def create_an_empty_map(plot_four_maps=False,ncols=None): start_year=1947 input_folder='/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta2/' letter_labels=np.array(['(a)','(b)','(c)','(d)','(e)','(f)','(g)','(h)','(i)']) field='CN' months_str='all' file_type='ice_month' pole='south' (All_data, lat, lon,z) =generate_data_file(start_year, start_year,input_folder,field, months_str,file_type,section_axes='xy',lat_lon_bounds=None) projection = 'splaea' boundinglat=-45 #boundinglat=-57.5 data_mean=None #Plot blank map. if plot_four_maps==True: for k in range(ncols): subplot(1,ncols,k+1) plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title='',\ p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat) ax=gca() text(1,1,letter_labels[k], ha='right', va='bottom',transform=ax.transAxes,fontsize=15) else: plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title='',\ p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat) m = Basemap(projection=projection, boundinglat=boundinglat, lon_0=180) #x, y = m(lon, lat) #x, y = m(0, -70) #m.scatter(x,y,3,marker='o',color='black') return [lat,lon,m]
def main():
start_year=1947
input_folder='/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta2/'
field='CN'
months=range(0,11)
file_type='ice_month'
pole='south'
(All_data, lat, lon) =generate_data_file(start_year, start_year, input_folder, field,months,file_type)
data=np.squeeze(All_data)
print data.shape
#plt.show()
#data(volcano)
volcano=data
m <- volcano
dimx <- nrow(m)
dimy <- ncol(m)
d1 <- list(x = seq(0, 1, length = dimx), y = seq(0, 1, length = dimy), z = m)
print 'Script complete'
def main():
#Clear screen
#os.system('clear')
input_folder='/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta9/'
field='CN'
pole='north'
pole=None
save_traj_data=False
input_folder='/home/Alon.Stern/Iceberg_Project/iceberg_scripts/python_scripts/size_matters_paper/Delta9_CN_1959_to_2019_all_south_xy_anomaly.mat'
(All_data, lat, lon,z) =generate_data_file(start_year, start_year, input_folder, field, months_str, file_type)
data_mean=np.squeeze(np.mean(All_data,axis=0))
data_mean=None
#Deciding on the projection.
if pole=='south':
projection = 'splaea'
boundinglat=-45
if pole=='north':
projection = 'nplaea'
boundinglat=45
if pole==None:
projection = 'lcc'
lat_1=80
lat_2=60
lat_0=63.5
lon_0=-59.
run_names=np.array(['tournadre']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta3', 'Delta9']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta2','Delta3','Delta6', 'Delta9','Delta10']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta2','Delta3', 'Delta9']) ; naming_flag='Delta'
datamap=m.scatter(Total_berg_lon,Total_berg_lat, c=Total_berg_mass0, marker='o',cmap='jet',norm=cNorm)
def main():
#Clear screen
#os.system('clear')
start_year = 1995
end_year0 = 1995
Number_of_years = 0
input_folder = '/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta9/'
second_folder = None
#field0='CN'
months_str = 'all'
constraint_name = None
months = range(0, 11)
file_type = 'ice_month'
pole = 'south'
save_Force_data = False
load_data_from_mat = False
#load_data_from_mat=True
file_path = 'processed_data/'
