psy_reg.plotters module
Module for fitting a linear model to the data
This module defines the LinRegPlotter
and the
DensityRegPlotter
plotter classes that can be used
to fit a linear model to the data and visualize it.
- class psy_reg.plotters.Ci(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Draw a confidence interval
Size of the confidence interval for the regression estimate. This will be drawn using translucent bands around the regression line. The confidence interval is estimated using a bootstrap; for large datasets, it may be advisable to avoid that computation by setting this parameter to None.
Possible types
None – Do not draw and calculate a confidence interval
float – A quantile between 0 and 100
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- dependencies = ['transpose', 'fit', 'nboot', 'fix']
list of str. List of formatoptions that force an update of this formatoption if they are updated.
- property fit
fit Formatoption instance in the plotter
- property fix
fix Formatoption instance in the plotter
- initialize_plot(*args, **kwargs)[source]
Method that is called when the plot is made the first time
- Parameters
value – The value to use for the initialization
- name = 'Draw a confidence interval'
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
- property nboot
nboot Formatoption instance in the plotter
- 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 transpose
transpose Formatoption instance in the plotter
- class psy_reg.plotters.DensityRegPlotter(data=None, ax=None, auto_update=None, project=None, draw=False, make_plot=True, clear=False, enable_post=False, **kwargs)[source]
Bases:
psy_simple.plotters.ScalarCombinedBase
,psy_simple.plotters.DensityPlotter
,psy_reg.plotters.LinRegPlotter
A plotter that visualizes the density of points together with a linear regression
- Parameters
data (InteractiveArray or ArrayList, optional) – Data object that shall be visualized. If given and plot is True, the
initialize_plot()
method is called at the end. Otherwise you can call this method later by yourselfax (matplotlib.axes.Axes) – Matplotlib Axes to plot on. If None, a new one will be created as soon as the
initialize_plot()
method is calledauto_update (bool) – Default: None. A boolean indicating whether this list shall automatically update the contained arrays when calling the
update()
method or not. See also theno_auto_update
attribute. If None, the value from the'lists.auto_update'
key in thepsyplot.rcParams
dictionary is used.draw (bool or None) – Boolean to control whether the figure of this array shall be drawn at the end. If None, it defaults to the ‘auto_draw’` parameter in the
psyplot.rcParams
dictionarymake_plot (bool) – If True, and data is not None, the plot is initialized. Otherwise only the framework between plotter and data is set up
clear (bool) – If True, the axes is cleared first
enable_post (bool) – If True, the
post
formatoption is enabled and post processing scripts are allowed**kwargs – Any formatoption key from the
formatoptions
attribute that shall be used
- 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
- bins
Specify the bins of the 2D-Histogramm
This formatoption can be used to specify, how many bins to use. In other words, it determines the grid size of the resulting histogram or kde plot. If however you also set the
precision
formatoption keyword then the minimum of precision and the bins specified here will be used.Possible types
- 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 necessarydict – 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 like1.0, 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 integeri
, 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
- ci
Draw a confidence interval
Size of the confidence interval for the regression estimate. This will be drawn using translucent bands around the regression line. The confidence interval is estimated using a bootstrap; for large datasets, it may be advisable to avoid that computation by setting this parameter to None.
Possible types
None – Do not draw and calculate a confidence interval
float – A quantile between 0 and 100
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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.See also
- 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
- 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
- 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
- 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 thepsyplot.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
- color
Set the color coding
This formatoptions sets the color of the lines, bars, etc.
Possible types
None – to use the axes color_cycle
iterable – (e.g. list) to specify the colors manually
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 thepsyplot.rcParams
dictionary (including their reversed color maps given via the ‘_r’ extension).matplotlib.colors.ColorMap – to automatically choose the colors according to the number of lines, etc. from the given colormap
- coord
Use an alternative variable as x-coordinate
This formatoption let’s you specify another variable in the base dataset of the data array in case you want to use this as the x-coordinate instead of the raw data
Possible types
None – Use the default
str – The name of the variable to use in the base dataset
xarray.DataArray – An alternative variable with the same shape as the displayed array
Examples
To see the difference, we create a simple test dataset:
>>> import xarray as xr >>> import numpy as np >>> import psyplot.project as psy >>> ds = xr.Dataset({ ... 'temp': xr.Variable(('time', ), np.arange(5)), ... 'std': xr.Variable(('time', ), np.arange(5, 10))}) >>> ds <xarray.Dataset> Dimensions: (time: 5) Coordinates: * time (time) int64 0 1 2 3 4 Data variables: temp (time) int64 0 1 2 3 4 std (time) int64 5 6 7 8 9
If we create a plot with it, we get the
'time'
dimension on the x-axis:>>> plotter = psy.plot.lineplot(ds, name=['temp']).plotters[0] >>> plotter.plot_data[0].dims ('time',)
If we however set the
'coord'
keyword, we get:>>> plotter = psy.plot.lineplot( ... ds, name=['temp'], coord='std').plotters[0] >>> plotter.plot_data[0].dims ('std',)
and
'std'
is plotted on the x-axis.
