# (C) Copyright 2017- 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.
import datetime
import keyword
import os
import pkgutil
import signal
import tempfile
import builtins
from enum import Enum
import cffi
import numpy as np
def string_from_ffi(s):
return ffi.string(s).decode("utf-8")
# -----------------------------------------------------------------------------
# Startup
# -----------------------------------------------------------------------------
class MetviewInvoker:
"""Starts a new Metview session on construction and terminates it on program exit"""
def __init__(self):
"""
Constructor - starts a Metview session and reads its environment information
Raises an exception if Metview does not respond within so-many seconds
"""
self.debug = os.environ.get("METVIEW_PYTHON_DEBUG", "0") == "1"
# check whether we're in a running Metview session
if "METVIEW_TITLE_PROD" in os.environ:
self.persistent_session = True
self.info_section = {"METVIEW_LIB": os.environ["METVIEW_LIB"]}
return
import atexit
import time
import subprocess
if self.debug:
print("MetviewInvoker: Invoking Metview")
self.persistent_session = False
self.metview_replied = False
self.metview_startup_timeout = int(
os.environ.get("METVIEW_PYTHON_START_TIMEOUT", "8")
) # seconds
# start Metview with command-line parameters that will let it communicate back to us
env_file = tempfile.NamedTemporaryFile(mode="rt")
pid = os.getpid()
# print('PYTHON:', pid, ' ', env_file.name, ' ', repr(signal.SIGUSR1))
signal.signal(signal.SIGUSR1, self.signal_from_metview)
# p = subprocess.Popen(['metview', '-edbg', 'tv8 -a', '-slog', '-python-serve',
# env_file.name, str(pid)], stdout=subprocess.PIPE)
metview_startup_cmd = os.environ.get("METVIEW_PYTHON_START_CMD", "metview")
metview_flags = [
metview_startup_cmd,
"-nocreatehome",
"-python-serve",
env_file.name,
str(pid),
]
if self.debug:
metview_flags.insert(2, "-slog")
print("Starting Metview using these command args:")
print(metview_flags)
try:
subprocess.Popen(metview_flags)
except Exception as exp:
print(
"Could not run the Metview executable ('" + metview_startup_cmd + "'); "
"check that the binaries for Metview (version 5 at least) are installed "
"and are in the PATH."
)
raise exp
# wait for Metview to respond...
wait_start = time.time()
while not (self.metview_replied) and (
time.time() - wait_start < self.metview_startup_timeout
):
time.sleep(0.001)
if not (self.metview_replied):
raise Exception(
'Command "metview" did not respond within '
+ str(self.metview_startup_timeout)
+ " seconds. "
"At least Metview 5 is required, so please ensure it is in your PATH, "
"as earlier versions will not work with the Python interface."
)
self.read_metview_settings(env_file.name)
# when the Python session terminates, we should destroy this object so that the Metview
# session is properly cleaned up. We can also do this in a __del__ function, but there can
# be problems with the order of cleanup - e.g. the 'os' module might be deleted before
# this destructor is called.
atexit.register(self.destroy)
def destroy(self):
"""Kills the Metview session. Raises an exception if it could not do it."""
if self.persistent_session:
return
if self.metview_replied:
if self.debug:
print("MetviewInvoker: Closing Metview")
metview_pid = self.info("EVENT_PID")
try:
os.kill(int(metview_pid), signal.SIGUSR1)
except Exception as exp:
print("Could not terminate the Metview process pid=" + metview_pid)
raise exp
def signal_from_metview(self, *args):
"""Called when Metview sends a signal back to Python to say that it's started"""