#mat_filename='processed_data/open_ocean_iceberg_forces.mat'
mat_filename = 'Forces_on_berg_Tournadre_1995_1995_constraints_depth_8000_to_1000.mat'
mat_filename = 'Forces_on_berg_Delta9_1995_1995_constraints_depth_8000_to_1000.mat'
mat_filename = 'Forces_on_berg_Delta9_1995_1995_constraints_lon_55_to_65_lat_82_to_78_mass_1000000000000000_to_10000000000.mat'
mat_filename = 'Forces_on_berg_Delta9_1995_1995_constraints_depth_8000_to_1000_mass_1000000000000000_to_10000000000.mat'
mat_filename = 'Forces_on_berg_Delta9_1990_1995_constraints_lat_0_to_90_depth_8000_to_1000_mass_1000000000000000_to_10000000000.mat'
color_vec = np.array([
'blue', 'red', 'green', 'grey', 'purple', 'cyan', 'magenta', 'black',
'orange', 'coral', 'yellow', 'orchid', 'black', 'orange', 'coral',
'yellow', 'orchid'
])
Force_list = np.array(['Fa', 'Fo', 'Fi', 'Fr', 'Fc', 'Fp', 'F_total'])
# The constraint has the form [field_name, lower_bonud, upper_bound]
constraint_lon_petermann = {
'Constraint_field_name': 'lon',
'lower_bound': -65,
'upper_bound': -55,
'original_values': True
} #Longitude of AB_plus_Ross
constraint_lat_petermann = {
'Constraint_field_name': 'lat',
'lower_bound': 78,
'upper_bound': 82,
'original_values': True
} #Longitude of AB_plus_Ross
constraint_depth = {
'Constraint_field_name': 'depth',
'lower_bound': 1000,
'upper_bound': 8000,
'original_values': False
}
constraints = []
constraint_mass = {
'Constraint_field_name': 'mass',
'lower_bound': 10**10,
'upper_bound': 10**15,
'original_values': False
}
constraint_lat_baffin_coast = {
'Constraint_field_name': 'lat',
'lower_bound': 30,
'upper_bound': 80,
'original_values': False
}
constraint_lat_southern_hemisphere = {
'Constraint_field_name': 'lat',
'lower_bound': -90,
'upper_bound': 0,
'original_values': False
}
#constraint_m = {'Constraint_field_name': 'mass', 'lower_bound': mass-100 , 'upper_bound': mass+100, 'original_values': True}
#constraints.append(constraint_m)
#constraints.append(constraint_lon_petermann)
#constraints.append(constraint_lat_petermann)
#constraints.append(constraint_lat_baffin_coast)
constraints.append(constraint_lat_southern_hemisphere)
constraints.append(constraint_depth)
#constraints.append(constraint_mass)
#Definging fields to be used.
field_list = np.array([
'width', 'length', 'mass', 'thickness', 'uvel', 'vvel', 'uo', 'vo',
'ui', 'vi', 'ua', 'va', 'ssh_x', 'ssh_y', 'hi'
])
root_path = '/ptmp/aas/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg'
(All_data, lat, lon, z) = generate_data_file(start_year, start_year,
input_folder, 'CN',
months_str, file_type)
data_mean = np.squeeze(np.mean(All_data, axis=0))
data_mean = None
#Plot blank map.
#plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1)
boundinglat = -45
projection = 'splaea'
m = Basemap(projection=projection, boundinglat=boundinglat, lon_0=180)
#run_names=np.array(['tournadre']) ; naming_flag='Tournadre'
run_names = np.array(['Delta1'])
naming_flag = 'Delta1'
if load_data_from_mat == False:
for k in range(1):
input_folder = root_path + '_bergs_' + run_names[k]
#subplot(2,4,k+1)
print input_folder
#Making sure the years work
(min_year,
max_year) = find_max_min_years(input_folder,