- 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 integersarray – 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()
functionSee 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 necessarydict – 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 like1.0, 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 integeri
, then this is the same as['bounds', i]
.
See also
- 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 andmatplotlib.pyplot.hlines()
for rectilinear grids)
See also
mask_datagrid
To display cells with NaN
- density
- error
Visualize the error range
This formatoption visualizes the error range. For this, you must provide a two-dimensional data array as input. The first dimension might be either of length
2 to provide the deviation from minimum and maximum error range from the data
3 to provide the minimum and maximum error range explicitly
Possible types
None – No errors are visualized
‘fill’ – The area between min- and max-error is filled with the same color as the line and the alpha is determined by the
fillalpha
attribute
Examples
Assume you have the standard deviation stored in the
'std'
-variable and the data in the'data'
variable. Then you can visualize the standard deviation simply via:>>> psy.plot.lineplot(input_ds, name=[['data', 'std']])
On the other hand, assume you want to visualize the area between the 25th and 75th percentile (stored in the variables
'p25'
and'p75'
):>>> psy.plot.lineplot(input_ds, name=[['data', 'p25', 'p75']])
See also
- erroralpha
Set the alpha value for the error range
This formatoption can be used to set the alpha value (opacity) for the
error
formatoptionPossible types
float – A float between 0 and 1
See also
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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()
functionNotes
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 thedelimiter
attribute of thisFigtitle
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.
See also
- 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
See also
- 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’.
See also
- 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’.
See also
- fit
Choose the linear fitting method
This formatoption consists makes a linear fit of the data
Possible types
‘fit’ or ‘linear’ – make a linear fit
‘robust’ – make a robust linear fit
‘poly<deg>’ – Make a polynomial fit of the order
'<deg>'
function – A callable function that takes an x-array and a y-array as input and can be used for the
scipy.optimize.curve_fit()
functionany object with a fit and predict method – A model that with a fit signature such as
model.fit(x, y).predict(x)
None – make no fit
Notes
You can access the intercept, slope and rsquared by the correponding attribute. E.g.:
>>> plotter.update( ... legendlabels='%(intercept)s + %(slope)s * x, ' ... '$R^2$=%(rsquared)s')
See also
- fix
Force the fit to go through a given point
Possible types
None – do not force the fit at all
float f – make a linear fit forced through
(x, y) = (0, f)
tuple (x’, y’) – make a linear fit forced through
(x, y) = (x', y')
See also
- 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'
).
- id_color
The colors of the ideal lines
Possible types
None – Let it be determined by the color cycle of the
color
formatoptioniterable – (e.g. list) to specify the colors manually
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 thepsyplot.rcParams
dictionary (including their reversed color maps given via the ‘_r’ extension).matplotlib.colors.ColorMap – to automatically choose the colors according to the number of lines, etc. from the given colormap
See also
- ideal
Draw an ideal line of the fit
Possible types
None – Don’t draw an ideal line
list of floats – The parameters for the line. If the
fit
formatoption is in'robust'
or'fit'
, then the first value corresponds to the interception, the second to the slope. Otherwise the list corrensponds to the parameters as used in the fit function of the lineslist of list of floats – The same as above but with the specification for each array
See also
- 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
See also
- 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’.
See also
- 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’.
See also
- legend
Draw a legend
This formatoption determines where and if to draw the legend. It uses the
labels
formatoption to determine the labels.Possible types
bool – Draw a legend or not
str or int – Specifies where to plot the legend (i.e. the location)
dict – Give the keywords for the
matplotlib.pyplot.legend()
function
See also
labels
- legendlabels
Set the labels of the arrays in the legend
This formatoption specifies the labels for each array in the legend. 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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 – A single string that shall be used for all arrays.
list of str – Same as a single string but specified for each array
See also
- 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 11numeric 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 necessarydict – 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 like1.0, 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 integeri
, then this is the same as['rounded', i]
.
- line_xlim
Specify how wide the range for the plot should be
This formatoption specifies the range of the line to use
Possible types
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
- lineplot
Choose the line style of the plot
Possible types
None – Don’t make any plotting
'area'
– To make an area plot (filled between y=0 and y), seematplotlib.pyplot.fill_between()
'areax'
– To make a transposed area plot (filled between x=0 and x), seematplotlib.pyplot.fill_betweenx()
'stacked'
– Make a stacked plotstr or list of str – The line style string to use ([‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | ‘-’ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’]).
