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| #!/usr/bin/env python | |
| import numpy as np | |
| import numpy.matlib | |
| import matplotlib.pyplot as plt | |
| import matplotlib.cm as cm | |
| import matplotlib.colors as mcolors | |
| from netCDF4 import Dataset | |
| import os as os | |
| import resource | |
| from mpl_toolkits.basemap import Basemap | |
| from scipy.stats import norm | |
| def listevar(fichier): | |
| datago = Dataset(fichier, 'r') | |
| x = datago.variables.keys() | |
| print x | |
| def extraction(fichier): | |
| datago = Dataset(fichier, 'r') | |
| lg = datago.variables['longitude'][:] | |
| lt = datago.variables['latitude'][:] | |
| ti = datago.variables['time'][:] | |
| atb = datago.variables['ATB'][:,:] | |
| SR = datago.variables['instant_SR'][:,:] | |
| sol_alt = datago.variables['SE'][:] | |
| alt = datago.variables['alt_bound'][:,:] | |
| datago.close() | |
| u, v = np.shape(alt) | |
| alt_bas = alt[0,:] | |
| alt_haut = alt[1,:] | |
| alt = np.zeros((v,1)) | |
| for i in range(0,v): | |
| alt[i] = alt_bas[i] | |
| #alt[v] = alt_haut[v-1] | |
| alt = alt[:,0] | |
| return lg, lt, ti, atb,alt, sol_alt, SR | |
| def affiche(n1,n2): | |
| lt = lt[n1:n2] | |
| sol_alt = sol_alt[n1:n2] | |
| u,v = np.shape(atb[n1:n2,:]) | |
| trait = lt[int (((n2-n1)/2))] | |
| plt.plot ([trait,trait] , [alt[0],alt[-1]],'w--',linewidth=2) | |
| plt.plot(lt, sol_alt,'w',linewidth=2) | |
| plt.pcolormesh(lt,alt,atb[n1:n2,:].T) | |
| plt.ylim(-1, 16) | |
| plt.xlim(lt[0],lt[-1]) | |
| #plt.gca().invert_xaxis() | |
| plt.clim(0, 0.005) | |
| plt.xlabel('Latitude') | |
| plt.ylabel('Altitude [km]') | |
| plt.colorbar() | |
| plt.show() | |
| def afficheSR(lg,lt,ti,atb,alt,sol_alt): | |
| n1 = 0 | |
| n2,x = np.shape(atb) | |
| lt = lt[n1:n2] | |
| sol_alt = sol_alt[n1:n2] | |
| u,v = np.shape(atb[n1:n2,:]) | |
| sol_alt = sol_alt[n1:n2] | |
| fig = plt.figure(figsize=(9, 6), dpi=100) | |
| plt.plot(lt, sol_alt,'w',linewidth=2) | |
| plt.pcolormesh(lt,alt,atb[n1:n2,:].T) | |
| plt.gca().invert_xaxis() | |
| plt.ylim(-1, 16) | |
| plt.clim(1e-5, 1e-1) | |
| plt.xlabel('Latitude') | |
| plt.ylabel('Altitude [km]') | |
| plt.colorbar() | |
| plt.show() | |
| def lonlat(n1, n2,lg,lt,ti,atb): | |
| from mpl_toolkits.basemap import Basemap | |
| m = Basemap() | |
| m.plot(lg, lt) | |
| lg = lg[n1:n2] | |
| lt = lt[n1:n2] | |
| m.plot(lg, lt, 'r') | |
| m.drawcoastlines() | |
| m.fillcontinents() | |
| plt.show() | |
| def draw(): | |
| m = Basemap() | |
| lon1 ,lon2,lat1,lat2 = -75,-90,0,15 # shallowcu | |
| #lon1 ,lon2,lat1,lat2 = 180,70,-15,15 # warmpool | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| m.plot([lon1,lon1], [lat1,lat2], lw = 2, color = 'Gold') | |
| m.plot([lon2,lon2], [lat1,lat2], lw = 2, color = 'Gold') | |
| m.plot([lon1,lon2], [lat1,lat1], lw = 2, color = 'Gold') | |
| m.plot([lon1,lon2], [lat2,lat2], lw = 2, color = 'Gold') | |
| m.bluemarble() | |
| parallels = np.arange(-90.,90,20.) | |
| m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10,color = 'Chocolate') | |
| meridians = np.arange(-180.,180.,20.) | |
| m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10, color = 'Chocolate') | |
| #m.drawcoastlines() | |
| #m.fillcontinents() | |
| #titre = 'Warmpool' | |
| titre = 'Shallowcu' | |
| path = titre + '_carte' | |
| plt.title(titre) | |
| plt.savefig(path) | |
| #plt.show() | |
| plt.close() | |
| def profil(n,lg,lt,ti,atb,alt,fichier): | |
| datago = Dataset(fichier, 'r') | |
| atmol = datago.variables['ATB_mol'][:] | |
| p1, = plt.semilogx(atb[n,:], alt) | |
| p2, = plt.semilogx(atmol[n,:], alt) | |
| plt.legend([p1,p2], ["ATB mesure","ATB moleculaire"]) | |
| #plt.xlim(1e-7, 1e-1) | |
| plt.ylim(0,20) | |
| plt.xlabel('ATB [km-1 sr-1]') | |
| plt.ylabel('Altitude [km]') | |
| plt.title('Profil ' + str(lt[n])) | |
| plt.show() | |
| def profil_SR(n,lg,lt,ti,atb,alt,fichier): | |
| plt.plot(atb[n,:], alt) | |
| plt.xlim(-0.1, 50) | |
| plt.ylim(0,20) | |
| plt.xlabel('SR') | |
| plt.ylabel('Altitude [km]') | |
| plt.title('Profil ' + str(lt[n])) | |
| plt.show() | |
| #path = fichier | |
| #path += '.png' | |
| #plt.savefig(path) | |
| #plt.close() | |
| def coord_pole(lg,lt,ti,atb, sol_alt): | |
| idx = ( lt < -60 ) & ( lt >= -90 ) | |
