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def data_import(self, json_response):
"""Import data from json response."""
if 'data' not in json_response:
raise PyVLXException('no element data found: {0}'.format(
json.dumps(json_response)))
data = json_response['data']
for item in data:
if 'category' not in item:
raise PyVLXException('no element category: {0}'.format(
json.dumps(item)))
category = item['category']
if category == 'Window opener':
self.load_window_opener(item)
elif category in ['Roller shutter', 'Dual Shutter']:
self.load_roller_shutter(item)
elif category in ['Blind']:
self.load_blind(item)
else:
self.pyvlx.logger.warning(
'WARNING: Could not parse product: %s', category)
|
Import data from json response.
|
entailment
|
def load_window_opener(self, item):
"""Load window opener from JSON."""
window = Window.from_config(self.pyvlx, item)
self.add(window)
|
Load window opener from JSON.
|
entailment
|
def load_roller_shutter(self, item):
"""Load roller shutter from JSON."""
rollershutter = RollerShutter.from_config(self.pyvlx, item)
self.add(rollershutter)
|
Load roller shutter from JSON.
|
entailment
|
def load_blind(self, item):
"""Load blind from JSON."""
blind = Blind.from_config(self.pyvlx, item)
self.add(blind)
|
Load blind from JSON.
|
entailment
|
def get_terminal_size(fallback=(80, 24)):
"""
Return tuple containing columns and rows of controlling terminal, trying harder
than shutil.get_terminal_size to find a tty before returning fallback.
Theoretically, stdout, stderr, and stdin could all be different ttys that could
cause us to get the wrong measurements (instead of using the fallback) but the much more
common case is that IO is piped.
"""
for stream in [sys.__stdout__, sys.__stderr__, sys.__stdin__]:
try:
# Make WINSIZE call to terminal
data = fcntl.ioctl(stream.fileno(), TIOCGWINSZ, b"\x00\x00\00\x00")
except OSError:
pass
else:
# Unpack two shorts from ioctl call
lines, columns = struct.unpack("hh", data)
break
else:
columns, lines = fallback
return columns, lines
|
Return tuple containing columns and rows of controlling terminal, trying harder
than shutil.get_terminal_size to find a tty before returning fallback.
Theoretically, stdout, stderr, and stdin could all be different ttys that could
cause us to get the wrong measurements (instead of using the fallback) but the much more
common case is that IO is piped.
|
entailment
|
def run_diff(self):
"""
Run checks on self.files, printing diff of styled/unstyled output to stdout.
"""
files = tuple(self.files)
# Use same header as more.
header, footer = (termcolor.colored("{0}\n{{}}\n{0}\n".format(
":" * 14), "cyan"), "\n") if len(files) > 1 else ("", "")
for file in files:
print(header.format(file), end="")
try:
results = self._check(file)
except Error as e:
termcolor.cprint(e.msg, "yellow", file=sys.stderr)
continue
# Display results
if results.diffs:
print()
print(*self.diff(results.original, results.styled), sep="\n")
print()
conjunction = "And"
else:
termcolor.cprint("Looks good!", "green")
conjunction = "But"
if results.diffs:
for type, c in sorted(self._warn_chars):
color, verb = ("on_green", "insert") if type == "+" else ("on_red", "delete")
termcolor.cprint(c, None, color, end="")
termcolor.cprint(" means that you should {} a {}.".format(
verb, "newline" if c == "\\n" else "tab"), "yellow")
if results.comment_ratio < results.COMMENT_MIN:
termcolor.cprint("{} consider adding more comments!".format(conjunction), "yellow")
if (results.comment_ratio < results.COMMENT_MIN or self._warn_chars) and results.diffs:
print()
|
Run checks on self.files, printing diff of styled/unstyled output to stdout.
|
entailment
|
def run_json(self):
"""
Run checks on self.files, printing json object
containing information relavent to the CS50 IDE plugin at the end.
"""
checks = {}
for file in self.files:
try:
results = self._check(file)
except Error as e:
checks[file] = {
"error": e.msg
}
else:
checks[file] = {
"score": results.score,
"comments": results.comment_ratio >= results.COMMENT_MIN,
"diff": "<pre>{}</pre>".format("\n".join(self.html_diff(results.original, results.styled))),
}
json.dump(checks, sys.stdout, indent=4)
print()
|
Run checks on self.files, printing json object
containing information relavent to the CS50 IDE plugin at the end.
|
entailment
|
def run_score(self):
"""
Run checks on self.files, printing raw percentage to stdout.
"""
diffs = 0
lines = 0
for file in self.files:
try:
results = self._check(file)
except Error as e:
termcolor.cprint(e.msg, "yellow", file=sys.stderr)
continue
diffs += results.diffs
lines += results.lines
try:
print(max(1 - diffs / lines, 0.0))
except ZeroDivisionError:
print(0.0)
|
Run checks on self.files, printing raw percentage to stdout.
|
entailment
|
def _check(self, file):
"""
Run apropriate check based on `file`'s extension and return it,
otherwise raise an Error
"""
if not os.path.exists(file):
raise Error("file \"{}\" not found".format(file))
_, extension = os.path.splitext(file)
try:
check = self.extension_map[extension[1:]]
except KeyError:
magic_type = magic.from_file(file)
for name, cls in self.magic_map.items():
if name in magic_type:
check = cls
break
else:
raise Error("unknown file type \"{}\", skipping...".format(file))
try:
with open(file) as f:
code = "\n".join(line.rstrip() for line in f)
except UnicodeDecodeError:
raise Error("file does not seem to contain text, skipping...")
