Add functions and update of calc_ref_state.py to plot lat-lon fields
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@ -9,6 +9,8 @@
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import numpy as np #
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import time # to measure elapsed time
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from get_data import get_data_woa2009 as read_data
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from myplot import myplot_2dmap # plot of lat-lon fields
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from myplot_inputs import mycalc_create_pn # create plotname
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# ############################################################################################
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# Input 0 ####################################################################################
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@ -23,7 +25,7 @@ print 'MANUAL DEFINED OUTPUTS MISSING'
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dim = ('lon','lat','z','time',)
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dir_plot = '/glusterfs/inspect/users/xg911182/Code/Python/plots_test/'
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variables = {'s':{},'theta':{},'grd':[],'valid':[]}
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lonlat_reg = [25.0, 25.0+360.0, -90.0, 90.0] # plotting range for 2dmap
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# Input 1 ####################################################################################
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# Physical constants
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# input : None
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@ -142,3 +144,36 @@ end_time = time.time()
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print 'Elapsed time to plot and save reference state: '+ '{:.2f}'.format(end_time-beg_time)+'s'
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print ' ----------------------------------------------'
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# step g #####################################################################################
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# plot of full 2d fields
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# input : None
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# output : None
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# saved/created : plots saved in dir_plot
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# dir_plot : output of Input 0
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# ############################################################################################
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beg_time = time.time()
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print ''
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print ' ----------------------------------------------'
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print 'Insert code to plot full 2d fields'
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# define plotname
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list_allkeys = data.keys()
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i_dep = 0
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i_t = 0
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date_str = '2009'
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for i_key in range(0,len(list_allkeys)):
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print 'put this plotname stuff into a function'
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pname_str = mycalc_create_pn({'lonlat':lonlat_reg})
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plotname_dum = dir_plot + 'Map2d_' + list_allkeys[i_key] + pname_str['lonlat'] + \
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'_z' + str(grd.z[i_dep]) + grd.Uz + '_' + date_str + '.png'
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# define plot input
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title_in = 'Depth='+'{:.1f}'.format(grd.z[i_dep])+grd.Uz
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data_in = data[list_allkeys[i_key]]['val'][:,:,i_dep,i_t]
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data_in[data_in==data[list_allkeys[i_key]]['fill_value']] = np.nan
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myplot_2dmap(data_in,grd,lonlat_range=lonlat_reg,saveplot=1,\
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title_c=title_in,plotname=plotname_dum)
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del data_in, title_in, pname_str,plotname_dum
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print ' ----------------------------------------------'
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end_time = time.time()
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print 'Elapsed time to plot 2d fields (lat-lon): '+ '{:.2f}'.format(end_time-beg_time)+'s'
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print ' ----------------------------------------------'
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108
mycalc_matrix.py
Normal file
108
mycalc_matrix.py
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@ -0,0 +1,108 @@
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def mymatrix_smooth(data_in,smooth_dim=(0,),data_per=(0,),window_len=3,window='step'):
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# from mymatrix_operations import mymatrix_smooth
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import numpy as np
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from mymath import mymath_multiplylist
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# general input info %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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shape_data_in = data_in.shape
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n_dim = len(shape_data_in)
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# reshape matrix to get smoothing dimension into 0 and 1 dimension
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rs_beg = np.array(range(0,n_dim))
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rs_end = np.array(range(0,n_dim))
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if n_dim > 1:
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rs_beg[np.array([0,smooth_dim[0]])] = (smooth_dim[0],0)
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if len(smooth_dim) > 1:
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rs_beg[np.array([1,smooth_dim[1]])] = (rs_beg[smooth_dim[1]],rs_beg[1])
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rs_end[np.array([1,smooth_dim[1]])] = (smooth_dim[1],1)
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rs_end[np.array([0,smooth_dim[0]])] = (rs_end[smooth_dim[0]],rs_end[0])
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# transpose data, so that smooth_dim are in the first two dimensions
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data_in = data_in.transpose(rs_beg)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# error checking %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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if len(smooth_dim) > 2:
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exit("smoothing only possible in two dimensions")
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# define window function %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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window_len = int(window_len)
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if window=='step':
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window_num = np.ones(window_len/2+1);
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elif window=='hanning':
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window_num = (np.cos(np.array(range(0,window_len/2+1),dtype=float)/(window_len/2)*np.pi)+1)/2;
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else:
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print 'Defined window function not available for smoothing. No smoothing.'
