iPOLARRIS v1.0.4

.gitignore

@@ -1,9 +1,18 @@
 *.ipynb
-*.nc
 *.cdf
 *.png
 *.tar.gz
 *.tar
 *.pyc
 *.p
 *.npy
+*.DS_Store
+*pycache*
+olym*
+inputtxt/*.txt
+configtxt/2*
+logs/*
+samples/*
+outputfig/*
+nexrad_obs_config.txt
+nexrad_wrf_config.txt

GeneralFunctions.py

@@ -35,7 +35,8 @@
 
 #import analysis_tools as AT
 #import lightning_tools as LT
-from CSU_RadarTools.csu_radartools import csu_fhc
+#from CSU_RadarTools.csu_radartools import csu_fhc
+import csu_fhc
 import general_tools as gentools
 import RadarConfig
 from matplotlib.colors import from_levels_and_colors
@@ -118,7 +119,7 @@ def cfad(data = None,cfad =None,hts=None,value_bins=None, above=2.0, below=15.0,
 #############################################################################################################
 
 def cfad_plot(var,data = None,cfad=None, hts=None, nbins=20, ax=None, maxval=10.0, above=2.0, below=15.0, bins=None, 
-        log=False, pick=None, z_resolution=1.0,levels=None,tspan =None,cont = False, rconf = None,mask = None,**kwargs):
+        log=False, pick=None, ylim=None, xlim=None, xlab=None, cbyes=0, z_resolution=1.0,levels=None,tspan =None,cont = False, rconf = None,mask = None,**kwargs):
 
     if hts is None:
         print ('please provide nominal heights to cfad_plot')
@@ -156,10 +157,10 @@ def cfad_plot(var,data = None,cfad=None, hts=None, nbins=20, ax=None, maxval=10.
 
     # plot the CFAD
     cfad_ma = np.ma.masked_where(cfad==0, cfad)
-    print(np.shape(cfad_ma),'cfad shape')
+    #print(np.shape(cfad_ma),'cfad shape')
+    levs = [0.02,0.05,0.1,0.2,0.5,1.0,2.0,5.0,10.0,15.0,20.,25.]
+    cols = ['lightgrey','silver','darkgray','slategrey','dimgray','blue','mediumaquamarine','yellow','orange','red','fuchsia','violet','thistle']
     if cont is True:
-        levs = [0.02,0.05,0.1,0.2,0.5,1.0,2.0,5.0,10.0,15.0,20.,25.]
-        cols = ['silver','darkgray','slategrey','dimgray','blue','mediumaquamarine','yellow','orange','red','fuchsia','violet']
         try:
             pc = ax.contourf(bins[:-1],reshts,cfad_ma,levs,colors=cols,extend = 'both')
         except TypeError as e:
@@ -168,17 +169,33 @@ def cfad_plot(var,data = None,cfad=None, hts=None, nbins=20, ax=None, maxval=10.
     else:
 
         if levels is not None:
-            cmap, norm = from_levels_and_colors([0.02,0.05,0.1,0.2,0.5,1.0,2.0,5.0,10.0,15.0,20.,25.], ['silver','darkgray','slategrey','dimgray','blue','mediumaquamarine','yellow','orange','red','fuchsia','violet']) # mention levels and colors here
+            cmap, norm = from_levels_and_colors(levs,cols) # mention levels and colors here
             #print cmap
             pc = ax.pcolormesh(bins, reshts, cfad_ma, norm=norm, cmap=cmap)
         else:
 
             pc = ax.pcolormesh(bins, reshts, cfad_ma, vmin=0, vmax=maxval, norm=norm, **kwargs)
 
-    cb = fig.colorbar(pc, ax=ax)
-    cb.set_label('Frequency (%)')
-    ax.set_ylabel('Height (km MSL)')
-#        try:
+    ax.set_xlabel(xlab,fontsize=16)
+    ax.tick_params(axis='both', which='major', labelsize=16)
+    ax.set_xlim(xlim)
+    ax.set_ylim(ylim)
+    if cbyes == 1:
+        lur,bur,wur,hur = ax.get_position().bounds
+        cbar_ax_dims = [lur+wur+0.02,bur,0.02,hur]
+        cbar_ax = fig.add_axes(cbar_ax_dims)
+        cbt = plt.colorbar(pc,cax=cbar_ax)
+        cbt.set_ticks(levs)
+        cbt.ax.tick_params(labelsize=16)
+        cbt.set_label('Frequency (%)', fontsize=16, rotation=270, labelpad=15)
+
+    #    cb = fig.colorbar(pc, ax=ax)
+    #    cb.set_label('Frequency (%)',fontsize=16,rotation=270,labelpad=20)
+    #    cb.ax.tick_params(labelsize=16)
+        ax.set_yticks([])
+        ax.set_yticklabels([])
+        ax.tick_params(axis='y', which='major', labelsize=0)
+
     if rconf is not None:
         if var == 'DRC' or var == 'DRS':
             varn = rconf.zdr_name