| lt6090 = lt[idx] | |
| lg6090 = lg[idx] | |
| ti6090 = ti[idx] | |
| sol_alt = sol_alt[idx] | |
| atb = atb [idx,:] | |
| n = len(lt6090) | |
| return n, lt6090, lg6090, ti6090,atb, sol_alt | |
| def alt_max(SR, alt, n): | |
| u, v = np.shape(SR) | |
| j = - 1 | |
| if (SR[n,0] > 0.01 or SR[n,0] < -10) or (SR[n,1] > 0.01 or SR[n,1] < -10): | |
| return j | |
| i = 2 | |
| while i < v: | |
| if (SR[n,i] > -10) and (SR[n,i] < 0.01): | |
| j = i | |
| elif (SR[n,i] > 0.01) and (SR[n,i-1] > 0.01): | |
| return j | |
| i = i + 1 | |
| return j | |
| def alt_max_orbite(alt, SR): | |
| p,v = np.shape(SR) | |
| tab1 = np.zeros((p)) | |
| tab2 = np.zeros((p)) | |
| for o in range (0,p): | |
| j = alt_max(SR,alt,o) | |
| if j != -1 : | |
| tab1[o] = alt[j] | |
| #if tab1[o] > 5.: print o | |
| else : tab1[o] = -10 | |
| tab2[o] = o | |
| return tab1 | |
| ''' | |
| tab1 = np.ma.masked_where(tab1 <= -1, tab1) | |
| fig = plt.figure(figsize=(15, 10), dpi=300) | |
| plt.plot(lt,tab1) | |
| plt.plot(lt, sol_alt,'g',linewidth=2) | |
| plt.xlim(np.min(lt), np.max(lt)) | |
| plt.ylabel('Altitude') | |
| plt.xlabel('indice') | |
| plt.show() | |
| ''' | |
| def alt_max_orbite_flag(alt, SR): | |
| u,v= np.shape(SR) | |
| tab1 = np.zeros((u,v)) | |
| for o in range (0,u): | |
| j = alt_max(SR,alt,o) | |
| if j != -1 :tab1[:][o] = alt[j] | |
| else : tab1[:][o] = -10 | |
| return tab1 | |
| def alt_min_SR5(alt_array,SR,altmax): | |
| u,v = np.shape(SR) | |
| alt_SR = np.zeros((u,v)) | |
| idx = (SR > 5) | |
| alt_copy = alt_array.copy() | |
| alt_copy[~idx] = 9999. | |
| alt_copy[altmax < 0] = 9999. | |
| alt_SR = np.min(alt_copy, axis=1) | |
| alt_SR[alt_SR == 9999] = -1. | |
| return alt_SR | |
| def alt_min_SR5_orbite(alt_array,SR,altmax): | |
| u,v = np.shape(SR) | |
| alt_SR = np.zeros((u,v)) | |
| alt_tab = np.zeros((u,v)) | |
| alt_total = np.zeros((u,v)) | |
| idx = (SR > 5) | |
| alt_copy = alt_array.copy() | |
| alt_copy[~idx] = 9999. | |
| alt_copy[altmax < 0] = 9999. | |
| alt_SR = np.min(alt_copy, axis=1) | |
| alt_SR[alt_SR == 9999] = -1. | |
| for i in range(0,v-1): | |
| if i == 0: alt_tab = alt_SR | |
| alt_tab = np.vstack((alt_tab,alt_SR)) | |
| alt_tab = alt_tab.T | |
| print alt_tab | |
| print np.shape(alt_tab) | |
| return alt_tab | |
| def alt_max_profil(alt,SR,n,fichier): | |
| j = alt_max(SR,alt,n) | |
| s = np.shape(alt) | |
| if j != -1 :alt_ext= alt[j] | |
| else : alt_ext= -10 | |
| print alt_ext | |
| profil_SR(n,lg,lt,ti,SR,alt,fichier) | |
| def affiche_flag(lg,lt,atb,alt,sol_alt): | |
| n1 = 0 | |
| n2, x = np.shape(atb) | |
| lt = lt[n1:n2] | |
| sol_alt = sol_alt[n1:n2] | |
| u,v = np.shape(atb[n1:n2,:]) | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| plt.plot(lt, sol_alt,'Maroon', alpha=1) | |
| cmap = cm.colors.ListedColormap(['White', 'Navy', 'Lime', 'Chocolate','Gold']) | |
| plot = plt.pcolormesh(lt,alt,atb.T,cmap=cmap) | |
| plt.ylim(0, 18) | |
| plt.xlim(-80, 80) | |
| plt.clim(0, 4) | |
| plt.xlabel('Latitude') | |
| plt.ylabel('Altitude en km') | |
| cb =plt.colorbar(ticks=[0, 1.3, 2, 2.75,3.5]) | |
| cb.ax.set_yticklabels(['Clear Sky','Nuages','Faux eteint','Zone de transition','Vrai eteint']) | |
| path = 'SR_orbite_vrai_faux' | |
| plt.savefig(path) | |
| plt.close() | |
| def affiche_flag_grl(lg,lt,atb,alt,sol_alt): | |
| n1 = 0 | |
| n2, x = np.shape(atb) | |
| lt = lt[n1:n2] | |
| sol_alt = sol_alt[n1:n2] | |
| u,v = np.shape(atb[n1:n2,:]) | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| plt.plot(lt, sol_alt,'Maroon', alpha=1) | |
| cmap = cm.colors.ListedColormap(['White', 'Navy', 'Chocolate']) | |
| plot = plt.pcolormesh(lt,alt,atb.T,cmap=cmap) | |
| plt.ylim(0, 18) | |
| plt.xlim(-80, 80) | |
| plt.clim(0, 2) | |
| plt.xlabel('Latitude') | |
| plt.ylabel('Altitude en km') | |
| cb =plt.colorbar(ticks=[0, 1.3, 2]) | |
| cb.ax.set_yticklabels(['Clear Sky','Nuages','Eteint']) | |
| path = 'SR_orbite_GRL' | |
| plt.savefig(path) | |
| plt.close() | |
| def flag_orbite_grl(alt,SR): | |
| u,v = np.shape(SR) | |
| flag = np.zeros((u,v)) | |
| alt_array = np.zeros((u,v)) | |
| alt_SR = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| alt_max = alt_max_orbite_flag(alt,SR) | |
| alt_SR = np.matlib.repmat(alt_min_SR5(alt_array,SR,alt_max),v,1).T | |