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window_num = 0;
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# create smoothing matrices for matrix multiplications %%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# Allocate smoothing matrix
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if n_dim == 1:
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smooth_ML = 1.
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smooth_MR = np.zeros((shape_data_in[0],shape_data_in[0]),dtype=float)
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np.fill_diagonal(smooth_MR[:], window_num[0])
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else:
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smooth_ML = np.zeros((shape_data_in[smooth_dim[0]],shape_data_in[smooth_dim[0]]),dtype=float)
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if len(smooth_dim) > 1:
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smooth_MR = np.zeros((shape_data_in[smooth_dim[1]],shape_data_in[smooth_dim[1]]),dtype=float)
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np.fill_diagonal(smooth_MR[:], window_num[0])
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else:
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smooth_MR = 1.
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np.fill_diagonal(smooth_ML[:], window_num[0])
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# Fill smoothing matrix with window_num values
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if n_dim == 1:
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for i_d in range(1,window_len/2+1):
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np.fill_diagonal(smooth_MR[i_d:], window_num[i_d])
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np.fill_diagonal(smooth_MR[:,i_d:], window_num[i_d])
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# modify smooth_matrix in case of periodic data
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if data_per[0] == 1:
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np.fill_diagonal(smooth_MR[(shape_data_in[0]-i_d):], window_num[i_d])
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np.fill_diagonal(smooth_MR[:,(shape_data_in[0]-i_d):], window_num[i_d])
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else:
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for i_d in range(1,window_len/2+1):
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np.fill_diagonal(smooth_ML[i_d:], window_num[i_d])
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np.fill_diagonal(smooth_ML[:,i_d:], window_num[i_d])
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# modify smooth_matrix in case of periodic data
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if data_per[0] == 1:
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np.fill_diagonal(smooth_ML[(shape_data_in[0]-i_d):], window_num[i_d])
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np.fill_diagonal(smooth_ML[:,(shape_data_in[0]-i_d):], window_num[i_d])
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if len(smooth_dim) > 1:
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for i_d in range(1,window_len/2+1):
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np.fill_diagonal(smooth_MR[i_d:], window_num[i_d])
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np.fill_diagonal(smooth_MR[:,i_d:], window_num[i_d])
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# modify smooth_matrix in case of periodic data
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if data_per[1] == 1:
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np.fill_diagonal(smooth_MR[(shape_data_in[1]-i_d):], window_num[i_d])
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np.fill_diagonal(smooth_MR[:,(shape_data_in[1]-i_d):], window_num[i_d])
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# apply smoothing matrices to input data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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if n_dim == 1:
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data_in = data_in.dot(smooth_MR)
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data_in = data_in/(np.ones(shape_data_in).dot(smooth_MR))
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elif n_dim == 2:
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data_in = smooth_ML.dot(data_in).dot(smooth_MR)
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data_in = data_in/(smooth_ML.dot(np.ones(shape_data_in)).dot(smooth_MR))
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else:
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shape_data_in_new = (shape_data_in[0],shape_data_in[1],mymath_multiplylist(shape_data_in[2:]))
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data_in = np.reshape(data_in,shape_data_in_new)
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# loop over all other dimensions
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for i_d in range(0,mymath_multiplylist(shape_data_in[2:])):
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# smoothing in first dimension
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if len(smooth_dim):
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data_in[:,:,i_d] = smooth_ML.dot(data_in[:,:,i_d]).dot(smooth_MR)
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data_in[:,:,i_d] = data_in[:,:,i_d]/(smooth_ML.dot(np.ones(shape_data_in[:2])).dot(smooth_MR))
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data_in = np.reshape(data_in,shape_data_in)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# define putput data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# transpose data back into original shape
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data_in = data_in.transpose(rs_end)
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return data_in
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285
myplot.py