# print ('PYTHON: GOT SIGNAL BACK FROM METVIEW!')
self.metview_replied = True
def read_metview_settings(self, settings_file):
"""Parses the settings file generated by Metview and sets the corresponding env vars"""
import configparser
cf = configparser.ConfigParser()
cf.read(settings_file)
env_section = cf["Environment"]
for envar in env_section:
# print('set ', envar.upper(), ' = ', env_section[envar])
os.environ[envar.upper()] = env_section[envar]
self.info_section = cf["Info"]
def info(self, key):
"""Returns a piece of Metview information that was not set as an env var"""
return self.info_section[key]
def store_signal_handlers(self):
"""Stores the set of signal handlers that Metview will override"""
self.sigint = signal.getsignal(signal.SIGINT)
self.sighup = signal.getsignal(signal.SIGHUP)
self.sighquit = signal.getsignal(signal.SIGQUIT)
self.sigterm = signal.getsignal(signal.SIGTERM)
self.sigalarm = signal.getsignal(signal.SIGALRM)
def restore_signal_handlers(self):
"""Restores the set of signal handlers that Metview has overridden"""
signal.signal(signal.SIGINT, self.sigint)
signal.signal(signal.SIGHUP, self.sighup)
signal.signal(signal.SIGQUIT, self.sighquit)
signal.signal(signal.SIGTERM, self.sigterm)
signal.signal(signal.SIGALRM, self.sigalarm)
mi = MetviewInvoker()
try:
ffi = cffi.FFI()
ffi.cdef(pkgutil.get_data("metview", "metview.h").decode("ascii"))
mv_lib = mi.info("METVIEW_LIB")
# is there a more general way to add to a path to a list of paths?
os.environ["LD_LIBRARY_PATH"] = mv_lib + ":" + os.environ.get("LD_LIBRARY_PATH", "")
try:
# Linux / Unix systems
lib = ffi.dlopen(os.path.join(mv_lib, "libMvMacro.so"))
except OSError:
# MacOS systems
lib = ffi.dlopen(os.path.join(mv_lib, "libMvMacro"))
except Exception as exp:
print(
"Error loading Metview/libMvMacro. LD_LIBRARY_PATH="
+ os.environ.get("LD_LIBRARY_PATH", "")
)
raise exp
# The C/C++ code behind lib.p_init() will call marsinit(), which overrides various signal
# handlers. We don't necessarily want this when running a Python script - we should use
# the default Python behaviour for handling signals, so we save the current signals
# before calling p_init() and restore them after.
mi.store_signal_handlers()
lib.p_init()
mi.restore_signal_handlers()
# fix for binder-hosted notebooks, where PWD and os.cwd() do not seem to be in sync
os.putenv("PWD", os.getcwd())
# -----------------------------------------------------------------------------
# Classes to handle complex Macro types
# -----------------------------------------------------------------------------
class Value:
def __init__(self, val_pointer):
self.val_pointer = val_pointer
self.pickled = False
def push(self):
if self.val_pointer is None:
lib.p_push_nil()
else:
lib.p_push_value(self.val_pointer)
# if we steal a value pointer from a temporary Value object, we need to
# ensure that the Metview Value is not destroyed when the temporary object
# is destroyed by setting its pointer to None
def steal_val_pointer(self, other):
self.val_pointer = other.val_pointer
other.val_pointer = None
def set_temporary(self, flag):
lib.p_set_temporary(self.val_pointer, flag)
# enable a more object-oriented interface, e.g. a = fs.interpolate(10, 29.4)
def __getattr__(self, fname):
def call_func_with_self(*args, **kwargs):
return call(fname, self, *args, **kwargs)