| print np.shape(alt_SR) | |
| #Nuage | |
| idx = (SR > 5) | |
| flag[idx] = 1 | |
| #Vrai eteint | |
| idx4 = (SR < 0.01) & (SR> -10) | |
| flag[idx4] = 2 | |
| #Zone de transition | |
| #idx3 = (alt_array > alt_max) & (alt_array < alt_SR) | |
| #flag[idx3] = 3 | |
| return flag | |
| def flag_orbite(alt,SR): | |
| u,v = np.shape(SR) | |
| flag = np.zeros((u,v)) | |
| alt_array = np.zeros((u,v)) | |
| alt_SR = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| alt_max = alt_max_orbite_flag(alt,SR) | |
| alt_SR = np.matlib.repmat(alt_min_SR5(alt_array,SR,alt_max),v,1).T | |
| print np.shape(alt_SR) | |
| #Nuage | |
| idx = (SR > 5) | |
| flag[idx] = 1 | |
| #Vrai eteint | |
| idx4 = (alt_array < alt_max)&(SR < 0.01) & (SR> -10) | |
| flag[idx4] = 4 | |
| #Faux eteint | |
| idx2 = ((alt_array > alt_max) & (alt_max!= -10)&(SR < 0.01) & (SR> -10)) | ((alt_max == -10) & (SR < 0.01) & (SR> -10)) | |
| flag[idx2] = 2 | |
| #Zone de transition | |
| idx3 = (alt_array > alt_max) & (alt_array < alt_SR) | |
| flag[idx3] = 3 | |
| return flag | |
| def lecture_dossier(repertoire): | |
| u = np.max(np.shape(os.listdir(repertoire))) | |
| return u, os.listdir(repertoire) | |
| def occur(flag,alt): | |
| clouds = (flag == 1).sum(axis=0) | |
| faux_eteint = (flag == 2).sum(axis=0) | |
| cloud_opa = (flag == 3).sum(axis=0) | |
| vrai_eteint = (flag == 4).sum(axis=0) | |
| return clouds, faux_eteint, cloud_opa, vrai_eteint | |
| def freq_occur(flag,alt): | |
| u,v = np.shape(flag) | |
| clouds, faux_eteint, cloud_opa, vrai_eteint = occur(flag,alt) | |
| clouds, faux_eteint, cloud_opa, vrai_eteint = (1.)*clouds / u, (1.)*faux_eteint / u, (1.)*cloud_opa / u, (1.)*vrai_eteint / u | |
| fig = plt.figure(figsize=(9, 15), dpi=100) | |
| p1, = plt.plot(vrai_eteint,alt) | |
| sum1 = vrai_eteint + cloud_opa | |
| p2, = plt.plot(sum1,alt) | |
| sum2 = vrai_eteint + cloud_opa + clouds | |
| p3, = plt.plot(sum2,alt) | |
| sum3 = vrai_eteint + cloud_opa + clouds + faux_eteint | |
| p4, = plt.plot(sum3,alt) | |
| #plt.xlim(0.0001, 0.1) | |
| plt.legend([p1,p2,p3,p4], ["Nuages","Faux eteint","Zone de transition","Vrai eteint"], loc=1) | |
| plt.xlabel("Frequence d'occurence") | |
| plt.ylabel("Altitude en km") | |
| plt.show() | |
| def occur_in_region(flag,alt,lt,latrange): | |
| idx = (lt < latrange[1]) & (lt > latrange[0]) | |
| flag = flag[idx] | |
| clouds = (flag == 1).sum(axis=0) | |
| faux_eteint = (flag == 2).sum(axis=0) | |
| cloud_opa = (flag == 3).sum(axis=0) | |
| vrai_eteint = (flag == 4).sum(axis=0) | |
| return clouds, faux_eteint, cloud_opa, vrai_eteint | |
| def freq_occur_region(dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| dic_opa_cloud = dict() | |
| dic_cloud = dict() | |
| dic_vrai = dict() | |
| dic_faux = dict() | |
| #nbr_fichier=1 | |
| nbr_fichier=np.max(nbr_fichier) | |
| latbands = {'tropique' :[-20,20],'pole_nord' :[60,90],'pole_sud' : [-90,-60],'mid_sud' :[-50,-30],'mid_nord' :[30, 50 ]} | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| flag = flag_orbite(alt,SR) | |
| u,v = np.shape(flag) | |
| print fichier[i] | |
| for region, tab_reg in latbands.items(): | |
| #flag = flag[tab_reg,:] | |
| clouds, faux_eteint, cloud_opa, vrai_eteint = occur_in_region(flag, alt, lt, latbands[region]) | |
| if region in dic_opa_cloud: | |
| dic_opa_cloud[region] += 1.* cloud_opa/ (u * nbr_fichier) | |
| dic_cloud[region] += 1.* clouds/ (u * nbr_fichier) | |
| dic_vrai[region] += 1.* vrai_eteint/ (u * nbr_fichier) | |
| dic_faux[region] += 1.* faux_eteint/ (u * nbr_fichier) | |
| else: | |
| dic_opa_cloud[region] = 1.* cloud_opa/ (u * nbr_fichier) | |
| dic_cloud[region] = 1.* clouds/ (u * nbr_fichier) | |
| dic_vrai[region] = 1.* vrai_eteint/ (u * nbr_fichier) | |
| dic_faux[region] = 1.* faux_eteint/ (u * nbr_fichier) | |
| for region in latbands.keys(): | |
| affiche_freq_separee(alt,dic_opa_cloud[region],dic_cloud[region],dic_vrai[region],dic_faux[region],region,fichier,nbr_fichier) | |
| def affiche_freq(alt,op,cl,vr,fa,region,fichier,nbr_fichier): | |
| fig = plt.figure(figsize=(9, 15), dpi=100) | |
| p1, = plt.plot(op,alt) | |
| sum1 = vr + op | |
| p2, = plt.plot(sum1,alt) | |
| sum2 = sum1 + fa | |
| p3, = plt.plot(sum2,alt) | |
| sum3 = sum2 + cl | |
| p4, = plt.plot(sum3,alt) | |
