def lb_format_labels(plot, fmt, minmax=None):
'''Applies a formatting to the lables of a label bar
lb_format_labels(plot, fmt, minmax=None)
plot : plot id of object that controlls the lable bar
fmt : formatting string
minmax : values of the maximum and minimum. Required, if cnLabelBarEndStyle
is set to IncludeMinMaxLabels. If not provided in this case, a ValueError
will be raised.
'''
levels = [float(s) for s in ngl.get_string_array(plot, "cnLevels")]
labels = [fmt % lev for lev in levels]
if ngl.get_string(plot, "cnLabelBarEndStyle") == "IncludeMinMaxLabels":
if not minmax:
raise ValueError("You need to provide minmax,"
+ " since cnLabelBarEndStyle is set to "
+ "IncludeMinMaxLabels!")
minlabel = [fmt % minmax[0]]
minlabel.extend(labels)
labels = minlabel
labels.append(fmt % minmax[1])
rlist = {"cnExplicitLabelBarLabelsOn": True,
"lbLabelStrings": labels}
_set_values(plot, rlist)
def add_axis(wks, plot, ax="XB", offset=0., res=None):
val_ax = ("XT", "XB", "YL", "YR")
if not res:
res = {}
else:
res = _resource2dict(res)
resp = {}
keys = ["vpXF", "vpYF", "vpWidthF", "vpHeightF", "trXMinF", "trXMaxF",
"trYMinF", "trYMaxF"]
for a in val_ax:
for k in ("LabelFontHeight", "MajorOutwardLength",
"MinorOutwardLength"):
keys.append("tm{}{}F".format(a, k))
for k in keys:
resp[k] = ngl.get_float(plot, k)
for k in ("tm" + a + k for a in val_ax for k in ("Values", "MinorValues")):
resp[k] = ngl.get_float_array(plot, k)
for k in ("tm{}MinorPerMajor".format(a) for a in val_ax):
resp[k] = ngl.get_integer(plot, k)
for k in ("tm{}MinorOn".format(a) for a in val_ax):
resp[k] = (ngl.get_integer(plot, k) == 1)
for k in ("tm" + a + "Labels".format(a) for a in val_ax):
resp[k] = ngl.get_string_array(plot, k)
resp.update(res)
for a in ("XT", "XB", "YL", "YR"):
resp["tm{}Mode".format(a)] = "Explicit"
resp["tm{}On".format(a)] = (a == ax)
resp["tm{}BorderOn".format(a)] = (a == ax)
resp["nglDraw"] = False
resp["nglFrame"] = False
blank_plot = ngl.blank_plot(wks, _dict2Resource(resp))
amres = {"amJust": "CenterCenter"}
if ax[1].lower() in "lt":
ampos_sig = -1.
else:
ampos_sig = 1.
if ax[0].lower() == "x":
amres["amOrthogonalPosF"] = ampos_sig * offset
else:
amres["amParallelPosF"] = ampos_sig * offset
return ngl.add_annotation(plot, blank_plot, _dict2Resource(amres))
def lb_set_phase_labels(plot):
'''Changes the labels of a color bar to -pi, -pi/2, 0, pi/2 and pi. The
label bar must already have only these lables.
lb_set_phase_labels(plot)
plot : plot id of object that controlls the lable bar
'''
lstride = ngl.get_integer(plot, "lbLabelStride")
label = ngl.get_string_array(plot, "lbLabelStrings")
fun_code = ngl.get_string(plot, "lbLabelFuncCode")
pi_str = fun_code.join(["", "F33", "p"])
pi_half_str = fun_code.join(["", "H2V15F33", "p", "H-15V-1", "_",
"H-16V-30", "2"])
label[::lstride] = ["-" + pi_str, "-" + pi_half_str, "0",
pi_half_str, pi_str]
rlist = {"cnExplicitLabelBarLabelsOn": True,
"lbLabelStrings": label}
_set_values(plot, rlist)
res.tiMainString = "ICON grid - raster fill"
res.tiMainOffsetYF = 0.03 #-- move main title towards plot
#-- create the contour plot to retrieve levels and colors
plot = Ngl.contour_map(wks,var,res)
Ngl.draw(plot)
Ngl.frame(wks)
del(levels)
#========== second plot ============
#-- retrieve the colors and levels from contour plot
levels = list(Ngl.get_float_array(plot.contour,"cnLevels"))
labels = list(Ngl.get_string_array(plot.contour,"cnLevels"))
nlevels = len(levels)
#-- define colormap (RGB value range 0-255)
colormap255 = np.array([[ 0, 0, 0], [255, 255, 255], [ 80, 255, 255], \
[ 27, 44, 98], [ 45, 102, 175], [ 66, 133, 196], \
[ 90, 166, 217], [119, 189, 230], [148, 211, 243], \
[215, 239, 249], [237, 248, 252], [255, 255, 255], \
[254, 248, 218], [253, 208, 107], [253, 167, 49], \
[247, 124, 43], [231, 75, 41], [203, 30, 38], \
[146, 21, 25]], int)
