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#,nmʺ*uoT}仪2UY.oTUғ<ړWj=64.0", "setuptools_scm[toml]>=8", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "pyaps3"
description = "Python based Atmospheric Phase Screen estimation"
authors = [
{name="Romain Jolivet", email="insar@geologie.ens.fr"},
{name="Angelique Benoit"},
]
requires-python = ">=3.8"
keywords = ["InSAR", "troposphere", "geodesy", "geophysics", "ERA5"]
license = {text = "GPL-3.0-or-later"}
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
]
# see section: setuptools_scm
# https://setuptools.pypa.io/en/latest/userguide/pyproject_config.html#dynamic-metadata
# dependencies will be read from text files
dynamic = ["version", "readme", "dependencies", "optional-dependencies"]
[project.urls]
"Homepage" = "https://github.com/insarlab/PyAPS"
"Issues" = "https://github.com/insarlab/PyAPS/issues"
[tool.setuptools]
include-package-data = true
zip-safe = false
[tool.setuptools.dynamic]
dependencies = { file = ["requirements.txt"] }
readme = { file = ["README.md"], content-type = "text/markdown" }
# extra requirements: `pip install pyaps3[test]` or `pip install .[test]`
[tool.setuptools.dynamic.optional-dependencies.test]
file = ["tests/requirements.txt"]
[tool.setuptools.packages.find]
where = ["src"]
[tool.setuptools.package-data]
pyaps3 = ["*.cfg"]
[tool.setuptools_scm]
version_scheme = "post-release"
local_scheme = "no-local-version"
PyAPS-0.3.6/requirements.txt 0000664 0000000 0000000 00000000227 14751542053 0015747 0 ustar 00root root 0000000 0000000 cdsapi>=0.7.2
numpy
pygrib
scipy
urllib3
#netcdf4 #for MERRA, which is currently not supported
#pyhdf #for MERRA, which is currently not supported
PyAPS-0.3.6/src/ 0000775 0000000 0000000 00000000000 14751542053 0013251 5 ustar 00root root 0000000 0000000 PyAPS-0.3.6/src/pyaps3/ 0000775 0000000 0000000 00000000000 14751542053 0014470 5 ustar 00root root 0000000 0000000 PyAPS-0.3.6/src/pyaps3/__init__.py 0000664 0000000 0000000 00000002437 14751542053 0016607 0 ustar 00root root 0000000 0000000 '''
PyAPS module to compute InSAR phase delay maps from weather models.
Written by Romain Jolivet and Piyush Agram .
The original Fortran package was written by Romain Jolivet and the Python version including
support for different models was written by Piyush Agram.
.. note::
Details of the python module can be obtained `here. `
'''
# get version info [requires python >=3.8]
from importlib.metadata import PackageNotFoundError, version
try:
__version__ = version(__name__)
except PackageNotFoundError:
print('package is not installed!\n'
'Please follow the installation instructions in the README.md.\n'
'Or, to just get the version number, use:\n'
' python -m setuptools_scm')
# top-level functions
from pyaps3.objects import PyAPS
from pyaps3.autoget import ECMWFdload, MERRAdload, NARRdload
__all__ = ['__version__', 'PyAPS', 'ECMWFdload', 'MERRAdload', 'NARRdload']
############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
############################################################
PyAPS-0.3.6/src/pyaps3/autoget.py 0000664 0000000 0000000 00000021455 14751542053 0016521 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
import os.path
import configparser
import urllib3
import cdsapi
import pyaps3 as pa
# Read account setup in model.cfg before using
config = None
cfg_file = os.path.join(os.path.dirname(pa.__file__), 'model.cfg')
if os.path.isfile(cfg_file):
config = configparser.RawConfigParser(delimiters='=')
config.read(cfg_file)
def ECMWFdload(bdate,hr,filedir,model='ERA5',datatype='fc',humidity='Q',snwe=None,flist=None):
'''
ECMWF data downloading.
Args:
* bdate : date to download (str)
* hr : hour to download (str)
* filedir : files directory (str)
* model : weather model ('ERA5', 'ERAINT', 'HRES')
* datatype : reanalysis data type (an)
* snwe : area extent (tuple of int)
* humidity : humidity
'''
#-------------------------------------------
# Initialize
# Check data
assert model in ('ERA5', 'ERAINT', 'HRES'), f'Unknown model for ECMWF: {model}'
# Infos for downloading
if model == 'ERAINT':
print('WARNING: you are downloading from the legacy ECMWF platform. '
'ERA-Interim is deprecated, use ERA-5 instead.')
if model == 'ERA5':
cds_url = 'https://cds.climate.copernicus.eu/api'
print('INFO: You are using the latest ECMWF platform for downloading datasets: ', cds_url)
#-------------------------------------------
# Define parameters
# Humidity
assert humidity in ('Q','R'), 'Unknown humidity field for ECMWF'
if humidity == 'Q':
humidparam = 'specific_humidity' if model == 'ERA5' else 133
elif humidity == 'R':
humidparam = 'relative_humidity' if model == 'ERA5' else 157
#-------------------------------------------
# file name
if not flist:
prefix_dict = {
'ERA5' : 'ERA5',
'ERAINT' : 'ERAI',
'HRES' : 'HRES',
}
if model not in prefix_dict.keys():
raise ValueError('unrecognized model input: {}'.format(model))
fbase = os.path.join(filedir, prefix_dict[model])
flist = []
for day in bdate:
fname = fbase
fname += pa.utils.snwe2str(snwe) if snwe is not None else ''
fname += '_{}_{}.grb'.format(day, hr)
flist.append(fname)
# Iterate over dates
for i, day in enumerate(bdate):
fname = flist[i]
#-------------------------------------------
# CASE 1: request for CDS API client (new ECMWF platform, for ERA5)
if model == 'ERA5':
# Contact the server
rc_file = os.path.expanduser('~/.cdsapirc')
if os.path.isfile(rc_file):
c = cdsapi.Client()
else:
url = cds_url
key = config.get('CDS', 'key')
c = cdsapi.Client(url=url, key=key)
# request dictionary
pressure_lvls = [
'1','2','3','5','7','10','20','30','50',
'70','100','125','150','175','200','225',
'250','300','350','400','450','500','550',
'600','650','700','750','775','800','825',
'850','875','900','925','950','975','1000',
]
indict = {
'product_type' : ['reanalysis'],
'variable' : ['geopotential', 'temperature', f'{humidparam}'],
'year' : [f'{day[0:4]}'],
'month' : [f'{day[4:6]}'],
'day' : [f'{day[6:8]}'],
'time' : [f'{hr}:00'],
'pressure_level' : pressure_lvls,
'data_format' : 'grib',
}
# download a geographical area subset
if snwe is not None:
s, n, w, e = snwe
indict['area'] = [n, w, s, e]
# Assert grib file not yet downloaded
if not os.path.exists(fname):
print(f'Downloading {i+1} of {len(bdate)}: {fname} ')
print(indict)
# Make the request
ds_name = f'reanalysis-{model.lower()}-pressure-levels'
c.retrieve(ds_name, indict, target=fname)
#-------------------------------------------
# CASE 2: request for WEB API client (old ECMWF platform, deprecated, for ERA-Int and HRES)
else:
# Grid size (only for HRES and ERA-Interim)
if model == 'HRES':
gridsize = '0.10/0.10'
elif model == 'ERAINT':
gridsize = '0.75/0.75'
# Contact the server
from pyaps3.ecmwfapi import ECMWFDataServer
url = "https://api.ecmwf.int/v1"
emid = config.get('ECMWF', 'email')
key = config.get('ECMWF', 'key')
server = ECMWFDataServer(url=url, key=key, email=emid)
# Dictionary
indict = {'dataset' : '{}'.format(model),
'type' : '{}'.format(datatype),
'date' : '{}'.format(day),
'time' : '{}'.format(hr),
'step' : '0',
'levtype' : "pl",
'levelist' : "all",
'grid' : '{}'.format(gridsize),
'param' : '129/130/{}'.format(humidparam),
'target' : '{}'.format(fname)}
# Assert grib file not yet downloaded
if not os.path.exists(fname):
print('Downloading %d of %d: %s '%(i+1,len(bdate),fname))
print(indict)
# Make the request
server.retrieve(indict)
return flist
def MERRAdload(bdate,hr,filedir, hdf=False):
print('By default, downloads MERRA-2 data.')
user = config.get('MERRA', 'user')
pw = config.get('MERRA', 'password')
if not os.path.isdir(filedir):
os.makedirs(filedir)
print('create foler: {}'.format(filedir))
flist = []
for i, date in enumerate(bdate):
filename = '%s/merra-%s-%s.nc4' %(filedir,date,hr)
flist.append(filename)
print('Downloading %d of %d: %s'%((i+1),len(bdate),filename))
yr = date[0:4]
mon = date[4:6]
year = int(yr)
url1 = 'http://goldsmr5.gesdisc.eosdis.nasa.gov/daac-bin/OTF/'
url1 += 'HTTP_services.cgi?FILENAME=%2Fdata%2Fs4pa%2FMERRA2%2FM2I6NPANA.5.12.4%2F'
url2 = '%2F'
url3 = '%2FMERRA2_300.inst6_3d_ana_Np.'
url3n = '%2FMERRA2_400.inst6_3d_ana_Np.'
url3o = '%2FMERRA2_100.inst6_3d_ana_Np.'
url4 = '.nc4&FORMAT=bmM0Yy8&BBOX=-90%2C-180%2C90%2C180&TIME=1979-01-01T'
url5 = '%3A00%3A00%2F1979-01-01T'
url6 = '%3A00%3A00&LABEL=svc_MERRA2_300.inst6_3d_ana_Np.'
url6n = '%3A00%3A00&LABEL=svc_MERRA2_400.inst6_3d_ana_Np.'
url6o = '%3A00%3A00&LABEL=svc_MERRA2_100.inst6_3d_ana_Np.'
url7 = '.nc4&FLAGS=&SHORTNAME=M2I6NPANA&SERVICE=SUBSET_MERRA2&LAYERS=&VERSION=1.02&VARIABLES='
if year < 1992:
weburl = '%s%s%s%s%s%s%s%s%s%s%s%s%s' %(url1,yr,url2,mon,url3o,date,url4,hr,url5,hr,url6o,date,url7)
elif year < 2001:
weburl = '%s%s%s%s%s%s%s%s%s%s%s%s%s' %(url1,yr,url2,mon,url3,date,url4,hr,url5,hr,url6,date,url7)
else:
weburl = '%s%s%s%s%s%s%s%s%s%s%s%s%s' %(url1,yr,url2,mon,url3n,date,url4,hr,url5,hr,url6n,date,url7)
dir = '%s' %(filename)
if not os.path.exists(dir):
#urllib3.urlretrieve(weburl,dir)
dloadCmd = 'wget "{}" --user {} --password {} -O {}'.format(weburl, user, pw, filename)
dloadCmd += ' --load-cookies ~/.urs_cookies --save-cookies ~/.urs_cookies'
dloadCmd += ' --auth-no-challenge=on --keep-session-cookies'
os.system(dloadCmd)
return flist
def NARRdload(bdate,hr,filedir):
if not os.path.isdir(filedir):
os.makedirs(filedir)
print('create foler: {}'.format(filedir))
flist = []
for i, day in enumerate(bdate):
webdir = day[0:6]
fname = 'narr-a_221_%s_%s00_000.grb'%(day,hr)
flist.append('%s/%s'%(filedir,fname))
weburl='http://nomads.ncdc.noaa.gov/data/narr/%s/%s/%s'%(webdir,day,fname)
dname = '%s/%s'%(filedir,fname)
print('Downloading %d of %d: %s'%(i+1,len(bdate),fname))
if not os.path.exists(dname):
urllib3.urlretrieve(weburl,dname)
return flist
PyAPS-0.3.6/src/pyaps3/delay.py 0000664 0000000 0000000 00000007020 14751542053 0016137 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
import numpy as np
#############Clausius-Clapeyron for ECMWF as used in Jolivet et al 2011#
def cc_eraorig(tmp,cdic):
'''This routine takes temperature profiles and returns Saturation water vapor
partial pressure using the Clausius-Clapeyron law applied in Jolivet et al. 2011,
GRL, doi:10.1029/2011GL048757. It can be used in case you are using Relative.
Humidity from ECMWF models.
Args:
* tmp (np.ndarray) : Temperature
* cdic (dict) : Dictionnary of constants
Returns:
* esat (np.ndarray) : Saturation water vapor partial pressure.
'''
a1w=cdic['a1w']
T3=cdic['T3']
Rv=cdic['Rv']
esat=a1w*np.exp( (2.5e6/Rv) * ( (1/T3) - (1/tmp) ) )
return esat
###############Completed CC_ERAORIG#####################################
##############Read Input text file #####################################
def read_eratxt(fname,cdic):
'''Read ECMWF files from 0.75 degree grid similar to Romain Jolivet's Delay Package.
Args:
* fname (str) : Path to the delay file
* cdic (float) : Dictionary of constants
Kwargs:
* humidity (str) : Specific ('Q') or relative humidity ('R').
Returns:
* lvls (np.ndarray): Pressure levels
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* gph (np.ndarray): Geopotential height
* tmp (np.ndarray): Temperature
* vpr (np.ndarray): Vapor pressure
.. note::
Uses cc_eraorig by default.
