diff --git a/LiCSBAS_lib/GMT/__init__.py b/LiCSBAS_lib/GMT/__init__.py new file mode 100644 index 0000000..f1cea8f --- /dev/null +++ b/LiCSBAS_lib/GMT/__init__.py @@ -0,0 +1,15 @@ +import os +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.colors import LinearSegmentedColormap + +folder = os.path.abspath(os.path.dirname(os.path.abspath(__file__))) + +__all__ = { + 'abyss', 'bathy', 'cool', 'copper', 'cubhelix', 'cyclic', 'dem1', 'dem2', 'dem3', 'dem4', 'drywet', 'earth', 'elevation', 'etopo1', 'geo', 'globe', 'gray', 'haxby', 'hot', 'inferno', 'jet', 'magma', 'nighttime', 'no_green', 'ocean', 'plasma', 'polar', 'rainbow', 'red2green', 'relief', 'seafloor', 'sealand', 'seis', 'split', 'srtm', 'terra', 'topo', 'turbo', 'viridis', 'world', 'wysiwyg'} + +for name in __all__: + file = os.path.join(folder, name, name + '.txt') + cm_data = np.loadtxt(file) + vars()[name] = LinearSegmentedColormap.from_list(name, cm_data) + vars()[name + '_r'] = LinearSegmentedColormap.from_list(name + '_r', np.flip(cm_data, axis=0)) diff --git a/LiCSBAS_lib/GMT/abyss/abyss.txt b/LiCSBAS_lib/GMT/abyss/abyss.txt new file mode 100644 index 0000000..148997d --- /dev/null +++ b/LiCSBAS_lib/GMT/abyss/abyss.txt @@ -0,0 +1,256 @@ +0.000000 0.000000 0.000000 +0.002451 0.003676 0.006495 +0.004902 0.007353 0.012990 +0.007353 0.011029 0.019485 +0.009804 0.014706 0.025980 +0.012255 0.018382 0.032475 +0.014706 0.022059 0.038971 +0.017157 0.025735 0.045467 +0.019608 0.029412 0.051961 +0.022059 0.033088 0.058455 +0.024510 0.036765 0.064949 +0.026961 0.040439 0.071447 +0.029412 0.044118 0.077941 +0.031863 0.047796 0.084435 +0.034314 0.051471 0.090933 +0.036765 0.055145 0.097427 +0.039216 0.058824 0.103922 +0.041667 0.062502 0.110416 +0.044118 0.066176 0.116910 +0.046569 0.069851 0.123408 +0.049020 0.073529 0.129902 +0.051471 0.077208 0.136396 +0.053922 0.080882 0.142894 +0.056373 0.084557 0.149388 +0.058824 0.088235 0.155882 +0.061275 0.091910 0.162376 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numpy as np -import statsmodels.api as sm import warnings +from matplotlib.colors import LinearSegmentedColormap as LSC +from matplotlib import pyplot as plt + #%% def bl2xy(lon, lat, width, length, lat1, postlat, lon1, postlon): @@ -50,7 +54,7 @@ def bl2xy(lon, lat, width, length, lat1, postlat, lon1, postlon): """ x = int(np.round((lon - lon1)/postlon)) y = int(np.round((lat - lat1)/postlat)) - + return [x, y] @@ -66,7 +70,7 @@ def comp_size_time(file_remote, file_local): """ response = requests.head(file_remote, allow_redirects=True) - + if response.status_code != 200: return 3 elif response.headers.get("Content-Length") is None: @@ -86,6 +90,63 @@ def comp_size_time(file_remote, file_local): return 0 +#%% +def cm_insar(): + rgbs = np.zeros((256,3), dtype=np.uint8) + + for kk in range(85): + rgbs[kk,0] = kk*3 + rgbs[kk,1] = 255-kk*3 + rgbs[kk,2] = 255 + + rgbs[85:170,0] = rgbs[0:85,2] + rgbs[85:170,1] = rgbs[0:85,0] + rgbs[85:170,2] = rgbs[0:85,1] + + rgbs[170:255,0] = rgbs[0:85,1] + rgbs[170:255,1] = rgbs[0:85,2] + rgbs[170:255,2] = rgbs[0:85,0] + + rgbs[255,0] = 0 + rgbs[255,1] = 255 + rgbs[255,2] = 255 + + rgbs = np.roll(rgbs, int(256/2), axis=0) #shift green to the center + rgbs = (rgbs/255.0*200+55)/255.0 + + return LSC.from_list('cm_insar', rgbs) + + +#%% +def cm_isce(): + # https://github.com/insarlab/MintPy/blob/main/mintpy/objects/colors.py#L199 + # Almost same as GAMMA except for bottom RGB (0vs0.2), shift and flip + rgbs = np.zeros((256,3), dtype=np.uint8) + + for kk in range(85): + rgbs[kk,0] = kk*3 + rgbs[kk,1] = 255-kk*3 + rgbs[kk,2] = 255 + + rgbs[85:170,0] = rgbs[0:85,2] + rgbs[85:170,1] = rgbs[0:85,0] + rgbs[85:170,2] = rgbs[0:85,1] + + rgbs[170:255,0] = rgbs[0:85,1] + rgbs[170:255,1] = rgbs[0:85,2] + rgbs[170:255,2] = rgbs[0:85,0] + + rgbs[255,0] = 0 + rgbs[255,1] = 255 + rgbs[255,2] = 255 + + rgbs = np.roll(rgbs, int(256/2-214), axis=0) #shift green to the center + rgbs = np.flipud(rgbs) #flip up-down so that orange is in the later half (positive) + rgbs = rgbs/255.0 + + return LSC.from_list('cm_isce', rgbs) + + #%% def cmap_insar(): """ @@ -96,7 +157,7 @@ def cmap_insar(): plt.register_cmap(cmap=mpl.colors.LinearSegmentedColormap('insar', cdict)) plt.register_cmap(name='insar', data=cdict) plt.imshow(array, cmap='insar', vmin=-np.pi, vmax=np.pi, interpolation='nearest') - + Note: - Input array should be wrapped and in radian - To wrap unwrapped phase, np.angle(np.exp(1j*unw/cycle)*cycle) @@ -115,18 +176,18 @@ def cmap_insar(): redtuple=[] greentuple=[] - bluetuple=[] + bluetuple=[] for j in range(18): redtuple.append((phase[j],red_norm[j],red_norm[j+1])) greentuple.append((phase[j],green_norm[j],green_norm[j+1])) bluetuple.append((phase[j],blue_norm[j],blue_norm[j+1])) - + redtuple=tuple(redtuple) - greentuple=tuple(greentuple) + greentuple=tuple(greentuple) bluetuple=tuple(bluetuple) - + cdict = { 'red': redtuple, 'green': greentuple, 'blue': bluetuple } - + return cdict @@ -141,7 +202,7 @@ def convert_size(size_bytes): return "%s%s" % (s, size_name[i]) -#%% +#%% def download_data(url, file, n_retry=3): for i in range(n_retry): try: @@ -162,7 +223,7 @@ def download_data(url, file, n_retry=3): print(' {}, {}, {}s, {}/s'.format(os.path.basename(file), fsize, elapsed, speed), flush=True) return # success - + except Exception as e: print( ' {} for {} in {}th try'.format( e.__class__.__name__, os.path.basename(url), i+1), flush=True) @@ -177,7 +238,7 @@ def download_data(url, file, n_retry=3): def fit2d(A,w=None,deg="1"): """ Estimate best fit plain with indicated degree of polynomial. - + Inputs: A : Input ndarray (can include nan) w : Wieight (1/std**2) for each element of A (with the same dimention as A) @@ -185,17 +246,18 @@ def fit2d(A,w=None,deg="1"): - 1 -> a+bx+cy (ramp) - bl -> a+bx+cy+dxy (biliner) - 2 -> a+bx+cy+dxy+ex**2_fy**2 (2d polynomial) - + Returns: Afit : Best fit plain with the same demention as A m : set of parameters of best fit plain (a,b,c...) - + """ + import statsmodels.api as sm ### Make design matrix G length,width = A.shape #read dimension Xgrid,Ygrid = np.meshgrid(np.arange(width),np.arange(length)) #mesh grid - + if str(deg) == "1": G = np.stack((np.ones((length*width)), Xgrid.flatten(), Ygrid.flatten())).T elif str(deg) == "bl": @@ -205,7 +267,7 @@ def fit2d(A,w=None,deg="1"): else: print('\nERROR: Not proper deg ({}) is used\n'.format(deg), file=sys.stderr) return False - + ### Handle nan by 0 padding and 0 weight # Not drop in sm because cannot return Afit if np.any(np.isnan(A)): @@ -222,7 +284,7 @@ def fit2d(A,w=None,deg="1"): results = sm.OLS(A.ravel(), G).fit() else: ## Weighted LS results = sm.WLS(A.ravel(), G, weights=w.ravel()).fit() - + m = results.params Afit = np.float32(results.predict().reshape((length,width))) @@ -233,7 +295,7 @@ def fit2d(A,w=None,deg="1"): def fit2dh(A, deg, hgt, hgt_min, hgt_max): """ Estimate best fit 2d ramp and topography-correlated component simultaneously. - + Inputs: A : Input ndarray (can include nan) deg : degree of polynomial for fitting ramp @@ -245,12 +307,13 @@ def fit2dh(A, deg, hgt, hgt_min, hgt_max): If blank, don*t estimate topo-corr component. hgt_min : Minimum hgt to take into account in hgt-linear hgt_max : Maximum hgt to take into account in hgt-linear - + Returns: Afit : Best fit solution with the same demention as A m : Set of parameters of best fit plain (a,b,c...) - + """ + import statsmodels.api as sm ### Make design matrix G length, width = A.shape @@ -271,7 +334,7 @@ def fit2dh(A, deg, hgt, hgt_min, hgt_max): print('\nERROR: Not proper deg ({}) is used\n'.format(deg), file=sys.stderr) return False G = sm.add_constant(G) - + if len(hgt) > 0: _hgt = hgt.copy() ## Not to overwrite hgt in main _hgt[np.isnan(_hgt)] = 0 @@ -291,13 +354,75 @@ def fit2dh(A, deg, hgt, hgt_min, hgt_max): return Afit, m +#%% +def get_cmap(cmap_name, cmapN=256): + """ + Return cmap (LinearSegmentedColormap). + cmap_name can be: + - Matplotlib predefined name (e.g. viridis) + - Scientific colour maps (e.g. SCM.roma) + - Generic Mapping Tools (e.g. GMT.polar) + - cmocean (e.g. cmocean.phase) + - colorcet (e.g. colorcet.CET_C1) + - cm_insar, cm_isce + All cmap can be reversed with "_r" + """ + flag = 0 # mpl + if cmap_name == 'cm_insar': + _cmap = cm_insar() + flag = 1 + elif cmap_name == 'cm_isce': + _cmap = cm_isce() + flag = 1 + elif cmap_name.startswith('SCM'): + import SCM as CMAP + flag = 2 + elif cmap_name.startswith('GMT'): + import GMT as CMAP + flag = 2 + elif cmap_name.startswith('cmocean'): + import cmocean as CMAP + flag = 2 + elif cmap_name.startswith('colorcet'): + import colorcet as CMAP + flag = 3 + + if flag >= 2: + cmdir = os.path.dirname(CMAP.__file__) + name = cmap_name.split('.')[1] + if not cmap_name.endswith('_r'): + if flag == 2: + file = os.path.join(cmdir, name, name+'.txt') + cm_data = np.loadtxt(file) + elif flag == 3: + file = os.path.join(cmdir, name+'.csv') + cm_data = np.loadtxt(file, delimiter=',') + _cmap = LSC.from_list(name, cm_data) + else: # Reversed + if flag == 2: + file = os.path.join(cmdir, name[:-2], name[:-2]+'.txt') + cm_data = np.loadtxt(file) + elif flag == 3: + file = os.path.join(cmdir, name[:-2]+'.csv') + cm_data = np.loadtxt(file, delimiter=',') + + _cmap = LSC.from_list(name, np.flip(cm_data, axis=0)) + + if flag >= 1: + plt.cm.register_cmap(name = cmap_name, cmap = _cmap) + + cmap = plt.get_cmap(cmap_name, cmapN) + + return cmap + + #%% def get_ifgdates(ifgdir): """ Get ifgdates and imdates in ifgdir. - + Returns: - ifgdates : List of dates of ifgs + ifgdates : List of dates of ifgs imdates : List of dates of images """ ifgdates = [str(k) for k in sorted(os.listdir(ifgdir)) @@ -314,7 +439,7 @@ def get_ifgdates(ifgdir): def get_patchrow(width, length, n_data, memory_size): """ Get patch number of rows for memory size (in MB). - + Returns: n_patch : Number of patches (int) patchrow : List of the number of rows for each patch. @@ -368,7 +493,7 @@ def multilook(array, nlook_r, nlook_c, n_valid_thre=0.5): n_valid = np.sum(~np.isnan(array_reshape), axis=(1, 3)) bool_invalid = n_valid < n_valid_thre*nlook_r*nlook_c array_ml[bool_invalid] = np.nan - + return array_ml @@ -384,7 +509,7 @@ def read_point(point_str, width, length): print("\nERROR:", file=sys.stderr) print("Point format seems to be wrong (should be x/y)", file=sys.stderr) return False - + return [x, y] @@ -407,7 +532,7 @@ def read_range(range_str, width, length): print("\nERROR:", file=sys.stderr) print("Range format seems to be wrong (should be x1:x2/y1:y2)", file=sys.stderr) return False - + return [x1, x2, y1, y2] @@ -423,7 +548,7 @@ def read_range_line(range_str, width, length): print("\nERROR:", file=sys.stderr) print("Range format seems to be wrong (must be x1,y1/x2,y2)", file=sys.stderr) return False - + return [x1, x2, y1, y2] @@ -437,7 +562,7 @@ def read_range_geo(range_str, width, length, lat1, postlat, lon1, postlon): """ lat2 = lat1+postlat*(length-1) lon2 = lon1+postlon*(width-1) - + if re.match('[+-]?