return call_func_with_self
# on destruction, ensure that the Macro Value is also destroyed.
# note the exception - if the variable has been pickled, then there
# may be a temporary file that another process will want to use
# later, so in this case we do not destroy the Macro Value.
def __del__(self):
try:
if self.val_pointer is not None and lib is not None:
if not self.pickled:
lib.p_destroy_value(self.val_pointer)
self.val_pointer = None
except Exception as exp:
print("Could not destroy Metview variable ", self)
raise exp
class Request(dict, Value):
verb = "UNKNOWN"
def __init__(self, req, myverb=None):
self.val_pointer = None
# initialise from Python object (dict/Request)
if isinstance(req, dict):
self.update(req)
self.to_metview_style()
if isinstance(req, Request):
self.verb = req.verb
self.val_pointer = req.val_pointer
else:
if myverb != None:
self.set_verb(myverb)
# initialise from a Macro pointer
else:
Value.__init__(self, req)
self.verb = string_from_ffi(lib.p_get_req_verb(req))
n = lib.p_get_req_num_params(req)
for i in range(0, n):
param = string_from_ffi(lib.p_get_req_param(req, i))
raw_val = lib.p_get_req_value(req, param.encode("utf-8"))
if raw_val != ffi.NULL:
val = string_from_ffi(raw_val)
self[param] = val
# self['_MACRO'] = 'BLANK'
# self['_PATH'] = 'BLANK'
def __str__(self):
return "VERB: " + self.verb + super().__str__()
# translate Python classes into Metview ones where needed
def to_metview_style(self):
for k, v in self.items():
# bool -> on/off
if isinstance(v, bool):
conversion_dict = {True: "on", False: "off"}
self[k] = conversion_dict[v]
# class_ -> class (because 'class' is a Python keyword and cannot be
# used as a named parameter)
elif k == "class_":
self["class"] = v
del self["class_"]
def set_verb(self, v):
self.verb = v
def get_verb(self):
return self.verb
def push(self):
# if we have a pointer to a Metview Value, then use that because it's more
# complete than the dict
if self.val_pointer:
Value.push(self)
else:
r = lib.p_new_request(self.verb.encode("utf-8"))
# to populate a request on the Macro side, we push each
# value onto its stack, and then tell it to create a new
# parameter with that name for the request. This allows us to
# use Macro to handle the addition of complex data types to
# a request
for k, v in self.items():
push_arg(v)
lib.p_set_request_value_from_pop(r, k.encode("utf-8"))
lib.p_push_request(r)
def __getitem__(self, index):
return subset(self, index)
def push_bytes(b):
lib.p_push_string(b)
def push_str(s):
push_bytes(s.encode("utf-8"))
def push_list(lst):
# ask Metview to create a new list, then add each element by
# pusing it onto the stack and asking Metview to pop it off
# and add it to the list
mlist = lib.p_new_list(len(lst))
for i, val in enumerate(lst):
push_arg(val)
lib.p_add_value_from_pop_to_list(mlist, i)
lib.p_push_list(mlist)
def push_date(d):
lib.p_push_datestring(np.datetime_as_string(d).encode("utf-8"))
def push_datetime(d):
lib.p_push_datestring(d.isoformat().encode("utf-8"))
def push_datetime_date(d):
s = d.isoformat() + "T00:00:00"
lib.p_push_datestring(s.encode("utf-8"))
def push_vector(npa):
# if this is a view with a non-contiguous step, make a copy so that
# we get contiguous data
if not npa.flags["C_CONTIGUOUS"]:
npa = npa.copy()
# convert numpy array to CData
dtype = npa.dtype
if dtype == np.float64: # can directly pass the data buffer
cffi_buffer = ffi.cast("double*", npa.ctypes.data)
lib.p_push_vector_from_double_array(cffi_buffer, len(npa), np.nan)
elif dtype == np.float32: # can directly pass the data buffer
cffi_buffer = ffi.cast("float*", npa.ctypes.data)
lib.p_push_vector_from_float32_array(cffi_buffer, len(npa), np.nan)
elif dtype == np.bool: # convert first to float32
f32_array = npa.astype(np.float32)
cffi_buffer = ffi.cast("float*", f32_array.ctypes.data)
lib.p_push_vector_from_float32_array(cffi_buffer, len(f32_array), np.nan)
else:
raise TypeError(
"Only float32 and float64 numPy arrays can be passed to Metview, not ",
npa.dtype,
)
class File(Value):
def __init__(self, val_pointer):
Value.__init__(self, val_pointer)
class FileBackedValue(Value):
def __init__(self, val_pointer):
Value.__init__(self, val_pointer)
def url(self):
# ask Metview for the file relating to this data (Metview will write it if necessary)
return string_from_ffi(lib.p_data_path(self.val_pointer))
class FileBackedValueWithOperators(FileBackedValue):
def __init__(self, val_pointer):
FileBackedValue.__init__(self, val_pointer)
def __add__(self, other):
return add(self, other)
def __radd__(self, other):
return add(other, self)
def __sub__(self, other):
return sub(self, other)
def __rsub__(self, other):
return sub(other, self)
def __mul__(self, other):
return prod(self, other)
def __rmul__(other, self):
return prod(other, self)
def __truediv__(self, other):
return div(self, other)
def __rtruediv__(self, other):
return div(other, self)
def __pow__(self, other):
return power(self, other)
def __rpow__(self, other):
return power(other, self)
def __ge__(self, other):
return greater_equal_than(self, other)
def __gt__(self, other):
return greater_than(self, other)
def __le__(self, other):
return lower_equal_than(self, other)
def __lt__(self, other):
return lower_than(self, other)
def __eq__(self, other):
return equal(self, other)
def __ne__(self, other):
return met_not_eq(self, other)
def __pos__(self):
return self
def __neg__(self):
return 0.0 - self
def __abs__(self):
return self.abs()
class ContainerValueIterator:
def __init__(self, data):
self.index = 0
self.data = data
def __iter__(self):
return self
def __next__(self):
if self.index >= len(self.data):
self.index = 0
raise StopIteration
else:
self.index += 1
return self.data[self.index - 1]