# Ensure we don't warn about adding trailing newline
try:
if code[-1] != '\n':
code += '\n'
except IndexError:
pass
return check(code)
|
Run apropriate check based on `file`'s extension and return it,
otherwise raise an Error
|
entailment
|
def split_diff(old, new):
"""
Returns a generator yielding the side-by-side diff of `old` and `new`).
"""
return map(lambda l: l.rstrip(),
icdiff.ConsoleDiff(cols=COLUMNS).make_table(old.splitlines(), new.splitlines()))
|
Returns a generator yielding the side-by-side diff of `old` and `new`).
|
entailment
|
def unified(old, new):
"""
Returns a generator yielding a unified diff between `old` and `new`.
"""
for diff in difflib.ndiff(old.splitlines(), new.splitlines()):
if diff[0] == " ":
yield diff
elif diff[0] == "?":
continue
else:
yield termcolor.colored(diff, "red" if diff[0] == "-" else "green", attrs=["bold"])
|
Returns a generator yielding a unified diff between `old` and `new`.
|
entailment
|
def html_diff(self, old, new):
"""
Return HTML formatted character-based diff between old and new (used for CS50 IDE).
"""
def html_transition(old_type, new_type):
tags = []
for tag in [("/", old_type), ("", new_type)]:
if tag[1] not in ["+", "-"]:
continue
tags.append("<{}{}>".format(tag[0], "ins" if tag[1] == "+" else "del"))
return "".join(tags)
return self._char_diff(old, new, html_transition, fmt=cgi.escape)
|
Return HTML formatted character-based diff between old and new (used for CS50 IDE).
|
entailment
|
def char_diff(self, old, new):
"""
Return color-coded character-based diff between `old` and `new`.
"""
def color_transition(old_type, new_type):
new_color = termcolor.colored("", None, "on_red" if new_type ==
"-" else "on_green" if new_type == "+" else None)
return "{}{}".format(termcolor.RESET, new_color[:-len(termcolor.RESET)])
return self._char_diff(old, new, color_transition)
|
Return color-coded character-based diff between `old` and `new`.
|
entailment
|
def _char_diff(self, old, new, transition, fmt=lambda c: c):
"""
Returns a char-based diff between `old` and `new` where each character
is formatted by `fmt` and transitions between blocks are determined by `transition`.
"""
differ = difflib.ndiff(old, new)
# Type of difference.
dtype = None
# Buffer for current line.
line = []
while True:
# Get next diff or None if we're at the end.
d = next(differ, (None,))
if d[0] != dtype:
line += transition(dtype, d[0])
dtype = d[0]
if dtype is None:
break
if d[2] == "\n":
if dtype != " ":
self._warn_chars.add((dtype, "\\n"))
# Show added/removed newlines.
line += [fmt(r"\n"), transition(dtype, " ")]
# Don't yield a line if we are removing a newline
if dtype != "-":
yield "".join(line)
line.clear()
line.append(transition(" ", dtype))
elif dtype != " " and d[2] == "\t":
# Show added/removed tabs.
line.append(fmt("\\t"))
self._warn_chars.add((dtype, "\\t"))
else:
line.append(fmt(d[2]))
# Flush buffer before quitting.
last = "".join(line)
# Only print last line if it contains non-ANSI characters.
if re.sub(r"\x1b[^m]*m", "", last):
yield last
|
Returns a char-based diff between `old` and `new` where each character
is formatted by `fmt` and transitions between blocks are determined by `transition`.
|
entailment
|
def count_lines(self, code):
"""
Count lines of code (by default ignores empty lines, but child could override to do more).
"""
return sum(bool(line.strip()) for line in code.splitlines())
|
Count lines of code (by default ignores empty lines, but child could override to do more).
|
entailment
|
def run(command, input=None, exit=0, shell=False):
"""
Run `command` passing it stdin from `input`, throwing a DependencyError if comand is not found.
Throws Error if exit code of command is not `exit` (unless `exit` is None).
"""
if isinstance(input, str):
input = input.encode()
# Only pipe stdin if we have input to pipe.
stdin = {} if input is None else {"stdin": subprocess.PIPE}
try:
child = subprocess.Popen(command, stdout=subprocess.PIPE,
stderr=subprocess.PIPE, **stdin)
except FileNotFoundError as e:
# Extract name of command.
name = command.split(' ', 1)[0] if isinstance(command, str) else command[0]
raise DependencyError(name)
stdout, _ = child.communicate(input=input)
if exit is not None and child.returncode != exit:
raise Error("failed to stylecheck code")
return stdout.decode()
|
Run `command` passing it stdin from `input`, throwing a DependencyError if comand is not found.
Throws Error if exit code of command is not `exit` (unless `exit` is None).
|
entailment
|
def frame_from_raw(raw):
"""Create and return frame from raw bytes."""
command, payload = extract_from_frame(raw)
frame = create_frame(command)
if frame is None:
PYVLXLOG.warning("Command %s not implemented, raw: %s", command, ":".join("{:02x}".format(c) for c in raw))
return None
frame.validate_payload_len(payload)
frame.from_payload(payload)
return frame
|
Create and return frame from raw bytes.
|
entailment
|
def create_frame(command):
"""Create and return empty Frame from Command."""