| plt.legend([p1], ["Nuages opaques"], loc=1) | |
| plt.legend([p1,p2,p3,p4], ["Zone de transition","Vrais eteints","Faux eteints","Nuages"], loc=1) | |
| plt.title(region + ' Du ' + fichier[0][17:27] +' au ' + fichier[nbr_fichier][17:27] + ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.xlabel("Frequence d'occurence") | |
| plt.ylabel("Altitude en km") | |
| path = region | |
| path += '.png' | |
| plt.savefig(path) | |
| plt.close() | |
| def affiche_freq_separee(alt,op,cl,vr,fa,region,fichier,nbr_fichier): | |
| fig = plt.figure(figsize=(9, 15), dpi=100) | |
| p1, = plt.plot(op,alt) | |
| p2, = plt.plot(cl,alt) | |
| p3, = plt.plot(vr,alt) | |
| plt.legend([p1,p2,p3], ["Zone de transition","Nuages","Vrai eteint"], loc=1) | |
| plt.title(region + ' Du ' + fichier[0][17:27] +' au ' + fichier[nbr_fichier][17:27] + ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.xlabel("Frequence d'occurence") | |
| plt.ylabel("Altitude en km") | |
| path = region | |
| path += 'occurence_zone_de_transition_nuage_separ.png' | |
| plt.savefig(path) | |
| plt.close() | |
| p3, = plt.plot(vr,alt) | |
| p4, = plt.plot(fa,alt) | |
| plt.legend([p3,p4], ["Vrais eteints","Faux eteints"], loc=1) | |
| plt.title(region + ' Du ' + fichier[0][17:27] +' au ' + fichier[nbr_fichier][17:27] + ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.xlabel("Frequence d'occurence") | |
| plt.ylabel("Altitude en km") | |
| path = region | |
| path += 'occurence_vrai_faux_separ.png' | |
| plt.savefig(path) | |
| plt.close() | |
| def histo_1D_orbite(dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier ) | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(dossier + fichier[0]) | |
| u,v = 60000,40 # passe manuellement car certains SR ont des tailles inferieur a 56295 | |
| print np.shape(alt) | |
| alt_array = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| print fichier3 | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| u,v = np.shape(SR) | |
| alt_array_copy = alt_array[0:u,0:v] | |
| alt_max = alt_max_orbite_flag(alt,SR) | |
| alt_SR5 = alt_min_SR5(alt_array_copy,SR,alt_max) | |
| idx = ( alt_SR5 > 0 ) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: total = temp | |
| else : total = np.concatenate([total, temp]) | |
| print np.shape(total) | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| plt.hist(total, bins=np.arange(0,14,0.5)) | |
| (mu, sigma) = norm.fit(total) | |
| plt.title('Du ' + fichier[0][17:27] +' au ' + fichier[nbr_fichier][17:27] + ' Nombre de fichiers :' + str(nbr_fichier)+ ' \n Moyenne : ' + str(mu) + ' Ecart type :' + str(sigma)) | |
| plt.xlabel('Taille de la zone de transition en km') | |
| plt.ylabel("Nombre d'occurences") | |
| plt.show() | |
| path = 'globale_distri_taille_transition.png' | |
| plt.savefig(path) | |
| plt.close() | |
| def histo_2D(alt, SR,lt,nbr_profil,profil_debut): | |
| n1 = profil_debut | |
| n2 = profil_debut + nbr_profil -1 | |
| u,v = np.shape(SR) | |
| alt_array = np.zeros_like(SR) | |
| alt_array[:][:] = alt | |
| fig = plt.figure(figsize=(14, 7)) | |
| SRbin=np.arange(-1,40) | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| x = np.concatenate([SR[n1,:], SR[n2,:]], axis=0) | |
| y = np.concatenate([alt_array[n1,:], alt_array[n2,:]], axis=0) | |
| #x = SR.ravel() | |
| #y = alt_array.ravel() | |
| print 'hehe',np.shape(x),n1,n2, x | |
| plt.hist2d(x, y,bins=(SRbin,altbin)) | |
| if nbr_profil == 2 : | |
| plt.plot(SR[n1,:], alt_array[0,:],'-*k',linewidth=2) | |
| plt.plot(SR[n2,:], alt_array[0,:],'-+y',linewidth=2) | |
| plt.xlim(-5,40) | |
| plt.xlabel('SR') | |
| #plt.clim(0,300) | |
| plt.ylabel('Altitude en km') | |
| if nbr_profil ==1 : plt.title('Latitude :'+ str( lt[n1])) | |
| else : plt.title('Latitude '+ str(lt[n1])+' a '+ str(lt[n2])) | |
| plt.colorbar() | |
| plt.show() | |
| def histo_2D_orbite(alt, SR,o,p, test): | |
| alt_array = np.zeros_like(SR) | |
| alt_array[:][:] = alt | |
| u, v = np.shape(SR) | |
| if test == 0: | |
| n1 = 0 | |
| n2 =u * (v) | |
| elif test == 1: | |
| n1 = o * (v) | |
| n2 = p * (v) | |
| alt_max = alt_max_orbite_flag(alt, SR) | |
| alt_minSR =alt_min_SR5_orbite(alt_array,SR,alt_max) | |
| idx = (alt_max != -10)#(alt_array <= alt_max) & (alt_array >= alt_minSR) & (alt_minSR != -1) | |