# ContainerValue
# val_pointer - pointer to a C++ Value
# macro_index_base - 0 or 1 - what do Macro indexing functions expect?
# element_types - the type of elements that the container contains
# support_slicing - does the container suppoer slicing?
class ContainerValue(Value):
def __init__(self, val_pointer, macro_index_base, element_types, support_slicing):
Value.__init__(self, val_pointer)
self.macro_index_base = macro_index_base
self.element_types = element_types
self.support_slicing = support_slicing
def __len__(self):
if self.val_pointer is None:
return 0
else:
return int(count(self))
def __getitem__(self, index):
if isinstance(index, slice):
if self.support_slicing:
indices = index.indices(len(self))
fields = [self[i] for i in range(*indices)]
if len(fields) == 0:
return None
else:
f = fields[0]
for i in range(1, len(fields)):
f = merge(f, fields[i])
return f
else:
raise IndexError(
"This object does not support extended slicing: " + str(self)
)
else: # normal index
if isinstance(index, str): # can have a string as an index
return subset(self, index)
elif isinstance(index, np.ndarray): # can have an array as an index
return subset(self, index + self.macro_index_base)
else:
if index < 0: # negative index valid for range [-len..-1]
c = int(count(self))
if index >= -c:
index = c + index
else:
raise IndexError("Index " + str(index) + " invalid ", self)
return subset(
self, index + self.macro_index_base
) # numeric index: 0->1-based
def __setitem__(self, index, value):
if isinstance(value, self.element_types):
if isinstance(index, int):
index += self.macro_index_base
push_arg(index)
push_arg(value)
lib.p_set_subvalue_from_arg_stack(self.val_pointer)
else:
raise IndexError("Cannot assign ", value, " as element of ", self)
def __iter__(self):
return ContainerValueIterator(self)
class Fieldset(FileBackedValueWithOperators, ContainerValue):
def __init__(self, val_pointer=None, path=None):
FileBackedValueWithOperators.__init__(self, val_pointer)
ContainerValue.__init__(
self,
val_pointer=val_pointer,
macro_index_base=1,
element_types=Fieldset,
support_slicing=True,
)
if path is not None:
temp = read(path)
self.steal_val_pointer(temp)
def append(self, other):
temp = merge(self, other)
if self.val_pointer != None: # we will overwrite ourselves, so delete
lib.p_destroy_value(self.val_pointer)
self.steal_val_pointer(temp)
def to_dataset(self):
# soft dependency on cfgrib
try:
from cfgrib import xarray_store
except ImportError:
print(
"Package cfgrib/xarray_store not found. Try running 'pip install cfgrib'."
)
raise
dataset = xarray_store.open_dataset(self.url())
return dataset
def __getstate__(self):
# used for pickling
# we cannot (and do not want to) directly pickle the Value pointer
# so we remove it and put instead the path to the file
d = dict(self.__dict__)
del d["val_pointer"]
d["url_path"] = self.url()
self.pickled = True
return d
def __setstate__(self, state):
# used for un-pickling
# read the data from the pickled path
self.__dict__.update(state)
self.__init__(val_pointer=None, path=state["url_path"])
class Bufr(FileBackedValue):
def __init__(self, val_pointer):
FileBackedValue.__init__(self, val_pointer)
class Geopoints(FileBackedValueWithOperators, ContainerValue):
def __init__(self, val_pointer):
FileBackedValueWithOperators.__init__(self, val_pointer)
ContainerValue.__init__(
self,
val_pointer=val_pointer,
macro_index_base=0,
element_types=(np.ndarray, list),
support_slicing=False,
)
def to_dataframe(self):
try:
import pandas as pd
except ImportError:
print("Package pandas not found. Try running 'pip install pandas'.")