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285
myplot.py
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@ -0,0 +1,285 @@
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def myplot_1d(xxx,yyy,FS=22,trend=0,rm_yyy=0,yyy_per=0,col_c=('b','r','k'),label_c=('None'),xlabel_c='no xlabel info',ylabel_c='no ylabel info',saveplot=0,plotname='dummy.png',window='step'):
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# from myplot import myplot_1d
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# input choices for myplot_1d %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# col_c=('b','r','k') : Default plotting colors, if more timeseries than num-
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# ber of colors, a longer list of colors is necessary
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# FS=[22] : Font Size for text, labels, etc
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# label_c=('None') : Specification of lines in legend. To use no legend, set
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# label_c=('None')
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# plotname='dummy.png' : in case of saveplot=1, the plot will be saved under
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# plotname (don't forget to include the path in plotname)
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# rm_yyy=0 : window size (in data points) for smoothing, see further 'window'
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# and yyy_per
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# saveplot=0 : save the plotting? 1 for yes, 0 for no, see further plotname
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# trend=0 : Include information about the trend of the timeseries (as text)
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# window='step' : In case of smoothing (rm_yyy), this defines the window
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# function used for smoothing. Available windows can be found in
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# in my_matrix_operations.py under the function mymatrix_smooth
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# xlabel_c='no xlabel info' : Text for xlabel
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# ylabel_c='no ylabel info' : Text for ylabel
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# yyy_per=0 : data periodic? (relevant for smoothing)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# load modules and functions %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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from mymath import mymath_multiplylist
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import numpy as np
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import matplotlib.pyplot as plt
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import math
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from mycalc_matrix import mymatrix_smooth
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# data handling and specification
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# general data info
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shape_yyy = yyy.shape
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n_dim = len(shape_yyy)
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if n_dim == 1:
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yyy = np.tile(yyy,(2,1))
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shape_yyy = yyy.shape
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xxxmin = np.min(xxx); xxxmax = np.max(xxx); xxxd = xxxmax-xxxmin;
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yyymin = np.min(yyy); yyymax = np.max(yyy); yyyd = yyymax-yyymin;
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# smoothing of yyy
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if rm_yyy > 0:
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yyy_sm = [None] * mymath_multiplylist(shape_yyy)
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yyy_sm = np.reshape(yyy_sm,shape_yyy)
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for i_d in range(0,n_dim):
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yyy_sm[i_d,:] = mymatrix_smooth(yyy[i_d,:],data_per=(yyy_per,),window_len=rm_yyy,window=window);
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# calculate trend of input data
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if trend == 1:
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yyy_trend = [None] * n_dim
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for i_d in range(0,n_dim):
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yyy_trend_d = np.polyfit(xxx,yyy[i_d,:],1)
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yyy_trend[i_d] = yyy_trend_d[0]
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del yyy_trend_d
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# general plotting setup
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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mpl_fig = plt.figure(figsize=(24,8))
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mpl_fig.patch.set_facecolor('w')
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# plotting (yyy)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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line_data = [None] * n_dim
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line_data_sm = [None] * n_dim
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for i_d in range(0,n_dim):
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if rm_yyy > 0:
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line_data[i_d], = plt.plot(xxx,yyy[i_d,:],color=col_c[i_d],linestyle='-.',lw=2,label=label_c[i_d])
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line_data_sm[i_d], = plt.plot(xxx,yyy_sm[i_d,:],color=col_c[i_d],linestyle='-',lw=2,label=label_c[i_d]+' (av='+str(rm_yyy)+'#,'+window+')')