'''
lvls=[]
latlist=[]
lonlist=[]
gpht=[]
tmpt=[]
reht=[]
g=cdic['g']
f=open(fname,'r')
tmp=f.readlines()
i=0
nstn=0
maxloop=int(len(tmp))
while i 0:
try:
return func(self, *args, **kwargs)
except HTTPError as e:
if self.verbose:
print("WARNING: HTTPError received %s" % (e))
if e.code < 500:
raise
last_error = e
except BadStatusLine as e:
if self.verbose:
print("WARNING: BadStatusLine received %s" % (e))
last_error = e
except URLError as e:
if self.verbose:
print("WARNING: URLError received %s %s" % (e.errno, e))
last_error = e
except APIException:
raise
except RetryError as e:
if self.verbose:
print("WARNING: HTTP received %s" % (e.code))
print(e.text)
last_error = e
except:
if self.verbose:
print("Unexpected error:", sys.exc_info()[0])
print(traceback.format_exc())
raise
print("Error contacting the WebAPI, retrying in %d seconds ..." % delay)
time.sleep(delay)
tries -= 1
# if all retries have been exhausted, raise the last exception caught
print("Could not contact the WebAPI after %d tries, failing !" % max_tries)
raise last_error
return wrapped
def get_api_url(url):
parsed_uri = urlparse(url)
return '{uri.scheme}://{uri.netloc}/{apiver}/'.format(
uri=parsed_uri, apiver=parsed_uri.path.split('/')[1])
SAY = True
class Ignore303(HTTPRedirectHandler):
def redirect_request(self, req, fp, code, msg, headers, newurl):
if code in [301, 302]:
# We want the posts to work even if we are redirected
if code == 301:
global SAY
if SAY:
o = req.get_full_url()
n = newurl
print()
print("*** ECMWF API has moved")
print("*** OLD: %s" % get_api_url(o))
print("*** NEW: %s" % get_api_url(n))
print("*** Please update your ~/.ecmwfapirc file")
print()
SAY = False
data = None
if req.has_data():
data = req.get_data()
return Request(newurl,
data=data,
headers=req.headers,
origin_req_host=req.get_origin_req_host(),
unverifiable=True)
return None
def http_error_303(self, req, fp, code, msg, headers):
infourl = addinfourl(fp, headers, req.get_full_url())
infourl.status = code
infourl.code = code
return infourl
class Connection(object):
def __init__(self, email=None, key=None, verbose=False, quiet=False):
self.email = email
self.key = key
self.retry = 5
self.location = None
self.done = False
self.value = True
self.offset = 0
self.verbose = verbose
self.quiet = quiet
self.status = None
@robust
def call(self, url, payload=None, method="GET"):
if self.verbose:
print(method, url)
headers = {"Accept": "application/json", "From": self.email, "X-ECMWF-KEY": self.key}
opener = build_opener(Ignore303)
data = None
if payload is not None:
data = json.dumps(payload).encode('utf-8')
headers["Content-Type"] = "application/json"
url = "%s?offset=%d&limit=500" % (url, self.offset)
req = Request(url=url, data=data, headers=headers)
if method:
req.get_method = lambda: method
error = False
try:
try:
res = opener.open(req)
except HTTPError as e:
# It seems that some version of urllib2 are buggy
if e.code <= 299:
res = e
else:
raise
except HTTPError as e:
if self.verbose:
print(e)
error = True
res = e
# 502: Proxy Error
# 503: Service Temporarily Unavailable
if e.code >= 500:
raise RetryError(e.code, e.read())
self.retry = int(res.headers.get("Retry-After", self.retry))
code = res.code
if code in [201, 202]:
self.location = res.headers.get("Location", self.location)
if self.verbose:
print("Code", code)
print("Content-Type", res.headers.get("Content-Type"))
print("Content-Length", res.headers.get("Content-Length"))
print("Location", res.headers.get("Location"))
body = res.read().decode("utf-8")
res.close()
if code in [204]:
self.last = None
return None
else:
try:
self.last = json.loads(body)
except Exception as e:
self.last = {"error": "%s: %s" % (e, body)}
error = True
if self.verbose:
print(json.dumps(self.last, indent=4))
self.status = self.last.get("status", self.status)
if self.verbose:
print("Status", self.status)
if "messages" in self.last:
for n in self.last["messages"]:
if not self.quiet:
print(n)
self.offset += 1
if code == 200 and self.status == "complete":
self.value = self.last
self.done = True
if isinstance(self.value, dict) and "result" in self.value:
self.value = self.value["result"]
if code in [303]:
self.value = self.last
self.done = True
if "error" in self.last:
#self.done = True
raise APIException("ecmwf.API error 1: %s" % (self.last["error"],))
if error:
#self.done = True
raise APIException("ecmwf.API error 2: %s" % (res, ))
return self.last
def submit(self, url, payload):
self.call(url, payload, "POST")
def POST(self, url, payload):
return self.call(url, payload, "POST")
def GET(self, url):
return self.call(url, None, "GET")
def wait(self):
if self.verbose:
print("Sleeping %s second(s)" % (self.retry))
time.sleep(self.retry)
self.call(self.location, None, "GET")
def ready(self):
return self.done
def result(self):
return self.value
def cleanup(self):
try:
if self.location:
self.call(self.location, None, "DELETE")
except:
pass
def no_log(msg):
pass
class APIRequest(object):
def __init__(self, url, service, email=None, key=None, log=no_log, quiet=False, verbose=False, news=True):
self.url = url
self.service = service
self.connection = Connection(email, key, quiet=quiet, verbose=verbose)
self.log = log
self.quiet = quiet
self.verbose = verbose
self.log("ECMWF API python library %s" % (VERSION,))
self.log("ECMWF API at %s" % (self.url,))
user = self.connection.call("%s/%s" % (self.url, "who-am-i"))
self.log("Welcome %s" % (user["full_name"] or "user '%s'" % user["uid"],))
if news:
try:
news = self.connection.call("%s/%s/%s" % (self.url, self.service, "news"))
for n in news["news"].split("\n"):
self.log(n)
except:
pass
def _bytename(self, size):
prefix = {'': 'K', 'K': 'M', 'M': 'G', 'G': 'T', 'T': 'P', 'P': 'E'}
l = ''
size = size * 1.0
while 1024 < size:
l = prefix[l]
size = size / 1024
s = ""
if size > 1:
s = "s"
return "%g %sbyte%s" % (size, l, s)
@robust
def _transfer(self, url, path, size):
self.log("Transfering %s into %s" % (self._bytename(size), path))
self.log("From %s" % (url, ))
start = time.time()
http = urlopen(url)
f = open(path, "wb")
total = 0
block = 1024 * 1024
while True:
chunk = http.read(block)
if not chunk:
break
f.write(chunk)
total += len(chunk)
f.flush()
f.close()
end = time.time()
header = http.info()
length = header.get("Content-Length")
if length is None:
self.log("Warning: Content-Length missing from HTTP header")
if end > start:
self.log("Transfer rate %s/s" % self._bytename(total / (end - start)), )
return total
def execute(self, request, target=None):
status = None
self.connection.submit("%s/%s/requests" % (self.url, self.service), request)
self.log('Request submitted')
self.log('Request id: ' + self.connection.last['name'])
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
while not self.connection.ready():
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
self.connection.wait()
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
result = self.connection.result()
if target:
size = -1
tries = 0
while size != result["size"] and tries < 10:
size = self._transfer(result["href"], target, result["size"])
if size != result["size"] and tries < 10:
tries += 1
self.log("Transfer interrupted, retrying...")
time.sleep(60)
else:
break
assert size == result["size"]
self.connection.cleanup()
return result
###############################################################################
class ECMWFDataServer(object):
def __init__(self, url=None, key=None, email=None, verbose=False, log=None):
if url is None or key is None or email is None:
key, url, email = get_apikey_values()
self.url = url
self.key = key
self.email = email
self.verbose = verbose
self.log = log
def trace(self, m):
if self.log:
self.log(m)
else:
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("%s %s" % (t, m,))
def retrieve(self, req):
target = req.get("target")
dataset = req.get("dataset")
c = APIRequest(self.url, "datasets/%s" % (dataset,), self.email, self.key, self.trace, verbose=self.verbose)
c.execute(req, target)
###############################################################################
class ECMWFService(object):
def __init__(self, service, url=None, key=None, email=None, verbose=False, log=None, quiet=False):
if url is None or key is None or email is None:
key, url, email = get_apikey_values()
self.service = service
self.url = url
self.key = key
self.email = email
self.verbose = verbose
self.quiet = quiet
self.log = log
def trace(self, m):
if self.log:
self.log(m)
else:
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("%s %s" % (t, m,))
def execute(self, req, target):
c = APIRequest(self.url, "services/%s" % (self.service,), self.email, self.key, self.trace, verbose=self.verbose, quiet=self.quiet)
c.execute(req, target)
self.trace("Done.")
###############################################################################
PyAPS-0.3.6/src/pyaps3/era.py 0000664 0000000 0000000 00000020576 14751542053 0015623 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
import numpy as np
import pygrib
#############Clausis-Clayperon for ECMWF###########################
def cc_era(tmp,cdic):
'''Clausius Clayperon law used by ERA Interim.
Args:
* tmp (np.ndarray) : Temperature.
* cdic (dict) : Dictionary of constants
Returns:
* esat (np.ndarray) : Water vapor saturation partial pressure.'''
a1w = cdic['a1w']
a3w = cdic['a3w']
a4w = cdic['a4w']
a1i = cdic['a1i']
a3i = cdic['a3i']
a4i = cdic['a4i']
T3 = cdic['T3']
Ti = cdic['Ti']
esatw = a1w*np.exp(a3w*(tmp-T3)/(tmp-a4w))
esati = a1i*np.exp(a3i*(tmp-T3)/(tmp-a4i))
esat = esati.copy()
for k in range(len(tmp)):
if (tmp[k] >= T3):
esat[k] = esatw[k]
elif (tmp[k] <= Ti):
esat[k] = esati[k]
else:
wgt = (tmp[k]-Ti)/(T3-Ti)
esat[k] = esati[k] + (esatw[k]-esati[k])*wgt*wgt
return esat
########Read in ERA data from a given ERA Interim file##################
def get_era(fname,minlat,maxlat,minlon,maxlon,cdic, humidity='Q',verbose=False):
'''Read data from ERA interim grib file.
Note that the Lon values should be between [0-360].
GRB file with weather model data can be downloaded from http://rda.ucar.edu/datasets/ds627.0/
Args:
* fname (str) : Path to the grib file
* minlat (float) : Minimum latitude
* maxlat (float) : Maximum latitude
* minlon (float) : Minimum longitude
* maxlon (float) : Maximum longitude
* cdic (float) : Dictionary of constants
Kwargs:
* humidity(str) : Specific ('Q') or relative humidity ('R').
Returns:
* lvls (np.ndarray): Pressure levels
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* gph (np.ndarray): Geopotential height
* tmp (np.ndarray): Temperature
* vpr (np.ndarray): Vapor pressure
.. note::
Uses cc_era by default.
'''
assert humidity in ('Q','R'), 'Undefined humidity field in get_era.'
if verbose:
print('PROGRESS: READING GRIB FILE {}'.format(fname))
lvls = np.array([1, 2, 3, 5, 7, 10, 20, 30, 50, 70, 100, 125, 150, 175,
200, 225, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775,
800, 825, 850, 875, 900, 925, 950, 975, 1000])
nlvls = len(lvls)
alpha = cdic['Rv']/cdic['Rd']
gphind = np.arange(nlvls)*12+1
grbs = pygrib.open(fname)
grbs.seek(gphind[0])
grb=grbs.read(1)[0]
lats, lons = grb.latlons()
g = cdic['g']
mask = (lats > minlat) & (lats < maxlat) & (lons > minlon) & (lons < maxlon)
[ii,jj] = np.where(mask == True)
del mask
latlist = lats[ii,jj]
lonlist = lons[ii,jj]
nstn = len(ii)
####Create arrays for 3D storage
gph = np.zeros((nlvls, nstn)) #Potential height
tmp = gph.copy() #Temperature
vpr = gph.copy() #Vapor pressure
if verbose:
print('Number of stations:', nstn)
lvls = 100.0*lvls #Conversion to absolute pressure
for i in range(nlvls):
grbs.seek(gphind[i]) #Reading potential height.
grb = grbs.read(3)
val = grb[0].values
gph[i,:] = val[ii,jj]/g
val = grb[1].values #Reading temperature
temp = val[ii,jj]
tmp[i,:] = temp
if humidity in ('R'):
esat = cc_era(temp,cdic)
grbs.seek(gphind[i]+6)
grb = grbs.read(1)
val = grb[0].values
temp = val[ii,jj]/100.0
vpr[i,:] = temp*esat
elif humidity in ('Q'):
val = grb[2].values #Specific humidity
temp = val[ii,jj]
vpr[i,:] = temp*lvls[i]*alpha/(1+(alpha - 1)*temp)
else:
assert 1==0, 'Undefined Humidity in get_era().'
return lvls,latlist,lonlist,gph,tmp,vpr
###############Completed GET_ERA########################################
########Read in ERA data from a given ERA Interim file##################
def get_ecmwf(model,fname,minlat,maxlat,minlon,maxlon,cdic, humidity='Q',verbose=False):
'''Read data from ERA Interim, ERA-5 or HRES grib file. Note that Lon values should be between [-180, 180].
Modified by A. Benoit, January 2019.
Args:
* model (str) : Model used (ERA5, ERAINT or HRES)
* fname (str) : Path to the grib file
* minlat (float) : Minimum latitude
* maxlat (float) : Maximum latitude
* minlon (float) : Minimum longitude
* maxlon (float) : Maximum longitude
* cdic (float) : Dictionary of constants
Kwargs:
* humidity (str) : Specific ('Q') or relative humidity ('R').
Returns:
* lvls (np.ndarray): Pressure levels
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* gph (np.ndarray): Geopotential height
* tmp (np.ndarray): Temperature
* vpr (np.ndarray): Vapor pressure
.. note::
Uses cc_era by default.