README

@@ -2,10 +2,18 @@ iPOLARRIS
 
 This is a complimentary program to POLARRIS-f, a forward model for producing polarimetric radar observations from model simulations. This suite of tools reads in gridded data (from radar or simulation), runs radar retrievals, and makes standardized plots.
 
+***NOTE: ipol.sh only works for iMAC environment.***
+
 Written by Brenda Dolan
 Colorado State University, Dept. Atmos. Sci.
 bdolan@atmos.colostate.edu
 May 2017
 
+Contributions by Anthony Di Stefano
+The University of British Columbia, Dept. EOAS
+adistefa@eoas.ubc.ca
+October 2020 - Present
+
 based on code from Brody Fuchs
 
+Last updated on August 16, 2021

RadarConfig.py

@@ -6,20 +6,23 @@
 import matplotlib.pyplot as plt
 from copy import deepcopy
 import datetime as dt
-
+import pyart
 
 class RadarConfig(object):
-    
+
     def __init__(self, dz='DZ', zdr='DR', kdp='KD', ldr='LH', rho='RH', hid = 'HID',conv='Con',
             temp='T', x='x', y='y', z='z', u='U', v='V',rr='RR', w='Wvar',vr='VR',mphys='None',exper = 'Case',
-            band = 'C',lat_0 = 0,lon_0=90.0,lat_r=None,lon_r=None,lat=None,lon=None,tm = None,radar_name = None):
+            band = 'C',lat_0 = 0,lon_0=90.0,lat_r=None,lon_r=None,lat=None,lon=None,tm = None,radar_name = None,
+            color_blind = False):
         # ******** first the polarimetric stuff *************
         self.dz_name = dz
         self.zdr_name = zdr
         self.kdp_name = kdp
         self.ldr_name = ldr
         self.rho_name = rho
         self.rr_name = rr
+        if self.rr_name == None:
+            self.rr_name = 'RR'
         self.temp_name = temp
         self.hid_name = hid
         self.vr_name = vr
@@ -53,33 +56,39 @@ def __init__(self, dz='DZ', zdr='DR', kdp='KD', ldr='LH', rho='RH', hid = 'HID',
         self.date = tm
         self.radar_name = radar_name
 
-
-
         self.species = np.array(['DZ','RN','CR','AG','WS','VI','LDG','HDG','HA','BD'])
-        self.hid_colors = ['White','LightBlue','MediumBlue','Darkorange','LightPink','Cyan','DarkGray',\
-            'Lime','Yellow','Red','Fuchsia']
+        self.species_long = np.array(['Drizzle','Rain','Ice\nCrystals','Snow\nAggre-\ngates','Wet\nSnow','Vertical\nIce','Low-\nDensity\nGraupel','High-\nDensity\nGraupel','Hail','Big\nDrops'])
+        #self.hid_colors = ['White','LightBlue','MediumBlue','Darkorange','LightPink','Cyan','DarkGray',\
+        #    'Lime','Yellow','Red','Fuchsia']
+        self.hid_colors = ['LightBlue','MediumBlue','Darkorange','Purple','Cyan','DarkGray',\
+            'Lime','Yellow','Red','Fuchsia'] 
         self.pol_vars = np.array([self.dz_name, self.zdr_name, self.kdp_name, self.ldr_name, self.rho_name, self.hid_name])
 
         self.cs_colors = ['#FFFFFF', 'DodgerBlue', 'Red', 'Khaki']
         self.cs_labels = ['', 'Strat', 'Conv', 'Mixed']
 
