjustment

Warning

There is no update method to undo what happend after this formatoption is set to True!

title

Show the title

Set the title of the plot. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The title for the title() function.

Notes

This is the title of this specific subplot! For the title of the whole figure, see the figtitle formatoption.

titleprops

Properties of the title

Specify the font properties of the figure title manually.

Possible types

dict: Items may be any valid text property

See also

title, titlesize, titleweight

titlesize

Set the size of the title

Possible types

float: The absolute font size in points (e.g., 12)
string: Strings might be ‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’.

See also

title, titleweight, titleprops

titleweight

Set the fontweight of the title

Possible types

float: a float between 0 and 1000
string: Possible strings are one of ‘ultralight’, ‘light’, ‘normal’, ‘regular’, ‘book’, ‘medium’, ‘roman’, ‘semibold’, ‘demibold’, ‘demi’, ‘bold’, ‘heavy’, ‘extra bold’, ‘black’.

See also

title, titlesize, titleprops

transect

Transect within a 2D plot

This formatoption takes a list of x-y tuples, the so-called transect, and extracts the raw data along this path.

Possible types

list of x-y tuples: The point coordinates of the transect.
None: Uses up to the first 100 cells

transect_method

Specify the method how to select the transect.

This formatoption specifies how the transect is selected.

Possible types

‘nearest’: Take the nearest grid point along the transect. This will not interpolate and return a unique list of grid points from the raw data.
‘nearest_exact’: Take the nearest grid point, one point from the raw data per point in the transect
‘inverse_distance_weighting’: Interpolation of the value at the requested position by inverse distance weighting method. See pyinterp.RTree.inverse_distance_weighting()
str: Any other method suitable for the rbf parameter of the pyinterp.RTree.radial_basis_function() method

transect_resolution

Expand the transect to a minimum resolution.

This formatoption expands the segments of the transect to fullfil a minimum resolution. Everything but False will expand the segments of the transect to fullfil the minimum resolution.

This formatoption is of particular importance if you want to use the vertical transect plotter in combination with a map.

Possible types

False: Do not make any changes to the provided transect but take it as it is
True or 'auto': The default value estimates the resolution of the underlying spatial data and estimates it’s minimum resolution. This won’t not work for unstructured data!
float: Specify the spatial resolution directly

transpose

xlabel

Set the x-axis label

Set the label for the x-axis. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The text for the xlabel() function.

See also

xlabelsize, xlabelweight, xlabelprops

xlim

Set the x-axis limits

Possible types

None

To not change the current limits

str or list [str, str] or [[str, float], [str, float]]

Automatically determine the ticks corresponding to the data. The given string determines how the limits are calculated. The float determines the percentile to use A string can be one of the following:

rounded: Sets the minimum and maximum of the limits to the rounded data minimum or maximum. Limits are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimum will always be lower or equal than the data minimum, the maximum will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the limits are chosen such that they are symmetric around zero
minmax: Uses the minimum and maximum
sym: Same as minmax but symmetric around zero

tuple (xmin, xmax)

xmin is the smaller value, xmax the larger. Any of those values can be None or one of the strings (or lists) above to use the corresponding value here

See also

ylim

xrotation

Rotate the x-axis ticks

Possible types

float: The rotation angle in degrees

See also

yrotation

xticklabels

Modify the x-axis ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

xtickprops

Specify the x-axis tick parameters

This formatoption can be used to make a detailed change of the ticks parameters on the x-axis.

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
dict: Items may be anything of the matplotlib.pyplot.tick_params() function

xticks

Modify the x-axis ticks

Possible types

dict

A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.

None

use the default ticks

int

for an integer i, only every i-th tick of the default ticks are used

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
hour: draw ticks every hour
day: draw ticks every day
week: draw ticks every week
month, monthend, monthbegin: draw ticks in the middle, at the end or at the beginning of each month
year, yearend, yearbegin: draw ticks in the middle, at the end or at the beginning of each year

For data, mid, hour, day, week, month, etc., the optional second value can be an integer i determining that every i-th data point shall be used (by default, it is set to 1). For rounded, roundedsym, minmax and sym, the second value determines the total number of ticks (defaults to 11).

Examples

Plot 11 ticks over the whole data range:

>>> plotter.update(xticks='rounded')

Plot 7 ticks over the whole data range where the maximal and minimal tick matches the data maximum and minimum:

>>> plotter.update(xticks=['minmax', 7])

Plot ticks every year and minor ticks every month:

>>> plotter.update(xticks={'major': 'year', 'minor': 'month'})

ylabel

Set the y-axis label

Set the label for the y-axis. You can insert any meta key from the xarray.DataArray.attrs via a string like '%(key)s'. Furthermore there are some special cases:

Strings like '%Y', '%b', etc. will be replaced using the datetime.datetime.strftime() method as long as the data has a time coordinate and this can be converted to a datetime object.
'%(x)s', '%(y)s', '%(z)s', '%(t)s' will be replaced by the value of the x-, y-, z- or time coordinate (as long as this coordinate is one-dimensional in the data)
any attribute of one of the above coordinates is inserted via axis + key (e.g. the name of the x-coordinate can be inserted via '%(xname)s').
Labels defined in the psyplot.rcParams 'texts.labels' key are also replaced when enclosed by ‘{}’. The standard labels are
- tinfo: %H:%M
- dtinfo: %B %d, %Y. %H:%M
- dinfo: %B %d, %Y
- desc: %(long_name)s [%(units)s]
- sdesc: %(name)s [%(units)s]

Possible types

str: The text for the ylabel() function.