'.iceberg_trajectories.nc')
end_year = min(max_year, end_year0)
start_year = max(end_year - Number_of_years, min_year)
title1 = run_names[k] + ' (' + str(start_year) + ' to ' + str(
end_year) + ')'
Total_berg_lat = np.array([])
Total_berg_lon = np.array([])
#Total_berg_mass0=np.array([])
#initializing the Total_berg_list
Total_berg_list = {}
for k in range(len(field_list)):
Total_berg_list['Total_berg_' + field_list[k]] = np.array([])
Total_berg_list[field_list[k]] = np.array([])
#Total_berg_list['Total_berg_'+field_list[k]]=[]
count = 0
for year in range(start_year, end_year + 1):
count = count + 1
filename = '/' + str(year) + '0101.iceberg_trajectories.nc'
input_file = input_folder + filename
print input_file
#Handling lon and lat first
[Total_berg_lon, Total_berg_lat
] = generate_Total_berg_lon_lat(Total_berg_lon,
Total_berg_lat, input_file,
constraints, m)
for k in range(len(field_list)):
Total_berg_list[field_list[k]] = get_Total_berg_field(
input_file, Total_berg_list[field_list[k]],
field_list[k], constraints)
[Force_x, Force_y, Force_mod, Force_list,
mass] = calculate_forces(Total_berg_list, Total_berg_lat)
if save_Force_data == True:
mat_filename = 'Forces_on_berg_' + naming_flag + '_' + str(
start_year) + '_' + str(end_year)
if constraints != None:
if len(constraints) > 0:
mat_filename = mat_filename + '_constraints'
for k in range(len(constraints)):
current_constraint = constraints[k]
constraint_name = current_constraint[
'Constraint_field_name']
lower_bound = current_constraint['lower_bound']
upper_bound = current_constraint['upper_bound']
original_values = current_constraint['original_values']
mat_filename = mat_filename + '_' + constraint_name + '_' + str(
abs(upper_bound)) + '_to_' + str(abs(lower_bound))
mat_filename = mat_filename + '.mat'
print 'Saving file: ', (file_path + mat_filename)
sc.savemat(file_path+mat_filename, {'Force_x':Force_x , 'Force_y':Force_y , 'Force_mod':Force_mod, 'mass':mass, 'Force_list':Force_list,'Total_berg_lat':Total_berg_lat,\
'Total_berg_lon':Total_berg_lon})
if load_data_from_mat == True:
print 'Loading file: ', mat_filename
mat_contents = sc.loadmat(file_path + mat_filename)
Force_x = mat_contents['Force_x'][0][0]
Force_y = mat_contents['Force_y'][0][0]
Force_mod = mat_contents['Force_mod'][0][0]
#Force_list=mat_contents['Force_list'][:]
Total_berg_lon = mat_contents['Total_berg_lon'][:]
Total_berg_lat = mat_contents['Total_berg_lat'][:]
mass = mat_contents['mass'][:]
#Converting force to acceleration
Accel_x = {}
Accel_y = {}
Accel_mod = {}
for k in range(7):
Accel_x[Force_list[k]] = Force_x[Force_list[k]] / mass
Accel_y[Force_list[k]] = Force_y[Force_list[k]] / mass
Accel_mod[Force_list[k]] = Force_mod[Force_list[k]] / mass
#Calculating the mean and std of each force
ind_list = np.arange(7)
Force_x_mean = ind_list * 0.
Force_y_mean = ind_list * 0.
Force_mod_mean = ind_list * 0.
Accel_x_mean = ind_list * 0.
Accel_y_mean = ind_list * 0.
Accel_mod_mean = ind_list * 0.
Force_x_std = ind_list * 0.
Force_y_std = ind_list * 0.
Force_mod_std = ind_list * 0.
Accel_x_std = ind_list * 0.
Accel_y_std = ind_list * 0.
Accel_mod_std = ind_list * 0.