'''
assert humidity in ('Q','R'), 'Undefined humidity field in get_era.'
assert model in ('ERA5', 'ERAINT','HRES'), 'Model not recognized.'
if verbose:
print('PROGRESS: READING GRIB FILE')
if model in 'HRES':
if verbose:
print('INFO: USING PRESSURE LEVELS OF HRES DATA')
lvls = np.array([1, 2, 3, 5, 7, 10, 20, 30, 50, 70, 100, 150,
200, 250, 300, 400, 500, 600, 700,
800, 850, 900, 925, 950, 1000])
else:
if verbose:
print('INFO: USING PRESSURE LEVELS OF ERA-INT OR ERA-5 DATA')
lvls = np.array([1, 2, 3, 5, 7, 10, 20, 30, 50, 70, 100, 125, 150, 175,
200, 225, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775,
800, 825, 850, 875, 900, 925, 950, 975, 1000])
nlvls = len(lvls)
alpha = cdic['Rv']/cdic['Rd']
gphind = np.arange(nlvls)*3
grbs = pygrib.open(fname)
grbs.seek(gphind[0])
grb = grbs.read(1)[0]
lats, lons = grb.latlons()
#if model == 'ERA5':
# lons[lons < 0.] += 360.
g = cdic['g']
#extract indices
mask = ((lats > minlat) & (lats < maxlat)) & ((lons > minlon) & (lons < maxlon))
uu = [i for i in list(range(np.shape(mask)[0])) if any(mask[i,:])]
vv = [j for j in list(range(np.shape(mask)[1])) if any(mask[:,j])]
latlist = lats[uu,:][:,vv]
lonlist = lons[uu,:][:,vv]
nlat, nlon = latlist.shape
####Create arrays for 3D storage
gph = np.zeros((nlvls, nlat, nlon)) #Potential height
tmp = gph.copy() #Temperature
vpr = gph.copy() #Vapor pressure
if verbose:
print('INFO: IMAGE DIMENSIONS: {} LATITUDES AND {} LONGITUDES'.format(nlat, nlon))
lvls = 100.0*lvls #Conversion to absolute pressure
for i in range(nlvls):
grbs.seek(gphind[i]) #Reading potential height.
grb = grbs.read(3)
gph[i,:,:] = grb[0].values[uu,:][:,vv]/g
#Reading temperature
temp = grb[1].values[uu,:][:,vv]
tmp[i,:,:] = temp
if humidity in ('R'): # Relative humidity
esat = cc_era(temp,cdic)
temp = grb[2].values[uu,:][:,vv]/100.0
vpr[i,:,:] = temp*esat
elif humidity in ('Q'):
val = grb[2].values #Specific humidity
temp = grb[2].values[uu,:][:,vv]
vpr[i,:,:] = temp*lvls[i]*alpha/(1+(alpha - 1)*temp)
else:
assert 1==0, 'Undefined Humidity in get_ecmwf().'
return lvls,latlist,lonlist,gph,tmp,vpr
###############Completed GET_ECMWF########################################
PyAPS-0.3.6/src/pyaps3/getaps.py 0000664 0000000 0000000 00000002001 14751542053 0016316 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
'''Script to automatically download weather model data corresponding to our interferograms.'''
import PyAPS
import tsinsar as ts
import datetime as dt
dates,sat,bperp = ts.load_list('ifg.list')
days,usat,Jmat = ts.ConnectMatrix(dates,sat)
daylist = []
for k in days:
dobj = dt.date.fromordinal(int(k))
strobj = '%4d%02d%02d'%(dobj.year,dobj.month,dobj.day)
daylist.append(strobj)
PyAPS.ECMWFdload(daylist,'18','./Atmos/ECMWF/')
#PyAPS.NARRdload(daylist,'18','./Atmos/NARR/')
#PyAPS.ERAdload(daylist,'18','./Atmos/ERA')
PyAPS-0.3.6/src/pyaps3/merra.py 0000664 0000000 0000000 00000022061 14751542053 0016151 0 ustar 00root root 0000000 0000000 from pyhdf.HDF import *
from pyhdf.SD import *
from pyhdf.V import *
from pyhdf.VS import *
import numpy as np
import netCDF4
def get_merra(fname,minlat,maxlat,minlon,maxlon,cdic,verbose=False):
'''Read data from MERRA hdf file. Note that the Lon values
should be between [0-360]. Hdf file with weather model
data can be downloaded from
http://disc.sci.gsfc.nasa.gov/daac-bin/FTPSubset.pl
Args:
* fname (str) : Path to the grib file
* minlat (float) : Minimum latitude
* maxlat (float) : Maximum latitude
* minlon (float) : Minimum longitude
* maxlon (float) : Maximum longitude
* cdic (float) : Dictionary of constants
Returns:
* lvls (np.ndarray): Pressure levels
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* gph (np.ndarray): Geopotential height
* tmp (np.ndarray): Temperature
* vpr (np.ndarray): Vapor pressure
'''
if fname[-3:]=='hdf':
print(minlat)
print(maxlat)
print(minlon)
print(maxlon)
# Read the hdf file
file = SD(fname)
if verbose:
print('PROGRESS: READING HDF FILE')
lvl = file.select('levels')
# Pressure levels are from lowest to highest
rlvls = lvl.get()
lvls = []
# Reverse the pressure levels to be consistent with other GAMss
for i in range(len(rlvls)):
index = len(rlvls) - i - 1
lvls.append(rlvls[index])
nlvls = len(lvls)
lvls = np.array(lvls)
alpha = cdic['Rv']/cdic['Rd']
# Select latitutde and longitude
lat = file.select('latitude')
lon = file.select('longitude')
lats = lat.get()
lons = lon.get()
mask1 = (lats > minlat) & (lats < maxlat)
mask2 = (lons > minlon) & (lons < maxlon)
[ii] = np.where(mask1 == True)
[jj] = np.where(mask2 == True)
del mask1
del mask2
iimemo = []
for m in range(len(ii)):
for i in range(len(jj)):
iimemo.append(ii[m])
jjmemo = []
for i in range(len(ii)):
jjmemo.append(jj)
jjmemo = np.array(jjmemo)
jjmemo = jjmemo.flatten()
iimemo = np.array(iimemo)
ii = iimemo
jj = jjmemo
latlist = lats[ii]
lonlist = lons[jj]
nstn = len(latlist)
# Create arrays for 3D storage
gph = np.zeros((nlvls, nstn)) #Potential height
tmp = gph.copy() #Temperature
vpr = gph.copy() #Vapor pressure
if verbose:
print('Number of stations:', nstn)
# Get data from files
h = file.select('h')
height = h.get()[0]
qv = file.select('qv')
humidity = qv.get()[0]
sp = file.select('ps')
spressure = sp.get()[0]
t = file.select('t')
temp = t.get()[0]
# Lvls are in hecto pascals, convert to pascals
lvls = 100.0*lvls
# Reverse altitude
for i in range(nlvls):
index = nlvls - i - 1
gph[i,:] = height[index][ii,jj]
idx = np.zeros(nstn)
for i in range(nstn):
for m in range(nlvls):
if spressure[ii[i]][jj[i]] > lvls[m]:
idx[i] = m
# extrapolation of temperature and humidity data at pressure levels under surface at each grid point
tk = np.zeros(nstn)
tb = np.zeros(nstn)
for i in range(nstn):
t = temp[:,ii[i],jj[i]]
x = [lvls[idx[i]],lvls[idx[i] -1 ]]
y = [t[nlvls - idx[i] - 1],t[nlvls - idx[i] ]]
coef = np.polyfit(x,y,1)
tk[i] = coef[0]
tb[i] = coef[1]
hk = np.zeros(nstn)
hb = np.zeros(nstn)
for i in range(nstn):
hum = humidity[:,ii[i],jj[i]]
x = [lvls[idx[i]],lvls[idx[i] -1 ]]
y = [hum[nlvls - idx[i] - 1],hum[nlvls - idx[i]]]
coef = np.polyfit(x,y,1)
hk[i] = coef[0]
hb[i] = coef[1]
#fill out the tmp and vpr array
for i in range(nstn):
ind = int(idx[i]+1)
for n in range(ind):
tmp[n,i] = temp[nlvls - 1 - n,ii[i],jj[i]]
exl = nlvls - ind
for m in range(exl):
tmp[ind+m,i] = tk[i]*lvls[ind+m] + tb[i]
for i in range(nstn):
ind = int(idx[i]+1)
for n in range(ind):
vpr[n,i] = humidity[nlvls - 1- n,ii[i],jj[i]]
exl = nlvls - ind
for m in range(exl):
vpr[ind+m,i] = hk[i]*lvls[ind+m] + hb[i]
memo = list(vpr)
memo = np.array(memo)
for i in range(nlvls):
vpr[i,:] = memo[i,:]*lvls[i]*alpha/(1+(alpha - 1)*memo[i,:])
# Close the hdf file
file.end()
if fname[-3:]=='nc4':
# Read the netcdf file
file = netCDF4.Dataset(fname)
if verbose:
print('PROGRESS: READING netcdf FILE')
ncv = file.variables
# Pressure levels are from lowest to highest
rlvls = ncv['lev'][:]
lvls = []
# Reverse the pressure levels to be consistent with other GAMs
for i in range(len(rlvls)):
index = len(rlvls) - i - 1
lvls.append(rlvls[index])
nlvls = len(lvls)
lvls = np.array(lvls)
alpha = cdic['Rv']/cdic['Rd']
# Select latitutde and longitude
lats = ncv['lat'][:]
lons = ncv['lon'][:]
mask1 = (lats > minlat) & (lats < maxlat)
mask2 = (lons > minlon) & (lons < maxlon)
[ii] = np.where(mask1 == True)
[jj] = np.where(mask2 == True)
del mask1
del mask2
iimemo = []
for m in range(len(ii)):
for i in range(len(jj)):
iimemo.append(ii[m])
jjmemo = []
for i in range(len(ii)):
jjmemo.append(jj)
jjmemo = np.array(jjmemo)
jjmemo = jjmemo.flatten()
iimemo = np.array(iimemo)
ii = iimemo
jj = jjmemo
latlist = lats[ii]
lonlist = lons[jj]
nstn = len(latlist)
# Create arrays for 3D storage
gph = np.zeros((nlvls, nstn)) #Potential height
tmp = gph.copy() #Temperature
vpr = gph.copy() #Vapor pressure
if verbose:
print('Number of stations:', nstn)
# Get data from files
height = ncv['H'][:]
height = height[0]
humidity = ncv['QV'][:]
humidity = humidity[0]
spressure = ncv['PS'][:]
spressure = spressure[0]
temp = ncv['T'][:]
temp = temp[0]
# Lvls are in hecto pascals, convert to pascals
lvls = 100.0*lvls
# Reverse altitude
for i in range(nlvls):
index = nlvls - i - 1
gph[i,:] = height[index][ii,jj]
idx = np.zeros(nstn)
for i in range(nstn):
for m in range(nlvls):
if spressure[ii[i]][jj[i]] > lvls[m]:
idx[i] = m
# extrapolation of temperature and humidity data at pressure levels under surface at each grid point
tk = np.zeros(nstn)
tb = np.zeros(nstn)
for i in range(nstn):
t = temp[:,ii[i],jj[i]]
x = [lvls[idx[i]],lvls[idx[i] -1 ]]
y = [t[nlvls - idx[i] - 1],t[nlvls - idx[i] ]]
coef = np.polyfit(x,y,1)
tk[i] = coef[0]
tb[i] = coef[1]
hk = np.zeros(nstn)
hb = np.zeros(nstn)
for i in range(nstn):
hum = humidity[:,ii[i],jj[i]]
x = [lvls[idx[i]],lvls[idx[i] -1 ]]
y = [hum[nlvls - idx[i] - 1],hum[nlvls - idx[i]]]
coef = np.polyfit(x,y,1)
hk[i] = coef[0]
hb[i] = coef[1]
#fill out the tmp and vpr array
for i in range(nstn):
ind = int(idx[i]+1)
for n in range(ind):
tmp[n,i] = temp[nlvls - 1 - n,ii[i],jj[i]]
exl = nlvls - ind
for m in range(exl):
tmp[ind+m,i] = tk[i]*lvls[ind+m] + tb[i]
for i in range(nstn):
ind = int(idx[i]+1)
for n in range(ind):
vpr[n,i] = humidity[nlvls - 1- n,ii[i],jj[i]]
exl = nlvls - ind
for m in range(exl):
vpr[ind+m,i] = hk[i]*lvls[ind+m] + hb[i]
memo = list(vpr)
memo = np.array(memo)
for i in range(nlvls):
vpr[i,:] = memo[i,:]*lvls[i]*alpha/(1+(alpha - 1)*memo[i,:])
# Close the netcdf file
file.close()
# Send data
return lvls,latlist,lonlist,gph,tmp,vpr
############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
############################################################
PyAPS-0.3.6/src/pyaps3/model.cfg 0000664 0000000 0000000 00000001604 14751542053 0016252 0 ustar 00root root 0000000 0000000 # vim: set filetype=cfg:
#####Personal Access Token for ECMWF in Climate Data Store Application Program Interface
#Get it from https://cds.climate.copernicus.eu/profile
#for ERA5
[CDS]
key = your-personal-access-token
#####The key to the new server for ECMWF
#Get it from https://software.ecmwf.int/wiki/display/WEBAPI/Accessing+ECMWF+data+servers+in+batch
#for ERA-Interim [outdated]
[ECMWF]
email = the-email-address-used-as-login@ecmwf-website.org
key =
#####Passwd and key for download from ucar
[ERA]
email = the-email-adress-used-as-login@ucar-website.org
key =
#####No username/password is required for NARR
[NARR]
#####Username and password for download from NASA Earthdata
##pre-authorize the "NASA GESDISC DATA ARCHIVE" application in your account to download MERRA2
[MERRA]
user = the-user-name-used-as-login@earthdata.nasa.gov
password = the-password-used-as-login@earthdata.nasa.gov
PyAPS-0.3.6/src/pyaps3/narr.py 0000664 0000000 0000000 00000012434 14751542053 0016010 0 ustar 00root root 0000000 0000000 import numpy as np
import pygrib
import scipy.interpolate as si
import sys
#############Clausius-Clapeyron for NARR ###########
def cc_narr(tmp,cdic):
'''Clausius Clayperon law used in the NARR model.