# pylint: disable=too-many-branches,too-many-return-statements
if command == Command.GW_ERROR_NTF:
return FrameErrorNotification()
if command == Command.GW_COMMAND_SEND_REQ:
return FrameCommandSendRequest()
if command == Command.GW_COMMAND_SEND_CFM:
return FrameCommandSendConfirmation()
if command == Command.GW_COMMAND_RUN_STATUS_NTF:
return FrameCommandRunStatusNotification()
if command == Command.GW_COMMAND_REMAINING_TIME_NTF:
return FrameCommandRemainingTimeNotification()
if command == Command.GW_SESSION_FINISHED_NTF:
return FrameSessionFinishedNotification()
if command == Command.GW_PASSWORD_ENTER_REQ:
return FramePasswordEnterRequest()
if command == Command.GW_PASSWORD_ENTER_CFM:
return FramePasswordEnterConfirmation()
if command == Command.GW_CS_DISCOVER_NODES_REQ:
return FrameDiscoverNodesRequest()
if command == Command.GW_CS_DISCOVER_NODES_CFM:
return FrameDiscoverNodesConfirmation()
if command == Command.GW_CS_DISCOVER_NODES_NTF:
return FrameDiscoverNodesNotification()
if command == Command.GW_GET_SCENE_LIST_REQ:
return FrameGetSceneListRequest()
if command == Command.GW_GET_SCENE_LIST_CFM:
return FrameGetSceneListConfirmation()
if command == Command.GW_GET_SCENE_LIST_NTF:
return FrameGetSceneListNotification()
if command == Command.GW_GET_NODE_INFORMATION_REQ:
return FrameGetNodeInformationRequest()
if command == Command.GW_GET_NODE_INFORMATION_CFM:
return FrameGetNodeInformationConfirmation()
if command == Command.GW_GET_NODE_INFORMATION_NTF:
return FrameGetNodeInformationNotification()
if command == Command.GW_GET_ALL_NODES_INFORMATION_REQ:
return FrameGetAllNodesInformationRequest()
if command == Command.GW_GET_ALL_NODES_INFORMATION_CFM:
return FrameGetAllNodesInformationConfirmation()
if command == Command.GW_GET_ALL_NODES_INFORMATION_NTF:
return FrameGetAllNodesInformationNotification()
if command == Command.GW_GET_ALL_NODES_INFORMATION_FINISHED_NTF:
return FrameGetAllNodesInformationFinishedNotification()
if command == Command.GW_ACTIVATE_SCENE_REQ:
return FrameActivateSceneRequest()
if command == Command.GW_ACTIVATE_SCENE_CFM:
return FrameActivateSceneConfirmation()
if command == Command.GW_GET_VERSION_REQ:
return FrameGetVersionRequest()
if command == Command.GW_GET_VERSION_CFM:
return FrameGetVersionConfirmation()
if command == Command.GW_GET_PROTOCOL_VERSION_REQ:
return FrameGetProtocolVersionRequest()
if command == Command.GW_GET_PROTOCOL_VERSION_CFM:
return FrameGetProtocolVersionConfirmation()
if command == Command.GW_SET_NODE_NAME_REQ:
return FrameSetNodeNameRequest()
if command == Command.GW_SET_NODE_NAME_CFM:
return FrameSetNodeNameConfirmation()
if command == Command.GW_NODE_INFORMATION_CHANGED_NTF:
return FrameNodeInformationChangedNotification()
if command == Command.GW_GET_STATE_REQ:
return FrameGetStateRequest()
if command == Command.GW_GET_STATE_CFM:
return FrameGetStateConfirmation()
if command == Command.GW_SET_UTC_REQ:
return FrameSetUTCRequest()
if command == Command.GW_SET_UTC_CFM:
return FrameSetUTCConfirmation()
if command == Command.GW_ACTIVATION_LOG_UPDATED_NTF:
return FrameActivationLogUpdatedNotification()
if command == Command.GW_HOUSE_STATUS_MONITOR_ENABLE_REQ:
return FrameHouseStatusMonitorEnableRequest()
if command == Command.GW_HOUSE_STATUS_MONITOR_ENABLE_CFM:
return FrameHouseStatusMonitorEnableConfirmation()
if command == Command.GW_HOUSE_STATUS_MONITOR_DISABLE_REQ:
return FrameHouseStatusMonitorDisableRequest()
if command == Command.GW_HOUSE_STATUS_MONITOR_DISABLE_CFM:
return FrameHouseStatusMonitorDisableConfirmation()
if command == Command.GW_NODE_STATE_POSITION_CHANGED_NTF:
return FrameNodeStatePositionChangedNotification()
return None
|
Create and return empty Frame from Command.
|
entailment
|
async def handle_frame(self, frame):
"""Handle incoming API frame, return True if this was the expected frame."""
if not isinstance(frame, FramePasswordEnterConfirmation):
return False
if frame.status == PasswordEnterConfirmationStatus.FAILED:
PYVLXLOG.warning('Failed to authenticate with password "%s****"', self.password[:2])
self.success = False
if frame.status == PasswordEnterConfirmationStatus.SUCCESSFUL:
self.success = True
return True
|
Handle incoming API frame, return True if this was the expected frame.
|
entailment
|
def get_payload(self):
"""Return Payload."""
return bytes(
[self.major_version >> 8 & 255, self.major_version & 255,
self.minor_version >> 8 & 255, self.minor_version & 255])
|
Return Payload.
|
entailment
|
def from_payload(self, payload):
"""Init frame from binary data."""
self.major_version = payload[0] * 256 + payload[1]
self.minor_version = payload[2] * 256 + payload[3]
|
Init frame from binary data.
|
entailment
|
def data_received(self, data):
"""Handle data received."""
self.tokenizer.feed(data)
while self.tokenizer.has_tokens():
raw = self.tokenizer.get_next_token()
frame = frame_from_raw(raw)
if frame is not None:
self.frame_received_cb(frame)
|
Handle data received.
|
entailment
|
async def connect(self):
"""Connect to gateway via SSL."""