for k in range(7):
Force_x_mean[k] = np.mean(Force_x[Force_list[k]])
Force_y_mean[k] = np.mean(Force_y[Force_list[k]])
Force_mod_mean[k] = np.mean(Force_mod[Force_list[k]])
Accel_x_mean[k] = np.mean(Accel_x[Force_list[k]])
Accel_y_mean[k] = np.mean(Accel_y[Force_list[k]])
Accel_mod_mean[k] = np.mean(Accel_mod[Force_list[k]])
Force_x_std[k] = np.std(Force_x[Force_list[k]])
Force_y_std[k] = np.std(Force_y[Force_list[k]])
Force_mod_std[k] = np.std(Force_mod[Force_list[k]])
Accel_x_std[k] = np.std(Accel_x[Force_list[k]])
Accel_y_std[k] = np.std(Accel_y[Force_list[k]])
Accel_mod_std[k] = np.std(Accel_mod[Force_list[k]])
plot_map_traj = True
if plot_map_traj == True:
#plt.figure(3)
ax1 = subplot(1, 1, 1)
plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=''\
,p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat )
m.scatter(Total_berg_lon,
Total_berg_lat,
1,
marker='o',
color=color_vec[k])
#F_max_lim=10**12
F_max_lim = 10**-4
F_min_lim = -10**-4
#F_min_lim=10**(-10)
do_scatter_plot = False
if do_scatter_plot == True:
plt.figure(2)
for k in range(7):
#for k in np.array([4,5]):
#A=Force_y[Force_list[k]]
#print Force_list[k],'max', np.max(A,axis=1) ,'min',np.min(A,axis=1)
ax = subplot(3, 3, k + 1)
ax.scatter(mass[:],
Accel_y[Force_list[k]][:],
color=color_vec[k],
label=Force_list[k])
#plt.plot(mass[:],Accel_y[Force_list[k]][:])
plt.ylim([F_min_lim, F_max_lim])
#ax.set_xscale('log')
#ax.set_yscale('log')
#plt.legend(loc='upper left', frameon=True)
plt.xlabel('Mass (kg)')
plt.ylabel('Force (N)')
plot_bar_graph = False
if plot_bar_graph == True:
plt.figure(3)
label_list = np.array(['Force_x', 'Force_y', 'Accel_x', 'Accel_y'])
Mean_Force_and_Accel = {
'Force_x': Force_x_mean,
'Force_y': Force_y_mean,
'Accel_x': Accel_x_mean,
'Accel_y': Accel_y_mean
}
for k in range(4):
ax = subplot(2, 2, k + 1)
width = 3
#ax.bar(ind+((bar_width/2)*j), mean_list[:,j],width=width/2,color=color_vec[j],label=sector_title_list[j])
#ax.bar(ind_list,Force_x_mean)
ax.bar(ind_list,
Mean_Force_and_Accel[label_list[k]],
width=width / 3,
label=label_list[k])
plt.title(label_list[k])
ax.set_xticks(ind_list + 0.5)
ax.set_xticklabels(Force_list)
#output_file= 'figures/traj_plot_' + str(start_year)+ '_to_' + str(end_year) + '_with_' + run_names[k] + '.png'
#plt.savefig(output_file, dpi=150, bbox_inches='tight', pad_inches=0.4)
plt.show()
print 'Script complete'
def main():
#Clear screen
#os.system('clear')
start_year=1915
end_year0=2019
Number_of_years=0
input_folder='/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta9/'
second_folder=None
field='CN'
months_str='all'
constraint_name=None
months=range(0,11)
file_type='ice_month'
pole='north'
save_traj_data=False
color_vec=np.array(['blue', 'red', 'green', 'grey','purple', 'cyan', 'magenta', 'black', 'orange', 'coral', 'yellow', 'orchid', 'black', 'orange', 'coral', 'yellow', 'orchid' ])
# The constraint has the form [field_name, lower_bonud, upper_bound]
#constraint1=np.array(['lat',-65.,-10.]) # Latituds north of -60 in the southern hemisphere
constraint_depth = {'Constraint_field_name': 'depth', 'lower_bound': 3000 , 'upper_bound': 8000, 'original_values': True}
constraint_dist_from_calving = {'Constraint_field_name': 'distance_from_calving', 'lower_bound': 1000000 , 'upper_bound': 10000000000000, 'original_values': False}