- linewidth
Choose the width of the lines
Possible types
None – Use the default from matplotlibs rcParams
float – The width of the lines
- marker
Choose the marker for points
Possible types
None – Use the default from matplotlibs rcParams
str – A valid symbol for the matplotlib markers (see
matplotlib.markers
)
- markersize
Choose the size of the markers for points
Possible types
None – Use the default from matplotlibs rcParams
float – The size of the marker
- 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 NaNPossible types
bool – Either True, to not display the data grid for cells with NaN, or False
See also
- maskbetween
Mask data points between two numbers
Possible types
float – The floating number to mask above
See also
- maskgeq
Mask data points greater than or equal to a number
Possible types
float – The floating number to mask above
See also
- maskgreater
Mask data points greater than a number
Possible types
float – The floating number to mask above
See also
- maskleq
Mask data points smaller than or equal to a number
Possible types
float – The floating number to mask below
See also
- maskless
Mask data points smaller than a number
Possible types
float – The floating number to mask below
See also
- 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.
- nboot
Set the number of bootstrap resamples for the confidence interval
- Parameters
int – Number of bootstrap resamples used to estimate the
ci
. The default value attempts to balance time and stability; you may want to increase this value for “final” versions of plots.
See also
- normed
Specify the normalization of the histogram
This formatoption can be used to normalize the histogram. It has no effect if the
density
formatoption is set to'kde'
Possible types
None – Do not make any normalization
str – One of
- counts
To make the normalization based on the total number counts
- area
To make the normalization basen on the total number of counts and area (the default behaviour of
numpy.histogram2d()
)- x, col, column or columns
To normalize every column
- y, row or rows
To normalize every row
See also
- p0
Initial parameters for the
scipy.optimize.curve_fit()
functionThis formatoptions can be used to set the initial parameters if the value of the
fit
formatoption is a callable function.Note that the automatic estimation uses the boundaries of the
param_bounds
formatoption. This only works if the boundaries are given for each parameter and finite.Possible types
‘auto’ – The initial parameters are estimated automatically using the
from scipy.optimize.differential_evolution()
functionlist of floats – The initial parameters
list of list of floats or ‘auto’ – A combination of the above types where each corresponds to one data array
- param_bounds
Parameter bounds for the function parameters
This formatoption can be used to specify the boundaries for the parameters. It only has an effect if the value of the
fit
formatoption is a callable function.These bounds will also be used by the
p0
formatoption to estimate the initial parameters.Possible types
None – Use open boundaries
list of tuples with length 2 – The boundaries for each of the parameters
list of tuples or None – A combination of the above types where each corresponds to one data array
- plot
Choose how to visualize a 2-dimensional scalar data field
Possible types
None – Don’t make any plotting
‘mesh’ – Use the
matplotlib.pyplot.pcolormesh()
function to make the plot or thematplotlib.pyplot.tripcolor()
for an unstructered grid‘poly’ – Draw each polygon indivually. This method is used by default for unstructured grids. If there are no grid cell boundaries in the dataset, we will interpolate them
‘contourf’ – Make a filled contour plot using the
matplotlib.pyplot.contourf()
function or thematplotlib.pyplot.tricontourf()
for unstructured data. The levels for the contour plot are controlled by thelevels
formatoption‘contour’ – Same a
'contourf'
, but does not make a filled contour plot, only lines.
- 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
variablePossible 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 thePlotter.enable_post
attribute. If you are sure that you can trust the script in this formatoption, set this attribute of the correspondingPlotter
toTrue
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 thepost_timing
formatoption, to run it automatically. E.g. for running it after every update of the plotter, you can setplotter.update(post_timing='always')
See also
post_timing
Determine the timing of this formatoption
- post_timing
Determine when to run the
post
formatoptionThis 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
- precision
Set the precision of the data
This formatoption can be used to specify the precision of the data which then will be the minimal bin width of the 2D histogram or the bandwith of the kernel size (if the
density
formatoption is set to'kde'
)Possible types
float – If 0, this formatoption has no effect at all. Otherwise it is assumed to be the precision of the data
str – One of
{'scott' | 'silverman'}
. This uses the statsmodels package to estimate the bandwidth of the data that is then used in the histogram or KDE plot
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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., seematplotlib.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
- 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’.