See also

ylabelsize, ylabelweight, ylabelprops

ylim

Set the y-axis limits

Possible types

None

To not change the current limits

str or list [str, str] or [[str, float], [str, float]]

Automatically determine the ticks corresponding to the data. The given string determines how the limits are calculated. The float determines the percentile to use A string can be one of the following:

rounded: Sets the minimum and maximum of the limits to the rounded data minimum or maximum. Limits are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimum will always be lower or equal than the data minimum, the maximum will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the limits are chosen such that they are symmetric around zero
minmax: Uses the minimum and maximum
sym: Same as minmax but symmetric around zero

tuple (xmin, xmax)

xmin is the smaller value, xmax the larger. Any of those values can be None or one of the strings (or lists) above to use the corresponding value here

See also

xlim

yrotation

Rotate the y-axis ticks

Possible types

float: The rotation angle in degrees

See also

xrotation

yticklabels

Modify the y-axis ticklabels

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
str: A formatstring like '%Y' for plotting the year (in the case that time is shown on the axis) or ‘%i’ for integers
array: An array of strings to use for the ticklabels

ytickprops

Specify the y-axis tick parameters

This formatoption can be used to make a detailed change of the ticks parameters of the y-axis.

Possible types

dict: A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.
dict: Items may be anything of the matplotlib.pyplot.tick_params() function

yticks

Modify the y-axis ticks

Possible types

dict

A dictionary with the keys 'minor' and (or) 'major' to specify which ticks are managed. If the given value is not a dictionary with those keys, it is put into a dictionary with the key determined by the rcParams 'ticks.which' key (usually 'major'). The values in the dictionary can be one types below.

None

use the default ticks

int

for an integer i, only every i-th tick of the default ticks are used

numeric array

specifies the ticks manually

str or list [str, …]

A list of the below mentioned values of the mapping like [method, N, percmin, percmax, vmin, vmax], where only the first one is absolutely necessary

dict

Automatically determine the ticks corresponding to the data. The mapping can have the following keys, but only method is not optional.

N

An integer describing the number of boundaries (or ticks per power of ten, see log and symlog above)

percmin

The percentile to use for the minimum (by default, 0, i.e. the minimum of the array)

percmax

The percentile to use for the maximum (by default, 100, i.e. the maximum of the array)

vmin

The minimum to use (in which case it is not calculated from the specified method)

vmax

The maximum to use (in which case it is not calculated from the specified method)

method

A string that defines how minimum and maximum shall be set. This argument is not optional and can be one of the following:

data: plot the ticks exactly where the data is.
mid: plot the ticks in the middle of the data.
rounded: Sets the minimum and maximum of the ticks to the rounded data minimum or maximum. Ticks are rounded to the next 0.5 value with to the difference between data max- and minimum. The minimal tick will always be lower or equal than the data minimum, the maximal tick will always be higher or equal than the data maximum.
roundedsym: Same as rounded above but the ticks are chose such that they are symmetric around zero
minmax: Uses the minimum as minimal tick and maximum as maximal tick
sym: Same as minmax but symmetric around zero
log: Use logarithmic bounds. In this case, the given number N determines the number of bounds per power of tenth (i.e. N == 2 results in something like 1.0, 5.0, 10.0, 50.0, etc., If this second number is None, then it will be chosen such that we have around 11 boundaries but at least one per power of ten.
symlog: The same as log but symmetric around 0. If the number N is None, then we have around 12 boundaries but at least one per power of ten
hour: draw ticks every hour
day: draw ticks every day
week: draw ticks every week
month, monthend, monthbegin: draw ticks in the middle, at the end or at the beginning of each month
year, yearend, yearbegin: draw ticks in the middle, at the end or at the beginning of each year

For data, mid, hour, day, week, month, etc., the optional second value can be an integer i determining that every i-th data point shall be used (by default, it is set to 1). For rounded, roundedsym, minmax and sym, the second value determines the total number of ticks (defaults to 11).

xticks: for possible examples

class psy_transect.plotters.VerticalTransectTranspose(*args, **kwargs)

Bases: Transpose

Methods:

`get_x`(arr)
`get_y`(arr)

get_x(arr)

get_y(arr)