raise
# create a dictionary of columns (note that we do not include 'time'
# because it is incorporated into 'date')
cols = self.columns()
if "time" in cols:
cols.remove("time")
pddict = {}
for c in cols:
pddict[c] = self[c]
df = pd.DataFrame(pddict)
return df
class NetCDF(FileBackedValueWithOperators):
def __init__(self, val_pointer):
FileBackedValueWithOperators.__init__(self, val_pointer)
def to_dataset(self):
# soft dependency on xarray
try:
import xarray as xr
except ImportError:
print("Package xarray not found. Try running 'pip install xarray'.")
raise
dataset = xr.open_dataset(self.url())
return dataset
class Odb(FileBackedValue):
def __init__(self, val_pointer):
FileBackedValue.__init__(self, val_pointer)
def to_dataframe(self):
try:
import pandas as pd
except ImportError:
print("Package pandas not found. Try running 'pip install pandas'.")
raise
cols = self.columns()
pddict = {}
for col in cols:
pddict[col] = self.values(col)
df = pd.DataFrame(pddict)
return df
class Table(FileBackedValue):
def __init__(self, val_pointer):
FileBackedValue.__init__(self, val_pointer)
def to_dataframe(self):
try:
import pandas as pd
except ImportError:
print("Package pandas not found. Try running 'pip install pandas'.")
raise
df = pd.read_csv(self.url())
return df
class GeopointSet(FileBackedValueWithOperators, ContainerValue):
def __init__(self, val_pointer):
FileBackedValueWithOperators.__init__(self, val_pointer)
ContainerValue.__init__(self, val_pointer, 1, Geopoints, False)
# -----------------------------------------------------------------------------
# Pushing data types to Macro
# -----------------------------------------------------------------------------
def dataset_to_fieldset(val, **kwarg):
# we try to import xarray as locally as possible to reduce startup time
# try to write the xarray as a GRIB file, then read into a fieldset
import xarray as xr
import cfgrib
if not isinstance(val, xr.core.dataset.Dataset):
raise TypeError(
"dataset_to_fieldset requires a variable of type xr.core.dataset.Dataset;"
" was supplied with ",
builtins.type(val),
)
f, tmp = tempfile.mkstemp(".grib")
os.close(f)
try:
# could add keys, e.g. grib_keys={'centre': 'ecmf'})
cfgrib.to_grib(val, tmp, **kwarg)
except:
print(
"Error trying to write xarray dataset to GRIB for conversion to Metview Fieldset"
)
raise
# TODO: tell Metview that this is a temporary file that should be deleted when no longer needed
fs = read(tmp)
fs.set_temporary(1)
return fs
def push_xarray_dataset(val):
fs = dataset_to_fieldset(val)
fs.push()
# try_to_push_complex_type exists as a separate function so that we don't have
# to import xarray at the top of the module - this saves some time on startup
def try_to_push_complex_type(val):
import xarray as xr
if isinstance(val, xr.core.dataset.Dataset):
push_xarray_dataset(val)
else:
raise TypeError(
"Cannot push this type of argument to Metview: ", builtins.type(val)
)
class ValuePusher:
"""Class to handle pushing values to the Macro library"""
def __init__(self):
# a set of pairs linking value types with functions to push them to Macro
# note that Request must come before dict, because a Request inherits from dict;
# this ordering requirement also means we should use list or tuple instead of a dict
self.funcs = (
(float, lambda n: lib.p_push_number(n)),
((int, np.number), lambda n: lib.p_push_number(float(n))),
(str, lambda n: push_str(n)),
(Request, lambda n: n.push()),
(dict, lambda n: Request(n).push()),
((list, tuple), lambda n: push_list(n)),
(type(None), lambda n: lib.p_push_nil()),
(FileBackedValue, lambda n: n.push()),
(np.datetime64, lambda n: push_date(n)),
(datetime.datetime, lambda n: push_datetime(n)),
(datetime.date, lambda n: push_datetime_date(n)),
(np.ndarray, lambda n: push_vector(n)),
(File, lambda n: n.push()),
)
def push_value(self, val):
for typekey, typefunc in self.funcs:
if isinstance(val, typekey):
typefunc(val)
return 1
# if we haven't returned yet, then try the more complex types
try_to_push_complex_type(val)
return 1
vp = ValuePusher()
def push_arg(n):
return vp.push_value(n)
def dict_to_pushed_args(d):
# push each key and value onto the argument stack
for k, v in d.items():
push_str(k)
push_arg(v)
return 2 * len(d) # return the number of arguments generated