\d+(?:\.\d+)?/[+-]?\d+(?:\.\d+)?/[+-]?\d+(?:\.\d+)?/[+-]?\d+(?:\.\d+)?', range_str): lon_w, lon_e, lat_s, lat_n = [float(s) for s in range_str.split('/')] x1 = int(np.round((lon_w - lon1)/postlon)) if lon_w > lon1 else 0 @@ -448,7 +573,7 @@ def read_range_geo(range_str, width, length, lat1, postlat, lon1, postlon): print("\nERROR:", file=sys.stderr) print("Range format seems to be wrong (should be lon1/lon2/lat1/lat2)", file=sys.stderr) return False - + return [x1, x2, y1, y2] @@ -469,7 +594,7 @@ def read_range_line_geo(range_str, width, length, lat_n, postlat, lon_w, postlon print("\nERROR:", file=sys.stderr) print("Range format seems to be wrong (should be lon1,lat1/lon2,lat2)", file=sys.stderr) return False - + return [x1, x2, y1, y2] @@ -480,5 +605,5 @@ def xy2bl(x, y, lat1, dlat, lon1, dlon): """ lat = lat1+dlat*y lon = lon1+dlon*x - + return lat, lon diff --git a/LiCSBAS_lib/cmocean/29-3_thyng.pdf b/LiCSBAS_lib/cmocean/29-3_thyng.pdf new file mode 100644 index 0000000..cd0c3c8 Binary files /dev/null and b/LiCSBAS_lib/cmocean/29-3_thyng.pdf differ diff --git a/LiCSBAS_lib/cmocean/__init__.py b/LiCSBAS_lib/cmocean/__init__.py new file mode 100644 index 0000000..25f8183 --- /dev/null +++ b/LiCSBAS_lib/cmocean/__init__.py @@ -0,0 +1,15 @@ +import os +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.colors import LinearSegmentedColormap + +folder = os.path.abspath(os.path.dirname(os.path.abspath(__file__))) + +__all__ = { + 'algae', 'amp', 'balance', 'curl', 'deep', 'delta', 'dense', 'diff', 'gray', 'haline', 'ice', 'matter', 'oxy', 'phase', 'rain', 'solar', 'speed', 'tarn', 'tempo', 'thermal', 'topo', 'turbid'} + +for name in __all__: + file = os.path.join(folder, name, name + '.txt') + cm_data = np.loadtxt(file) + vars()[name] = LinearSegmentedColormap.from_list(name, cm_data) + vars()[name + '_r'] = LinearSegmentedColormap.from_list(name + '_r', np.flip(cm_data, axis=0)) diff --git a/LiCSBAS_lib/cmocean/algae/algae.txt b/LiCSBAS_lib/cmocean/algae/algae.txt new file mode 100644 index 0000000..6abc90f --- /dev/null +++ b/LiCSBAS_lib/cmocean/algae/algae.txt @@ -0,0 +1,256 @@ +8.429022637670927631e-01 9.769128443086748659e-01 8.146495714674897304e-01 +8.379898654100343958e-01 9.732407342044756549e-01 8.088430556678033456e-01 +8.330792003033266058e-01 9.695822214541992556e-01 8.030532648620265501e-01 +8.281700574948731575e-01 9.659372187629376993e-01 7.972802422761141594e-01 +8.232591263824388106e-01 9.623071583180456967e-01 7.915177499867750432e-01 +8.183491723383330418e-01 9.586904682961984170e-01 7.857720506350698297e-01 +8.134400361234097598e-01 9.550870346415619716e-01 7.800433040617480440e-01 +8.085287334688994187e-01 9.514980955891142456e-01 7.743261813916382241e-01 +8.036173420648491383e-01 9.479224436104144447e-01 7.686253533397395810e-01 +7.987060409170214648e-01 9.443598003220095016e-01 7.629416545120045745e-01 +7.937925122347354590e-01 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b/LiCSBAS_lib/colorcet/__init__.py @@ -0,0 +1,15 @@ +import os +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.colors import LinearSegmentedColormap + +folder = os.path.abspath(os.path.dirname(os.path.abspath(__file__))) + +__all__ = { + 'CET_C1', 'CET_C1s', 'CET_C2', 'CET_C2s', 'CET_C4', 'CET_C4s', 'CET_C5', 'CET_C5s', 'CET_CBC1', 'CET_CBC2', 'CET_CBD1', 'CET_CBL1', 'CET_CBL2', 'CET_CBTC1', 'CET_CBTC2', 'CET_CBTD1', 'CET_CBTL1', 'CET_CBTL2', 'CET_D1', 'CET_D10', 'CET_D11', 