tcp_client = TCPTransport(self.frame_received_cb, self.connection_closed_cb)
self.transport, _ = await self.loop.create_connection(
lambda: tcp_client,
host=self.config.host,
port=self.config.port,
ssl=self.create_ssl_context())
self.connected = True
|
Connect to gateway via SSL.
|
entailment
|
def write(self, frame):
"""Write frame to Bus."""
if not isinstance(frame, FrameBase):
raise PyVLXException("Frame not of type FrameBase", frame_type=type(frame))
PYVLXLOG.debug("SEND: %s", frame)
self.transport.write(slip_pack(bytes(frame)))
|
Write frame to Bus.
|
entailment
|
def create_ssl_context():
"""Create and return SSL Context."""
ssl_context = ssl.create_default_context(ssl.Purpose.SERVER_AUTH)
ssl_context.check_hostname = False
ssl_context.verify_mode = ssl.CERT_NONE
return ssl_context
|
Create and return SSL Context.
|
entailment
|
def frame_received_cb(self, frame):
"""Received message."""
PYVLXLOG.debug("REC: %s", frame)
for frame_received_cb in self.frame_received_cbs:
# pylint: disable=not-callable
self.loop.create_task(frame_received_cb(frame))
|
Received message.
|
entailment
|
def read_config(self, path):
"""Read configuration file."""
self.pyvlx.logger.info('Reading config file: ', path)
try:
with open(path, 'r') as filehandle:
doc = yaml.load(filehandle)
if 'config' not in doc:
raise PyVLXException('no element config found in: {0}'.format(path))
if 'host' not in doc['config']:
raise PyVLXException('no element host found in: {0}'.format(path))
if 'password' not in doc['config']:
raise PyVLXException('no element password found in: {0}'.format(path))
self.host = doc['config']['host']
self.password = doc['config']['password']
except FileNotFoundError as ex:
raise PyVLXException('file does not exist: {0}'.format(ex))
|
Read configuration file.
|
entailment
|
async def process_frame(self, frame):
"""Update nodes via frame, usually received by house monitor."""
if isinstance(frame, FrameNodeStatePositionChangedNotification):
if frame.node_id not in self.pyvlx.nodes:
return
node = self.pyvlx.nodes[frame.node_id]
if isinstance(node, OpeningDevice):
node.position = Position(frame.current_position)
await node.after_update()
elif isinstance(frame, FrameGetAllNodesInformationNotification):
if frame.node_id not in self.pyvlx.nodes:
return
node = self.pyvlx.nodes[frame.node_id]
if isinstance(node, OpeningDevice):
node.position = Position(frame.current_position)
await node.after_update()
|
Update nodes via frame, usually received by house monitor.
|
entailment
|
def add(self, scene):
"""Add scene, replace existing scene if scene with scene_id is present."""
if not isinstance(scene, Scene):
raise TypeError()
for i, j in enumerate(self.__scenes):
if j.scene_id == scene.scene_id:
self.__scenes[i] = scene
return
self.__scenes.append(scene)
|
Add scene, replace existing scene if scene with scene_id is present.
|
entailment
|
async def load(self):
"""Load scenes from KLF 200."""
get_scene_list = GetSceneList(pyvlx=self.pyvlx)
await get_scene_list.do_api_call()
if not get_scene_list.success:
raise PyVLXException("Unable to retrieve scene information")
for scene in get_scene_list.scenes:
self.add(Scene(pyvlx=self.pyvlx, scene_id=scene[0], name=scene[1]))
|
Load scenes from KLF 200.
|
entailment
|
def best_prefix(bytes, system=NIST):
"""Return a bitmath instance representing the best human-readable
representation of the number of bytes given by ``bytes``. In addition
to a numeric type, the ``bytes`` parameter may also be a bitmath type.
Optionally select a preferred unit system by specifying the ``system``
keyword. Choices for ``system`` are ``bitmath.NIST`` (default) and
``bitmath.SI``.
Basically a shortcut for:
>>> import bitmath
>>> b = bitmath.Byte(12345)
>>> best = b.best_prefix()
Or:
>>> import bitmath
>>> best = (bitmath.KiB(12345) * 4201).best_prefix()
"""
if isinstance(bytes, Bitmath):
value = bytes.bytes
else:
value = bytes
return Byte(value).best_prefix(system=system)
|
Return a bitmath instance representing the best human-readable
representation of the number of bytes given by ``bytes``. In addition
to a numeric type, the ``bytes`` parameter may also be a bitmath type.
Optionally select a preferred unit system by specifying the ``system``
keyword. Choices for ``system`` are ``bitmath.NIST`` (default) and
``bitmath.SI``.
Basically a shortcut for:
>>> import bitmath
>>> b = bitmath.Byte(12345)
>>> best = b.best_prefix()
Or:
>>> import bitmath
>>> best = (bitmath.KiB(12345) * 4201).best_prefix()
|
entailment
|
def query_device_capacity(device_fd):
"""Create bitmath instances of the capacity of a system block device
Make one or more ioctl request to query the capacity of a block
device. Perform any processing required to compute the final capacity
value. Return the device capacity in bytes as a :class:`bitmath.Byte`
instance.
Thanks to the following resources for help figuring this out Linux/Mac
ioctl's for querying block device sizes:
* http://stackoverflow.com/a/12925285/263969
* http://stackoverflow.com/a/9764508/263969
:param file device_fd: A ``file`` object of the device to query the
capacity of (as in ``get_device_capacity(open("/dev/sda"))``).
:return: a bitmath :class:`bitmath.Byte` instance equivalent to the
capacity of the target device in bytes.