ncol = colormap255.shape[0] #-- number of colors
colormap = np.array(colormap255)/255. #-- convert to RGB value range 0.0-1.0
#-- open a workstation for second plot: triangles plot
#
# Open a workstation and draw a contour plot.
#
wks_type = "ps"
wks = Ngl.open_wks(wks_type,"cns01p")
res = Ngl.Resources()
res.cnMonoLineDashPattern = False
plot1 = Ngl.contour(wks,T,res)
#
# Retrieve the automatically set line labels.
# These will be: ['-80', '-60', '-40', '-20', '0', '20', '40', '60', '80']
#
line_labels1 = Ngl.get_string_array(plot1,"cnLineLabelStrings")
#
# Set explicit line labels. Notice that the dash line
# setting carries over from the first plot.
#
res.cnExplicitLineLabelsOn = True
res.cnLineLabelStrings = ["Lab1", "Lab2", "Lab3", "Lab4", "Lab5",
"Lab6", "Lab7", "Lab8", "Lab9"]
plot2 = Ngl.contour(wks,T,res)
#
# Retrieve the explicitly set line labels.
# These will be: ['Lab1', 'Lab2', 'Lab3', 'Lab4', 'Lab5',
# 'Lab6', 'Lab7', 'Lab8', 'Lab9']
#
#
# Open a workstation and draw a contour plot.
#
wks_type = "png"
wks = Ngl.open_wks(wks_type, "cns01p")
res = Ngl.Resources()
res.cnMonoLineDashPattern = False
plot1 = Ngl.contour(wks, T, res)
#
# Retrieve the automatically set line labels.
# These will be: ['-80', '-60', '-40', '-20', '0', '20', '40', '60', '80']
#
line_labels1 = Ngl.get_string_array(plot1, "cnLineLabelStrings")
#
# Set explicit line labels. Notice that the dash line
# setting carries over from the first plot.
#
res.cnExplicitLineLabelsOn = True
res.cnLineLabelStrings = [
"Lab1", "Lab2", "Lab3", "Lab4", "Lab5", "Lab6", "Lab7", "Lab8", "Lab9"
]
plot2 = Ngl.contour(wks, T, res)
#
# Retrieve the explicitly set line labels.
# These will be: ['Lab1', 'Lab2', 'Lab3', 'Lab4', 'Lab5',
# 'Lab6', 'Lab7', 'Lab8', 'Lab9']
# Arkansas : 01, group 7
# Arkansas : 02, group 8
# Arkansas : 03, group 7
# Arkansas : 04, group 6
# Arkansas : 05, group 5
# Arkansas : 06, group 6
# Arkansas : 07, group 4
# Arkansas : 08, group 7
# Arkansas : 09, group 4
#
# From this, if you chose to use the default group numbers to color each
# climate area, then climate areas (01,03,08) would be the same color,
# (07,09) would be the same, and (04,06) would be the same, and
# 02 and 05 would each be their own color.
#
anames = Ngl.get_string_array(map,"mpAreaNames")
groups = Ngl.get_integer_array(map,"mpDynamicAreaGroups")
# Areas 659 through 1116 are the states with their climates.
# print(anames[659:1116] + ", group " + groups[659:1116])
states = ["Alabama", "Arizona", "Arkansas", "California", "Colorado",\
"Connecticut", "Delaware", "Florida", "Georgia", "Idaho",\
"Illinois", "Indiana", "Iowa", "Kansas", "Kentucky",\
"Louisiana", "Maine", "Maryland", "Massasachusetts", "Michigan",\
"Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska", \
"Nevada", "New Hampshire", "New Jersey", "New Mexico", \
"New York", "North Carolina", "North Dakota", "Ohio", \
"Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", \
"South Carolina", "South Dakota", "Tennessee", "Texas", \
"Utah", "Vermont", "Virginia", "Washington", "West Virginia",\
# Arkansas : 01, group 7
# Arkansas : 02, group 8
# Arkansas : 03, group 7
# Arkansas : 04, group 6
# Arkansas : 05, group 5
# Arkansas : 06, group 6
# Arkansas : 07, group 4
# Arkansas : 08, group 7
# Arkansas : 09, group 4
#
# From this, if you chose to use the default group numbers to color each
# climate area, then climate areas (01,03,08) would be the same color,
# (07,09) would be the same, and (04,06) would be the same, and
# 02 and 05 would each be their own color.
#
anames = Ngl.get_string_array(map, "mpAreaNames")
groups = Ngl.get_integer_array(map, "mpDynamicAreaGroups")
# Areas 659 through 1116 are the states with their climates.
# print(anames[659:1116] + ", group " + groups[659:1116])
states = ["Alabama", "Arizona", "Arkansas", "California", "Colorado",\
"Connecticut", "Delaware", "Florida", "Georgia", "Idaho",\
"Illinois", "Indiana", "Iowa", "Kansas", "Kentucky",\
"Louisiana", "Maine", "Maryland", "Massasachusetts", "Michigan",\
"Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska", \
"Nevada", "New Hampshire", "New Jersey", "New Mexico", \
"New York", "North Carolina", "North Dakota", "Ohio", \
"Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", \
"South Carolina", "South Dakota", "Tennessee", "Texas", \
"Utah", "Vermont", "Virginia", "Washington", "West Virginia",\