Args:
* tmp (np.ndarray): Temperature.
* cdic (dict) : Dictionnary of constants.
Returns:
* esat (np.ndarray): Saturation water vapor partial pressure.'''
a1w=cdic['a1w']
a3w=cdic['a3w']
a4w=cdic['a4w']
T3=cdic['T3']
Rv=cdic['Rv']
esat = a1w*np.exp(a3w*(tmp-T3)/(tmp-a4w))
return esat
###############Completed CC_NARR#####################################
########Read in ERA data from a given ERA Interim file##################
def get_narr(fname,minlat,maxlat,minlon,maxlon,cdic,verbose=False):
'''Read data from NARR grib file. Note that the Lon values should be between [0-360].
GRB file with weather model data can be downloaded from http://nomads.ncdc.noaa.gov/data/narr .
Args:
* fname (str) : Path to the grib file
* minlat (float): Minimum latitude
* maxlat (float): Maximum latitude
* minlon (float): Minimum longitude
* maxlon (float): Maximum longitude
* cdic (float): Dictionary of constants
Kwargs:
* humidity (str): Specific ('Q') or relative humidity ('R').
Returns:
* lvls (np.ndarray): Pressure levels
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* gph (np.ndarray): Geopotential height
* tmp (np.ndarray): Temperature
* vpr (np.ndarray): Vapor pressure
.. note::
Uses cc_narr by default.
'''
if verbose:
print('PROGRESS: READING GRIB FILE')
lvls = np.array([100, 125, 150, 175, 200, 225, 250, 275, 300, 350, 400, 450, 500, 550,
600, 650, 700, 725, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975, 1000])
nlvls = len(lvls)
alpha = cdic['Rv']/cdic['Rd']
gphind = np.array([16,24,32,40,48,56,64,72,80,88,96,104,112,120,128,137,
146,155,164,173,182,191,200,210,219,228,237,246,255])
grbs = pygrib.open(fname)
grbs.seek(gphind[0])
grb=grbs.read(1)[0]
lats,lons = grb.latlons()
lons[lons<0] += 360.
g = cdic['g']
mask = (lats > minlat) & (lats < maxlat) & (lons > minlon) & (lons < maxlon)
[ii,jj] = np.where(mask == True)
del mask
latlist = lats[ii,jj]
lonlist = lons[ii,jj]
nstn = len(ii)
####Create arrays for 3D storage
gph = np.zeros((nlvls, nstn)) #Potential height
tmp = gph.copy() #Temperature
vpr = gph.copy() #Vapor pressure
if verbose:
print('Number of stations:', nstn)
lvls = 100.0*lvls #Conversion to absolute pressure
for i in range(nlvls):
grbs.seek(gphind[i]) #Reading potential height.
grb = grbs.read(3)
val = grb[0].values
gph[i,:] = val[ii,jj]
val = grb[1].values #Reading temperature
temp = val[ii,jj]
tmp[i,:] = temp
val = grb[2].values #Specific humidity
temp = val[ii,jj]
vpr[i,:] = temp*lvls[i]*alpha/(1+(alpha - 1)*temp)
return lvls,latlist,lonlist,gph,tmp,vpr
###############Completed GET_ERA########################################
########Interpolates the NARR delay to a regular grid####################
def intdel(hgt,latlin,lonlin,delcin,spacing=0.3):
'''Interpolates the NARR data to a regular grid with a grid spacing being the average of previous grid spaces
Args:
* hgt (np.ndarray): Altitude levels
* latlin (np.ndarray): Latitudes of the stations
* lonlin (np.ndarray): Longitudes of the stations
* delcin (np.ndarray): Delay cube len(latlist)xlen(hgt)
Returns:
* latlist (np.ndarray): Latitudes of the stations
* lonlist (np.ndarray): Longitudes of the stations
* delc (np.ndarray): Delay cube len(latlist)xlen(hgt)
.. note::
'''
# Points array
nstn = len(latlin)
Points = np.zeros((nstn,2))
Points[:,0] = lonlin
Points[:,1] = latlin
# Output arrays
minlat = latlin.min()
maxlat = latlin.max()
minlon = lonlin.min()
maxlon = lonlin.max()
latlist = np.arange(minlat,maxlat,spacing)
lonlist = np.arange(minlon,maxlon,spacing)
[lonlist,latlist] = np.meshgrid(lonlist,latlist)
latlist = latlist.flatten()
lonlist = lonlist.flatten()
# Xi arrays
nstno = len(latlist)
Xi = np.zeros((nstno,2))
Xi[:,0] = lonlist
Xi[:,1] = latlist
# Create the arrays
nlvls = len(hgt)
delc = np.zeros((nstno,nlvls))
# Loop on the pressure levels
for n in range(nlvls):
delc[:,n] = si.griddata(
Points,
delcin[:,n],
Xi,
method='cubic',
#fill_value=10*float(n),
)
return delc,latlist,lonlist
############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
############################################################
PyAPS-0.3.6/src/pyaps3/newapi/ 0000775 0000000 0000000 00000000000 14751542053 0015753 5 ustar 00root root 0000000 0000000 PyAPS-0.3.6/src/pyaps3/newapi/ecmwfapi/ 0000775 0000000 0000000 00000000000 14751542053 0017546 5 ustar 00root root 0000000 0000000 PyAPS-0.3.6/src/pyaps3/newapi/ecmwfapi/__init__.py 0000664 0000000 0000000 00000001155 14751542053 0021661 0 ustar 00root root 0000000 0000000 """Python client for ECMWF web services API."""
#
# (C) Copyright 2012-2013 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
#
from ecmwfapi import api
__all__ = [
"ECMWFDataServer",
"ECMWFService",
]
__version__ = api.VERSION
ECMWFDataServer = api.ECMWFDataServer
ECMWFService = api.ECMWFService
PyAPS-0.3.6/src/pyaps3/newapi/ecmwfapi/api.py 0000664 0000000 0000000 00000036754 14751542053 0020710 0 ustar 00root root 0000000 0000000 #
# (C) Copyright 2012-2013 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
# make the python3-like print behave in python 2
from __future__ import print_function
import os
import sys
import time
import traceback
# python 2 and 3 compatible urllib and httplib imports
try:
from urllib.parse import urlparse
from urllib.error import HTTPError, URLError
from urllib.request import HTTPRedirectHandler, Request, build_opener, urlopen, addinfourl
from http.client import BadStatusLine
except ImportError:
from urlparse import urlparse
from urllib2 import HTTPError, URLError
from urllib2 import HTTPRedirectHandler, Request, build_opener, urlopen, addinfourl
from httplib import BadStatusLine
try:
import json
except ImportError:
import simplejson as json
try:
import ssl
except ImportError:
print("Python socket module was not compiled with SSL support. Aborting...")
sys.exit(1)
###############################################################################
VERSION = '1.4.1'
###############################################################################
class APIKeyFetchError(Exception):
pass
def _get_apikey_from_environ():
try:
key = os.environ["ECMWF_API_KEY"]
url = os.environ["ECMWF_API_URL"]
email = os.environ["ECMWF_API_EMAIL"]
return key, url, email
except KeyError:
raise APIKeyFetchError("ERROR: Could not get the API key from the environment")
def _get_apikey_from_rcfile():
rc = os.path.normpath(os.path.expanduser("~/.ecmwfapirc"))
try:
with open(rc) as f:
config = json.load(f)
except IOError as e: # Failed reading from file
raise APIKeyFetchError(str(e))
except ValueError: # JSON decoding failed
raise APIKeyFetchError("ERROR: Missing or malformed API key in '%s'" % rc)
except Exception as e: # Unexpected error
raise APIKeyFetchError(str(e))
try:
key = config["key"]
url = config["url"]
email = config["email"]
return key, url, email
except:
raise APIKeyFetchError("ERROR: Missing or malformed API key in '%s'" % rc)
def get_apikey_values():
"""Get the API key from the environment or the '.ecmwfapirc' file.
The environment is looked at first.
Returns:
Tuple with the key, url, and email forming our API key.
Raises:
APIKeyFetchError: When unable to get the API key from either the
environment or the ecmwfapirc file.
"""
try:
key_values = _get_apikey_from_environ()
except APIKeyFetchError:
try:
key_values = _get_apikey_from_rcfile()
except APIKeyFetchError:
raise
return key_values
###############################################################################
class RetryError(Exception):
def __init__(self, code, text):
self.code = code
self.text = text
def __str__(self):
return "%d %s" % (self.code, self.text)
class APIException(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
def robust(func):
def wrapped(self, *args, **kwargs):
max_tries = tries = 10
delay = 60 # retry delay
last_error = None
while tries > 0:
try:
return func(self, *args, **kwargs)
except HTTPError as e:
if self.verbose:
print("WARNING: HTTPError received %s" % (e))
if e.code < 500:
raise
last_error = e
except BadStatusLine as e:
if self.verbose:
print("WARNING: BadStatusLine received %s" % (e))
last_error = e
except URLError as e:
if self.verbose:
print("WARNING: URLError received %s %s" % (e.errno, e))
last_error = e
except APIException:
raise
except RetryError as e:
if self.verbose:
print("WARNING: HTTP received %s" % (e.code))
print(e.text)
last_error = e
except:
if self.verbose:
print("Unexpected error:", sys.exc_info()[0])
print(traceback.format_exc())
raise
print("Error contacting the WebAPI, retrying in %d seconds ..." % delay)
time.sleep(delay)
tries -= 1
# if all retries have been exhausted, raise the last exception caught
print("Could not contact the WebAPI after %d tries, failing !" % max_tries)
raise last_error
return wrapped
def get_api_url(url):
parsed_uri = urlparse(url)
return '{uri.scheme}://{uri.netloc}/{apiver}/'.format(
uri=parsed_uri, apiver=parsed_uri.path.split('/')[1])
SAY = True
class Ignore303(HTTPRedirectHandler):
def redirect_request(self, req, fp, code, msg, headers, newurl):
if code in [301, 302]:
# We want the posts to work even if we are redirected
if code == 301:
global SAY
if SAY:
o = req.get_full_url()
n = newurl
print()
print("*** ECMWF API has moved")
print("*** OLD: %s" % get_api_url(o))
print("*** NEW: %s" % get_api_url(n))
print("*** Please update your ~/.ecmwfapirc file")
print()
SAY = False
data = None
if req.has_data():
data = req.get_data()
return Request(newurl,
data=data,
headers=req.headers,
origin_req_host=req.get_origin_req_host(),
unverifiable=True)
return None
def http_error_303(self, req, fp, code, msg, headers):
infourl = addinfourl(fp, headers, req.get_full_url())
infourl.status = code
infourl.code = code
return infourl
class Connection(object):
def __init__(self, email=None, key=None, verbose=False, quiet=False):
self.email = email
self.key = key
self.retry = 5
self.location = None
self.done = False
self.value = True
self.offset = 0
self.verbose = verbose
self.quiet = quiet
self.status = None
@robust
def call(self, url, payload=None, method="GET"):
if self.verbose:
print(method, url)
headers = {"Accept": "application/json", "From": self.email, "X-ECMWF-KEY": self.key}
opener = build_opener(Ignore303)
data = None
if payload is not None:
data = json.dumps(payload).encode('utf-8')
headers["Content-Type"] = "application/json"
url = "%s?offset=%d&limit=500" % (url, self.offset)
req = Request(url=url, data=data, headers=headers)
if method:
req.get_method = lambda: method
error = False
try:
try:
res = opener.open(req)
except HTTPError as e:
# It seems that some version of urllib2 are buggy
if e.code <= 299:
res = e
else:
raise
except HTTPError as e:
if self.verbose:
print(e)
error = True
res = e
# 502: Proxy Error
# 503: Service Temporarily Unavailable
if e.code >= 500:
raise RetryError(e.code, e.read())
self.retry = int(res.headers.get("Retry-After", self.retry))
code = res.code
if code in [201, 202]:
self.location = res.headers.get("Location", self.location)
if self.verbose:
print("Code", code)
print("Content-Type", res.headers.get("Content-Type"))
print("Content-Length", res.headers.get("Content-Length"))
print("Location", res.headers.get("Location"))
body = res.read().decode("utf-8")
res.close()
if code in [204]:
self.last = None
return None
else:
try:
self.last = json.loads(body)
except Exception as e:
self.last = {"error": "%s: %s" % (e, body)}
error = True
if self.verbose:
print(json.dumps(self.last, indent=4))
self.status = self.last.get("status", self.status)
if self.verbose:
print("Status", self.status)
if "messages" in self.last:
for n in self.last["messages"]:
if not self.quiet:
print(n)
self.offset += 1
if code == 200 and self.status == "complete":
self.value = self.last
self.done = True
if isinstance(self.value, dict) and "result" in self.value:
self.value = self.value["result"]
if code in [303]:
self.value = self.last
self.done = True
if "error" in self.last:
#self.done = True
raise APIException("ecmwf.API error 1: %s" % (self.last["error"],))
if error:
#self.done = True
raise APIException("ecmwf.API error 2: %s" % (res, ))
return self.last
def submit(self, url, payload):
self.call(url, payload, "POST")
def POST(self, url, payload):
return self.call(url, payload, "POST")
def GET(self, url):
return self.call(url, None, "GET")
def wait(self):
if self.verbose:
print("Sleeping %s second(s)" % (self.retry))
time.sleep(self.retry)
self.call(self.location, None, "GET")
def ready(self):
return self.done
def result(self):
return self.value
def cleanup(self):
try:
if self.location:
self.call(self.location, None, "DELETE")
except:
pass
def no_log(msg):
pass
class APIRequest(object):
def __init__(self, url, service, email=None, key=None, log=no_log, quiet=False, verbose=False, news=True):
self.url = url
self.service = service
self.connection = Connection(email, key, quiet=quiet, verbose=verbose)
self.log = log
self.quiet = quiet
self.verbose = verbose
self.log("ECMWF API python library %s" % (VERSION,))
self.log("ECMWF API at %s" % (self.url,))
user = self.connection.call("%s/%s" % (self.url, "who-am-i"))
self.log("Welcome %s" % (user["full_name"] or "user '%s'" % user["uid"],))
if news:
try:
news = self.connection.call("%s/%s/%s" % (self.url, self.service, "news"))
for n in news["news"].split("\n"):
self.log(n)
except:
pass
def _bytename(self, size):
prefix = {'': 'K', 'K': 'M', 'M': 'G', 'G': 'T', 'T': 'P', 'P': 'E'}
l = ''
size = size * 1.0
while 1024 < size:
l = prefix[l]
size = size / 1024
s = ""
if size > 1:
s = "s"
return "%g %sbyte%s" % (size, l, s)
@robust
def _transfer(self, url, path, size):
self.log("Transfering %s into %s" % (self._bytename(size), path))
self.log("From %s" % (url, ))
start = time.time()
http = urlopen(url)
f = open(path, "wb")
total = 0
block = 1024 * 1024
while True:
chunk = http.read(block)
if not chunk:
break
f.write(chunk)
total += len(chunk)
f.flush()
f.close()
end = time.time()
header = http.info()
length = header.get("Content-Length")
if length is None:
self.log("Warning: Content-Length missing from HTTP header")
if end > start:
self.log("Transfer rate %s/s" % self._bytename(total / (end - start)), )
return total
def execute(self, request, target=None):
status = None
self.connection.submit("%s/%s/requests" % (self.url, self.service), request)
self.log('Request submitted')
self.log('Request id: ' + self.connection.last['name'])
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
while not self.connection.ready():
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
self.connection.wait()
if self.connection.status != status:
status = self.connection.status
self.log("Request is %s" % (status, ))
result = self.connection.result()
if target:
size = -1
tries = 0
while size != result["size"] and tries < 10:
size = self._transfer(result["href"], target, result["size"])
if size != result["size"] and tries < 10:
tries += 1
self.log("Transfer interrupted, retrying...")