"""
if os_name() != 'posix':
raise NotImplementedError("'bitmath.query_device_capacity' is not supported on this platform: %s" % os_name())
s = os.stat(device_fd.name).st_mode
if not stat.S_ISBLK(s):
raise ValueError("The file descriptor provided is not of a device type")
# The keys of the ``ioctl_map`` dictionary correlate to possible
# values from the ``platform.system`` function.
ioctl_map = {
# ioctls for the "Linux" platform
"Linux": {
"request_params": [
# A list of parameters to calculate the block size.
#
# ( PARAM_NAME , FORMAT_CHAR , REQUEST_CODE )
("BLKGETSIZE64", "L", 0x80081272)
# Per <linux/fs.h>, the BLKGETSIZE64 request returns a
# 'u64' sized value. This is an unsigned 64 bit
# integer C type. This means to correctly "buffer" the
# result we need 64 bits, or 8 bytes, of memory.
#
# The struct module documentation include a reference
# chart relating formatting characters to native C
# Types. In this case, using the "native size", the
# table tells us:
#
# * Character 'L' - Unsigned Long C Type (u64) - Loads into a Python int type
#
# Confirm this character is right by running (on Linux):
#
# >>> import struct
# >>> print 8 == struct.calcsize('L')
#
# The result should be true as long as your kernel
# headers define BLKGETSIZE64 as a u64 type (please
# file a bug report at
# https://github.com/tbielawa/bitmath/issues/new if
# this does *not* work for you)
],
# func is how the final result is decided. Because the
# Linux BLKGETSIZE64 call returns the block device
# capacity in bytes as an integer value, no extra
# calculations are required. Simply return the value of
# BLKGETSIZE64.
"func": lambda x: x["BLKGETSIZE64"]
},
# ioctls for the "Darwin" (Mac OS X) platform
"Darwin": {
"request_params": [
# A list of parameters to calculate the block size.
#
# ( PARAM_NAME , FORMAT_CHAR , REQUEST_CODE )
("DKIOCGETBLOCKCOUNT", "L", 0x40086419),
# Per <sys/disk.h>: get media's block count - uint64_t
#
# As in the BLKGETSIZE64 example, an unsigned 64 bit
# integer will use the 'L' formatting character
("DKIOCGETBLOCKSIZE", "I", 0x40046418)
# Per <sys/disk.h>: get media's block size - uint32_t
#
# This request returns an unsigned 32 bit integer, or
# in other words: just a normal integer (or 'int' c
# type). That should require 4 bytes of space for
# buffering. According to the struct modules
# 'Formatting Characters' chart:
#
# * Character 'I' - Unsigned Int C Type (uint32_t) - Loads into a Python int type
],
# OS X doesn't have a direct equivalent to the Linux
# BLKGETSIZE64 request. Instead, we must request how many
# blocks (or "sectors") are on the disk, and the size (in
# bytes) of each block. Finally, multiply the two together
# to obtain capacity:
#
# n Block * y Byte
# capacity (bytes) = -------
# 1 Block
"func": lambda x: x["DKIOCGETBLOCKCOUNT"] * x["DKIOCGETBLOCKSIZE"]
# This expression simply accepts a dictionary ``x`` as a
# parameter, and then returns the result of multiplying
# the two named dictionary items together. In this case,
# that means multiplying ``DKIOCGETBLOCKCOUNT``, the total
# number of blocks, by ``DKIOCGETBLOCKSIZE``, the size of
# each block in bytes.
}
}
platform_params = ioctl_map[platform.system()]
results = {}
for req_name, fmt, request_code in platform_params['request_params']:
# Read the systems native size (in bytes) of this format type.
buffer_size = struct.calcsize(fmt)
# Construct a buffer to store the ioctl result in
buffer = ' ' * buffer_size
# This code has been ran on only a few test systems. If it's
# appropriate, maybe in the future we'll add try/except
# conditions for some possible errors. Really only for cases
# where it would add value to override the default exception
# message string.
buffer = fcntl.ioctl(device_fd.fileno(), request_code, buffer)
# Unpack the raw result from the ioctl call into a familiar
# python data type according to the ``fmt`` rules.
result = struct.unpack(fmt, buffer)[0]
# Add the new result to our collection
results[req_name] = result
return Byte(platform_params['func'](results))
|
Create bitmath instances of the capacity of a system block device
Make one or more ioctl request to query the capacity of a block
device. Perform any processing required to compute the final capacity
value. Return the device capacity in bytes as a :class:`bitmath.Byte`
instance.
Thanks to the following resources for help figuring this out Linux/Mac
ioctl's for querying block device sizes:
* http://stackoverflow.com/a/12925285/263969
* http://stackoverflow.com/a/9764508/263969
:param file device_fd: A ``file`` object of the device to query the
capacity of (as in ``get_device_capacity(open("/dev/sda"))``).
:return: a bitmath :class:`bitmath.Byte` instance equivalent to the
capacity of the target device in bytes.
|
entailment
|
def getsize(path, bestprefix=True, system=NIST):
"""Return a bitmath instance in the best human-readable representation
of the file size at `path`. Optionally, provide a preferred unit
system by setting `system` to either `bitmath.NIST` (default) or
`bitmath.SI`.
Optionally, set ``bestprefix`` to ``False`` to get ``bitmath.Byte``
instances back.
"""
_path = os.path.realpath(path)
size_bytes = os.path.getsize(_path)
if bestprefix:
return Byte(size_bytes).best_prefix(system=system)
else:
return Byte(size_bytes)
|
Return a bitmath instance in the best human-readable representation
of the file size at `path`. Optionally, provide a preferred unit
system by setting `system` to either `bitmath.NIST` (default) or
`bitmath.SI`.
