-
Notifications
You must be signed in to change notification settings - Fork 0
/
movie_pancakeconc.m
288 lines (264 loc) · 10.5 KB
/
movie_pancakeconc.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
% movie_pancakeconc is a script that will produce movies of pancake ice
% given a defintion.
% Definition 1: Areal ice concentration in FSD cat 1 and ITD cat 1.
% Definition 2: Areal ice concentration in FSD cat 1 and ITD cat 1/ aice.
% Definition 2: Areal ice concentration in FSD cat 16 and ITD cat 5/ aice.
%% Case info
clear all
clc
close all
addpath functions
pancake_def = [2];
plot_type = "univariate"; % Just plot a single def
% bivariate takes the difference pancake_def(1)-pancake_def(2);
historydir = '/Users/noahday/GitHub/CICE-plotting-tools/cases/monthwim/history/';
sector = "SH";
user = "noahday";
%'/Users/noahday/GitHub/CICE-plotting-tools/cases/monthwim/history/';
% '/Volumes/NoahDay5TB/cases/monthwim/history/';
a = dir([historydir '/*.nc']);
n_files = numel(a);
for i = 1:n_files
filenames(i,:) = strcat(historydir,a(i).name);
dirdates(i,:) = a(i).name(6:end-3);
end
% Get the data
SIC = 0.01;
pancakeconc(:,:,:)= get_pancakes(pancake_def,n_files,filenames,SIC,plot_type);
% Plotting
clear writerObj
video_name = strcat("pan_def2", '_', "monthwim", '_', '2022_06_17', '.mp4');
writerObj = VideoWriter(video_name,'MPEG-4');
set(writerObj,'FrameRate',n_files/20); % 0.5 = 2 seconds per frame
%writerObj.Quality = 70;
% open the writer
open(writerObj);
% Plotting and saving
clear C2
month_strings = ["Jan. 2005","Feb. 2005","Mar. 2005","Apr. 2005","May 2005","June 2005","July 2005","Aug. 2005","Sep. 2005","Oct. 2005","Nov. 2005","Dec. 2005","Jan. 2006","Feb. 2006","Mar. 2006","Apr. 2006","May 2006","June 2006","July 2006","Aug. 2006","Sep. 2006","Oct. 2006","Nov. 2006","Dec. 2006","Jan. 2007","Feb. 2007","Mar. 2007","Apr. 2007","May 2007","June 2007","July 2007","Aug. 2007","Sep. 2007","Oct. 2007","Nov. 2007","Dec. 2007","Jan. 2008","Feb. 2008","Mar. 2008","Apr. 2008","May 2008","June 2008","July 2008","Aug. 2008","Sep. 2008","Oct. 2008","Nov. 2008","Dec. 2008","Jan. 2009","Feb. 2009","Mar. 2009","Apr. 2009","May 2009","June 2009","July 2009","Aug. 2009","Sep. 2009","Oct. 2009","Nov. 2009","Dec. 2009"];
for i = 1:n_files
basicwaitbar(i,n_files,"Plotting and saving")
% Plot the map
conFigure(30,1.1)
%set(gcf, 'Position', [0, 0, 1782, 1830])
f = figure;
if plot_type == "univariate"
[p,a] = map_plot(pancakeconc(:,:,i),"aice",sector);
%C = colormap(cool(20));
C = cmocean('thermal',10);
C2 = C;
% For 'cool'
%C2(:,1) = sqrt(C(:,1));
%C2(:,2) = (C(:,2)).^2;
%C2(:,3) = sqrt(C(:,3));
%C2(1,:) = ones(1,3); % 0.05 and less is considered white!