| SR = SR[idx] | |
| alt_array = alt_array[idx] | |
| print 'SR',np.shape(SR) | |
| fig = plt.figure(figsize=(14, 7)) | |
| #SRb=np.arange(-1,40,1) | |
| SRb=np.concatenate([np.arange(-1,3,0.2),np.arange(3,40,1)]) | |
| binwidth = np.max(np.shape(SRb)) | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| #altbin = np.linspace(-0.240,19,binwidth) | |
| #x = np.concatenate([SR[0,:], SR[u-1,:]], axis=0) | |
| #y = np.concatenate([alt_array[0,:], alt_array[u-1,:]], axis=0) | |
| x = SR.ravel() | |
| y = alt_array.ravel() | |
| plt.hist2d(x[n1:n2], y[n1:n2],bins=(SRb,altbin)) | |
| plt.xlabel('SR') | |
| plt.clim(0,800) | |
| plt.ylabel('Altitude en km') | |
| titre = ('Histogramme 2D de la latitude '+str(lt[o])+' a '+str(lt[p])) | |
| plt.title(titre) | |
| plt.colorbar() | |
| plt.show() | |
| def histo_1D_region2(dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier) | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(dossier + fichier[0]) | |
| u,v = 60000,40 # passe manuellement car certains SR ont des tailles inferieur a 56295 | |
| print np.shape(alt) | |
| alt_array = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| latbands = {'tropique' :[-20,20],'pole_nord' :[60,90],'pole_sud' : [-90,-60],'mid_sud' :[-50,-30],'mid_nord' :[30, 50 ]} | |
| dic_hist = dict() | |
| jour = np.zeros((nbr_fichier),dtype = int) | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| jour[i] = int(fichier[i][25:27]) | |
| print jour[i], fichier[i] | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| u,v = np.shape(SR) | |
| alt_array_copy = alt_array[0:u,0:v] | |
| print np.shape(alt_array_copy),np.shape(SR) | |
| print i, '/', nbr_fichier | |
| #idx1 = (lt < latbands[region][1]) & (lt > latbands[region][0]) | |
| alt_max = alt_max_orbite_flag(alt,SR) | |
| alt_SR5 = alt_min_SR5(alt_array_copy,SR,alt_max) | |
| idx = ( alt_SR5 > 0 ) & (lt < 20) & (lt > -20) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: dic_hist['tropique'] = temp | |
| else : dic_hist['tropique'] = np.concatenate([dic_hist['tropique'], temp]) | |
| idx = ( alt_SR5 > 0 ) & (lt < 90) & (lt > 60) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: dic_hist['pole_nord'] = temp | |
| else : dic_hist['pole_nord'] = np.concatenate([dic_hist['pole_nord'], temp]) | |
| idx = ( alt_SR5 > 0 ) & (lt < -60) & (lt >-90) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: dic_hist['pole_sud'] = temp | |
| else : dic_hist['pole_sud'] = np.concatenate([dic_hist['pole_sud'], temp]) | |
| idx = ( alt_SR5 > 0 ) & (lt < -30) & (lt > -50) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: dic_hist['mid_sud'] = temp | |
| else : dic_hist['mid_sud'] = np.concatenate([dic_hist['mid_sud'] , temp]) | |
| idx = ( alt_SR5 > 0 ) & (lt < 50) & (lt > 30) | |
| temp = alt_SR5[idx]-alt_max[idx,0] | |
| if i == 0: dic_hist['mid_nord'] = temp | |
| else : dic_hist['mid_nord'] = np.concatenate([dic_hist['mid_nord'] , temp]) | |
| for region, tab in dic_hist.items(): | |
| print tab | |
| (mu, sigma) = norm.fit(tab) | |
| plt.hist(tab, bins=np.arange(0,14,0.5)) | |
| plt.rcParams["axes.titlesize"] = 8 | |
| plt.title(region+' Du ' + fichier[0][17:25]+str(np.min(jour)) +' au ' + fichier[nbr_fichier][17:25] +str(np.max(jour))+ ' Nombre de fichiers :' + str(nbr_fichier)+ '\n Moyenne : '+ str(mu) +' Ecart type : '+ str(sigma)) | |
| plt.xlabel('Taille de la zone de transition en km') | |
| plt.ylabel("Nombre d'occurences") | |
| path = region | |
| path += '_histo_1D_moins.png' | |
| plt.savefig(path) | |
| plt.close() | |
| #plt.show() | |
| def histo_2D_region(SR,alt,dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier / 1.) | |
| latbands = {'tropique' :[-20,20],'pole_nord' :[60,90],'pole_sud' : [-90,-60],'mid_sud' :[-50,-30],'mid_nord' :[30, 50 ]} | |
| dic_hist = dict() | |
| jour = np.zeros((nbr_fichier),dtype = int) | |
| print nbr_fichier | |
| u,v = 100000*(nbr_fichier)/5,40 # passe manuellement car certains SR ont des tailles inferieur a 56295 | |
| print np.shape(alt) | |
| alt_array = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| alt_array = alt_array.ravel() | |
| SRb=[0,0.01,1.2,3,5,7,10,15,20,25,30,40,50,60,80] | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| jour[i] = int(fichier[i][25:27]) | |