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else:
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line_data[i_d], = plt.plot(xxx,yyy[i_d,:],color=col_c[i_d],linestyle='-',lw=2,label=label_c[i_d])
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# plotting (additional horizontal lines)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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for i_d in range(0,n_dim):
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plt.plot(xxx[[0,-1]],np.mean(yyy[i_d,:])*np.ones(2,'d'),color=col_c[i_d],lw=2)
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# include text
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# include trend information
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if trend == 1:
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exponent = int(math.floor(math.log10(abs(yyy_trend[0]))))
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coeff = round(yyy_trend[0]/float(10**exponent),1)
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if exponent==0:
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trend_str = str(coeff)
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else:
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trend_str = str(coeff)+'x1e'+str(exponent)
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if yyymax-np.mean(yyy)>np.mean(yyy[0,:])-yyymin:
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plt.text(xxxmax-xxxd/5,yyymax-yyyd/20,'Trend: '+trend_str, fontsize=FS-2)
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else:
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plt.text(xxxmax-xxxd/5,yyymin+yyyd/80,'Trend: '+trend_str, fontsize=FS-2)
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del coeff, exponent, trend_str
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# labeling, axis, etc
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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plt.ylabel(ylabel_c, fontsize=FS)
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plt.xlabel(xlabel_c, fontsize=FS)
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plt.xticks(fontsize=FS)
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plt.yticks(fontsize=FS)
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plt.xlim(xxxmin,xxxmax)
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if yyymax-np.mean(yyy)>np.mean(yyy)-yyymin:
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loc_c = 2
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if rm_yyy > 0:
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line_dummy = [None] * (n_dim*2)
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line_dummy[0::2] = line_data
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line_dummy[1::2] = line_data_sm
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else:
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line_dummy = line_data
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else:
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loc_c = 3
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if rm_yyy > 0:
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line_dummy = [None] * (n_dim*2)
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line_dummy[0::2] = line_data
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line_dummy[1::2] = line_data_sm
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else:
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line_dummy = line_data
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plt.legend(handles=line_dummy,loc=loc_c, prop={'size': FS-4})
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# save plot
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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if saveplot:
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print 'save plot under: ' + plotname
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plt.savefig(plotname,dpi=300,bbox_inches='tight')
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else:
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plt.show()
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plt.close()
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#def myplot_2dmap(xxx,yyy,FS=22,trend=0,rm_yyy=0,yyy_per=0,col_c=('b','r','k'),label_c=('None'),xlabel_c='no xlabel info',ylabel_c='no ylabel info',saveplot=0,plotname='dummy.png',window='step',title_c=[]):
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def myplot_2dmap(data_in,grd,FS=22,plotname='dummy.png',saveplot=0,lonlat_range=[0.0,360.0,-90.0,90.0],\
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xlabel_c=[],ylabel_c=[],title_c=[]):
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# from myplot import myplot_2dmap
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# input choices for myplot_1d %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# data_in is the 2d field for plotting
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# lonlat_range=[0.0,360.0,-90.0,90.0] : longitude/latitude range used for
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# plotting
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# plotname='dummy.png' : in case of saveplot=1, the plot will be saved under
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# plotname (don't forget to include the path in plotname)
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# saveplot=0 : save the plotting? 1 for yes, 0 for no, see further plotname
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# FS=[22] : Font Size for text, labels, etc
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# load modules and functions
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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import numpy as np
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import matplotlib.pyplot as plt
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import math
