Plot Function#

get_levels#

get levels of data

Parameter#

  • data (np.ndarray): data need to get levels

  • percentile (int,default=98%): max value or min value percentile

  • num_level (int, default=13): colorbar levels

  • zero_sym (bool, default=True): levels is zero symmetric or not

Returns:#

  • np.ndarray: levels for contourf or contourf

Example#

[2]:

import sacpy as scp
import sacpy.Map

sacpy.Map.get_levels(scp.load_sst()['sst'][0])

[2]:

array([-2.97376192e+01, -2.47813493e+01, -1.98250795e+01, -1.48688096e+01,
       -9.91253974e+00, -4.95626987e+00,  3.55271368e-15,  4.95626987e+00,
        9.91253974e+00,  1.48688096e+01,  1.98250795e+01,  2.47813493e+01,
        2.97376192e+01])

GeoAxesSubplot.scontourf#

contourf function for Cartopy.GeoAxesSubplot

parameter#

  • the same parameter for plt.contourf

  • automatically choose the levels (use get_levels)

  • no need for “transform”

  • default cmap is “RdBu_r”

Returns:#

  • mpl.contour.QuadContourSet

GeoAxesSubplot.scontour#

contour function for Cartopy.GeoAxesSubplot

parameter#

  • the same parameter for plt.contour

  • automatically choose the levels (use get_levels)

  • no need for “transform”

Returns:#

  • mpl.contour.QuadContourSet

GeoAxesSubplot.sig_plot#

Significance test dot

Parameter:#

  • x (np.ndarray or xr.Dataarray): x

  • y (np.ndarray or xr.Dataarray): y

  • pvalue (np.ndarray): p value

  • thrshd (float, optional): threshold of pvalue. Defaults to 0.05.

  • marker (str, optional): mark of Significance test dot. Defaults to “..”.

Returns:#

  • mpl.contour.QuadContourSet

GeoAxesSubplot.spcolormesh#

pcolormesh function for Cartopy.GeoAxesSubplot

parameter#

  • the same parameter for plt.pcolormesh

  • automatically choose the levels (use get_levels)

  • no need for “transform”

  • default cmap is “RdBu_r”

GeoAxesSubplot.squive#

pcolormesh function for Cartopy.GeoAxesSubplot

parameter#

  • the same parameter for plt.pcolormesh

  • stepx: Number of intervals in x direction

  • stepy: Number of intervals in y direction

  • no need for “transform”

GeoAxesSubplot.draw_ticks#

draw map ticks

Parameter:#

  • extend (list): extend of map [x1, x2, y1, y2]

  • stepx (int, optional): big x step. Defaults to 30.

  • stepy (int, optional): big y step. Defaults to 10.

  • smallx (int, optional): x small step. Defaults to 5.

  • smally (int, optional): y small step. Defaults to 5.

  • bigx/bigy (int, optional): Resolution in X and Y directions

GeoAxesSubplot.init_map#

plot the coastlines of the map and draw longitude and latitude ticks

Parameter#

  • same_size: if True, use ax.set_aspect(“auto)

  • *kwargs for draw_ticks

xr.Dataarray.splot#

2-D plot.contourf for xr.Dataarray

Parameter#

  • ax

  • label

  • kw1: for scontourf

  • kw2: for init_map()

Return#

  • mpl.contour.QuadContourSet

  • ax

Plot Example#

[15]:

import sacpy.Map
import sacpy as scp

sst = scp.load_sst()['sst'].mean("time").loc[-20:30,150:275]
m,ax = sst.splot()
ax.scontour(m,colors="white")
u,v = scp.load_10mwind()['u'].mean("time"),scp.load_10mwind()['v'].mean("time")
ax.squiver(u.lon,v.lat,u,v,stepx=2,stepy=1)

[15]:

<matplotlib.quiver.Quiver at 0x16b3484c0>
../_images/notebooks_PlotFunction_12_1.png