See also
- 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
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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.See also
- 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
- 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
- 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
- transpose
Switch x- and y-axes
By default, one-dimensional arrays have the dimension on the x-axis and two dimensional arrays have the first dimension on the y and the second on the x-axis. You can set this formatoption to True to change this behaviour
Possible types
bool – If True, axes are switched
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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
- xrange
Specify the range of the histogram for the x-dimension
This formatoption specifies the minimum and maximum of the histogram in the x-dimension
Possible types
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
Notes
This formatoption always acts on the coordinate, no matter what the value of the
transpose
formatoption isSee also
- xrotation
Rotate the x-axis ticks
Possible types
float – The rotation angle in degrees
See also
- 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 integersarray – An array of strings to use for the ticklabels
See also
- 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
See also
- 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 necessarydict – 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 like1.0, 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'})
See also
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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
- yrange
Specify the range of the histogram for the x-dimension
This formatoption specifies the minimum and maximum of the histogram in the x-dimension
Possible types
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
Notes
This formatoption always acts on the DataArray, no matter what the value of the
transpose
formatoption isSee also
- yrotation
Rotate the y-axis ticks
Possible types
float – The rotation angle in degrees
See also
- 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 integersarray – An array of strings to use for the ticklabels
See also
- 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
See also
- 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 necessarydict – 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 like1.0, 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).
- class psy_reg.plotters.FitPointDensity(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psy_simple.plotters.PointDensity
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property bins
bins Formatoption instance in the plotter
- children = ['line_xlim']
list of str. List of formatoptions that have to be updated before this one is updated. Those formatoptions are only updated if they exist in the update parameters.
- property coord
coord Formatoption instance in the plotter
- property line_xlim
line_xlim Formatoption instance in the plotter
- property normed
normed Formatoption instance in the plotter
- property precision
precision Formatoption instance in the plotter
- property xrange
xrange Formatoption instance in the plotter
- property yrange
yrange Formatoption instance in the plotter
- class psy_reg.plotters.FixPoint(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Force the fit to go through a given point
Possible types
None – do not force the fit at all
float f – make a linear fit forced through
(x, y) = (0, f)
tuple (x’, y’) – make a linear fit forced through
(x, y) = (x', y')
See also
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- connections = ['fit']
list of str. Connections to other formatoptions that are (different from
dependencies
andchildren
) not important for the update process
- property fit
fit Formatoption instance in the plotter
- name = 'Force the fit to go through a given point'
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
- class psy_reg.plotters.IdealLine(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Draw an ideal line of the fit
Possible types
None – Don’t draw an ideal line
list of floats – The parameters for the line. If the
fit
formatoption is in'robust'
or'fit'
, then the first value corresponds to the interception, the second to the slope. Otherwise the list corrensponds to the parameters as used in the fit function of the lineslist of list of floats – The same as above but with the specification for each array
See also
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- dependencies = ['fit', 'id_color', 'plot']
list of str. List of formatoptions that force an update of this formatoption if they are updated.
- property fit
fit Formatoption instance in the plotter
- property id_color
id_color Formatoption instance in the plotter
- initialize_plot(*args, **kwargs)[source]
Method that is called when the plot is made the first time
- Parameters
value – The value to use for the initialization
- property plot
plot Formatoption instance in the plotter
- remove()[source]
Method to remove the effects of this formatoption
This method is called when the axes is cleared due to a formatoption with
requires_clearing
set to True. You don’t necessarily have to implement this formatoption if your plot results are removed by the usualmatplotlib.axes.Axes.clear()
method.
- class psy_reg.plotters.IdealLineColor(*args, **kwargs)[source]
Bases:
psy_simple.plotters.LineColors
The colors of the ideal lines
Possible types
None – Let it be determined by the color cycle of the
color
formatoptioniterable – (e.g. list) to specify the colors manually
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 thepsyplot.rcParams
dictionary (including their reversed color maps given via the ‘_r’ extension).matplotlib.colors.ColorMap – to automatically choose the colors according to the number of lines, etc. from the given colormap
See also
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property color
color Formatoption instance in the plotter
- dependencies = ['color']
list of str. List of formatoptions that force an update of this formatoption if they are updated.
- property ideal
ideal Formatoption instance in the plotter
- parents = ['ideal']
list of str. List of formatoptions that, if included in the update, prevent the update of this formatoption.
- class psy_reg.plotters.InitialParameters(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Initial parameters for the
scipy.optimize.curve_fit()
functionThis formatoptions can be used to set the initial parameters if the value of the
fit
formatoption is a callable function.Note that the automatic estimation uses the boundaries of the
param_bounds
formatoption. This only works if the boundaries are given for each parameter and finite.Possible types
‘auto’ – The initial parameters are estimated automatically using the
from scipy.optimize.differential_evolution()
functionlist of floats – The initial parameters
list of list of floats or ‘auto’ – A combination of the above types where each corresponds to one data array
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- connections = ['fit']
list of str. Connections to other formatoptions that are (different from
dependencies
andchildren
) not important for the update process
- data_dependent = True
bool
or a callable. This attribute indicates whether thisFormatoption
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 = ['param_bounds']
list of str. List of formatoptions that force an update of this formatoption if they are updated.