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from mycalc_matrix import mymatrix_smooth
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from mpl_toolkits.basemap import Basemap, addcyclic, shiftgrid
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# => cartopy instead of basemap
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# general plotting setup
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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mpl_fig = plt.figure(edgecolor='w',figsize=(18./360.*np.diff(lonlat_range[0:2]),12./180.*np.diff(lonlat_range[2:4])))
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mpl_fig.patch.set_facecolor('w')
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# define map projection, include grid and map
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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mapproj = Basemap(projection='cyl',llcrnrlat=np.min(lonlat_range[2:4]), llcrnrlon=np.min(lonlat_range[0:2]),\
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urcrnrlat=np.max(lonlat_range[2:4]), urcrnrlon=np.max(lonlat_range[0:2]))
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mapproj.drawcoastlines()
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mapproj.drawparallels(np.array([-90, -45, 0, 45, 90]),labels=[1,0,0,0])
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mapproj.drawmeridians(np.array([0, 90, 180, 270, 360]),labels=[0,0,0,1])
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# redefine longitudes
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# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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# Create 2D lat/lon arrays for Basemap
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for i_d in range(0,grd.Nlat):
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data_in[:,i_d],lon_shift = shiftgrid(360.0*(np.min(lonlat_range[0:2])<0)+np.min(lonlat_range[0:2]), \
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data_in[:,i_d], grd.lon, start=True, cyclic=360.0)
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yyy, xxx = np.meshgrid(grd.lat,lon_shift)
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#yyy, xxx = np.meshgrid(grd.lat,grd.lon)
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#data_in,lon_shift = shiftgrid(360.0*(np.min(lonlat_range[0:2])<0)+np.min(lonlat_range[0:2]), \
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# data_in, xxx, start=True, cyclic=360.0-np.mean(np.diff(grd.lon)))
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lonall, latall = mapproj(xxx, yyy)
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del yyy, xxx
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# plotting of data_in
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
mymapf = plt.contourf(lonall, latall, data_in, 10, cmap=plt.cm.Reds)
|
||||
mymap = plt.contour(lonall, latall, data_in, 10, colors='k')
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# include contour labels, colorbar, etc.
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
fmt_d = int(math.floor(np.max((0,-(np.log10(np.nanmean(data_in[:]))-2)))))
|
||||
plt.clabel(mymap, fontsize=FS, colors='w', fmt='%.'+str(fmt_d)+'f')
|
||||
del fmt_d
|
||||
if title_c:
|
||||
plt.title(title_c, fontsize=FS)
|
||||
plt.colorbar(mymapf, orientation='horizontal', shrink=0.95)
|
||||
#plt.colorbar(mymapf, orientation='horizontal', shrink=0.64)
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# labeling, axis, etc
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
plt.xticks(fontsize=FS)
|
||||
plt.yticks(fontsize=FS)
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# save plot
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if saveplot:
|
||||
print 'save plot under: ' + plotname
|
||||
plt.savefig(plotname,dpi=300,bbox_inches='tight')
|
||||
else:
|
||||
plt.show()
|
||||
plt.close()
|
||||
del data_in, FS, plotname, lonlat_range
|
||||
|
||||
|
||||
#def myplot_2d(xxx,yyy,FS=22,trend=0,rm_yyy=0,yyy_per=0,col_c=('b','r','k'),label_c=('None'),xlabel_c='no xlabel info',ylabel_c='no ylabel info',saveplot=0,plotname='dummy.png',window='step'):
|
||||
def myplot_2d(xxx,yyy,zzz,FS=22,plotname='dummy.png',saveplot=0,xlabel_c=[],ylabel_c=[],\
|
||||
d_xtick=[],cbarlabel_c=[],title_c=[],con_lines=[]):
|
||||
# from myplot import myplot_2d
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# input choices for myplot_2d %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# zzz is the 2d field for plotting
|
||||
# plotname='dummy.png' : in case of saveplot=1, the plot will be saved under
|
||||
# plotname (don't forget to include the path in plotname)
|
||||
# saveplot=0 : save the plotting? 1 for yes, 0 for no, see further plotname
|
||||
# FS=[22] : Font Size for text, labels, etc
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# load modules and functions
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# general plotting setup
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
mpl_fig = plt.figure(edgecolor='w')
|
||||
mpl_fig.patch.set_facecolor('w')
|
||||
ax = plt.gca()
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# plotting of zzz
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
#plt.pcolor(xxx,yyy,zzz,vmin=np.nanmin(zzz),vmax=np.nanmax(zzz))
|
||||
mmm = np.ma.masked_where(np.isnan(zzz),zzz)
|
||||
plt.pcolor(xxx,yyy,mmm,vmin=np.nanmin(zzz),vmax=np.nanmax(zzz))
|
||||
ax.set_facecolor('gray')
|
||||
#plt.imshow(zzz)
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# plotting additional contour lines
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if con_lines:
|
||||
con_lines_val = con_lines['value']
|
||||
for i_d in range(0,len(con_lines_val)):
|
||||
plt.plot(con_lines_val[i_d][0],con_lines_val[i_d][1],con_lines['col'][i_d],label=con_lines['col'][i_d])
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# include contour labels, colorbar, etc.