constraint2 = {'Constraint_field_name': 'lon', 'lower_bound': -150 , 'upper_bound': -65, 'original_values': True} #Longitude of AB
constraint3 = {'Constraint_field_name': 'lon', 'lower_bound': -210 , 'upper_bound': -65, 'original_values': True} #Longitude of AB_plus_Ross
constraint_SH = {'Constraint_field_name': 'lat', 'lower_bound': -90 , 'upper_bound': 0, 'original_values': True} #age
constraint_age = {'Constraint_field_name': 'age', 'lower_bound': 30 , 'upper_bound': 300, 'original_values': True} #age
constraints=[]
#mass=3.9e11 ;constraint_name='massD9'
#mass=8.8e7 ;constraint_name='massD1'
#constraint_m = {'Constraint_field_name': 'mass', 'lower_bound': mass-100 , 'upper_bound': mass+100, 'original_values': True}
#constraints.append(constraint2) ; constraint_name='AB'
#constraints.append(constraint3) ; constraint_name='AB_plus_Ross'
#constraints.append(constraint4)
#constraints.append(constraint_m)
#constraints.append(constraint_depth)
#constraints.append(constraint_dist_from_calving)
#constraints.append(constraint_age)
#constraints.append(constraint_SH)
#plot_multiple_panels==1:
constraint2 = {'Constraint_field_name': 'lon', 'lower_bound': -150 , 'upper_bound': -65, 'original_values': True} #Longitude of AB
root_path='/ptmp/aas/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg'
(All_data, lat, lon,z) =generate_data_file(start_year, start_year, input_folder, field, months_str, file_type)
data_mean=np.squeeze(np.mean(All_data,axis=0))
data_mean=None
#run_names=np.array(['freq','all_big', 'mass', 'all_small']) ; naming_flag='groups'
#run_names=np.array(['Delta1', 'Delta2', 'Delta3', 'Delta6', 'Delta9','Delta10']) ; naming_flag='Delta'
#run_names=np.array(['Delta1' ,'Delta10','Delta1_thick', 'Delta10_thick', 'Delta1b_thick', 'Delta10b_thick']) ; naming_flag='Thick'
#run_names=np.array(['Delta6', 'Delta6','Delta9']) ; naming_flag='Delta'
run_names=np.array(['tournadre']) ; naming_flag='Delta'
#run_names=np.array(['Delta1','Delta3','Delta4','Delta5', 'Delta6','Delta9']) ; naming_flag='Delta'
for k in range(1):
input_folder=root_path + '_bergs_' + run_names[k]
subplot(1,1,k)
print input_folder
#Making sure the years work
(min_year, max_year)=find_max_min_years(input_folder,'.iceberg_trajectories.nc')
end_year=min(max_year,end_year0)
start_year=max(end_year-Number_of_years,min_year)
title1= run_names[k] + ' (' + str(start_year) + ' to ' + str(end_year) + ')'
#Plot blank map.
if pole=='south':
projection = 'splaea'
boundinglat=-45
if pole=='north':
projection = 'nplaea'
boundinglat=45
projection = 'nplaea'
plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1\
,p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat)
m = Basemap(projection=projection, boundinglat=boundinglat, lon_0=180)
print 'You are here'
print projection
count=0
Total_berg_lat=np.array([])
Total_berg_lon=np.array([])
Total_berg_mass0=np.array([])
for year in range(start_year, end_year+1):
count=count+1
filename ='/' + str(year) + '0101.iceberg_trajectories.nc'
input_file=input_folder + filename
print input_file
all_bergs_lat = get_valid_data_from_traj_file(input_file,'lat')
all_bergs_lon = get_valid_data_from_traj_file(input_file,'lon')
all_bergs_mass0 = get_valid_data_from_traj_file(input_file,'mass',subtract_orig=False,get_original_values=True) # Getting iceberg mass too.