time.sleep(60)
else:
break
assert size == result["size"]
self.connection.cleanup()
return result
###############################################################################
class ECMWFDataServer(object):
def __init__(self, url=None, key=None, email=None, verbose=False, log=None):
if url is None or key is None or email is None:
key, url, email = get_apikey_values()
self.url = url
self.key = key
self.email = email
self.verbose = verbose
self.log = log
def trace(self, m):
if self.log:
self.log(m)
else:
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("%s %s" % (t, m,))
def retrieve(self, req):
target = req.get("target")
dataset = req.get("dataset")
c = APIRequest(self.url, "datasets/%s" % (dataset,), self.email, self.key, self.trace, verbose=self.verbose)
c.execute(req, target)
###############################################################################
class ECMWFService(object):
def __init__(self, service, url=None, key=None, email=None, verbose=False, log=None, quiet=False):
if url is None or key is None or email is None:
key, url, email = get_apikey_values()
self.service = service
self.url = url
self.key = key
self.email = email
self.verbose = verbose
self.quiet = quiet
self.log = log
def trace(self, m):
if self.log:
self.log(m)
else:
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("%s %s" % (t, m,))
def execute(self, req, target):
c = APIRequest(self.url, "services/%s" % (self.service,), self.email, self.key, self.trace, verbose=self.verbose, quiet=self.quiet)
c.execute(req, target)
self.trace("Done.")
###############################################################################
PyAPS-0.3.6/src/pyaps3/newapi/example.py 0000664 0000000 0000000 00000001563 14751542053 0017765 0 ustar 00root root 0000000 0000000 #!/usr/bin/env python
#
# (C) Copyright 2012-2013 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
#
from ecmwfapi import ECMWFDataServer
# To run this example, you need an API key
# available from https://api.ecmwf.int/v1/key/
server = ECMWFDataServer()
server.retrieve({
'dataset' : "tigge",
'step' : "24",
'number' : "all",
'levtype' : "sl",
'date' : "20071001",
'time' : "00",
'origin' : "all",
'type' : "pf",
'param' : "tp",
'area' : "70/-130/30/-60",
'grid' : "2/2",
'target' : "data.grib"
})
PyAPS-0.3.6/src/pyaps3/newapi/setup.py 0000664 0000000 0000000 00000001577 14751542053 0017477 0 ustar 00root root 0000000 0000000 #!/usr/bin/env python
#
# (C) Copyright 2012-2013 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
#
from setuptools import setup, find_packages
import ecmwfapi
setup(
name="ecmwf-api-client",
version=ecmwfapi.__version__,
description=ecmwfapi.__doc__,
author="ECMWF",
author_email="software.support@ecmwf.int",
url="https://software.ecmwf.int/stash/projects/PRDEL/repos/ecmwf-api-client/browse",
# entry_points={
# "console_scripts": [
# "mars = XXX:main",
# ],
# },
packages=find_packages(),
zip_safe=False,
)
PyAPS-0.3.6/src/pyaps3/objects.py 0000664 0000000 0000000 00000030312 14751542053 0016472 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
import os.path
import sys
import numpy as np
import scipy.interpolate as si
from pyaps3 import utils, processor
##############Creating a class object for PyAPS use.
class PyAPS:
'''Class for dealing with Atmospheric phase corrections in radar/geo coordinates.
Operates on one weather model file and one Geo.rsc file at a time.'''
def __init__(self, gribfile, dem, lat, lon, inc=0.0, mask=None,
grib='era5', humidity='Q', Del='comb', model='ERA5', verb=False):
'''Initiates the data structure for atmos corrections in geocoded domain.
Args:
* gribfile (str) : path to downloaded grib file
* dem (np.ndarray) : height in size of (length, width)
* lat (np.ndarray) : latitude in size of (length, width)
* lon (np.ndarray) : longitude in size of (length, width)
Kwargs:
* inc (np.ndarray) : incidence angle (in size of (length, width) for np.ndarray)
* mask (np.ndarray) : mask of valid pixels in size of (length, width)
* grib (str) : grib name in ['ERA5', 'ERAINT', 'HRES', 'NARR', 'MERRA']
* humidity (str) : ['Q', 'R']
* Del (str) : ['comb', 'wet', 'dry']
* model (str) : ECMWF dataset name in ['era5', 'eraint', 'hres']
* verb (bool) : True or False
.. note::
For ISCE products, lat/lon can be read from lat/lon.rdr file
For ROIPAC products, lat, lon = utils.get_lat_lon('radar_16rlks.hgt.rsc')
'''
#--------- Check files exist and we have what's needed for computation
# check grib type and import module
grib = grib.upper()
if grib in ['ERA5','ERAINT','HRES']:
from pyaps3 import era
elif grib == 'NARR':
from pyaps3 import narr
elif grib == 'MERRA':
from pyaps3 import merra
else:
raise ValueError('PyAPS: Undefined grib file source: {}'.format(grib))
self.grib = grib
# Check Humidity variable
humidity = humidity.upper()
assert humidity in ('Q','R'), 'PyAPS: Undefined humidity.'
self.humidity = humidity
if self.grib in ('NARR','MERRA'):
assert self.humidity in ('Q'), 'PyAPS: Relative humidity not provided by NARR/MERRA.'
# Check the model for ECMWF
self.model = model
# Check grib file exists
assert os.path.isfile(gribfile), 'PyAPS: GRIB File does not exist.'
self.gfile = gribfile
# Get altitude, lon, lat, etc
self.dem = dem
self.lon = lon
self.lat = lat
self.inc = inc
self.mask = np.ones(self.dem.shape) if mask is None else mask
# Get size
self.ny, self.nx = self.dem.shape
assert self.lon.shape == (self.ny, self.nx), 'PyAPS: Longitude array size mismatch'
assert self.lat.shape == (self.ny, self.nx), 'PyAPS: Latitude array size mismatch'
assert self.mask.shape == (self.ny, self.nx), 'PyAPS: Mask array size mismatch'
# check incidence angle size and type
if isinstance(self.inc, np.ndarray):
assert self.inc.shape == (self.ny, self.nx), 'PyAPS: Incidence array size mismatch'
if verb:
print('INFO: INCIDENCE ANGLE AS AN ARRAY')
elif isinstance(self.inc, (int, float, np.float32, np.float64)):
if verb:
print('INFO: INCIDENCE ANGLE AS A NUMBER: {} DEG'.format(self.inc))
else:
raise ValueError('PyAPS: unrecognized incidence data type: {}'.format(type(self.inc)))
#--------- Initialize variables
self.dict = processor.initconst()
# Get some scales
if self.grib in ('ERA5','ERAINT','HRES'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) / self.dict['nhgt']) / 0.703
self.bufspc = 1.2
elif self.grib in ('NARR'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) / self.dict['nhgt']) / 0.3
self.bufspc = 1.2
elif self.grib in ('MERRA'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) / self.dict['nhgt']) / 0.5
self.bufspc = 1.0
# Problems in isce when lon and lat arrays have weird numbers
if self.grib in ('ERA5','ERAINT','HRES'):
self.lon[self.lon > 180.] -= 360.
else:
self.lon[self.lon < 0.] += 360.0
self.minlon = np.nanmin(self.lon[np.nonzero(self.mask)]) - self.bufspc
self.maxlon = np.nanmax(self.lon[np.nonzero(self.mask)]) + self.bufspc
self.minlat = np.nanmin(self.lat[np.nonzero(self.mask)]) - self.bufspc
self.maxlat = np.nanmax(self.lat[np.nonzero(self.mask)]) + self.bufspc
if verb:
print('INFO: AREA COVERAGE IN SNWE: ({:.2f}, {:.2f}, {:.2f}, {:.2f})'.format(
self.maxlat, self.minlat, self.minlon, self.maxlon))
#--------- Extract infos from gribfiles
if self.grib in ('ERA'):
assert False, 'Need to modify get_era to fit with the new standards'
[lvls,latlist,lonlist,gph,tmp,vpr] = era.get_era(
self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb,
)
elif self.grib in ('ERA5','ERAINT','HRES'):
[lvls,latlist,lonlist,gph,tmp,vpr] = era.get_ecmwf(
self.model,
self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb,
)
elif self.grib in ('NARR'):
assert False, 'Need to modify get_narr to fit with the new standards'
[lvls,latlist,lonlist,gph,tmp,vpr] = narr.get_narr(
self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb,
)
elif self.grib in ('MERRA'):
assert False, 'Need to modify get_merra to fit with the new standards'
[lvls,latlist,lonlist,gph,tmp,vpr] = merra.get_merra(
self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb,
)
lonlist[lonlist < 0.] += 360.0
# Make a height scale
hgt = np.linspace(self.dict['minAltP'], gph.max().round(), self.dict['nhgt'])
# Interpolate pressure, temperature and Humidity of hgt
[Pi,Ti,Vi] = processor.intP2H(lvls, hgt, gph, tmp, vpr, self.dict, verbose=verb)
# Calculate the delays
[DDry,DWet] = processor.PTV2del(Pi,Ti,Vi,hgt,self.dict,verbose=verb)
if Del.lower() == 'comb':
Delfn = DDry+DWet
elif Del.lower() == 'dry':
Delfn = DDry
elif Del.lower() == 'wet':
Delfn = DWet
else:
raise ValueError('Unrecognized delay type: {}'.format(Del))
if self.grib in ('NARR'):
assert False, 'Need to check narr.intdel'
[Delfn, latlist, lonlist] = narr.intdel(hgt, latlist, lonlist, Delfn)
#--------- Save things
self.Delfn = Delfn
self.latlist = latlist
self.lonlist = lonlist
self.lat = lat
self.lon = lon
self.hgt = hgt
self.Pi = Pi
self.Ti = Ti
self.Vi = Vi
self.verb = verb
# All done
return
def getdelay(self, dout=None, outFile=None, wvl=np.pi*4., writeStations=True):
'''Get the 2D matrix of tropospheric delay with bilinear interpolation.
Kwargs:
* dout : 2D np.ndarray, output delay matrix
* outFile : str, file path of output delay matrix
* wvl : Wavelength in meters.
4*pi (by default) --> output results in delay in meters.
0.056 --> output results in delay in radians for C-band SAR.
Returns:
* dout : 2D np.ndarray in size of (ny, nx) in float32.