'CET_D12', 'CET_D13', 'CET_D1A', 'CET_D2', 'CET_D3', 'CET_D4', 'CET_D6', 'CET_D7', 'CET_D8', 'CET_D9', 'CET_I1', 'CET_I2', 'CET_I3', 'CET_L1', 'CET_L10', 'CET_L11', 'CET_L12', 'CET_L13', 'CET_L14', 'CET_L15', 'CET_L16', 'CET_L17', 'CET_L18', 'CET_L19', 'CET_L2', 'CET_L3', 'CET_L4', 'CET_L5', 'CET_L6', 'CET_L7', 'CET_L8', 'CET_L9', 'CET_R1', 'CET_R2', 'CET_R3'} + +for name in __all__: + file = os.path.join(folder, name + '.csv') + cm_data = np.loadtxt(file, delimiter=',') + vars()[name] = LinearSegmentedColormap.from_list(name, cm_data) + vars()[name + '_r'] = LinearSegmentedColormap.from_list(name + '_r', np.flip(cm_data, axis=0)) diff --git a/LiCSBAS_lib/extract_cmaps_GMT.sh b/LiCSBAS_lib/extract_cmaps_GMT.sh new file mode 100755 index 0000000..3102c37 --- /dev/null +++ b/LiCSBAS_lib/extract_cmaps_GMT.sh @@ -0,0 +1,66 @@ +#!/bin/bash -eu + +cptdir="[Insert path]/gmt/cpt" +outdir="GMT" +init="$outdir/__init__.py" + +discrete=("categorical" "gebco" "ibcso" "mag" "paired" "panoply") +SCM=("acton" "bam" "bamO" "bamako" "batlow" "batlowK" "batlowW" "berlin" "bilbao" "broc" "brocO" "buda" "bukavu" "cork" "corkO" "davos" "devon" "fes" "grayC" "hawaii" "imola" "lajolla" "lapaz" "lisbon" "nuuk" "oleron" "oslo" "roma" "romaO" "tofino" "tokyo" "turku" "vanimo" "vik" "vikO") + +### header of init file +mkdir -p $outdir +cat << EOF > $init +import os +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.colors import LinearSegmentedColormap + +folder = os.path.abspath(os.path.dirname(os.path.abspath(__file__))) + +__all__ = { +EOF + + +### Make cmap.txt for all colors +for cpt in $(ls $cptdir/*.cpt | awk -F/ '{print $NF}') +do + cmap="${cpt%.cpt}" + echo "$cmap" + + for a in ${discrete[@]} + do + if [ "$cmap" == "$a" ]; then + echo "Skip because discrete." + continue 2 + fi + done + + for a in ${SCM[@]} + do + if [ "$cmap" == "$a" ]; then + echo "Skip because SCM." + continue 2 + fi + done + + mkdir -p $outdir/$cmap + + echo -n " '${cmap}'," >> $init + + gmt makecpt -C$cpt -T0/256/1 -Fr -Z | head -256 | awk '{print $2}' | \ + awk -F/ '{printf "%8.6f %8.6f %8.6f\n", $1/255, $2/255, $3/255}' > $outdir/$cmap/${cmap}.txt +done + + +### footer of init file +sed -i '$s/.$//' $init ## remove last "," +cat << EOF >> $init +} + +for name in __all__: + file = os.path.join(folder, name, name + '.txt') + cm_data = np.loadtxt(file) + vars()[name] = LinearSegmentedColormap.from_list(name, cm_data) + vars()[name + '_r'] = LinearSegmentedColormap.from_list(name + '_r', np.flip(cm_data, axis=0)) +EOF + diff --git a/bin/LiCSBAS_color_geotiff.py b/bin/LiCSBAS_color_geotiff.py index 204c5cd..bb38c54 100755 --- a/bin/LiCSBAS_color_geotiff.py +++ b/bin/LiCSBAS_color_geotiff.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -v1.3 20200904 Yu Morishita, GSI +v1.4 20210205 Yu Morishita, GSI ======== Overview @@ -13,10 +13,20 @@ LiCSBAS_color_geotiff.py -i infile [-c cmap] [-o outfile] [--cmin float] [--cmax float] [--n_color int] [--no_colorbar] -i Input data GeoTIFF file - -c Colormap name (Default: SCM.roma_r. See below for available colormap) - - https://matplotlib.org/tutorials/colors/colormaps.html - - http://www.fabiocrameri.ch/colourmaps.php (e.g., SCM.roma) - - insar (n_color=16) + -c Colormap name (Default: SCM.roma_r, reverse of SCM.roma) + Available colormaps (all cmap can be reversed with "_r"): + - Matplotlib predefined name (e.g. viridis) + https://matplotlib.org/tutorials/colors/colormaps.html + - Scientific colour maps (e.g. SCM.roma) + http://www.fabiocrameri.ch/colourmaps.php + - Generic Mapping Tools (e.g. GMT.polar) + https://docs.generic-mapping-tools.org/dev/cookbook/cpts.html + - cmocean (e.g. cmocean.phase) + https://matplotlib.org/cmocean/ + - colorcet (e.g. colorcet.CET_C1) + https://colorcet.holoviz.org/ + - cm_insar (GAMMA standard rainbow color for wrapped phase) + - cm_isce (ISCE standard rainbow color for wrapped phase) -o Output colored GeoTIFF file (Default: [infile%.tif].cmap_cmin_cmax.tif) --cmin|cmax Min|max values of color (Default: None (auto)) --n_color Number of rgb quantization levels (Default: 256) @@ -25,6 +35,8 @@ """ #%% Change log ''' +v1.4 20210205 Yu Morishita, GSI + - More cmap available v1.3 20200904 Yu Morishita, GSI - Avoid segmentation fault v1.2 20200827 Yu Morishita, GSI @@ -42,11 +54,11 @@ import sys #import gdal # may cause segmentation fault in savefig? import time -import SCM import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl import LiCSBAS_tools_lib as tools_lib +from osgeo import gdal class Usage(Exception): """Usage context manager""" @@ -58,9 +70,9 @@ def __init__(self, msg): ## Not use def main to use global valuables if __name__ == "__main__": argv = sys.argv - + start = time.time() - ver=1.3; date=20200904; author="Y. Morishita" + ver=1.4; date=20210205; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) @@ -73,7 +85,7 @@ def __init__(self, msg): cmax = None n_color = 256 cbar_flag = True - + gdal_option = ['COMPRESS=DEFLATE'] #%% Read options @@ -115,37 +127,11 @@ def __init__(self, msg): sys.exit(2) - #%% Set cmap if SCM - if cmap_name.startswith('SCM'): - cmap = [] ## Not necessary - if cmap_name.endswith('_r'): - exec("cmap = {}.reversed()".format(cmap_name[:-2])) - else: - exec("cmap = {}".format(cmap_name)) - cmap_name = cmap_name.replace('SCM.', '') - plt.register_cmap(name=cmap_name, cmap=cmap, lut=n_color) - elif cmap_name == 'insar': - cdict = tools_lib.cmap_insar() - plt.register_cmap(cmap=mpl.colors.LinearSegmentedColormap('insar', cdict)) + #%% Set cmap + cmap = tools_lib.get_cmap(cmap_name, n_color) - cmap = plt.get_cmap(cmap_name, n_color) - - - #%% colorbar - if cbar_flag: - fig, ax = plt.subplots(figsize=(3, 1)) - norm = mpl.colors.Normalize(cmin, cmax) - mpl.colorbar.ColorbarBase(ax, cmap=cmap, norm=norm, orientation='horizontal') - cbarfile = "{}_{}_{}.pdf".format(cmap_name, cmin, cmax) - plt.tight_layout() - plt.savefig(cbarfile, transparent=True) - plt.close() - - #%% Set color range - from osgeo import gdal - ### Auto if cmin is None: cmin = gdal.Info(infile, computeMinMax=True, format="json")["bands"][0]['computedMin'] @@ -178,16 +164,16 @@ def __init__(self, msg): format="GTiff", creationOptions=gdal_option, addAlpha=4) - #%% colorbar. Move before import gdal to avoid segmentation fault - # if cbar_flag: - # fig, ax = plt.subplots(figsize=(3, 1)) - # norm = mpl.colors.Normalize(cmin, cmax) - # mpl.colorbar.ColorbarBase(ax, cmap=cmap, norm=norm, orientation='horizontal') - # cbarfile = "{}_{}_{}.pdf".format(cmap_name, cmin, cmax) - # plt.tight_layout() - # plt.savefig(cbarfile, transparent=True) - # plt.close() - + #%% colorbar. Move before import gdal to avoid segmentation fault + if cbar_flag: + fig, ax = plt.subplots(figsize=(3, 1)) + norm = mpl.colors.Normalize(cmin, cmax) + mpl.colorbar.ColorbarBase(ax, cmap=cmap, norm=norm, orientation='horizontal') + cbarfile = "{}_{}_{}.pdf".format(cmap_name, cmin, cmax) + plt.tight_layout() + plt.savefig(cbarfile, transparent=True) + plt.close() + #%% Remove intermediate files os.remove(colorfile) diff --git a/bin/LiCSBAS_disp_img.py b/bin/LiCSBAS_disp_img.py index 3d395e7..be9c920 100755 --- a/bin/LiCSBAS_disp_img.py +++ b/bin/LiCSBAS_disp_img.