# -----------------------------------------------------------------------------
# Returning data types from Macro
# -----------------------------------------------------------------------------
def list_from_metview(val):
mlist = lib.p_value_as_list(val)
result = []
n = lib.p_list_count(mlist)
all_vectors = True
for i in range(0, n):
mval = lib.p_list_element_as_value(mlist, i)
v = value_from_metview(mval)
if all_vectors and not isinstance(v, np.ndarray):
all_vectors = False
result.append(v)
# if this is a list of vectors, then create a 2-D numPy array
if all_vectors and n > 0:
result = np.stack(result, axis=0)
# delete the Metview list - this will decrement the reference counts of its objects
lib.p_destroy_value(val)
return result
def datestring_from_metview(val):
mdate = string_from_ffi(lib.p_value_as_datestring(val))
dt = datetime.datetime.strptime(mdate, "%Y-%m-%dT%H:%M:%S")
return dt
def vector_from_metview(val):
vec = lib.p_value_as_vector(val, np.nan)
n = lib.p_vector_count(vec)
s = lib.p_vector_elem_size(vec)
if s == 4:
nptype = np.float32
b = lib.p_vector_float32_array(vec)
elif s == 8:
nptype = np.float64
b = lib.p_vector_double_array(vec)
else:
raise Exception("Metview vector data type cannot be handled: ", s)
bsize = n * s
c_buffer = ffi.buffer(b, bsize)
np_array = (
np.frombuffer(c_buffer, dtype=nptype)
).copy() # copy so that we can destroy
lib.p_destroy_value(val)
return np_array
def handle_error(val):
msg = string_from_ffi(lib.p_error_message(val))
if "Service" in msg and "Examiner" in msg:
return None
else:
return Exception("Metview error: " + (msg))
def string_from_metview(val):
return string_from_ffi(lib.p_value_as_string(val))
class MvRetVal(Enum):
tnumber = 0
tstring = 1
tgrib = 2
trequest = 3
tbufr = 4
tgeopts = 5
tlist = 6
tnetcdf = 7
tnil = 8
terror = 9
tdate = 10
tvector = 11
todb = 12
ttable = 13
tgptset = 14
tfile = 15
tunknown = 99
class ValueReturner:
"""Class to handle return values from the Macro library"""
def __init__(self):
self.funcs = {}
self.funcs[MvRetVal.tnumber.value] = lambda val: lib.p_value_as_number(val)
self.funcs[MvRetVal.tstring.value] = lambda val: string_from_metview(val)
self.funcs[MvRetVal.tgrib.value] = lambda val: Fieldset(val)
self.funcs[MvRetVal.trequest.value] = lambda val: Request(val)
self.funcs[MvRetVal.tbufr.value] = lambda val: Bufr(val)
self.funcs[MvRetVal.tgeopts.value] = lambda val: Geopoints(val)
self.funcs[MvRetVal.tlist.value] = lambda val: list_from_metview(val)
self.funcs[MvRetVal.tnetcdf.value] = lambda val: NetCDF(val)
self.funcs[MvRetVal.tnil.value] = lambda val: None
self.funcs[MvRetVal.terror.value] = lambda val: handle_error(val)
self.funcs[MvRetVal.tdate.value] = lambda val: datestring_from_metview(val)
self.funcs[MvRetVal.tvector.value] = lambda val: vector_from_metview(val)
self.funcs[MvRetVal.todb.value] = lambda val: Odb(val)
self.funcs[MvRetVal.ttable.value] = lambda val: Table(val)
self.funcs[MvRetVal.tgptset.value] = lambda val: GeopointSet(val)
self.funcs[MvRetVal.tfile.value] = lambda val: File(val)
def translate_return_val(self, val):
rt = lib.p_value_type(val)
try:
return self.funcs[rt](val)
except Exception:
raise Exception(
"value_from_metview got an unhandled return type: " + str(rt)
)
vr = ValueReturner()
def value_from_metview(val):
retval = vr.translate_return_val(val)
if isinstance(retval, Exception):
raise retval
return retval
# -----------------------------------------------------------------------------
# Creating and calling Macro functions
# -----------------------------------------------------------------------------
def _call_function(mfname, *args, **kwargs):
nargs = 0
for n in args:
actual_n_args = push_arg(n)
nargs += actual_n_args
merged_dict = {}
merged_dict.update(kwargs)
if len(merged_dict) > 0:
dn = dict_to_pushed_args(Request(merged_dict))
nargs += dn
lib.p_call_function(mfname.encode("utf-8"), nargs)
def make(mfname):
def wrapped(*args, **kwargs):
err = _call_function(mfname, *args, **kwargs)
if err:
pass # throw Exceception
val = lib.p_result_as_value()
return value_from_metview(val)
return wrapped
def bind_functions(namespace, module_name=None):
"""Add to the module globals all metview functions except operators like: +, &, etc."""