- property fit
fit Formatoption instance in the plotter
- name = 'Initial parameter values for the fit'
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
- property param_bounds
param_bounds Formatoption instance in the plotter
- class psy_reg.plotters.LinRegPlotter(data=None, ax=None, auto_update=None, project=None, draw=False, make_plot=True, clear=False, enable_post=False, **kwargs)[source]
Bases:
psy_simple.plotters.LinePlotter
A plotter to visualize the fit on the data
The most important formatoptions are the
fit
andci
formatoption. Otherwise this plotter behaves like thepsyplot.plotter.simple.LinePlotter
plotter class- Parameters
data (InteractiveArray or ArrayList, optional) – Data object that shall be visualized. If given and plot is True, the
initialize_plot()
method is called at the end. Otherwise you can call this method later by yourselfax (matplotlib.axes.Axes) – Matplotlib Axes to plot on. If None, a new one will be created as soon as the
initialize_plot()
method is calledauto_update (bool) – Default: None. A boolean indicating whether this list shall automatically update the contained arrays when calling the
update()
method or not. See also theno_auto_update
attribute. If None, the value from the'lists.auto_update'
key in thepsyplot.rcParams
dictionary is used.draw (bool or None) – Boolean to control whether the figure of this array shall be drawn at the end. If None, it defaults to the ‘auto_draw’` parameter in the
psyplot.rcParams
dictionarymake_plot (bool) – If True, and data is not None, the plot is initialized. Otherwise only the framework between plotter and data is set up
clear (bool) – If True, the axes is cleared first
enable_post (bool) – If True, the
post
formatoption is enabled and post processing scripts are allowed**kwargs – Any formatoption key from the
formatoptions
attribute that shall be used
- allowed_vars = 1
The number variables that one data array visualized by this plotter might have. We allow up to 3 variableswhere the second and third variable might be the errors (see the
error
formatoption)
- 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
- ci
Draw a confidence interval
Size of the confidence interval for the regression estimate. This will be drawn using translucent bands around the regression line. The confidence interval is estimated using a bootstrap; for large datasets, it may be advisable to avoid that computation by setting this parameter to None.
Possible types
None – Do not draw and calculate a confidence interval
float – A quantile between 0 and 100
- color
Set the color coding
This formatoptions sets the color of the lines, bars, etc.
Possible types
None – to use the axes color_cycle
iterable – (e.g. list) to specify the colors manually
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 thepsyplot.rcParams
dictionary (including their reversed color maps given via the ‘_r’ extension).matplotlib.colors.ColorMap – to automatically choose the colors according to the number of lines, etc. from the given colormap
- coord
Use an alternative variable as x-coordinate
This formatoption let’s you specify another variable in the base dataset of the data array in case you want to use this as the x-coordinate instead of the raw data
Possible types
None – Use the default
str – The name of the variable to use in the base dataset
xarray.DataArray – An alternative variable with the same shape as the displayed array
Examples
To see the difference, we create a simple test dataset:
>>> import xarray as xr >>> import numpy as np >>> import psyplot.project as psy >>> ds = xr.Dataset({ ... 'temp': xr.Variable(('time', ), np.arange(5)), ... 'std': xr.Variable(('time', ), np.arange(5, 10))}) >>> ds <xarray.Dataset> Dimensions: (time: 5) Coordinates: * time (time) int64 0 1 2 3 4 Data variables: temp (time) int64 0 1 2 3 4 std (time) int64 5 6 7 8 9
If we create a plot with it, we get the
'time'
dimension on the x-axis:>>> plotter = psy.plot.lineplot(ds, name=['temp']).plotters[0] >>> plotter.plot_data[0].dims ('time',)
If we however set the
'coord'
keyword, we get:>>> plotter = psy.plot.lineplot( ... ds, name=['temp'], coord='std').plotters[0] >>> plotter.plot_data[0].dims ('std',)
and
'std'
is plotted on the x-axis.
- error
Visualize the error range
This formatoption visualizes the error range. For this, you must provide a two-dimensional data array as input. The first dimension might be either of length
2 to provide the deviation from minimum and maximum error range from the data
3 to provide the minimum and maximum error range explicitly
Possible types
None – No errors are visualized
‘fill’ – The area between min- and max-error is filled with the same color as the line and the alpha is determined by the
fillalpha
attribute
Examples
Assume you have the standard deviation stored in the
'std'
-variable and the data in the'data'
variable. Then you can visualize the standard deviation simply via:>>> psy.plot.lineplot(input_ds, name=[['data', 'std']])
On the other hand, assume you want to visualize the area between the 25th and 75th percentile (stored in the variables
'p25'
and'p75'
):>>> psy.plot.lineplot(input_ds, name=[['data', 'p25', 'p75']])
See also
- erroralpha
Set the alpha value for the error range
This formatoption can be used to set the alpha value (opacity) for the
error
formatoptionPossible types
float – A float between 0 and 1
See also
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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()
functionNotes
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 thedelimiter
attribute of thisFigtitle
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.