'''
# To know the type of incidence (float, array)
if isinstance(self.inc, (int, float, np.float32, np.float64)):
cinc = np.cos(self.inc*np.pi/180.)
incFileFlag = 'number'
else:
incFileFlag = 'array'
# Get some info from the dictionary
minAltp = self.dict['minAltP']
# initiate output
dout = np.zeros((self.ny, self.nx), dtype=np.float32) if dout is None else dout
fout = open(outFile, 'wb') if outFile else None
#######################################################################################
# BILINEAR INTERPOLATION
# Create the 1d interpolator to interpolate delays in altitude direction
if self.verb:
print('PROGRESS: FINE INTERPOLATION OF HEIGHT LEVELS')
intp_1d = si.interp1d(self.hgt, self.Delfn, kind='cubic', axis=-1)
# Interpolate the delay function every meter, for each station
self.dem[np.isnan(self.dem)] = minAltp
self.dem[self.dem < minAltp] = minAltp
minH = np.max([np.nanmin(self.dem*self.mask), self.hgt.min()])
maxH = int(np.nanmax(self.dem*self.mask)) + 100.
kh = np.arange(minH,maxH)
self.Delfn_1m = intp_1d(kh)
self.alti = kh
# no reshape
Lonu = self.lonlist[0,:]
Latu = self.latlist[:,0]
# Create the cube interpolator for the bilinear method, to interpolate delays into a grid (x,y,z)
if self.verb:
print('PROGRESS: CREATE THE BILINEAR INTERPOLATION FUNCTION')
# Define a linear interpolating function on the 3D grid: ((x, y, z), data)
# We do the weird trick of [::-1,:,:] because Latu has to be in increasing order
# for the RegularGridInterpolator method of scipy.interpolate
linearint = si.RegularGridInterpolator(
(Latu[::-1], Lonu,kh),
self.Delfn_1m[::-1,:,:],
method='linear',
bounds_error=False,
fill_value=0.0,
)
# Show progress bar
if self.verb:
toto = utils.ProgressBar(maxValue=self.ny)
print('PROGRESS: MAPPING THE DELAY')
# Loop on the lines
for m in range(self.ny):
# Update progress bar
if self.verb:
toto.update(m+1, every=5)
# Get latitude and longitude arrays
lati = self.lat[m,:]*self.mask[m,:]
loni = self.lon[m,:]*self.mask[m,:]
# Remove negative values
if self.grib in ('ERA5','ERAINT','HRES'):
loni[loni > 180.] -= 360.
else:
loni[loni < 0.] += 360.
# Remove NaN values
ii = np.where(np.isnan(lati))
jj = np.where(np.isnan(loni))
xx = np.union1d(ii,jj)
lati[xx]=0.0
loni[xx]=0.0
# Get incidence if file provided
if incFileFlag == 'array':
cinc = np.cos(self.mask[m,:]*self.inc[m,:]*np.pi/180.)
# Make the bilinear interpolation
D = self.dem[m,:]
val = linearint(np.vstack((lati, loni, D)).T)*np.pi*4.0/(cinc*wvl)
val[xx] = np.nan
# save output
dout[m,:] = val
if outFile:
val.astype(np.float32).tofile(fout)
if self.verb:
toto.close()
if outFile:
fout.close()
return dout
PyAPS-0.3.6/src/pyaps3/processor.py 0000664 0000000 0000000 00000034466 14751542053 0017076 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
import numpy as np
import scipy.interpolate as intp
import scipy.integrate as intg
def initconst():
'''Initialization of various constants needed for computing delay.
Args:
* None
Returns:
* constdict (dict): Dictionary of constants
'''
constdict = {}
constdict['k1'] = 0.776 #(K/Pa)
constdict['k2'] = 0.716 #(K/Pa)
constdict['k3'] = 3750 #(K^2.Pa)
constdict['g'] = 9.81 #(m/s^2)
constdict['Rd'] = 287.05 #(J/Kg/K)
constdict['Rv'] = 461.495 #(J/Kg/K)
constdict['mma'] = 29.97 #(g/mol)
constdict['mmH'] = 2.0158 #(g/mol)
constdict['mmO'] = 16.0 #(g/mol)
constdict['Rho'] = 1000.0 #(kg/m^3)
constdict['a1w'] = 611.21 # hPa
constdict['a3w'] = 17.502 #
constdict['a4w'] = 32.19 # K
constdict['a1i'] = 611.21 # hPa
constdict['a3i'] = 22.587 #
constdict['a4i'] = -0.7 # K
constdict['T3'] = 273.16 # K
constdict['Ti'] = 250.16 # K
constdict['nhgt'] = 300 # Number of levels for interpolation (OLD 151)
constdict['minAlt'] = -200.0
constdict['maxAlt'] = 50000.0
constdict['minAltP'] = -200.0
return constdict
###############Completed the list of constants################
##########Interpolating to heights from Pressure levels###########
def intP2H(lvls,hgt,gph,tmp,vpr,cdic,verbose=False):
'''Interpolates the pressure level data to altitude.
Args:
* lvls (np.ndarray) : Pressure levels.
* hgt (np.ndarray) : Height values for interpolation.
* gph (np.ndarray) : Geopotential height.
* tmp (np.ndarray) : Temperature.
* vpr (np.ndarray) : Vapor pressure.
* cdic (dict) : Dictionary of constants.
.. note::
gph,tmp,vpr are of size (nstn,nlvls).
Returns:
* Presi (np.ndarray): Interpolated pressure.
* Tempi (np.ndarray): Interpolated temperature.
* Vpri (np.ndarray): Interpolated vapor pressure.
.. note::
Cubic splines are used to convert pressure level data to height level data.'''
minAlt = cdic['minAlt'] #Hardcoded parameter.
maxAlt = gph.max().round()
if verbose:
print('PROGRESS: INTERPOLATING FROM PRESSURE TO HEIGHT LEVELS')
nlat = gph.shape[1] #Number of stations
nlon = gph.shape[2]
nhgt = len(hgt) #Number of height points
Presi = np.zeros((nlat,nlon,nhgt))
Tempi = np.zeros((nlat,nlon,nhgt))
Vpri = np.zeros((nlat,nlon,nhgt))
for i in range(nlat):
for j in range(nlon):
temp = gph[:,i,j] #Obtaining height values
hx = temp.copy()
sFlag = False
eFlag = False
#Add point at start
if (hx.min() > minAlt):
sFlag = True
#changed from 1 to 0 (-1 should also work), CL
hx = np.concatenate((hx,[minAlt-1]),axis = 0)
#Add point at end
if (hx.max() < maxAlt):
eFlag = True
#changed from 1 to 0 (-1 should also work), CL
hx = np.concatenate(([maxAlt+1],hx),axis=0)
#Splines needs monotonically increasing.
hx = -hx
#Interpolating pressure values
hy = lvls.copy()
if (sFlag == True):
val = hy[-1] + (hx[-1] - hx[-2]) * (hy[-1] - hy[-2]) / (hx[-2] - hx[-3])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate((hy,[val]),axis=0)
if (eFlag == True):
val = hy[0] - (hx[0] - hx[1]) * (hy[0] - hy[1]) / (hx[1] - hx[2])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate(([val],hy),axis=0)
tck = intp.interp1d(hx,hy,kind='cubic')
#Again negative for consistency with hx
temp = tck(-hgt)
Presi[i,j,:] = temp.copy()
del temp
#Interpolating temperature
temp = tmp[:,i,j]
hy = temp.copy()
if (sFlag == True):
val = hy[-1] + (hx[-1] - hx[-2]) * (hy[-1] - hy[-2]) / (hx[-2] - hx[-3])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate((hy,[val]),axis=0)
if (eFlag == True):
val = hy[0] - (hx[0] - hx[1]) * (hy[0] - hy[1]) / (hx[1] - hx[2])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate(([val],hy),axis=0)
tck = intp.interp1d(hx,hy,kind='cubic')
temp = tck(-hgt)
Tempi[i,j,:] = temp.copy()
del temp
#Interpolating vapor pressure
temp = vpr[:,i,j]
hy = temp.copy()
if (sFlag == True):
val = hy[-1] + (hx[-1] - hx[-2]) * (hy[-1] - hy[-2]) / (hx[-2] - hx[-3])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate((hy,[val]),axis=0)
if (eFlag == True):
val = hy[0] - (hx[0] - hx[1]) * (hy[0] - hy[1]) / (hx[1] - hx[2])
#changed from 1 to 0 (-1 should also work), CL
hy = np.concatenate(([val],hy),axis=0)
tck = intp.interp1d(hx,hy,kind='cubic')
temp = tck(-hgt)
Vpri[i,j,:] = temp.copy()
del temp
## Save into files for plotting (test for era5 interpolation)
#out_dir = '/home/angel/Tests/test_era5interpolation/Outputs'
#suffix = '20141023_20141210_era5'
#np.savetxt(f'{out_dir}/alt_{suffix}.txt', gph, fmt=' '.join(['%s']*380)) # altitude (of lvls)
#np.savetxt(f'{out_dir}/lvls_{suffix}.txt', lvls.T, fmt='%s') # pressure
#np.savetxt(f'{out_dir}/tmp_{suffix}.txt', tmp, fmt=' '.join(['%s']*380)) # temperature
#np.savetxt(f'{out_dir}/vpr_{suffix}.txt', vpr, fmt=' '.join(['%s']*380)) # vapor
#np.savetxt(f'{out_dir}/Alti_{suffix}.txt', hgt.T, fmt='%s') # interpo altitude
#np.savetxt(f'{out_dir}/Presi_{suffix}.txt', Presi.T, fmt=' '.join(['%s']*380)) # interpo pressure
#np.savetxt(f'{out_dir}/Tempi_{suffix}.txt', Tempi.T, fmt=' '.join(['%s']*380)) # interpo temperature
#np.savetxt(f'{out_dir}/Vpri_{suffix}.txt', Vpri.T, fmt=' '.join(['%s']*380)) # interpo vapor
return Presi,Tempi,Vpri
###########Completed interpolation to height levels #####################
###########Computing the delay function ###############################
def PTV2del(Presi,Tempi,Vpri,hgt,cdict,verbose=False):
'''Computes the delay function given Pressure, Temperature and Vapor pressure.
Args:
* Presi (np.ndarray) : Pressure at height levels.
* Tempi (np.ndarray) : Temperature at height levels.
* Vpri (np.ndarray) : Vapor pressure at height levels.
* hgt (np.ndarray) : Height levels.
* cdict (np.ndarray) : Dictionary of constants.
Returns:
* DDry2 (np.ndarray) : Dry component of atmospheric delay.
* DWet2 (np.ndarray) : Wet component of atmospheric delay.
.. note::
Computes refractive index at each altitude and integrates the delay using cumtrapz.'''
if verbose:
print('PROGRESS: COMPUTING DELAY FUNCTIONS')
nhgt = len(hgt) #Number of height points
nlat = Presi.shape[0] #Number of stations
nlon = Presi.shape[1]
WonT = Vpri/Tempi
WonT2 = WonT/Tempi
k1 = cdict['k1']
Rd = cdict['Rd']
Rv = cdict['Rv']
k2 = cdict['k2']
k3 = cdict['k3']
g = cdict['g']
#Dry delay
DDry2 = np.zeros((nlat,nlon,nhgt))
DDry2[:,:,:] = k1*Rd*(Presi[:,:,:] - Presi[:,:,-1][:,:,np.newaxis])*1.0e-6/g
#Wet delay
S1 = intg.cumulative_trapezoid(WonT,x=hgt,axis=-1)
val = 2*S1[:,:,-1]-S1[:,:,-2]
val = val[:,:,None]
S1 = np.concatenate((S1,val),axis=-1)
del WonT
S2 = intg.cumulative_trapezoid(WonT2,x=hgt,axis=-1)
val = 2*S2[:,:,-1]-S2[:,:,-2]
val = val[:,:,None]
S2 = np.concatenate((S2,val),axis=-1)
DWet2 = -1.0e-6*((k2-k1*Rd/Rv)*S1+k3*S2)
for i in range(nlat):
for j in range(nlon):
DWet2[i,j,:] = DWet2[i,j,:] - DWet2[i,j,-1]
return DDry2,DWet2
####################Completed delay function#################
####Setting up 3D interpolation function in geo/xy coordinates#######
def make3dintp(Delfn,lonlist,latlist,hgt,hgtscale):
'''Returns a 3D interpolation function that can be used to interpolate using llh coordinates.
Args:
* Delfn (np.ndarray) : Array of delay values.
* lonlist (np.ndarray) : Array of station longitudes.
* latlist (np.ndarray) : Array of station latitudes.
* hgt (np.ndarray) : Array of height levels.
* hgtscale (float) : Height scale factor for interpolator.
Returns:
* fnc (function) : 3D interpolation function.
.. note::
We currently use the LinearNDInterpolator from scipy.
'''
##Delfn = Ddry + Dwet. Delay function.
##lonlist = list of lons for stations. / x
##latlist = list of lats for stations. / y
nstn = Delfn.shape[0]
nhgt = Delfn.shape[1]
xyz = np.zeros((nstn*nhgt,3))
Delfn = np.reshape(Delfn,(nstn*nhgt,1))
print('3D interpolation')
count = 0
for m in range(nstn):
for n in range(nhgt):
xyz[count,0] = lonlist[m]
xyz[count,1] = latlist[m]
xyz[count,2] = hgt[n]/hgtscale #For same grid spacing as lat/lon
count += 1
#xyz[:,2] = xyz[:,2] #+ 1e-30*np.random.rand((nstn*nhgt))/hgtscale #For unique Delaunay
del latlist
del lonlist
del hgt
if verbose:
print('PROGRESS: BUILDING INTERPOLATION FUNCTION')
fnc = intp.LinearNDInterpolator(xyz,Delfn)
return fnc
###########Completed 3D interpolation in geo coordinates############
########### Class for bilinear interpolation at a certain level in a 3d cube
class Bilinear2DInterpolator:
'''Bilinear interpolation in 2D. The code is modified from mpl_toolkits.basemap.interp and scipy.interpolate'''
def __init__(self, xin, yin, datain,cube=False):
'''Setting up the interpolator.