#Adding constraints to the data:
print 'Lendth of original field: ' , len(all_bergs_lat)
all_bergs_lat=add_constraint_to_data(input_file,all_bergs_lat,constraints)
all_bergs_lon=add_constraint_to_data(input_file,all_bergs_lon,constraints)
all_bergs_mass0=add_constraint_to_data(input_file,all_bergs_mass0,constraints)
print 'Lendth of field after constraints: ' , len(all_bergs_lat)
x, y = m(all_bergs_lon, all_bergs_lat)
plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1\
,p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat)
m.scatter(x,y,3,marker='o',color=color_vec[k])
#plt.plot(all_bergs_lon,all_bergs_lat,'o')
Total_berg_lon=np.concatenate((Total_berg_lon,x),axis=0)
Total_berg_lat=np.concatenate((Total_berg_lat,y),axis=0)
Total_berg_mass0=np.concatenate((Total_berg_mass0,all_bergs_mass0),axis=0)
if save_traj_data==True:
save_traj_mat_file(lat,lon, Total_berg_lon, Total_berg_lat, Total_berg_mass0, pole,input_folder,start_year,end_year,months_str,constraint_name)
#plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1)
#m.scatter(Total_berg_lon,Total_berg_lat,1,marker='o',color=color_vec[k])
output_file= 'figures/traj_plot_' + str(start_year)+ '_to_' + str(end_year) + '_with_' + run_names[k] + '.png'
#plt.savefig(output_file, dpi=150, bbox_inches='tight', pad_inches=0.4)
plt.show()
print 'Script complete'
def main():
#Clear screen
#os.system('clear')
start_year=1915
end_year0=1992
Number_of_years=0
input_folder='/ptmp/Alon.Stern/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg_bergs_Delta9/'
second_folder=None
field='CN'
months_str='all'
constraint_name=None
months=range(0,11)
file_type='ice_month'
pole='north'
pole=None
save_traj_data=False
Title_list={'Delta1':'$L_{0}=60m$','Delta2':'$L_{0}=100m$','Delta3':'$L_{0}=200m$','Delta4':'$L_{0}=350m$','Delta5':'$L_{0}=500m$',\
'Delta6':'$L_{0}=700m$','Delta7':'$L_{0}=900m$','Delta8':'$L_{0}=1200m$','Delta9':'$L_{0}=1600m$','Delta10':'$L_{0}=2200m$'}
color_vec=np.array(['blue', 'red', 'green', 'grey','purple', 'cyan', 'magenta', 'black', 'orange', 'coral', 'yellow', 'orchid', 'black', 'orange', 'coral', 'yellow', 'orchid' ])
cNorm = mpl.colors.LogNorm(vmin=8.8e7, vmax=7.4e11)
plot_each_time=False
# The constraint has the form [field_name, lower_bonud, upper_bound]
#constraint1=np.array(['lat',-65.,-10.]) # Latituds north of -60 in the southern hemisphere
constraint_depth = {'Constraint_field_name': 'depth', 'lower_bound': 3000 , 'upper_bound': 8000, 'original_values': True}
constraint_dist_from_calving = {'Constraint_field_name': 'distance_from_calving', 'lower_bound': 1000000 , 'upper_bound': 10000000000000, 'original_values': False}
constraint_lon_Rink = {'Constraint_field_name': 'lon', 'lower_bound': -55 , 'upper_bound': -45, 'original_values': True} #Longitude of Rink
constraint_lat_Rink = {'Constraint_field_name': 'lat', 'lower_bound': 70.75 , 'upper_bound': 72.75, 'original_values': True} #Longitude of Rink
constraints=[]
#mass=3.9e11 ;constraint_name='massD9'
#mass=8.8e7 ;constraint_name='massD1'
#constraint_m = {'Constraint_field_name': 'mass', 'lower_bound': mass-100 , 'upper_bound': mass+100, 'original_values': True}
#constraints.append(constraint2) ; constraint_name='AB'
#constraints.append(constraint3) ; constraint_name='AB_plus_Ross'
#constraints.append(constraint4)
#constraints.append(constraint_m)
#constraints.append(constraint_depth)
#constraints.append(constraint_dist_from_calving)
constraints.append(constraint_lon_Rink)
constraints.append(constraint_lat_Rink)
#constraints.append(constraint_SH)
#plot_multiple_panels==1:
constraint2 = {'Constraint_field_name': 'lon', 'lower_bound': -150 , 'upper_bound': -65, 'original_values': True} #Longitude of AB
root_path='/ptmp/aas/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg'
(All_data, lat, lon,z) =generate_data_file(start_year, start_year, input_folder, field, months_str, file_type)
data_mean=np.squeeze(np.mean(All_data,axis=0))
data_mean=None
#Deciding on the projection.
if pole=='south':
projection = 'splaea'
boundinglat=-45
if pole=='north':
projection = 'nplaea'
boundinglat=45
if pole==None:
projection = 'lcc'
lat_1=80
lat_2=60
lat_0=63.5
lon_0=-59.