| print jour[i], fichier[i] | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| print i, '/', nbr_fichier | |
| #idx1 = (lt < latbands[region][1]) & (lt > latbands[region][0]) | |
| idx = (lt < 20) & (lt > -20) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['tropique'] = temp | |
| else : dic_hist['tropique'] = dic_hist['tropique'] + temp | |
| idx = (lt < 90) & (lt > 60) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['pole_nord'] = temp | |
| else : dic_hist['pole_nord'] = dic_hist['pole_nord'] + temp | |
| idx = (lt < -60) & (lt > -90) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['pole_sud'] = temp | |
| else : dic_hist['pole_sud'] = dic_hist['pole_sud'] + temp | |
| idx = (lt < -30) & (lt > -50) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['mid_sud'] = temp | |
| else : dic_hist['mid_sud'] = dic_hist['mid_sud'] + temp | |
| idx = (lt < 50) & (lt > 30) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['mid_nord'] = temp | |
| else : dic_hist['mid_nord'] = dic_hist['mid_nord'] + temp | |
| SR_copy = SR.ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['total'] = temp | |
| else : dic_hist['total'] = dic_hist['total'] + temp | |
| for region, tab in dic_hist.items(): | |
| x = np.arange(0,np.shape(SRb)[0]) | |
| plt.pcolormesh(x, altbin, dic_hist[region].T / np.sum(dic_hist[region]) ) | |
| plt.gca().set_xticks(x) | |
| plt.gca().set_xticklabels(SRb) | |
| plt.rcParams["axes.titlesize"] = 10 | |
| plt.title(region+' Du ' + fichier[0][17:25]+str(np.min(jour)) +' au ' + fichier[0][17:25] +str(np.max(jour))+ ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.clim(0,0.001) | |
| #plt.xlim(0,80) | |
| plt.ylim(0,20) | |
| plt.xlabel('SR') | |
| plt.ylabel("Altitude en km") | |
| plt.colorbar() | |
| path = region | |
| path += '_histo_2D.png' | |
| plt.savefig(path) | |
| plt.clf() | |
| def hist_cloud_ext(fichier,date): | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier) | |
| SRb=[0,0.01,1.2,3,5,7,10,15,20,25,30,40,50,60,80] | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| u,v = np.shape(SR) | |
| alt_array = np.zeros((u,v)) | |
| alt_array [:][:] = alt | |
| alt_max = alt_max_orbite_flag(alt, SR) | |
| #idx = ( alt_max != -10) | |
| alt_max = alt_max_orbite_flag(alt, SR) | |
| alt_minSR =alt_min_SR5_orbite(alt_array,SR,alt_max) | |
| idx = (alt_max != -10) & ((alt_array <= alt_max) | (alt_array >= alt_minSR)) & (alt_minSR != -1) | |
| SR = SR[idx].ravel() | |
| alt_array= alt_array[idx].ravel() | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| #plt.hist2d(SR,alt_array,bins= (SRb,altbin)) | |
| histSR, x,y = np.histogram2d(SR ,alt_array,bins = (SRb, altbin)) | |
| x = np.arange(0,np.shape(SRb)[0]) | |
| plt.pcolormesh(x, altbin, histSR.T / np.sum(histSR)) | |
| plt.gca().set_xticks(x) | |
| plt.gca().set_xticklabels(SRb) | |
| plt.xlabel('SR') | |
| plt.ylabel('Altitude en km') | |
| plt.ylim(0,19) | |
| plt.title('Histogramme 2D sur une orbite des nuages responsables des extinctions') | |
| plt.clim(0,0.001) | |
| plt.colorbar() | |
| path = './lot/'+ date + '.png' | |
| plt.show() | |
| plt.savefig(path) | |
| plt.clf | |
| plt.close() | |
| def hist_could_ext_dossier(dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier ) | |
| for i in range(0,nbr_fichier): | |
| print '== fichier', fichier[i] | |
| print i ,'/', nbr_fichier | |
| calfile = dossier + fichier[i] | |
| date = fichier[i][17:27] | |
| hist_cloud_ext(calfile,date) | |
| def histo_2D_region_eteint(SR,alt,dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier ) | |
| latbands = {'tropique' :[-20,20],'pole_nord' :[60,90],'pole_sud' : [-90,-60],'mid_sud' :[-50,-30],'mid_nord' :[30, 50 ]} | |
| dic_hist = dict() | |
| jour = np.zeros((nbr_fichier),dtype = int) | |
| print nbr_fichier | |
| u,v = 100000*(nbr_fichier)/5,40 # passe manuellement car certains SR ont des tailles inferieur a 56295 | |
| print np.shape(alt) | |
| alt_array = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| alt_array = alt_array.ravel() | |
| SRb=[0,0.01,1.2,3,5,7,10,15,20,25,30,40,50,60,80] | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| jour[i] = int(fichier[i][25:27]) | |
| print jour[i], fichier[i] | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| alt_max = alt_max_orbite(alt, SR) | |