Optionally, set ``bestprefix`` to ``False`` to get ``bitmath.Byte``
instances back.
|
entailment
|
def listdir(search_base, followlinks=False, filter='*',
relpath=False, bestprefix=False, system=NIST):
"""This is a generator which recurses the directory tree
`search_base`, yielding 2-tuples of:
* The absolute/relative path to a discovered file
* A bitmath instance representing the "apparent size" of the file.
- `search_base` - The directory to begin walking down.
- `followlinks` - Whether or not to follow symbolic links to directories
- `filter` - A glob (see :py:mod:`fnmatch`) to filter results with
(default: ``*``, everything)
- `relpath` - ``True`` to return the relative path from `pwd` or
``False`` (default) to return the fully qualified path
- ``bestprefix`` - set to ``False`` to get ``bitmath.Byte``
instances back instead.
- `system` - Provide a preferred unit system by setting `system`
to either ``bitmath.NIST`` (default) or ``bitmath.SI``.
.. note:: This function does NOT return tuples for directory entities.
.. note:: Symlinks to **files** are followed automatically
"""
for root, dirs, files in os.walk(search_base, followlinks=followlinks):
for name in fnmatch.filter(files, filter):
_path = os.path.join(root, name)
if relpath:
# RELATIVE path
_return_path = os.path.relpath(_path, '.')
else:
# REAL path
_return_path = os.path.realpath(_path)
if followlinks:
yield (_return_path, getsize(_path, bestprefix=bestprefix, system=system))
else:
if os.path.isdir(_path) or os.path.islink(_path):
pass
else:
yield (_return_path, getsize(_path, bestprefix=bestprefix, system=system))
|
This is a generator which recurses the directory tree
`search_base`, yielding 2-tuples of:
* The absolute/relative path to a discovered file
* A bitmath instance representing the "apparent size" of the file.
- `search_base` - The directory to begin walking down.
- `followlinks` - Whether or not to follow symbolic links to directories
- `filter` - A glob (see :py:mod:`fnmatch`) to filter results with
(default: ``*``, everything)
- `relpath` - ``True`` to return the relative path from `pwd` or
``False`` (default) to return the fully qualified path
- ``bestprefix`` - set to ``False`` to get ``bitmath.Byte``
instances back instead.
- `system` - Provide a preferred unit system by setting `system`
to either ``bitmath.NIST`` (default) or ``bitmath.SI``.
.. note:: This function does NOT return tuples for directory entities.
.. note:: Symlinks to **files** are followed automatically
|
entailment
|
def parse_string(s):
"""Parse a string with units and try to make a bitmath object out of
it.
String inputs may include whitespace characters between the value and
the unit.
"""
# Strings only please
if not isinstance(s, (str, unicode)):
raise ValueError("parse_string only accepts string inputs but a %s was given" %
type(s))
# get the index of the first alphabetic character
try:
index = list([i.isalpha() for i in s]).index(True)
except ValueError:
# If there's no alphabetic characters we won't be able to .index(True)
raise ValueError("No unit detected, can not parse string '%s' into a bitmath object" % s)
# split the string into the value and the unit
val, unit = s[:index], s[index:]
# see if the unit exists as a type in our namespace
if unit == "b":
unit_class = Bit
elif unit == "B":
unit_class = Byte
else:
if not (hasattr(sys.modules[__name__], unit) and isinstance(getattr(sys.modules[__name__], unit), type)):
raise ValueError("The unit %s is not a valid bitmath unit" % unit)
unit_class = globals()[unit]
try:
val = float(val)
except ValueError:
raise
try:
return unit_class(val)
except: # pragma: no cover
raise ValueError("Can't parse string %s into a bitmath object" % s)
|
Parse a string with units and try to make a bitmath object out of
it.
String inputs may include whitespace characters between the value and
the unit.
|
entailment
|
def parse_string_unsafe(s, system=SI):
"""Attempt to parse a string with ambiguous units and try to make a
bitmath object out of it.
This may produce inaccurate results if parsing shell output. For
example `ls` may say a 2730 Byte file is '2.7K'. 2730 Bytes == 2.73 kB
~= 2.666 KiB. See the documentation for all of the important details.
Note the following caveats:
* All inputs are assumed to be byte-based (as opposed to bit based)
* Numerical inputs (those without any units) are assumed to be a
number of bytes
* Inputs with single letter units (k, M, G, etc) are assumed to be SI
units (base-10). Set the `system` parameter to `bitmath.NIST` to
change this behavior.
* Inputs with an `i` character following the leading letter (Ki, Mi,
Gi) are assumed to be NIST units (base 2)
* Capitalization does not matter
"""
if not isinstance(s, (str, unicode)) and \
not isinstance(s, numbers.Number):
raise ValueError("parse_string_unsafe only accepts string/number inputs but a %s was given" %
type(s))
######################################################################
# Is the input simple to parse? Just a number, or a number
# masquerading as a string perhaps?
# Test case: raw number input (easy!)
if isinstance(s, numbers.Number):
# It's just a number. Assume bytes
return Byte(s)
# Test case: a number pretending to be a string
if isinstance(s, (str, unicode)):
try:
# Can we turn it directly into a number?
return Byte(float(s))
except ValueError:
# Nope, this is not a plain number
pass
######################################################################
# At this point:
# - the input is also not just a number wrapped in a string
# - nor is is just a plain number type
#
# We need to do some more digging around now to figure out exactly
# what we were given and possibly normalize the input into a
# format we can recognize.
# First we'll separate the number and the unit.
#
# Get the index of the first alphabetic character
try:
index = list([i.isalpha() for i in s]).index(True)
except ValueError: # pragma: no cover
# If there's no alphabetic characters we won't be able to .index(True)
raise ValueError("No unit detected, can not parse string '%s' into a bitmath object" % s)
# Split the string into the value and the unit
val, unit = s[:index], s[index:]
# Don't trust anything. We'll make sure the correct 'b' is in place.
unit = unit.rstrip('Bb')
unit += 'B'
# At this point we can expect `unit` to be either:
#
# - 2 Characters (for SI, ex: kB or GB)
# - 3 Caracters (so NIST, ex: KiB, or GiB)
#
# A unit with any other number of chars is not a valid unit
# SI
if len(unit) == 2:
# Has NIST parsing been requested?
if system == NIST:
# NIST units requested. Ensure the unit begins with a
# capital letter and is followed by an 'i' character.
unit = capitalize_first(unit)
# Insert an 'i' char after the first letter
_unit = list(unit)
_unit.insert(1, 'i')
# Collapse the list back into a 3 letter string
unit = ''.join(_unit)
unit_class = globals()[unit]
else:
# Default parsing (SI format)
#
# Edge-case checking: SI 'thousand' is a lower-case K
if unit.startswith('K'):
unit = unit.replace('K', 'k')
elif not unit.startswith('k'):
# Otherwise, ensure the first char is capitalized
unit = capitalize_first(unit)
# This is an SI-type unit
if unit[0] in SI_PREFIXES:
unit_class = globals()[unit]
# NIST
elif len(unit) == 3:
unit = capitalize_first(unit)
# This is a NIST-type unit
if unit[:2] in NIST_PREFIXES:
unit_class = globals()[unit]
else:
# This is not a unit we recognize
raise ValueError("The unit %s is not a valid bitmath unit" % unit)
try:
unit_class
except UnboundLocalError:
raise ValueError("The unit %s is not a valid bitmath unit" % unit)
return unit_class(float(val))
|
Attempt to parse a string with ambiguous units and try to make a
bitmath object out of it.
This may produce inaccurate results if parsing shell output. For
example `ls` may say a 2730 Byte file is '2.7K'. 2730 Bytes == 2.73 kB
~= 2.666 KiB. See the documentation for all of the important details.
Note the following caveats:
* All inputs are assumed to be byte-based (as opposed to bit based)
* Numerical inputs (those without any units) are assumed to be a
number of bytes
* Inputs with single letter units (k, M, G, etc) are assumed to be SI
units (base-10). Set the `system` parameter to `bitmath.NIST` to
change this behavior.
* Inputs with an `i` character following the leading letter (Ki, Mi,
Gi) are assumed to be NIST units (base 2)
* Capitalization does not matter
|
entailment
|
def format(fmt_str=None, plural=False, bestprefix=False):
"""Context manager for printing bitmath instances.
``fmt_str`` - a formatting mini-language compat formatting string. See
the @properties (above) for a list of available items.
``plural`` - True enables printing instances with 's's if they're
plural. False (default) prints them as singular (no trailing 's').
``bestprefix`` - True enables printing instances in their best
human-readable representation. False, the default, prints instances
using their current prefix unit.
"""
if 'bitmath' not in globals():
import bitmath
if plural:
orig_fmt_plural = bitmath.format_plural
bitmath.format_plural = True
if fmt_str:
orig_fmt_str = bitmath.format_string
bitmath.format_string = fmt_str
yield
if plural:
bitmath.format_plural = orig_fmt_plural
if fmt_str:
bitmath.format_string = orig_fmt_str
|
Context manager for printing bitmath instances.
``fmt_str`` - a formatting mini-language compat formatting string. See
the @properties (above) for a list of available items.
``plural`` - True enables printing instances with 's's if they're
plural. False (default) prints them as singular (no trailing 's').
``bestprefix`` - True enables printing instances in their best
human-readable representation. False, the default, prints instances
using their current prefix unit.
|
entailment
|
def cli_script_main(cli_args):
"""
A command line interface to basic bitmath operations.
"""
choices = ALL_UNIT_TYPES
parser = argparse.ArgumentParser(
description='Converts from one type of size to another.')
parser.add_argument('--from-stdin', default=False, action='store_true',
help='Reads number from stdin rather than the cli')
parser.add_argument(
'-f', '--from', choices=choices, nargs=1,
type=str, dest='fromunit', default=['Byte'],
help='Input type you are converting from. Defaultes to Byte.')
parser.add_argument(
'-t', '--to', choices=choices, required=False, nargs=1, type=str,
help=('Input type you are converting to. '
'Attempts to detect best result if omitted.'), dest='tounit')
parser.add_argument(
'size', nargs='*', type=float,
help='The number to convert.')
args = parser.parse_args(cli_args)
# Not sure how to cover this with tests, or if the functionality
# will remain in this form long enough for it to make writing a
# test worth the effort.
if args.from_stdin: # pragma: no cover
args.size = [float(sys.stdin.readline()[:-1])]
results = []
for size in args.size:
instance = getattr(__import__(
'bitmath', fromlist=['True']), args.fromunit[0])(size)
# If we have a unit provided then use it
if args.tounit:
result = getattr(instance, args.tounit[0])
# Otherwise use the best_prefix call
else:
result = instance.best_prefix()
results.append(result)
return results
|
A command line interface to basic bitmath operations.
|
entailment
|
def _do_setup(self):
"""Setup basic parameters for this class.
`base` is the numeric base which when raised to `power` is equivalent
to 1 unit of the corresponding prefix. I.e., base=2, power=10
represents 2^10, which is the NIST Binary Prefix for 1 Kibibyte.