run_names=np.array(['tournadre']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta3', 'Delta9']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta2','Delta3','Delta6', 'Delta9','Delta10']) ; naming_flag='Delta'
run_names=np.array(['Delta1' ,'Delta3', 'Delta9']) ; naming_flag='Delta'
nrows=1 ;ncols=3
fig, axes = plt.subplots(nrows=nrows, ncols=ncols)
for k in range(ncols*nrows):
input_folder=root_path + '_bergs_' + run_names[k]
subplot(nrows,ncols,k+1)
print input_folder
#Making sure the years work
(min_year, max_year)=find_max_min_years(input_folder,'.iceberg_trajectories.nc')
end_year=min(max_year,end_year0)
start_year=max(end_year-Number_of_years,min_year)
title1= run_names[k] + ' (' + str(start_year) + ' to ' + str(end_year) + ')'
#plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1\
# ,p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat)
if pole==None:
m = Basemap(width=1750000,height=4300000, rsphere=(6378137.00,6356752.3142),resolution='l',area_thresh=1000.,\
projection=projection,lat_1=lat_1,lat_2=lat_2,lat_0=lat_0,lon_0=lon_0)
else:
m = Basemap(projection=projection, boundinglat=boundinglat, lon_0=180)
m.drawcoastlines()
m.fillcontinents(color='grey',lake_color='white')
count=0
Total_berg_lat=np.array([])
Total_berg_lon=np.array([])
Total_berg_mass0=np.array([])
for year in range(start_year, end_year+1):
count=count+1
filename ='/' + str(year) + '0101.iceberg_trajectories.nc'
input_file=input_folder + filename
print input_file
all_bergs_lat = get_valid_data_from_traj_file(input_file,'lat')
all_bergs_lon = get_valid_data_from_traj_file(input_file,'lon')
all_bergs_mass0 = get_valid_data_from_traj_file(input_file,'mass',subtract_orig=False,get_original_values=True) # Getting iceberg mass too.
#Adding constraints to the data:
print 'Lendth of original field: ' , len(all_bergs_lat)
all_bergs_lat=add_constraint_to_data(input_file,all_bergs_lat,constraints)
all_bergs_lon=add_constraint_to_data(input_file,all_bergs_lon,constraints)
all_bergs_mass0=add_constraint_to_data(input_file,all_bergs_mass0,constraints)
print 'Lendth of field after constraints: ' , len(all_bergs_lat)
x, y = m(all_bergs_lon, all_bergs_lat)
if plot_each_time==True:
plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1\
,p_values=None,cscale=None,field=None,colorbar_on=True,return_data_map=False,plot_lat_lon_lines=True,boundinglat=boundinglat)
m.scatter(x,y,3,marker='o',color=color_vec[k])
#plt.plot(all_bergs_lon,all_bergs_lat,'o')
Total_berg_lon=np.concatenate((Total_berg_lon,x),axis=0)
Total_berg_lat=np.concatenate((Total_berg_lat,y),axis=0)
Total_berg_mass0=np.concatenate((Total_berg_mass0,all_bergs_mass0),axis=0)
datamap=m.scatter(Total_berg_lon,Total_berg_lat, c=Total_berg_mass0, marker='o',cmap='jet',norm=cNorm)
if run_names[k]=='tournadre':
cbar=fig.colorbar(datamap)
cbar.set_label('Calving Mass (kg)')
else:
plt.title(Title_list[run_names[k]])
if save_traj_data==True:
save_traj_mat_file(lat,lon, Total_berg_lon, Total_berg_lat, Total_berg_mass0, pole,input_folder,start_year,end_year,months_str,constraint_name)
#plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=title1)
#m.scatter(Total_berg_lon,Total_berg_lat,1,marker='o',color=color_vec[k])
output_file= 'figures/Leigh_Rink_figure2.png'
#output_file= 'figures/Northern_Trajectories_tournadre.png'