| print i, '/', nbr_fichier | |
| #idx1 = (lt < latbands[region][1]) & (lt > latbands[region][0]) | |
| idx = (lt < 20) & (lt > -20) & (alt_max != -10 ) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['tropique'] = temp | |
| else : dic_hist['tropique'] = dic_hist['tropique'] + temp | |
| idx = (lt < 90) & (lt > 60) & (alt_max != -10 ) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['pole_nord'] = temp | |
| else : dic_hist['pole_nord'] = dic_hist['pole_nord'] + temp | |
| idx = (lt < -60) & (lt > -90) & (alt_max != -10 ) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['pole_sud'] = temp | |
| else : dic_hist['pole_sud'] = dic_hist['pole_sud'] + temp | |
| idx = (lt < -30) & (lt > -50) & (alt_max != -10 ) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['mid_sud'] = temp | |
| else : dic_hist['mid_sud'] = dic_hist['mid_sud'] + temp | |
| idx = (lt < 50) & (lt > 30) & (alt_max != -10 ) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: dic_hist['mid_nord'] = temp | |
| else : dic_hist['mid_nord'] = dic_hist['mid_nord'] + temp | |
| for region, tab in dic_hist.items(): | |
| x = np.arange(0,np.shape(SRb)[0]) | |
| plt.pcolormesh(x, altbin, dic_hist[region].T / np.sum(dic_hist[region]) ) | |
| plt.gca().set_xticks(x) | |
| plt.gca().set_xticklabels(SRb) | |
| plt.rcParams["axes.titlesize"] = 10 | |
| plt.title(region + ' Eteints' +' Du ' + fichier[0][17:25]+str(np.min(jour)) +' au ' + fichier[0][17:25] +str(np.max(jour))+ ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.clim(0,0.001) | |
| #plt.xlim(0,80) | |
| plt.ylim(0,20) | |
| plt.xlabel('SR') | |
| plt.ylabel("Altitude en km") | |
| plt.colorbar() | |
| path = region | |
| path += '_histo_2D_eteint.png' | |
| plt.savefig(path) | |
| plt.clf() | |
| def histo_2D_warmpool_eteint(SR,alt,dossier): | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier) | |
| jour = np.zeros((nbr_fichier),dtype = int) | |
| print nbr_fichier | |
| u,v = 100000*(nbr_fichier)/5,40 # passe manuellement car certains SR ont des tailles inferieur a 56295 | |
| print np.shape(alt) | |
| alt_array = np.zeros((u,v)) | |
| alt_array[:][:] = alt | |
| alt_array = alt_array.ravel() | |
| SRb=[0,0.01,1.2,3,5,7,10,15,20,25,30,40,50,60,80] | |
| altbin = np.arange(-0.240,18.71+0.240,0.480) | |
| for i in range(0,nbr_fichier): | |
| fichier3 = dossier + fichier[i] | |
| jour[i] = int(fichier[i][25:27]) | |
| print jour[i], fichier[i] | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| alt_max = alt_max_orbite(alt, SR) | |
| print i, '/', nbr_fichier | |
| # idx = (lt < 15) & (lt > -15) & (alt_max != -10 ) & ( lg<180 ) & (lg >70) #warmpool | |
| idx = (lt < 0) & (lt > -15) & (alt_max != -10 ) & ( lg<-75 ) & (lg >-90) | |
| SR_copy = SR[idx,:].ravel() | |
| o = np.max(np.shape(SR_copy)) | |
| alt_array_copy = alt_array[0:o] | |
| temp, xx , yy = np.histogram2d(SR_copy, alt_array_copy, bins = (SRb, altbin)) | |
| if i == 0: total = temp | |
| else : total = total + temp | |
| x = np.arange(0,np.shape(SRb)[0]) | |
| plt.pcolormesh(x, altbin, total.T / np.sum(total) ) | |
| plt.gca().set_xticks(x) | |
| plt.gca().set_xticklabels(SRb) | |
| plt.rcParams["axes.titlesize"] = 10 | |
| plt.title('Shallowcu ' +' Du ' + fichier[0][17:25]+str(np.min(jour)) +' au ' + fichier[0][17:25] +str(np.max(jour))+ ' Nombre de fichiers :' + str(nbr_fichier)) | |
| plt.clim(0,0.001) | |
| #plt.xlim(0,80) | |
| plt.ylim(0,20) | |
| plt.xlabel('SR') | |
| plt.ylabel("Altitude en km") | |
| plt.colorbar() | |
| #path = '_warmpool.png' | |
| path = '_shallow2.png' | |
| plt.savefig(path) | |
| plt.clf() | |
| def distri_alt_max(dossier) : | |
| dic_distri = dict() | |
| latbands = {'tropique' :[-20,20],'pole_nord' :[60,90],'pole_sud' : [-90,-60],'mid_sud' :[-50,-30],'mid_nord' :[30, 50 ]} | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier ) | |
| for i in range(0,nbr_fichier): | |
| print i, '/',nbr_fichier | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(dossier + fichier[i]) | |
| alt_max = alt_max_orbite(alt, SR) | |
| for region in latbands.keys(): | |
| idx = (lt < latbands[region][1]) & (lt > latbands[region][0]) | |
| temp = alt_max[idx] | |
| if i == 0 : dic_distri[region] = temp | |
| else : dic_distri[region] = np.concatenate([dic_distri[region],temp]) | |