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -v1.10.0 20210120 Yu Morishita, GSI +v1.11.0 20210205 Yu Morishita, GSI This script displays an image file. @@ -14,11 +14,20 @@ -i Input image file in float32, uint8, GeoTIFF, or NetCDF -p Parameter file containing width and length (e.g., EQA.dem_par or mli.par) (Not required if input is GeoTIFF or NetCDF) - -c Colormap name (see below for available colormap) - - https://matplotlib.org/tutorials/colors/colormaps.html - - http://www.fabiocrameri.ch/colourmaps.php - - insar (GAMMA standard rainbow color for wrapped phase) - (Default: SCM.roma_r, reverse of SCM.roma) + -c Colormap name (Default: SCM.roma_r, reverse of SCM.roma) + Available colormaps (all cmap can be reversed with "_r"): + - Matplotlib predefined name (e.g. viridis) + https://matplotlib.org/tutorials/colors/colormaps.html + - Scientific colour maps (e.g. SCM.roma) + http://www.fabiocrameri.ch/colourmaps.php + - Generic Mapping Tools (e.g. GMT.polar) + https://docs.generic-mapping-tools.org/dev/cookbook/cpts.html + - cmocean (e.g. cmocean.phase) + https://matplotlib.org/cmocean/ + - colorcet (e.g. colorcet.CET_C1) + https://colorcet.holoviz.org/ + - cm_insar (GAMMA standard rainbow color for wrapped phase) + - cm_isce (ISCE standard rainbow color for wrapped phase) --cmin|cmax Min|max values of color (Default: None (auto)) --auto_crange % of color range used for automatic determination (Default: 99) --n_color Number of rgb quantization levels (Default: 256) @@ -34,6 +43,9 @@ #%% Change log ''' +v1.11 20210205 Yu Morishita, GSI + - More cmap available + - Show colorbar for cyclic cmaps v1.10 20210120 Yu Morishita, GSI - Add --n_color option - Bug fix in creating kmz with standard cmap @@ -71,11 +83,11 @@ import getopt import sys import os +import re import matplotlib.pyplot as plt import matplotlib as mpl import numpy as np import subprocess as subp -import SCM import zipfile from osgeo import gdal @@ -111,7 +123,7 @@ def make_kmz(lat1, lat2, lon1, lon2, pngfile, kmzfile, pngcfile, description): if __name__ == "__main__": argv = sys.argv - ver="1.10.0"; date=20210120; author="Y. Morishita" + ver="1.11.0"; date=20210205; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) @@ -179,22 +191,6 @@ def make_kmz(lat1, lat2, lon1, lon2, pngfile, kmzfile, pngcfile, description): sys.exit(2) - #%% Set cmap if SCM or insar - if cmap_name.startswith('SCM'): - cmap = [] ## Not necessary - if cmap_name.endswith('_r'): - exec("cmap = {}.reversed()".format(cmap_name[:-2])) - else: - exec("cmap = {}".format(cmap_name)) - cmap_name = cmap_name.replace('SCM.', '') - plt.register_cmap(name=cmap_name, cmap=cmap, lut=n_color) - elif cmap_name == 'insar': - cdict = tools_lib.cmap_insar() - plt.register_cmap(cmap=mpl.colors.LinearSegmentedColormap('insar', cdict)) - - cmap = plt.get_cmap(cmap_name, n_color) - - #%% Get info and Read data if gdal.IdentifyDriver(infile): ## If Geotiff or grd geotiff = gdal.Open(infile) @@ -257,8 +253,17 @@ def make_kmz(lat1, lat2, lon1, lon2, pngfile, kmzfile, pngcfile, description): data[data==nodata] = np.nan - #%% Set cyclic and color range - if cmap_name == 'insar' or (cmap_name.startswith('SCM') and 'O' in cmap_name): + #%% Get cmap, set cyclic and color range + cmap = tools_lib.get_cmap(cmap_name, n_color) + + if cmap_name == 'cm_insar' or \ + cmap_name == 'cm_isce' or \ + (cmap_name.startswith('SCM') and 'O' in cmap_name) or \ + 'GMT.cyclic' in cmap_name or \ + 'cmocean.phase' in cmap_name or \ + (cmap_name.startswith('colorcet') and + re.search(r'C[1-5]', cmap_name) is not None): + print('\n{} is a cyclic cmap.'