-        self.set_dbz_colorbar()
+        self.cfad_levs = [0.02,0.05,0.1,0.2,0.5,1.0,2.0,5.0,10.0,15.0,20.,25.]
+        self.cfad_cols = ['silver','darkgray','slategrey','dimgray','blue','mediumaquamarine','yellow','orange','red','fuchsia','violet'] 
+
+        self.set_dbz_colorbar(color_blind=color_blind)
         self.set_hid_colorbar()
         self.set_cs_colorbar()
 
         # Now just set some defaults
-        self.lims = {dz: [0,80], zdr: [-1, 3], kdp: [-0.5, 3], ldr: [-35, -20], rho: [0.95, 1.00], hid: [0, len(self.species)+1],w:[-25,25],vr:[-25,25],self.cs_name:[0,4],self.rr_name:[0.01,150]}
-        self.delta = {dz: 10, zdr: 1, kdp: 1, ldr: 5, rho: 0.005, hid: 1,w:5,vr:5,self.cs_name:1,self.rr_name:10}
-        self.units = {dz: '(dBZ)', zdr: '(dB)', kdp: '($^{\circ}$/km)', ldr: '(dB)', rho: '', hid: '',w:'m s$^{-1}$',vr:'m s$^{-1}$',self.cs_name:'',self.rr_name:'mm hr$^{-1}$'}
-        self.names = {dz: 'Z', zdr: 'Z$_{DR}$', kdp: 'K$_{dp}$', ldr: 'LDR', rho: r'$\rho_{hv}$', hid: '',w:'',vr:'V$_r$',self.cs_name:'',self.rr_name:'RR'}
-        self.longnames = {dz: 'Reflectivity', zdr: 'Differntial reflectivity', kdp: 'Specific differential phase',\
-                ldr: 'Linear depolarization ratio', rho: 'Correlation coefficient', hid: 'Hydrometeor identification',w:'Vertical Velocity',vr:'Radial Velocity',\
-                self.cs_name: 'Convective/Stratiform',self.rr_name:'Rain Rate'}
-        self.cmaps = {dz: self.temp_cmap, zdr: plt.cm.Spectral_r, kdp: plt.cm.gist_heat_r, \
-                ldr: plt.cm.gist_rainbow_r, rho: plt.cm.jet, hid: self.hid_cmap,w:plt.cm.seismic,vr:plt.cm.bwr,self.cs_name: self.cs_cmap,self.rr_name:plt.cm.Spectral_r}
+        self.lims = {dz: [0,80], zdr: [-1, 3], kdp: [-0.5, 3], ldr: [-35, -20], rho: [0.95, 1.00], hid: [0,len(self.species)+1],w:[-25,25],vr:[-25,25],self.cs_name:[0,4],self.rr_name:[0,30],self.temp_name:[-30,30]}
+        self.cfbins = {dz: np.arange(-10,60.1,1), zdr: np.arange(-2,6.01,0.05), kdp: np.arange(-2,2.01,0.05), rho: np.arange(0.5,1.01,0.02), hid: '' , w: np.arange(-25,25.1,0.5), self.temp_name: np.arange(20,-60.1,-5)} 
+        self.delta = {dz: 10, zdr: 1, kdp: 1, ldr: 5, rho: 0.005, hid: 1,w:5,vr:5,self.cs_name:1,self.rr_name:10,self.temp_name:5}
+        self.units = {dz: '(dBZ)', zdr: '(dB)', kdp: '($^{\circ}$ km$^{-1}$)', ldr: '(dB)', rho: '', hid: '',w:'(m s$^{-1}$)',vr:'(m s$^{-1}$)',self.cs_name:'',self.rr_name:'(mm hr$^{-1}$)',self.temp_name:'C'}
+        self.names = {dz: 'Z', zdr: 'Z$_{DR}$', kdp: 'K$_{dp}$', ldr: 'LDR', rho: r'$\rho_{hv}$', hid: '',w:'',vr:'V$_r$',self.cs_name:'',self.rr_name:'RR',self.temp_name:'T'}
+        self.names_uc = {dz: 'REF', zdr: 'ZDR', kdp: 'KDP', ldr: 'LDR', rho: 'RHO', hid: 'HID',w:'W',vr:'VRAD',self.cs_name:'',self.rr_name:'RR',self.temp_name:'T'}
+        self.longnames = {dz: 'Reflectivity', zdr: 'Differential Reflectivity', kdp: 'Specific Differential Phase',\
+                ldr: 'Linear Depolarization Ratio', rho: 'Correlation Coefficient', hid: 'Hydrometeor Identification',w:'Vertical Velocity',vr:'Radial Velocity',\
+                self.cs_name: 'Convective/Stratiform',self.rr_name:'Rain Rate',self.temp_name:'Temperature'}
+        #self.cmaps = {dz: self.temp_cmap, zdr: plt.cm.Spectral_r, kdp: plt.cm.gist_heat_r, ldr: plt.cm.gist_rainbow_r, rho: plt.cm.jet, hid: self.hid_cmap,w:plt.cm.seismic,vr:plt.cm.bwr,self.cs_name: self.cs_cmap,self.rr_name:plt.cm.Spectral_r,self.temp_name:'RdYlBu_r'}
+        self.cmaps = {dz: self.temp_cmap, zdr: plt.cm.Spectral_r, kdp: plt.cm.gist_heat_r, ldr: plt.cm.gist_rainbow_r, rho: plt.cm.jet, hid: self.hid_cmap,w:plt.cm.seismic,vr:plt.cm.bwr,self.cs_name: self.cs_cmap,self.rr_name:plt.get_cmap('pyart_HomeyerRainbow'),self.temp_name:'RdYlBu_r'}
         self.ticklabels = {dz: np.arange(0, 90, 10), zdr: np.arange(-1, 4, 1), kdp: np.arange(-0.5, 4.5, 1), 
                 ldr: np.arange(-35, -15, 5), rho: np.arange(0.95, 1.01, 0.005), hid: np.append('', self.species),w:np.arange(-25,30.0,5.0),vr:np.arange(-25,30.0,5.0),
-                self.cs_name: self.cs_labels,self.rr_name:[0.1,1,10,30,50,70,100,130,150]}
+                self.cs_name: self.cs_labels,self.rr_name:[0.1,1,10,30,50,70,100,130,150],self.temp_name:np.arange(-30,35,5)}
 #############################################################################################################
 