| for region, tab in dic_distri.items(): | |
| tab = np.ma.masked_where(tab == -10, tab) | |
| bin = np.arange(0,14,0.5) | |
| #plt.hist(hist[0],hist[1],orientation = 'horizontal' ) | |
| idx = tab >=0 | |
| me = tab[idx] | |
| plt.hist(tab, bins=bin,orientation = 'horizontal') | |
| plt.rcParams["axes.titlesize"] = 8 | |
| (mu, sigma) = norm.fit(me) | |
| plt.title(region+' Nombre de fichiers : '+str(nbr_fichier) + '\n Moyenne :' + str(mu) +' km Ecart type : ' + str(sigma) +' km') | |
| plt.xlabel('Nombre d occurences') | |
| plt.ylabel("Epaisseur de la zone de transition (km)") | |
| plt.ylim(0,19) | |
| path = region | |
| path += 'distri_alt_max.png' | |
| plt.savefig(path) | |
| plt.close() | |
| def hist_lonlat(dossier): | |
| fig = plt.figure(figsize=(14, 7), dpi=100) | |
| m = Basemap() | |
| nbr_fichier,fichier = lecture_dossier(dossier) | |
| nbr_fichier = int(nbr_fichier / 2) | |
| for i in range(0,nbr_fichier): | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(dossier + fichier[i]) | |
| print np.shape(lt),np.shape(lg) | |
| alt_max = alt_max_orbite(alt,SR) | |
| idx = (alt_max != -10 ) | |
| alt_max = alt_max[idx] | |
| lg = lg[idx] | |
| lt = lt[idx] | |
| lonb = np.arange(-90,90,2) | |
| latb = np.arange(-180,180,2) | |
| if i == 0: | |
| latotal = lt | |
| lgtotal = lg | |
| else: | |
| latotal = np.concatenate([latotal,lt]) | |
| lgtotal = np.concatenate([lgtotal,lg]) | |
| binlt = np.arange(-90,90,4) | |
| binlg = np.arange(-180,180,4) | |
| print np.shape(bin), np.shape(lt), np.shape(lg) | |
| hist,xx,yy = np.histogram2d( lgtotal, latotal, bins = (binlg,binlt) ) | |
| #x = np.arange(0,np.shape(SRb)[0]) | |
| m.fillcontinents() | |
| plt.pcolormesh(binlg, binlt, hist.T / np.sum(hist),alpha = 1 ) | |
| plt.rcParams["axes.titlesize"] = 8 | |
| plt.title(' Distribution de alt max - Nombre de fichiers : '+str(nbr_fichier)) | |
| plt.colorbar() | |
| #m.bluemarble() | |
| path = 'lon_lat2.png' | |
| plt.xlim(-180,180) | |
| plt.ylim(-90,90) | |
| plt.savefig(path) | |
| #plt.show() | |
| plt.close() | |
| if __name__=='__main__': | |
| fichier3="/bdd/CFMIP/CFMIP_OBS_LOCAL/GOCCP/instant_SR_CR_DR/grid_L40/2013/201308/night/instant_SR_CR_DR_2013-08-24T23-19-30ZN_night_CFMIP2_2.70.nc"#38418 mid | |
| #fichier3="/bdd/CFMIP/CFMIP_OBS_LOCAL/GOCCP/instant_SR_CR_DR/grid_L40/2013/201308/night/instant_SR_CR_DR_2013-08-23T19-18-36ZN_night_CFMIP2_2.70.nc" #20632 trop | |
| listevar(fichier3) | |
| n1=0 | |
| n1 , n2 = 0 , 20632 | |
| lg, lt, ti, atb,alt, sol_alt, SR = extraction(fichier3) | |
| #alt_max(SR, alt, n1,2*n2) | |
| #profil_SR(n1,2*n2,lg,lt,ti,SR,alt) | |
| #affiche(n1,n2,lg, lt, ti, SR,alt,sol_alt) | |
| ''' | |
| n1 = 0 | |
| n2, lt, lg, ti, atb, sol_alt = coord_pole(lg, lt, ti, atb,sol_alt) | |
| alt_max(SR, alt, n1,n2) | |
| profil(n1,n2,lg,lt,ti,atb,alt) | |
| affiche(n1,n2,lg, lt, ti, atb,alt,sol_alt) | |
| lonlat(n1, n2,lg, lt, ti, atb) | |
| ''' | |
| #lonlat(n1, n2,lg, lt, ti, atb) | |
| #affiche(n1,n2,lg, lt, ti, SR,alt,sol_alt) | |
| #alt_max_orbite(alt, sol_alt, SR,lt) | |
| # Tableau de flag | |
| #affiche_flag(lg, lt, flag,alt,sol_alt) | |
| #freq_occur(flag,alt) | |
| #n2,x = np.shape(SR) | |
| dossier = '/bdd/CFMIP/CFMIP_OBS_LOCAL/GOCCP/instant_SR_CR_DR/grid_L40/2013/201308/night/' | |
| #freq_occur_region(dossier) | |
| #lonlat(n1, n2,lg, lt, ti, atb) | |
| #afficheSR(lg, lt, ti, SR,alt,sol_alt) | |
| n = 38418 | |
| #profil_SR(n,lg,lt,ti,atb,alt,fichier3) | |
| #n = 41750 | |
| #profil_SR(n,lg,lt,ti,SR,alt,fichier3) | |
| #freq_occur_region(dossier) | |
| #alti = alt_min_SR5(alt,SR) | |
| #flag = flag_orbite(alt,SR) | |
| #affiche_flag(lg, lt, flag,alt,sol_alt) | |
| #n1,n2 = 38352 , 42466 | |
| #histo_2D_orbite(alt,SR,n1,n2,0)#test : 1 = on definit les bornes 0 = sur l'orbite | |
| #alt_min_SR5(alt,SR) | |
| #histo_1D_region2(dossier) | |
| #histo_1D(SR,alt) | |
| #nbr = 2 | |
| #debut = 38418 | |
| #histo_2D(alt,SR,lt,nbr,debut) | |
| #histo_2D_region(SR,alt,dossier) | |
| #hist_cloud_ext(fichier3,'test_normalisation') | |
| #hist_could_ext_dossier(dossier) | |
| #distri_alt_max(dossier) | |
| #histo_2D_warmpool_eteint(SR,alt,dossier) | |
| #hist_lonlat(dossier) | |
| #draw() | |
| #listevar(fichier3) |
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