.format(cmap_name)) cyclic= True data = np.angle(np.exp(1j*(data/cycle))*cycle) cmin = -np.pi @@ -292,18 +297,20 @@ def make_kmz(lat1, lat2, lon1, lon2, pngfile, kmzfile, pngcfile, description): plt.close() ### Make cbar png + fig, ax = plt.subplots(figsize=(3, 1)) + norm = mpl.colors.Normalize(cmin, cmax) + cbar = mpl.colorbar.ColorbarBase(ax, cmap=cmap, norm=norm, orientation='horizontal') + pngcfile = kmzname.replace('.kmz', '_ctmp.png') + plt.tight_layout() if cyclic: - description = '{}*2pi/cycle'.format(cycle) - pngcfile = [] + cbar.set_ticks([]) + descr_cycle = '{}*2pi/cycle'.format(cycle) else: - fig, ax = plt.subplots(figsize=(3, 1)) - norm = mpl.colors.Normalize(cmin, cmax) - mpl.colorbar.ColorbarBase(ax, cmap=cmap, norm=norm, orientation='horizontal') - pngcfile = kmzname.replace('.kmz', '_ctmp.png') - plt.tight_layout() - plt.savefig(pngcfile, transparent=True) - plt.close() - description = ']]>'.format(os.path.basename(pngcfile)) + descr_cycle = '' + plt.savefig(pngcfile, transparent=True) + plt.close() + + description = ']]>'.format(descr_cycle, os.path.basename(pngcfile)) make_kmz(lat_s_p, lat_n_p, lon_w_p, lon_e_p, pngnametmp, kmzname, pngcfile, description) @@ -324,6 +331,8 @@ def make_kmz(lat1, lat2, lon1, lon2, pngfile, kmzfile, pngcfile, description): plt.imshow(data, clim=[cmin, cmax], cmap=cmap, interpolation=interp) if cyclic: plt.title('{}*2pi/cycle'.format(cycle)) + cbar = plt.colorbar() + cbar.set_ticks([]) else: plt.colorbar() plt.tight_layout() diff --git a/bin/LiCSBAS_plot_ts.py b/bin/LiCSBAS_plot_ts.py index 05b125c..f7a0c29 100755 --- a/bin/LiCSBAS_plot_ts.py +++ b/bin/LiCSBAS_plot_ts.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -v1.13.2 20210126 Yu Morishita, GSI +v1.13.3 20210205 Yu Morishita, GSI ======== Overview @@ -38,9 +38,8 @@ --ref_geo Initial reference area in geographical coordinates. -p Initial selected point for time series plot (Default: ref point) --p_geo Initial selected point in geographical coordinates. - -c Color map for velocity and cumulative displacement - - https://matplotlib.org/tutorials/colors/colormaps.html - - http://www.fabiocrameri.ch/colourmaps.php + -c Color map for velocity and cumulative displacement. + See help of LiCSBAS_disp_img.py. (Default: SCM.roma_r, reverse of SCM.roma) --nomask Not use mask (Default: use mask) --vmin|vmax Min|max values of color for velocity map (Default: auto) @@ -54,6 +53,8 @@ """ #%% Change log ''' +v1.13.3 20210205 Yu Morishita, GSI + - More cmap available v1.13.2 20210126 Yu Morishita, GSI - Small bug fix in -r and noise indices - Change initial point to center of ref area @@ -169,7 +170,7 @@ def calc_model(dph, imdates_ordinal, xvalues, model): if __name__ == "__main__": argv = sys.argv - ver="1.13.2"; date=20210126; author="Y. Morishita" + ver="1.13.3"; date=20210205; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) @@ -190,7 +191,7 @@ def calc_model(dph, imdates_ordinal, xvalues, model): ts_pngfile = [] vmin = None vmax = None - cmap = "SCM.roma_r" + cmap_name = "SCM.roma_r" auto_crange = 99.0 #%% Read options @@ -224,7 +225,7 @@ def calc_model(dph, imdates_ordinal, xvalues, model): elif o == '--p_geo': point_geo = a elif o == '-c': - cmap = a + cmap_name = a elif o == '--nomask': maskflag = False elif o == '--vmin': @@ -249,12 +250,9 @@ def calc_model(dph, imdates_ordinal, xvalues, model): sys.exit(2) - #%% Set cmap if SCM - if cmap.startswith('SCM'): - if cmap.endswith('_r'): - exec("cmap = {}.reversed()".format(cmap[:-2])) - else: - exec("cmap = {}".format(cmap)) + #%% Set cmap + cmap = tools_lib.get_cmap(cmap_name) + #%% Set files ### cumfile