#output_file= 'figures/Northern_Trajectories_Deltas.png'
fig.set_size_inches(21.0, 8.5,forward=True)
plt.savefig(output_file, dpi=150, bbox_inches='tight', pad_inches=0.4)
plt.show()
print 'Script complete'
def main():
#Clear screen
#os.system('clear')
start_year=1980
end_year0=1980
field='melt'
months_str='all'
months=range(0,11)
file_type='icebergs'
pole='south'
Number_of_years=20
color_vec=np.array(['blue', 'red', 'green', 'grey','purple', 'cyan', 'magenta', 'black', 'orange', 'coral', 'yellow', 'orchid', 'black', 'orange', 'coral', 'yellow', 'orchid' ])
second_folder=None
distribution=np.array([0.24, 0.12, 0.15, 0.18, 0.12, 0.07, 0.03, 0.03, 0.03, 0.02])
initial_mass=np.array([8.8e7, 4.1e8, 3.3e9, 1.8e10, 3.8e10, 7.5e10, 1.2e11, 2.2e11, 3.9e11, 7.4e11])
Total_mass=np.sum(distribution*initial_mass)
#plot_multiple_panels==1:
root_path='/ptmp/aas/model_output/ulm_mom6_2015.07.20_again_myIcebergTag/AM2_LM3_SIS2_MOM6i_1deg'
#run_names=np.array(['freq','all_big', 'mass', 'all_small']) ; naming_flag='groups'
#run_names=np.array(['Delta1', 'Delta2', 'Delta3', 'Delta6', 'Delta9','Delta10']) ; naming_flag='Delta'
run_names=np.array(['Delta1', 'Delta2', 'Delta3','Delta4','Delta5','Delta6','Delta7', 'Delta8', 'Delta9','Delta10']) ; naming_flag='Delta'
#run_names=np.array(['Delta1', 'Delta9']) ; naming_flag='Delta'
Number_of_files=10
multi_berg_run_name='freq'
if multi_berg_run_name=='freq':
weights=np.zeros((10,1))
for i in range(10):
weights[i]=distribution[i]*initial_mass[i]/Total_mass
print sum(weights)
count=-1
for k in range(Number_of_files):
count=count+1
input_folder=root_path + '_bergs_' + run_names[k]
(min_year, max_year)=find_max_min_years(input_folder,'.' + file_type + '_month.nc')
end_year=max_year
start_year=max(end_year-Number_of_years+1,min_year)
(All_data, lat, lon) =generate_data_file(start_year, end_year, input_folder, field,months,file_type)
data_mean=np.squeeze(np.mean(All_data,axis=0))
#Set up the matrix on the first time around
if count==0:
M=data_mean.shape
Big_data_matrix=np.zeros((Number_of_files,M[0],M[1]))
Big_data_matrix[count,:,:]=data_mean
linear_sum_data=construct_linear_sum(Big_data_matrix,weights)
#Getting the data for the multi_berg_run
input_folder=root_path + '_bergs_' + multi_berg_run_name
(min_year, max_year)=find_max_min_years(input_folder,'.' + file_type + '_month.nc')
end_year=max_year
start_year=max(end_year-Number_of_years+1,min_year)
(All_data, lat, lon) =generate_data_file(start_year, end_year, input_folder, field,months,file_type)
data_mean=np.squeeze(np.mean(All_data,axis=0))
relative_error=(data_mean-linear_sum_data)#/data_mean
#ralative_error=relative_error*np.where(data_mean!=0)
#Plotting the linear sum
subplot(1,3,1)
plot_polar_field(lat,lon,linear_sum_data,pole,difference_on=0.,title='linear combination',p_values=None,cscale=None,field=field)
subplot(1,3,2)
plot_polar_field(lat,lon,data_mean,pole,difference_on=0.,title=multi_berg_run_name,p_values=None,cscale=None,field=field)
subplot(1,3,3)
plot_polar_field(lat,lon,-relative_error,pole,difference_on=0.,title='relative_error',p_values=None,cscale=None,field=field)
output_file='linearity_test_neg' + multi_berg_run_name + '.png'
plt.savefig(output_file, dpi=150, bbox_inches='tight', pad_inches=0.4)
plt.show()
print 'Script complete'