for metview_name in make("dictionary")():
if metview_name.isidentifier():
python_name = metview_name
# NOTE: we append a '_' to metview functions that clash with python reserved keywords
# as they cannot be used as identifiers, for example: 'in' -> 'in_'
if keyword.iskeyword(metview_name):
python_name += "_"
python_func = make(metview_name)
python_func.__name__ = python_name
python_func.__qualname__ = python_name
if module_name:
python_func.__module__ = module_name
namespace[python_name] = python_func
# else:
# print('metview function %r not bound to python' % metview_name)
# HACK: some fuctions are missing from the 'dictionary' call.
namespace["neg"] = make("neg")
namespace["nil"] = make("nil")
# override some functions that need special treatment
# FIXME: this needs to be more structured
namespace["plot"] = plot
namespace["setoutput"] = setoutput
namespace["dataset_to_fieldset"] = dataset_to_fieldset
namespace["Fieldset"] = Fieldset
namespace["Request"] = Request
# some explicit bindings are used here
add = make("+")
call = make("call")
count = make("count")
div = make("/")
equal = make("=")
filter = make("filter")
greater_equal_than = make(">=")
greater_than = make(">")
lower_equal_than = make("<=")
lower_than = make("<")
merge = make("&")
met_not_eq = make("<>")
met_plot = make("plot")
nil = make("nil")
png_output = make("png_output")
power = make("^")
prod = make("*")
ps_output = make("ps_output")
read = make("read")
met_setoutput = make("setoutput")
sub = make("-")
subset = make("[]")
# -----------------------------------------------------------------------------
# Particular code for calling the plot() command
# -----------------------------------------------------------------------------
class Plot:
def __init__(self):
self.plot_to_jupyter = False
def __call__(self, *args, **kwargs):
if self.plot_to_jupyter:
f, tmp = tempfile.mkstemp(".png")
os.close(f)
base, ext = os.path.splitext(tmp)
met_setoutput(
png_output(output_name=base, output_name_first_page_number="off")
)
met_plot(*args)
image = Image(tmp)
os.unlink(tmp)
return image
else:
map_outputs = {
"png": png_output,
"ps": ps_output,
}
if "output_type" in kwargs:
output_function = map_outputs[kwargs["output_type"].lower()]
kwargs.pop("output_type")
met_plot(output_function(kwargs), *args)
else:
met_plot(*args)
# the Macro plot command returns an empty definition, but
# None is better for Python
return None
plot = Plot()
# On a test system, importing IPython took approx 0.5 seconds, so to avoid that hit
# under most circumstances, we only import it when the user asks for Jupyter
# functionality. Since this occurs within a function, we need a little trickery to
# get the IPython functions into the global namespace so that the plot object can use them
def setoutput(*args):
if "jupyter" in args:
try:
global Image
global get_ipython
IPython = __import__("IPython", globals(), locals())
Image = IPython.display.Image
get_ipython = IPython.get_ipython
except ImportError as imperr:
print("Could not import IPython module - plotting to Jupyter will not work")
raise imperr
# test whether we're in the Jupyter environment
if get_ipython() is not None:
plot.plot_to_jupyter = True
else:
print(
"ERROR: setoutput('jupyter') was set, but we are not in a Jupyter environment"
)
raise (Exception("Could not set output to jupyter"))
else:
plot.plot_to_jupyter = False
met_setoutput(*args)