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
cbar = plt.colorbar()
|
||||
if cbarlabel_c:
|
||||
cbar.set_label(cbarlabel_c, rotation=270, labelpad=10)
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# labeling, axis, etc
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if d_xtick:
|
||||
xtick_c = np.arange(xxx.min()+d_xtick*(xxx.min()%d_xtick>0)-\
|
||||
xxx.min()%d_xtick,xxx.max()-xxx.max()%d_xtick+d_xtick,d_xtick)
|
||||
plt.xticks(xtick_c,fontsize=FS)
|
||||
del xtick_c
|
||||
else:
|
||||
plt.xticks(fontsize=FS)
|
||||
plt.yticks(fontsize=FS)
|
||||
if ylabel_c:
|
||||
plt.ylabel(ylabel_c, fontsize=FS)
|
||||
if xlabel_c:
|
||||
plt.xlabel(xlabel_c, fontsize=FS)
|
||||
if title_c:
|
||||
plt.title(title_c, fontsize=FS)
|
||||
# set axis range
|
||||
plt.xlim((xxx.min(),xxx.max()))
|
||||
plt.ylim((yyy.min(),yyy.max()))
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
# save plot
|
||||
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if saveplot:
|
||||
print 'save plot under: ' + plotname
|
||||
plt.savefig(plotname,dpi=300,bbox_inches='tight')
|
||||
else:
|
||||
plt.show()
|
||||
plt.close()
|
||||
del FS, plotname
|
||||
33
myplot_inputs.py
Normal file
33
myplot_inputs.py
Normal file
@ -0,0 +1,33 @@
|
||||
def mycalc_create_pn(dict_in):
|
||||
|
||||
# Allocation
|
||||
pname_str = {}
|
||||
# check if restriction to region exist
|
||||
list_allkeys = dict_in.keys()
|
||||
if 'lonlat' in list_allkeys:
|
||||
dummy = dict_in['lonlat']
|
||||
if dummy[0] < 0:
|
||||
pn1 = '{:03d}'.format(int(abs(round(dummy[0])))) + 'W'
|
||||
elif dummy[0] > 360:
|
||||
pn1 = '{:03d}'.format(int(round(dummy[0])-360)) + 'E'
|
||||
else:
|
||||
pn1 = '{:03d}'.format(int(round(dummy[0]))) + 'E'
|
||||
if dummy[1] < 0:
|
||||
pn2 = '{:03d}'.format(int(abs(round(dummy[1])))) + 'W'
|
||||
elif dummy[1] > 360:
|
||||
pn2 = '{:03d}'.format(int(round(dummy[1])-360)) + 'E'
|
||||
else:
|
||||
pn2 = '{:03d}'.format(int(round(dummy[1]))) + 'E'
|
||||
if dummy[2] < 0:
|
||||
pn3 = '{:02d}'.format(int(abs(round(dummy[2])))) + 'S'
|
||||
else:
|
||||
pn3 = '{:02d}'.format(int(round(dummy[2]))) + 'N'
|
||||
if dummy[3] < 0:
|
||||
pn4 = '{:02d}'.format(int(abs(round(dummy[3])))) + 'S'
|
||||
else:
|
||||
pn4 = '{:02d}'.format(int(round(dummy[3]))) + 'N'
|
||||
pname_str['lonlat'] = '_reg' + pn1 + 'to' + pn2 + pn3 + 'to' + pn4
|
||||
del dummy
|
||||
|
||||
del dict_in, list_allkeys
|
||||
return pname_str
|
||||
Loading…
Reference in New Issue
Block a user