.. Args:
* xin -> Monotonic array of x coordinates
* yin -> Monotonic array of y coordinates
* datain -> 2D array corresponding to (y,x) if cube=False, else 3D array corresponding to (nz,y,x)
.. Kwargs:
* cube -> 2D array or 3D array cube.'''
if cube:
if xin.shape[0] != datain.shape[2]:
raise ValueError('Shapes of datain and x do not match')
if yin.shape[0] != datain.shape[1]:
raise ValueError('Shapes of datain and y do not match')
else:
if xin.shape[0] != datain.shape[1]:
raise ValueError('Shapes of datain and x do not match')
if yin.shape[0] != datain.shape[0]:
raise ValueError('Shapes of datain and y do not match')
if xin[-1] < xin[0]:
raise ValueError('Array x not sorted')
if yin[-1] < yin[0]:
raise ValueError('Array y not sorted')
self.xin = xin.copy()
self.yin = yin.copy()
delx = xin[1:] - xin[0:-1]
dely = yin[1:] - yin[0:-1]
if max(delx)-min(delx) < 1.e-4 and max(dely)-min(dely) < 1.e-4:
self.regular = True
else:
self.regular = False
self.xinlist = self.xin.tolist()
self.yinlist = self.yin.tolist()
self.nx = len(self.xinlist)
self.ny = len(self.yinlist)
self.cube = cube
self.zin = datain.copy()
# All done
return
def __call__(self,xi,yi,iz=0):
'''Function call to actually interpolate.'''
if xi.shape != yi.shape:
raise ValueError('xi and yi must have same shape.')
if self.regular:
xcoords = (self.nx-1)*(xi-self.xin[0])/(self.xin[-1]-self.xin[0])
ycoords = (self.ny-1)*(yi-self.yin[0])/(self.yin[-1]-self.yin[0])
else:
xiflat = xi.flatten()
yiflat = yi.flatten()
ix = (np.searchsorted(self.xin,xiflat)-1).tolist()
iy = (np.searchsorted(self.yin,yiflat)-1).tolist()
xiflat = xiflat.tolist()
yiflat = yiflat.tolist()
xin = self.xinlist
yin = self.yinlist
xcoords = []
ycoords = []
for n,i in enumerate(ix):
if i < 0:
xcoords.append(-1)
elif i >= self.nx-1:
xcoords.append(self.nx)
else:
xcoords.append(float(i)+(xiflat[n]-xin[i])/(xin[i+1]-xin[i]))
for m,j in enumerate(iy):
if j < 0:
ycoords.append(-1)
elif j >= self.ny-1:
ycoords.append(self.ny)
else:
ycoords.append(float(j)+(yiflat[m]-yin[j])/(yin[j+1]-yin[j]))
xcoords = np.reshape(xcoords, xi.shape)
ycoords = np.reshape(ycoords, yi.shape)
xcoords = np.clip(xcoords,0,self.nx-1)
ycoords = np.clip(ycoords,0,self.ny-1)
xint = xcoords.astype(np.int32)
yint = ycoords.astype(np.int32)
xip1 = np.clip(xint+1,0,self.nx-1)
yip1 = np.clip(yint+1,0,self.ny-1)
delx = xcoords - xint.astype(np.float32)
dely = ycoords - yint.astype(np.float32)
zin = self.zin
if self.cube:
dataout = (1.-delx)*(1.-dely)*zin[iz,yint,xint] + \
delx*dely*zin[iz,yip1,xip1] + \
(1.-delx)*dely*zin[iz,yip1,xint] + \
delx*(1.-dely)*zin[iz,yint,xip1]
else:
dataout = (1.-delx)*(1.-dely)*zin[yint,xint] + \
delx*dely*zin[yip1,xip1] + \
(1.-delx)*dely*zin[yip1,xint] + \
delx*(1.-dely)*zin[yint,xip1]
return dataout
PyAPS-0.3.6/src/pyaps3/utils.py 0000664 0000000 0000000 00000057051 14751542053 0016212 0 ustar 00root root 0000000 0000000 ############################################################
# Program is part of PyAPS #
# Copyright 2012, by the California Institute of Technology#
# Contact: earthdef@gps.caltech.edu #
# Modified by A. Benoit and R. Jolivet 2019 #
# Ecole Normale Superieure, Paris #
# Contact: insar@geologie.ens.fr #
############################################################
# Add more utils functions, Zhang Yunjun, April 2019
# get_lat_lon()
# read_(meta)data()
# read_isce_xml/data/lalo_ref()
# read_roipac_data/rsc()
import os
import sys
import time
import numpy as np
def snwe2str(snwe):
"""Get area extent in string"""
if not snwe:
return None
s, n, w, e = snwe
area = ''
area += '_S{}'.format(abs(s)) if s < 0 else '_N{}'.format(abs(s))
area += '_S{}'.format(abs(n)) if n < 0 else '_N{}'.format(abs(n))
area += '_W{}'.format(abs(w)) if w < 0 else '_E{}'.format(abs(w))
area += '_W{}'.format(abs(e)) if e < 0 else '_E{}'.format(abs(e))
return area
############### Read ISCE / ROIPAC file ###############
def get_lat_lon(metafile):
"""Get 2D lat and lon from rsc/xml file
Args:
* metafile (str or dict) : path to metadata file, or dict of metadata
"""
if isinstance(metafile, str):
fext = os.path.splitext(metafile)[1]
if fext == '.rsc':
meta = read_roipac_rsc(metafile)
elif fext == '.xml':
meta = read_isce_xml(metafile)
else:
raise ValueError('unrecognized file extension: {}'.format(fext))
elif isinstance(metafile, dict):
meta = {}
for key, value in metafile.items():
meta[key] = value
length, width = int(meta['FILE_LENGTH']), int(meta['WIDTH'])
# get bbox
if 'Y_FIRST' in meta.keys():
# geo coordinates
lat0 = float(meta['Y_FIRST'])
lon0 = float(meta['X_FIRST'])
lat_step = float(meta['Y_STEP'])
lon_step = float(meta['X_STEP'])
lat1 = lat0 + lat_step * (length - 1)
lon1 = lon0 + lon_step * (width - 1)
else:
# radar coordinates
lats = [float(meta['LAT_REF{}'.format(i)]) for i in [1,2,3,4]]
lons = [float(meta['LON_REF{}'.format(i)]) for i in [1,2,3,4]]
lat0 = np.mean(lats[0:2])
lat1 = np.mean(lats[2:4])
lon0 = np.mean(lons[0:3:2])
lon1 = np.mean(lons[1:4:2])
# bbox --> 2D array
lat, lon = np.mgrid[lat0:lat1:length*1j,
lon0:lon1:width*1j]
return lat, lon
def read_data(fname, dname='inc'):
"""Read 2D data from ISCE / ROIPAC file"""
# get meta file extension
meta_exts = [i for i in ['.xml', '.rsc'] if os.path.isfile(fname+i)]
if len(meta_exts) == 0:
raise FileNotFoundError('No metadata file found for data file: {}'.format(fname))
meta_ext = meta_exts[0]
if meta_ext == '.xml':
data = read_isce_data(fname, dname=dname)
elif meta_ext == '.rsc':
data = read_roipac_data(fname)
return data
def read_metadata(fname, latfile=None, lonfile=None, full=False, verbose=False):
'''Reading metadata for ISCE or ROIPAC style data file
Args:
* fname (str): Path to the ROIPAC or ISCE data file.
Returns:
* lat (np.ndarray): Array of lat of the 4 corners.
* lon (np.ndarray): Array of lon of the 4 corners.
* nx (int) : Number of range bins.
* ny (int) : Number of azimuth lines.
* dpix (float) : Average pixel spacing.
* meta (dict) : Dictionary of metadata [return if full==True]
'''
# get meta file extension
meta_exts = [i for i in ['.rsc','.xml'] if os.path.isfile(fname+i)]
if len(meta_exts) == 0:
raise FileNotFoundError('No metadata file found for data file: {}'.format(fname))
meta_ext = meta_exts[0]
if verbose:
print("PROGRESS: READING {} FILE".format(fname+meta_ext))
# read metadata
meta = {}
if meta_ext == '.rsc':
meta = read_roipac_rsc(fname+meta_ext)
elif meta_ext == '.xml':
meta = read_isce_xml(fname+meta_ext)
# default latfile
if not latfile:
latfile = os.path.join(os.path.dirname(fname),'lat.rdr')
if not os.path.isfile(latfile):
raise FileNotFoundError("No latitude file found in ISCE style!")
# default lonfile
if not lonfile:
lonfile = os.path.join(os.path.dirname(fname),'lon.rdr')
if not os.path.isfile(lonfile):
raise FileNotFoundError("No longitude file found in ISCE style!")
meta.update(get_isce_lalo_ref(latfile, lonfile))
# prepare output
nx = int(meta['WIDTH'])
ny = int(meta['FILE_LENGTH'])
lat = np.zeros((4,1))
lon = np.zeros((4,1))
lat[0] = float(meta['LAT_REF1'])
lon[0] = float(meta['LON_REF1'])
lat[1] = float(meta['LAT_REF2'])
lon[1] = float(meta['LON_REF2'])
lat[2] = float(meta['LAT_REF3'])
lon[2] = float(meta['LON_REF3'])
lat[3] = float(meta['LAT_REF4'])
lon[3] = float(meta['LON_REF4'])
rgpix = 90.0
azpix = 90.0
dpix = np.sqrt(6.25*rgpix*rgpix + azpix*azpix)
if full:
return lon,lat,nx,ny,dpix,meta
else:
return lon,lat,nx,ny,dpix
def read_isce_xml(xmlfile):
"""Read ISCE XML file into dict.
Add from mintpy.utils.readfile.py by Zhang Yunjun
"""
import xml.etree.ElementTree as ET
meta = {}
root = ET.parse(xmlfile).getroot()
if root.tag.startswith('image'):
for child in root.findall('property'):
key = child.get('name')
value = child.find('value').text
meta[key] = value
# Read lat/lon info for geocoded file
# in form: root/component coordinate*/property name/value
for coord_name, prefix in zip(['coordinate1', 'coordinate2'], ['X', 'Y']):
child = root.find("./component[@name='{}']".format(coord_name))
if ET.iselement(child):
v_step = float(child.find("./property[@name='delta']").find('value').text)
v_first = float(child.find("./property[@name='startingvalue']").find('value').text)
if abs(v_step) < 1. and abs(v_step) > 1e-7:
meta['{}_STEP'.format(prefix)] = v_step
meta['{}_FIRST'.format(prefix)] = v_first - v_step / 2.
# convert key name from isce to roipac
isce2roipacKeyDict = {
'width':'WIDTH',
'length':'FILE_LENGTH',
}
for key,value in isce2roipacKeyDict.items():
meta[value] = meta[key]
return meta
def read_isce_data(fname, dname=None):
"""Read ISCE data file"""
# read xml file
xml_file = fname+'.xml'
meta = read_isce_xml(xml_file)
# get data_type
dataTypeDict = {
'byte': 'bool_',
'float': 'float32',
'double': 'float64',
'cfloat': 'complex64',
}
data_type = dataTypeDict[meta['data_type'].lower()]
width = int(meta['width'])
length = int(meta['length'])
num_band = int(meta['number_bands'])
band = 1
if fname.startswith('los') and dname and dname.startswith('az'):
band = 2
# read
data = np.fromfile(fname, dtype=data_type, count=length*width*num_band).reshape(-1, width*num_band)
data = data[:, width*(band-1):width*band]
return data
def get_isce_lalo_ref(lat_file, lon_file):
"""Get LAT/LON_REF1/2/3/4 value from ISCE lat/lon.rdr file
Add from mintpy.prep_isce.py by Zhang Yunjun
"""
def get_nonzero_row_number(data, buffer=2):
"""Find the first and last row number of rows without zero value
for multiple swaths data
"""
if np.all(data):
r0, r1 = 0 + buffer, -1 - buffer
else:
row_flag = np.sum(data != 0., axis=1) == data.shape[1]
row_idx = np.where(row_flag)[0]
r0, r1 = row_idx[0] + buffer, row_idx[-1] - buffer
return r0, r1
meta = {}
# read LAT/LON_REF1/2/3/4 from lat/lonfile
lat = read_isce_data(lat_file)
r0, r1 = get_nonzero_row_number(lat)
meta['LAT_REF1'] = str(lat[r0, 0])
meta['LAT_REF2'] = str(lat[r0, -1])
meta['LAT_REF3'] = str(lat[r1, 0])
meta['LAT_REF4'] = str(lat[r1, -1])
lon = read_isce_data(lon_file)
r0, r1 = get_nonzero_row_number(lon)
meta['LON_REF1'] = str(lon[r0, 0])
meta['LON_REF2'] = str(lon[r0, -1])
meta['LON_REF3'] = str(lon[r1, 0])
meta['LON_REF4'] = str(lon[r1, -1])
return meta
def read_roipac_rsc(rscfile):
"""Read ROIPAC style RSC file into dict"""
meta = {}
f = open(rscfile,'r')
line = f.readline()
while line:
llist = line.split()
if len(llist)>0 :
meta[llist[0]] = llist[1]
line = f.readline()
f.close()
return meta
def read_roipac_data(fname):
"""Read ROIPAC data file"""
# get length / width
rsc_file = fname+'.rsc'
meta = read_roipac_rsc(rsc_file)
length = int(meta['FILE_LENGTH'])
width = int(meta['WIDTH'])
# get datatype / band
data_type = 'float32'
num_band = 1
band = 1
fext = os.path.splitext(fname)[1]
if fext == '.dem':
data_type = 'int16'
elif fext == '.hgt':
num_band = 2
band = 2
# read
data = np.fromfile(fname, dtype=data_type, count=length*width*num_band).reshape(-1, width*num_band)
data = data[:, width*(band-1):width*band]
return data
############### Read ISCE / ROIPAC file - end #########
############### obsolete: RSC for radar ###############
def rd_rsc(inname,full=False,verbose=False):
'''Reading a ROI-PAC style RSC file.
Args:
* inname (str): Path to the RSC file.
Returns:
* lat (np.ndarray): Array of lat of the 4 corners.
* lon (np.ndarray): Array of lon of the 4 corners.
* nx (int) : Number of range bins.
* ny (int) : Number of azimuth lines.
* dpix (float) : Average pixel spacing.
