source: trunk/UTIL/PYTHON/README.PP @ 402

Last change on this file since 402 was 394, checked in by aslmd, 13 years ago

GRAPHIcs: pp.py: no winds is now default. use option -W to get winds. no more option -x.

File size: 6.2 KB
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1**************************************
2**************************************
3**************************************
4    PLANETOPLOT TUTORIAL EXAMPLES
5**************************************
6         Authors : AC + AS
7**************************************
8  DON'T FORGET YOUR BEST FRIEND IS
9     pp.py -h [or] pp.py --help
10**************************************
11**************************************
12**************************************
13
14
15*************************************
16MAPMODE 1
17MAPPING MODE
18SIMPLE EXAMPLES on a SAMPLE GCM FILE
19*************************************
20
21Goal: The simplest, most minimal example. Mapping topography.
22pp.py -f diagfired.nc
23
24Goal: I would like finer contours.
25pp.py -f diagfired.nc --div 30
26
27Goal: I would like wind vectors.
28pp.py -f diagfired.nc -W
29
30Goal: I would like more vectors [i.e. lower the stride].
31pp.py -f diagfired.nc -W -s 1
32
33Goal: I want to map a given field (surface temperature).
34pp.py -f diagfired.nc -v tsurf
35
36Goal: I want to map two fields next to one another (topography and tauice).
37pp.py -f diagfired.nc -v phisinit,tauice
38
39Goal: I want to map two fields, tauice shaded, topography contoured, same plot.
40pp.py -f diagfired.nc -v tauice -w phisinit
41
42Goal: I want to map a field but projected on the sphere.
43pp.py -f diagfired.nc -v tauice -p ortho
44
45Goal: I want to redefine the minimum and maximum values shown.
46pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9
47
48Goal: I want to insert holes wherever values are lower than 0.2 and higher than 0.9
49pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9 -H
50
51Goal: I want to fill holes with an background image of Mars [you have to be connected to Internet]
52pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9 -H -b vishires
53
54Goal: I want the same map, but projected on the sphere
55pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9 -H -b vishires -p ortho
56
57Goal: I want the same map, but projected with north polar stereographic view
58pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9 -H -b vishires -p npstere
59
60Goal: I want to save this in PNG format
61pp.py -f diagfired.nc -v tauice -m 0.2 -M 0.9 -H -b vishires -p ortho -S png
62
63Goal: I want to plot results from two simulation files next to one another
64pp.py -f diagfired.nc,diagfired.nc -x -v tsurf
65
66***********************************************************************************
67Simple 2D plot: Zonal mean.
68**********************************************************************************
69
70Goal:
71
72Plot the zonal mean temperature from a netcdf fiel representing one month.
73
74Command:
75
76gcm.py -f POLAR_NIGHT_RUN/diagfi16.nc --var temp --lon 180,-180 --time 0,65
77
78Note:
79
80The --time, --lat, --lon and --vert command takes in input values corresponding to the unit stored in the netcdf file, and not indices ! For example, if the "Time" unit is in sol (which is common for a gcm output), --time 2 means sol 2.0 and not index 2 along the time direction. Consequently, one can ask --time 2.5 for temperatures at 12:00 on sol 2.
81
82Means are easy to perform by specifying a range. Here: --time 0,65 and --lat -180,180.
83
84***********************************************************************************
85Vertical interpolation of the field.
86***********************************************************************************
87
88Goal:
89
90Calls to zrecast and api are built-in the python functions. One can call them using -i with the appropriate argument (see meso.py -h or gcm.py -h). Here is an example that re-interpolates data using zrecast before plotting it in a 2D contour.
91
92Command:
93
94gcm.py -f POLAR_NIGHT_RUN/diagfi16.nc --var temp --lon -180,180 --time 0,65 -i 4
95
96Note:
97
98All interpolation modes available in zrecast and api (pressure, AGL, distance from planet center, etc...) are theoretically possible, but may not be coded yet in the routine. See gcm.py -h or meso.py -h.
99
100For this example, the default behavior of zrecast for -i 4 is to interpolate in (m) from the local surface, between 0 and 150 km. The command will generate a reinterpolated netcdf file "POLAR_NIGHT_RUN/diagfi16_S.nc" with only the requested field, which is not deleted afterward.
101
102
103***********************************************************************************
1042D plot of the difference between two files.
105***********************************************************************************
106
107Goal:
108
109Comparing two .nc files with similar dimension axis can be done in a single command, by specifying which files to compare and the comparison operator (i.e. is it a difference, an addition, etc...). When comparing data along a vertical axis, it can be wise to also ask for an interpolation of the fields to make sure the comparison is correct.
110
111Command:
112
113gcm.py -f POLAR_NIGHT_RUN/stats16.nc --var temp --lon -180,180 --time 1 -i 4 --fref POLAR_NIGHT_REF/stats16.nc --operation - --mope -2 --Mope 2 --title "Polar temperatures with new parametrizations" --titleref "Reference run"
114
115Note:
116
117The command will output 3 plots: the field from file 1, the field from file 2, and the comparison between the two. One can specify specific names for the title of these plots by using --title and --titleref for the titles of file 1 and file 2, and can specify different plotting range for the normal field (-m -M) and the compared field (--mope --Mope).
118
119One can combine this command with projections and means, so that for example, to compare co2 depletion at the south pole:
120
121gcm.py -f POLAR_NIGHT_RUN/start16.nc --var co2 --vert 0,150 --proj spstere --time 1 -i 4 --fref POLAR_NIGHT_REF/start16.nc --operation - --mope -0.5 --Mope 0.5 --title "Polar co2 with new parametrizations" --titleref "Reference run"
122
123***********************************************************************************
1242D plot of data with missing values, along a pressure axis (decreasing with height).
125***********************************************************************************
126
127Goal:
128
129By default, python will force the y-axis of a 2D plot to be ordered by increasing values. Here is how to force it otherwise.
130
131Command:
132
133gcm.py -f TES.MappedClimatology.nadir.MY25.nc --var T_nadir_day --lat -76. --time 90 --ymin 500 --ymax 1 -m 128 -M 148 -H
134
135Note:
136
137The axis reversal is done by specifying ymin and ymax in the right order. One can also simply use --inverty and not specify (ymin,ymax). Missing values (out of range values) are replaced by holes by the option "-H".
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