See also
- 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
See also
- 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’.
See also
- 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’.
See also
- fit
Choose the linear fitting method
This formatoption consists makes a linear fit of the data
Possible types
‘fit’ or ‘linear’ – make a linear fit
‘robust’ – make a robust linear fit
‘poly<deg>’ – Make a polynomial fit of the order
'<deg>'
function – A callable function that takes an x-array and a y-array as input and can be used for the
scipy.optimize.curve_fit()
functionany object with a fit and predict method – A model that with a fit signature such as
model.fit(x, y).predict(x)
None – make no fit
Notes
You can access the intercept, slope and rsquared by the correponding attribute. E.g.:
>>> plotter.update( ... legendlabels='%(intercept)s + %(slope)s * x, ' ... '$R^2$=%(rsquared)s')
See also
- fix
Force the fit to go through a given point
Possible types
None – do not force the fit at all
float f – make a linear fit forced through
(x, y) = (0, f)
tuple (x’, y’) – make a linear fit forced through
(x, y) = (x', y')
See also
- 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'
).
- id_color
The colors of the ideal lines
Possible types
None – Let it be determined by the color cycle of the
color
formatoptioniterable – (e.g. list) to specify the colors manually
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 thepsyplot.rcParams
dictionary (including their reversed color maps given via the ‘_r’ extension).matplotlib.colors.ColorMap – to automatically choose the colors according to the number of lines, etc. from the given colormap
See also
- ideal
Draw an ideal line of the fit
Possible types
None – Don’t draw an ideal line
list of floats – The parameters for the line. If the
fit
formatoption is in'robust'
or'fit'
, then the first value corresponds to the interception, the second to the slope. Otherwise the list corrensponds to the parameters as used in the fit function of the lineslist of list of floats – The same as above but with the specification for each array
See also
- 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
See also
- 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’.
See also
- 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’.
See also
- legend
Draw a legend
This formatoption determines where and if to draw the legend. It uses the
labels
formatoption to determine the labels.Possible types
bool – Draw a legend or not
str or int – Specifies where to plot the legend (i.e. the location)
dict – Give the keywords for the
matplotlib.pyplot.legend()
function
See also
labels
- legendlabels
Set the labels of the arrays in the legend
This formatoption specifies the labels for each array in the legend. 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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 – A single string that shall be used for all arrays.
list of str – Same as a single string but specified for each array
See also
- line_xlim
Specify how wide the range for the plot should be
This formatoption specifies the range of the line to use
Possible types
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
- linewidth
Choose the width of the lines
Possible types
None – Use the default from matplotlibs rcParams
float – The width of the lines
- marker
Choose the marker for points
Possible types
None – Use the default from matplotlibs rcParams
str – A valid symbol for the matplotlib markers (see
matplotlib.markers
)
- markersize
Choose the size of the markers for points
Possible types
None – Use the default from matplotlibs rcParams
float – The size of the marker
- 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
- maskbetween
Mask data points between two numbers
Possible types
float – The floating number to mask above
See also
- maskgeq
Mask data points greater than or equal to a number
Possible types
float – The floating number to mask above
See also
- maskgreater
Mask data points greater than a number
Possible types
float – The floating number to mask above
See also
- maskleq
Mask data points smaller than or equal to a number
Possible types
float – The floating number to mask below
See also
- maskless
Mask data points smaller than a number
Possible types
float – The floating number to mask below
See also
- nboot
Set the number of bootstrap resamples for the confidence interval
- Parameters
int – Number of bootstrap resamples used to estimate the
ci
. The default value attempts to balance time and stability; you may want to increase this value for “final” versions of plots.