%C2(2,:) = C(1,:);
%C2(2:end,:) = C(1:end-1,:);
colormap(C2)
else
[p,a] = map_plot(pancakeconc(:,:,i),"aice",sector,"gx1",[-0.5,0.5]);
C = cmocean('balance',20);
colormap(C)
end
% INCLUDE IF DEF = x then the label is y
a.Label.String = "Pancake ice concentration/aice";
title(month_strings(i),'Interpreter','latex')
figname = sprintf('image%d.png', i);
filedir = sprintf('/Users/%s/GitHub/CICE-plotting-tools/frames', user);
%exportgraphics(f,figname,'ContentType','vector')
saveas(f,fullfile(filedir, figname));
close(f)
end
% iterate over each image
for k=1:n_files
% use imread to read the image
figname = sprintf('frames/image%d.png',k);
img = imread(figname);
% resize the imagei_vec
%img = imresize(img,2);
% convert the image to a frame using im2frame
frame = im2frame(img);
% write the frame to the video
%[height width ~] = size(frame.cdata);
%writerObj.Height = height;
%writerObj.Width = width;
writeVideo(writerObj,frame);
end
% close the writer
close(writerObj);
%% Ice thickness
aice = data_format_sector(filenames(21,:),"aice",sector);
ice_mask = aice > SIC;
hi(:,:) = data_format_sector(filenames(21,:),"hi",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = hi;
% apply mask
temp(~ice_mask) = NaN;
hi(:,:) = temp;
% Plot the map
conFigure(11,1.1)
%set(gcf, 'Position', [0, 0, 1782, 1830])
f = figure;
[p,a] = map_plot(hi(:,:),"hi",sector,"gx1",[0,3]);
a.Label.String = "Ice thickness [m]";
exportgraphics(f,'hi.pdf','ContentType','vector')
%% FSDrad
[lat lon] = grid_read("gx1");
aice = data_format_sector(filenames(21,:),"aice",sector);
ice_mask = aice > SIC;
hi(:,:) = data_format_sector(filenames(21,:),"fsdrad",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = hi;
% apply mask
temp(~ice_mask) = NaN;
fsdraddata(:,:) = temp;
% Plot the map
% conFigure(11,1.1)
% %set(gcf, 'Position', [0, 0, 1782, 1830])
% f = figure;
% [p,a] = map_plot(hi(:,:),"fsdrad",sector,"gx1",[0,3000]);
% colors = cmocean('thermal');
% colormap(colors(end:-1:1,:))
% a.Label.String = "Mean floe size [m]";
% exportgraphics(f,'ra.pdf','ContentType','vector')
close all
conFigure(11,1.1)
f = figure;
%[p,a] = map_plot(fsdraddata,"fsdrad",sector);
w = worldmap('world');
axesm eqaazim; %, wetch
setm(w, 'Origin', [-90 0 0]);
setm(w, 'maplatlimit', [-90,-55]);
setm(w, 'maplonlimit', [-180,-55]);
setm(w, 'meridianlabel', 'on')
setm(w, 'parallellabel', 'off')
setm(w, 'mlabellocation', 60);
setm(w, 'plabellocation', 10);
setm(w, 'mlabelparallel', -45);
setm(w, 'mlinelimit', [-75 -55]);
setm(w, 'plinelimit', [-75 -55]);
setm(w, 'grid', 'off');
%setm(w, 'frame', 'on');
setm(w, 'labelrotation', 'on')
pcolorm(lat,lon,fsdraddata)
land = shaperead('landareas', 'UseGeoCoords', true);
geoshow(w, land, 'FaceColor', [0.5 0.7 0.5])
a = colorbar;
s = scaleruler;
setm(handlem('scaleruler'), ...
'XLoc',0.3, ... '
'YLoc',-0.52, ...
'TickDir','down', ...
'MajorTick',0:1000:1000, ...
'MinorTick',0:500:500, ...
'MajorTickLength',km2nm(150),...
'MinorTickLength',km2nm(150))
a.TickLabelInterpreter = 'latex';
a.Label.Interpreter = 'latex';
a.Label.String = 'Mean floe size radius (m)';
w.ZTickLabel = 'test';
w.ColorScale = 'log';
w.FontName = 'CMU Serif';
cmocean('matter');
%colormap parula
exportgraphics(f,'fsdradsep.pdf','ContentType','vector')
%% Functions
function [data] = get_pancakes(definition,n_files,filenames,SIC,plot_type)
sector = "SH"; % Southern Hemisphere
if plot_type == "univariate"
if definition == 1
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1);
% apply mask
temp(~ice_mask) = NaN;
data(:,:,i) = temp;
end
elseif definition == 2
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1)./aice(:,:);
% apply mask
temp(~ice_mask) = NaN;
data(:,:,i) = temp;
end
elseif definition == 3 % Largest FSD
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,end,1).*NFSD(end)./aice(:,:);
% apply mask
temp(~ice_mask) = NaN;
data(:,:,i) = temp;
end
else
error('No pancake definition specified')
end
elseif plot_type == "bivariate"
% Calcualte def 1
if definition(1) == 1
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1);
% apply mask
temp(~ice_mask) = NaN;
temp1(:,:,i) = temp;
end
elseif definition(1) == 2
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1)./aice(:,:);
% apply mask
temp(~ice_mask) = NaN;
temp1(:,:,i) = temp;
end
end
if definition(2) == 1 % Calculate def 2
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1);
% apply mask
temp(~ice_mask) = NaN;
temp2(:,:,i) = temp;
end
elseif definition(2) == 2
for i = 1:n_files
NFSD = ncread(filenames(1,:),"NFSD");
aice = data_format_sector(filenames(i,:),"aice",sector);
ice_mask = aice > SIC;
afsdn(:,:,:,:) = data_format_sector(filenames(i,:),"afsdn",sector);
% Define pancakes as the thinnest NCAT and smallest NFSD
temp(:,:) = afsdn(:,:,1,1).*NFSD(1)./aice(:,:);
% apply mask
temp(~ice_mask) = NaN;
temp2(:,:,i) = temp;
end
end
data(:,:,:) = temp1 - temp2;
else
error('No plot_type specified.')
end
end