.. note::
Currently set up to work with SIM_nrlks.hgt from ROI-PAC.'''
if verbose:
print("PROGRESS: READING %s RSC FILE" %inname)
rpacdict = {}
infile = open(inname+'.rsc','r')
line = infile.readline()
rpacdict['LAT_REF1']=0.0
rpacdict['LON_REF1']=0.0
rpacdict['LAT_REF2']=0.0
rpacdict['LON_REF2']=0.0
rpacdict['LAT_REF3']=0.0
rpacdict['LON_REF3']=0.0
rpacdict['LAT_REF4']=0.0
rpacdict['LON_REF4']=0.0
while line:
llist = line.split()
if len(llist)>0 :
rpacdict[llist[0]] = llist[1]
line = infile.readline()
infile.close()
# prepare output
nx = int(rpacdict['WIDTH'])
ny = int(rpacdict['FILE_LENGTH'])
lat=np.zeros((4,1))
lon=np.zeros((4,1))
lat[0] = float(rpacdict['LAT_REF1'])
lon[0] = float(rpacdict['LON_REF1'])
lat[1] = float(rpacdict['LAT_REF2'])
lon[1] = float(rpacdict['LON_REF2'])
lat[2] = float(rpacdict['LAT_REF3'])
lon[2] = float(rpacdict['LON_REF3'])
lat[3] = float(rpacdict['LAT_REF4'])
lon[3] = float(rpacdict['LON_REF4'])
rgpix = 90.0 # float(rpacdict['RANGE_PIXEL_SIZE'])
azpix = 90.0 # float(rpacdict['AZIMUTH_PIXEL_SIZE'])
dpix = np.sqrt(6.25*rgpix*rgpix+azpix*azpix)
if full:
return lon,lat,nx,ny,dpix,rpacdict
else:
return lon,lat,nx,ny,dpix
#######################Finished rd_rsc###########################
###############Reading input RSC file for geo###############
def geo_rsc(inname,full=False,verbose=False):
'''Reading a ROI-PAC style geocoded rsc file.
Args:
* inname (str): Path to the RSC file.
Returns:
* lon (np.ndarray): Array of min and max lon values.
* lat (np.ndarray): Array of min and max lat values.
* nx (int) : Number of lon bins.
* ny (int) : Number of lat bins.
.. note::
Currently set up to work with dem.rsc file from ROI-PAC.'''
if verbose:
print("PROGRESS: READING %s RSC FILE" %inname)
rpacdict = {}
infile = open(inname+'.rsc','r')
line = infile.readline()
while line:
llist = line.split()
if len(llist)>0 :
rpacdict[llist[0]] = llist[1]
line = infile.readline()
infile.close()
nx = int(rpacdict['WIDTH'])
ny = int(rpacdict['FILE_LENGTH'])
lat=np.zeros((2,1))
lon=np.zeros((2,1))
lat[1] = float(rpacdict['Y_FIRST'])
lon[0] = float(rpacdict['X_FIRST'])
if(lon[0] < 0):
lon[0] = lon[0] + 360.0
dx = float(rpacdict['X_STEP'])
dy = float(rpacdict['Y_STEP'])
lat[0] = lat[1] + dy*ny
lon[1] = lon[0] + dx*nx
if full:
return lon,lat,nx,ny,rpacdict
else:
return lon,lat,nx,ny
############### obsolete: RSC for radar - end #########
############### obsolete: simple geo2radar ############
def lonlat2rdr(lon, lat, lonlist, latlist, plotflag=False):
'''
Transfer the lat lon coordinates of the weather stations into the index
range and azimuth coordinates of the radar scene.
Args:
* lon : Longitude array of the radar scene size=(ny,nx)
* lat : Latitude array of the radar scene size=(ny,nx)
* lonlist : Longitude list of the weeather stations
* latlist : Latitude list of the weather stations.
Kwargs:
* plotflag : Plot something to check. (default is False)
note:
Mapping function is :
* range = a1*lat+b1*lon+c1
* azimu = a2*lat+b2*lon+c2
* First point is (1,1) i.e. Near Range, First Lane <==> Lat[0,0],Lon[0,0]
* Second point is (nx,1) i.e. Far Range, First Lane <==> Lat[0,-1],Lon[0,-1]
* Third point is (1,ny) i.e. Near Range, Last Lane <==> Lat[-1,0],Lon[-1,0]
* Fourth point is (nx,ny) i.e. Far Range, Last Lane <==> Lat[-1,-1],Lon[-1,-1]
'''
# Size
ny, nx = lon.shape
# Mapping function
A=np.array([ [lat[0,0], lon[0,0], 1.],
[lat[0,-1], lon[0,-1], 1.],
[lat[-1,0], lon[-1,0], 1.],
[lat[-1,-1], lon[-1,-1], 1.]])
b=np.array([[1., 1.],[nx, 1.],[1., ny],[nx,ny]])
mfcn=np.linalg.lstsq(A,b)[0]
#Get grid points xi yi coordinates from this mapping function
A=np.vstack([latlist, lonlist, np.ones(len(lonlist),)]).T
xi=np.dot(A,mfcn[:,0])
yi=np.dot(A,mfcn[:,1])
# Plot y/n
if plotflag:
from matplotlib import pyplot as plt, patches
plt.figure()
plt.subplot(211)
plt.scatter(lonlist,latlist,s=8,c=np.cumsum(np.ones(len(lonlist),)))
xline=[lon[0,0],lon[0,-1],lon[-1,-1],lon[-1,0],lon[0,0]]
yline=[lat[0,0],lat[0,-1],lat[-1,-1],lat[-1,0],lat[0,0]]
plt.plot(xline,yline,'-r')
plt.title('Area of interest and {} stations used'.format(len(lonlist)))
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.subplot(212)
plt.scatter(xi,yi,s=8,c=np.cumsum(np.ones(len(lonlist),)))
p = patches.Rectangle((1,1),lon.shape[1],lon.shape[0],
edgecolor="Red",fill=False)
plt.gca().add_patch(p)
plt.title('Area of interest in Radar Geometry')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.show()
# All done
return np.array(xi).astype(float), np.array(yi).astype(float)
def glob2rdr(nx,ny,lat,lon,latl,lonl,plotflag='n'):
'''Transfert these latlon coordinates into radar geometry (xi,yi) with a
simple linear transformation given the first pixel and the pixel
spacing of the simulation.
Args:
* nx (int) : Number of range bins.
* ny (int) : Number of azimuth lines.
* lat (np.ndarray) : Array of latitudes of the corners
* lon (np.ndarray) : Array of longitudes of the corners
* latl (np.ndarray) : Latitudes of the stations.
* lonl (np.ndarray) : Longitudes of the stations.
Kwargs:
* plotflag (bool) : Plot the stations distribution.
Returns:
* xi (np.ndarray) : Position of stations in range.
* yi (np.ndarray) : Position of stations in azimuth.
.. note::
Mapping function is :
* range = a1*lat+b1*lon+c1
* azimu = a2*lat+b2*lon+c2
* First point is (1,1) i.e. Near Range, First Lane <==> Lat[1],Lon[1]
* Second point is (nx,1) i.e. Far Range, First Lane <==> Lat[2],Lon[2]
* Third point is (1,ny) i.e. Near Range, Last Lane <==> Lat[3],Lon[3]
* Fourth point is (nx,ny) i.e. Far Range, Last Lane <==> Lat[4],Lon[4] '''
# Mapping function
A = np.hstack([lat,lon,np.ones((4,1))])
b = np.array([[1, 1],[nx, 1],[1, ny],[nx,ny]])
mfcn = np.linalg.lstsq(A,b,rcond=None)[0]
#Get grid points xi yi coordinates from this mapping function
nstn = latl.size
A = np.array([latl.reshape(-1,1), lonl.reshape(-1,1), np.ones((nstn,1))]).T
xi = np.dot(A,mfcn[:,0]).reshape(latl.shape)
yi = np.dot(A,mfcn[:,1]).reshape(latl.shape)
if plotflag in ('y','Y'):
from matplotlib import pyplot as plt, patches
plt.figure(1)
plt.subplot(211)
plt.scatter(lonl,latl,s=8,c='k');
xline=[lon[0],lon[1],lon[3],lon[2],lon[0]]
yline=[lat[0],lat[1],lat[3],lat[2],lat[0]]
plt.plot(xline,yline,'-r')
plt.title('Area of interest and %d stations used'%(nstn))
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.subplot(212)
plt.scatter(xi,yi,s=8,c='k')
p = patches.Rectangle((1,1),nx,ny,edgecolor="Red",fill=False)
plt.gca().add_patch(p)
plt.title('Area of interest in Radar Geometry')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.show()
return xi,yi
############### obsolete: simple geo2radar - end ######
############### obsolete: simple radar2geo ############
def rdr2glob(wid,lgt,lat,lon,x,y,plotflag='n'): #nx,ny,lat,lon,latl,lonl,plotflag='n'):
'''Transfert these radar geometry (x,y) coordinates in lat/lon coordinates with a
simple linear transformation given the image width/length and the lat/lon coordinates
of the 4 corners
Args:
* wid (int) : Width of the image (i.e. number of range bins)
* lgt (int) : Length of the image (i.e. number of azimuth lines)
* lat (np.ndarray) : Array of latitudes of the corners
* lon (np.ndarray) : Array of longitudes of the corners
* rang (np.ndarray) : Range of the points to transfert
* azim (np.ndarray) : Azimuth of the points to transfert
Kwargs:
* plotflag (bool) : Plot the stations distribution.
Returns:
* loni (np.ndarray) : Longitude of the points.
* lati (np.ndarray) : Latitude of the points.
.. note::
Mapping function is :
* lat = a1*rang + b1*azim + c1
* lon = a2*rang + b2*azim + c2
* First point is (1,1) i.e. Near Range, First Lane <==> Lat[1],Lon[1]
* Second point is (nx,1) i.e. Far Range, First Lane <==> Lat[2],Lon[2]
* Third point is (1,ny) i.e. Near Range, Last Lane <==> Lat[3],Lon[3]
* Fourth point is (nx,ny) i.e. Far Range, Last Lane <==> Lat[4],Lon[4] '''
A = np.array([[1, 1, 1.],[wid, 1, 1.],[1, lgt, 1.],[wid, lgt, 1.]])
b = np.hstack((lat,lon))
mfcn = np.linalg.lstsq(A,b)[0]
#Get grid points xi yi coordinates from this mapping function
nstn = len(x)
A = np.array([x, y, np.ones((nstn,1))]).T
lati = np.dot(A,mfcn[:,0])
loni = np.dot(A,mfcn[:,1])
if plotflag in ('y','Y'):
from matplotlib import pyplot as plt, patches
plt.figure(1)
plt.subplot(211)
plt.scatter(lon,lat,s=8,c='k');
xline=[lon[0],lon[1],lon[3],lon[2],lon[0]]
yline=[lat[0],lat[1],lat[3],lat[2],lat[0]]
plt.scatter(loni,lati,s=8,c='r')
plt.plot(xline,yline,'-r')
plt.title('Area of interest in geographic coordinates')
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.subplot(212)
plt.scatter(x,y,s=8,c='k')
p = patches.Rectangle((1,1),wid,lgt,edgecolor="Red",fill=False)
plt.gca().add_patch(p)
plt.title('Area of interest in Radar Geometry')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.show()
return loni,lati
############### obsolete: simple radar2geo - end ######
############### Simple progress bar ###################
class ProgressBar:
""" Creates a text-based progress bar. Call the object with
the simple `print'command to see the progress bar, which looks
something like this:
[=======> 22% ]
You may specify the progress bar's width, min and max values on init.
.. note::
Code originally from http://code.activestate.com/recipes/168639/"""
def __init__(self, minValue = 0, maxValue = 100, totalWidth=80):
self.progBar = "[]" # This holds the progress bar string
self.min = minValue
self.max = maxValue
self.span = maxValue - minValue
self.width = totalWidth
self.reset()
def reset(self):
self.start_time = time.time()
self.amount = 0 # When amount == max, we are 100% done
self.updateAmount(0) # Build progress bar string
def updateAmount(self, newAmount = 0):
""" Update the progress bar with the new amount (with min and max
values set at initialization; if it is over or under, it takes the
min or max value as a default. """
if newAmount < self.min:
newAmount = self.min
if newAmount > self.max:
newAmount = self.max
self.amount = newAmount
# Figure out the new percent done, round to an integer
diffFromMin = float(self.amount - self.min)
percentDone = (diffFromMin / float(self.span)) * 100.0
percentDone = int(np.round(percentDone))
# Figure out how many hash bars the percentage should be
allFull = self.width - 2 - 18
numHashes = (percentDone / 100.0) * allFull
numHashes = int(np.round(numHashes))
# Build a progress bar with an arrow of equal signs; special cases for
# empty and full
if numHashes == 0:
self.progBar = '[>%s]' % (' '*(allFull-1))
elif numHashes == allFull:
self.progBar = '[%s]' % ('='*allFull)
else:
self.progBar = '[%s>%s]' % ('='*(numHashes-1),
' '*(allFull-numHashes))
# figure out where to put the percentage, roughly centered
percentPlace = (len(self.progBar) // 2) - len(str(percentDone))
percentString = ' ' + str(percentDone) + '% '
elapsed_time = time.time() - self.start_time
# slice the percentage into the bar
self.progBar = ''.join([self.progBar[0:percentPlace],
percentString,
self.progBar[percentPlace+len(percentString):]])
if percentDone > 0:
self.progBar += ' %6ds / %6ds' % (int(elapsed_time),int(elapsed_time*(100.//percentDone-1)))
def update(self, value, every=1):
""" Updates the amount, and writes to stdout. Prints a
carriage return first, so it will overwrite the current
line in stdout."""
if value % every == 0 or value >= self.max:
self.updateAmount(newAmount=value)
sys.stdout.write('\r' + self.progBar)
sys.stdout.flush()
def close(self):
"""Prints a blank space at the end to ensure proper printing
of future statements."""
print(' ')
############### Simple progress bar - end #############
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