     def print_date(self,tm=None, fmt='%Y-%m-%d %H:%M:%S %Z'):
@@ -126,13 +135,19 @@ def sav_title(self,tm = None):
         return extra
 #############################################################################################################
 
-    def set_dbz_colorbar(self, color_list=None):
+    def set_dbz_colorbar(self, color_list=None, color_blind=False):
         if color_list is None:
             # just use the default here
-            radarcbar = ['PeachPuff','Aqua','DodgerBlue','MediumBlue','Lime', \
-                'LimeGreen','Green','Yellow','Orange','OrangeRed', \
-                'Red', 'Crimson','Fuchsia','Indigo','DarkCyan','White']
-        else:
+            if color_blind is not True:
+                radarcbar = ['PeachPuff','Aqua','DodgerBlue','Blue','Lime', \
+                    'LimeGreen','Green','Yellow','Orange','DarkOrange','Red', \
+                    'Crimson','Fuchsia','Purple','Indigo','MidnightBlue'] 
+            #radarcbar = ['PeachPuff','Aqua','DodgerBlue','MediumBlue','Lime', \
+            #    'LimeGreen','Green','Yellow','Orange','OrangeRed','Red', \
+            #    'Crimson','Fuchsia','Indigo','DarkCyan','White'] 
+            else:
+                radarcbar = ['Lavender', 'Thistle', 'Plum', 'MediumPurple', 'CornFlowerBlue', 'SkyBlue', 'PaleTurquoise', 'LightCyan', 'Yellow', 'Gold', 'Orange', 'DarkOrange', 'Chocolate', 'IndianRed', 'FireBrick', 'Maroon']
+        else: 
             radarcbar = deepcopy(color_list)
 
         temp_cmap = colors.ListedColormap(radarcbar)
@@ -151,7 +166,8 @@ def set_hid_colorbar(self, color_list=None):
             hidcbar = deepcopy(color_list)
         self.hid_cmap = colors.ListedColormap(hidcbar)
 
-        self.boundshid = np.arange(0,12)
+        #self.boundshid = np.arange(0,12)
+        self.boundshid = np.arange(self.hid_cmap.N+1)
         self.normhid = colors.BoundaryNorm(self.boundshid, self.hid_cmap.N)
 #############################################################################################################
     def set_cs_colorbar(self, color_list=None):