See also
- p0
Initial parameters for the
scipy.optimize.curve_fit()
functionThis formatoptions can be used to set the initial parameters if the value of the
fit
formatoption is a callable function.Note that the automatic estimation uses the boundaries of the
param_bounds
formatoption. This only works if the boundaries are given for each parameter and finite.Possible types
‘auto’ – The initial parameters are estimated automatically using the
from scipy.optimize.differential_evolution()
functionlist of floats – The initial parameters
list of list of floats or ‘auto’ – A combination of the above types where each corresponds to one data array
- param_bounds
Parameter bounds for the function parameters
This formatoption can be used to specify the boundaries for the parameters. It only has an effect if the value of the
fit
formatoption is a callable function.These bounds will also be used by the
p0
formatoption to estimate the initial parameters.Possible types
None – Use open boundaries
list of tuples with length 2 – The boundaries for each of the parameters
list of tuples or None – A combination of the above types where each corresponds to one data array
- plot
Choose the line style of the plot
Possible types
None – Don’t make any plotting
'area'
– To make an area plot (filled between y=0 and y), seematplotlib.pyplot.fill_between()
'areax'
– To make a transposed area plot (filled between x=0 and x), seematplotlib.pyplot.fill_betweenx()
'stacked'
– Make a stacked plotstr or list of str – The line style string to use ([‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | ‘-’ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’]).
- 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
variablePossible 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 thePlotter.enable_post
attribute. If you are sure that you can trust the script in this formatoption, set this attribute of the correspondingPlotter
toTrue
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 thepost_timing
formatoption, to run it automatically. E.g. for running it after every update of the plotter, you can setplotter.update(post_timing='always')
See also
post_timing
Determine the timing of this formatoption
- post_timing
Determine when to run the
post
formatoptionThis 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
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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., seematplotlib.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
- 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’.
See also
- 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
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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.See also
- 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
- 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
- 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
- transpose
Switch x- and y-axes
By default, one-dimensional arrays have the dimension on the x-axis and two dimensional arrays have the first dimension on the y and the second on the x-axis. You can set this formatoption to True to change this behaviour
Possible types
bool – If True, axes are switched
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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
- xrange
Specify the range for the fit to use for the x-dimension
This formatoption specifies the minimum and maximum of the fit in the x-dimension
Possible types
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
Notes
This formatoption always acts on the coordinate, no matter what the value of the
transpose
formatoption is
- xrotation
Rotate the x-axis ticks
Possible types
float – The rotation angle in degrees
See also
- 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 integersarray – An array of strings to use for the ticklabels
See also
- 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
See also
- 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 necessarydict – 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 like1.0, 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'})
See also
- 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 thedatetime.datetime.strftime()
method as long as the data has a time coordinate and this can be converted to adatetime
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 aretinfo:
%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
- yrange
Specify the range for the fit to use for the y-dimension
This formatoption specifies the minimum and maximum of the fit in the y-dimension
Possible types
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
Notes
This formatoption always acts on the coordinate, no matter what the value of the
transpose
formatoption isSee also
- yrotation
Rotate the y-axis ticks
Possible types
float – The rotation angle in degrees
See also
- 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 integersarray – An array of strings to use for the ticklabels
See also
- 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
See also
- 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 necessarydict – 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 like1.0, 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).
- class psy_reg.plotters.LinRegTranspose(*args, **kwargs)[source]
Bases:
psy_simple.plotters.Transpose
Switch x- and y-axes
By default, one-dimensional arrays have the dimension on the x-axis and two dimensional arrays have the first dimension on the y and the second on the x-axis. You can set this formatoption to True to change this behaviour
Possible types
bool – If True, axes are switched
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- class psy_reg.plotters.LinearRegressionFit(*args, **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Choose the linear fitting method
This formatoption consists makes a linear fit of the data
Possible types
‘fit’ or ‘linear’ – make a linear fit
‘robust’ – make a robust linear fit
‘poly<deg>’ – Make a polynomial fit of the order
'<deg>'
function – A callable function that takes an x-array and a y-array as input and can be used for the
scipy.optimize.curve_fit()
functionany object with a fit and predict method – A model that with a fit signature such as
model.fit(x, y).predict(x)
None – make no fit
Notes
You can access the intercept, slope and rsquared by the correponding attribute. E.g.:
>>> plotter.update( ... legendlabels='%(intercept)s + %(slope)s * x, ' ... '$R^2$=%(rsquared)s')
See also
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property coord
coord Formatoption instance in the plotter
- data_dependent = True
bool
or a callable. This attribute indicates whether thisFormatoption
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 = ['transpose', 'fix', 'xrange', 'yrange', 'coord', 'line_xlim', 'p0', 'param_bounds']
list of str. List of formatoptions that force an update of this formatoption if they are updated.
- property fix
fix Formatoption instance in the plotter
- property func_args
The arguments for the fit function if the
method
is ‘curve_fit’
- property line_xlim
line_xlim Formatoption instance in the plotter
- name = 'Change the fit method'
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
- property p0
p0 Formatoption instance in the plotter
- property param_bounds
param_bounds Formatoption instance in the plotter
- 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 transpose
transpose Formatoption instance in the plotter
- update(value)[source]
Method that is call to update the formatoption on the axes
- Parameters
value – Value to update
- property xrange
xrange Formatoption instance in the plotter
- property yrange
yrange Formatoption instance in the plotter
- class psy_reg.plotters.LinearRegressionFitCombined(*args, **kwargs)[source]
Bases:
psy_reg.plotters.LinearRegressionFit
Choose the linear fitting method
This formatoption consists makes a linear fit of the data
Possible types
‘fit’ or ‘linear’ – make a linear fit
‘robust’ – make a robust linear fit
‘poly<deg>’ – Make a polynomial fit of the order
'<deg>'
function – A callable function that takes an x-array and a y-array as input and can be used for the
scipy.optimize.curve_fit()
functionany object with a fit and predict method – A model that with a fit signature such as
model.fit(x, y).predict(x)
None – make no fit
Notes
You can access the intercept, slope and rsquared by the correponding attribute. E.g.:
>>> plotter.update( ... legendlabels='%(intercept)s + %(slope)s * x, ' ... '$R^2$=%(rsquared)s')
See also
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property coord
coord Formatoption instance in the plotter
- property fix
fix Formatoption instance in the plotter
- property line_xlim
line_xlim Formatoption instance in the plotter
- property p0
p0 Formatoption instance in the plotter
- property param_bounds
param_bounds Formatoption instance in the plotter
- property transpose
transpose Formatoption instance in the plotter
- property xrange
xrange Formatoption instance in the plotter
- property yrange
yrange Formatoption instance in the plotter
- class psy_reg.plotters.NBoot(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Set the number of bootstrap resamples for the confidence interval
- Parameters
int – Number of bootstrap resamples used to estimate the
ci
. The default value attempts to balance time and stability; you may want to increase this value for “final” versions of plots.
See also
ci
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- name = 'Set the bootstrapping number to calculate the confidence interval'
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
- class psy_reg.plotters.ParameterBounds(key, plotter=None, index_in_list=None, additional_children=[], additional_dependencies=[], **kwargs)[source]
Bases:
psyplot.plotter.Formatoption
Parameter bounds for the function parameters
This formatoption can be used to specify the boundaries for the parameters. It only has an effect if the value of the
fit
formatoption is a callable function.These bounds will also be used by the
p0
formatoption to estimate the initial parameters.Possible types
None – Use open boundaries
list of tuples with length 2 – The boundaries for each of the parameters
list of tuples or None – A combination of the above types where each corresponds to one data array
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- class psy_reg.plotters.XFitRange(*args, **kwargs)[source]
Bases:
psy_simple.plotters.Hist2DXRange
Specify the range for the fit to use for the x-dimension
This formatoption specifies the minimum and maximum of the fit in the x-dimension
Possible types
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
Notes
This formatoption always acts on the coordinate, no matter what the value of the
transpose
formatoption isSee also
yrange
,line_xlim
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property coord
coord Formatoption instance in the plotter
- property plot
plot Formatoption instance in the plotter
- property range
The range for each of the curves
- property transpose
transpose Formatoption instance in the plotter
- class psy_reg.plotters.XLineRange(*args, **kwargs)[source]
Bases:
psy_reg.plotters.XFitRange
Specify how wide the range for the plot should be
This formatoption specifies the range of the line to use
Possible types
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
xrange
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property coord
coord Formatoption instance in the plotter
- property plot
plot Formatoption instance in the plotter
- property transpose
transpose Formatoption instance in the plotter
- class psy_reg.plotters.YFitRange(*args, **kwargs)[source]
Bases:
psy_simple.plotters.Hist2DYRange
Specify the range for the fit to use for the y-dimension
This formatoption specifies the minimum and maximum of the fit in the y-dimension
Possible types
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
Notes
This formatoption always acts on the coordinate, no matter what the value of the
transpose
formatoption isSee also
xrange
- Parameters
key (str) – formatoption key in the plotter
plotter (psyplot.plotter.Plotter) – Plotter instance that holds this formatoption. If None, it is assumed that this instance serves as a descriptor.
index_in_list (int or None) – The index that shall be used if the data is a
psyplot.InteractiveList
additional_children (list or str) – Additional children to use (see the
children
attribute)additional_dependencies (list or str) – Additional dependencies to use (see the
dependencies
attribute)**kwargs – Further keywords may be used to specify different names for children, dependencies and connection formatoptions that match the setup of the plotter. Hence, keywords may be anything of the
children
,dependencies
andconnections
attributes, with values being the name of the new formatoption in this plotter.
- property coord
coord Formatoption instance in the plotter
- property plot
plot Formatoption instance in the plotter
- property range
The range for each of the curves
- property transpose
transpose Formatoption instance in the plotter