Likewise, for the SI prefix classes `base` will be 10, and the `power`
for the Kilobyte is 3.
"""
(self._base, self._power, self._name_singular, self._name_plural) = self._setup()
self._unit_value = self._base ** self._power
|
Setup basic parameters for this class.
`base` is the numeric base which when raised to `power` is equivalent
to 1 unit of the corresponding prefix. I.e., base=2, power=10
represents 2^10, which is the NIST Binary Prefix for 1 Kibibyte.
Likewise, for the SI prefix classes `base` will be 10, and the `power`
for the Kilobyte is 3.
|
entailment
|
def _norm(self, value):
"""Normalize the input value into the fundamental unit for this prefix
type.
:param number value: The input value to be normalized
:raises ValueError: if the input value is not a type of real number
"""
if isinstance(value, self.valid_types):
self._byte_value = value * self._unit_value
self._bit_value = self._byte_value * 8.0
else:
raise ValueError("Initialization value '%s' is of an invalid type: %s. "
"Must be one of %s" % (
value,
type(value),
", ".join(str(x) for x in self.valid_types)))
|
Normalize the input value into the fundamental unit for this prefix
type.
:param number value: The input value to be normalized
:raises ValueError: if the input value is not a type of real number
|
entailment
|
def system(self):
"""The system of units used to measure an instance"""
if self._base == 2:
return "NIST"
elif self._base == 10:
return "SI"
else:
# I don't expect to ever encounter this logic branch, but
# hey, it's better to have extra test coverage than
# insufficient test coverage.
raise ValueError("Instances mathematical base is an unsupported value: %s" % (
str(self._base)))
|
The system of units used to measure an instance
|
entailment
|
def unit(self):
"""The string that is this instances prefix unit name in agreement
with this instance value (singular or plural). Following the
convention that only 1 is singular. This will always be the singular
form when :attr:`bitmath.format_plural` is ``False`` (default value).
For example:
>>> KiB(1).unit == 'KiB'
>>> Byte(0).unit == 'Bytes'
>>> Byte(1).unit == 'Byte'
>>> Byte(1.1).unit == 'Bytes'
>>> Gb(2).unit == 'Gbs'
"""
global format_plural
if self.prefix_value == 1:
# If it's a '1', return it singular, no matter what
return self._name_singular
elif format_plural:
# Pluralization requested
return self._name_plural
else:
# Pluralization NOT requested, and the value is not 1
return self._name_singular
|
The string that is this instances prefix unit name in agreement
with this instance value (singular or plural). Following the
convention that only 1 is singular. This will always be the singular
form when :attr:`bitmath.format_plural` is ``False`` (default value).
For example:
>>> KiB(1).unit == 'KiB'
>>> Byte(0).unit == 'Bytes'
>>> Byte(1).unit == 'Byte'
>>> Byte(1.1).unit == 'Bytes'
>>> Gb(2).unit == 'Gbs'
|
entailment
|
def from_other(cls, item):
"""Factory function to return instances of `item` converted into a new
instance of ``cls``. Because this is a class method, it may be called
from any bitmath class object without the need to explicitly
instantiate the class ahead of time.
*Implicit Parameter:*
* ``cls`` A bitmath class, implicitly set to the class of the
instance object it is called on
*User Supplied Parameter:*
* ``item`` A :class:`bitmath.Bitmath` subclass instance
*Example:*
>>> import bitmath
>>> kib = bitmath.KiB.from_other(bitmath.MiB(1))
>>> print kib
KiB(1024.0)
"""
if isinstance(item, Bitmath):
return cls(bits=item.bits)
else:
raise ValueError("The provided items must be a valid bitmath class: %s" %
str(item.__class__))
|
Factory function to return instances of `item` converted into a new
instance of ``cls``. Because this is a class method, it may be called
from any bitmath class object without the need to explicitly
instantiate the class ahead of time.
*Implicit Parameter:*
* ``cls`` A bitmath class, implicitly set to the class of the
instance object it is called on
*User Supplied Parameter:*
* ``item`` A :class:`bitmath.Bitmath` subclass instance
*Example:*
>>> import bitmath
>>> kib = bitmath.KiB.from_other(bitmath.MiB(1))
>>> print kib
KiB(1024.0)
|
entailment
|
def format(self, fmt):
"""Return a representation of this instance formatted with user
supplied syntax"""
_fmt_params = {
'base': self.base,
'bin': self.bin,
'binary': self.binary,
'bits': self.bits,
'bytes': self.bytes,
'power': self.power,
'system': self.system,
'unit': self.unit,
'unit_plural': self.unit_plural,
'unit_singular': self.unit_singular,
'value': self.value
}
return fmt.format(**_fmt_params)
|
Return a representation of this instance formatted with user
supplied syntax
|
entailment
|
def best_prefix(self, system=None):
"""Optional parameter, `system`, allows you to prefer NIST or SI in
the results. By default, the current system is used (Bit/Byte default
to NIST).
Logic discussion/notes:
Base-case, does it need converting?
If the instance is less than one Byte, return the instance as a Bit
instance.
Else, begin by recording the unit system the instance is defined
by. This determines which steps (NIST_STEPS/SI_STEPS) we iterate over.
If the instance is not already a ``Byte`` instance, convert it to one.
NIST units step up by powers of 1024, SI units step up by powers of
1000.
Take integer value of the log(base=STEP_POWER) of the instance's byte
value. E.g.:
>>> int(math.log(Gb(100).bytes, 1000))
3
This will return a value >= 0. The following determines the 'best
prefix unit' for representation:
* result == 0, best represented as a Byte
* result >= len(SYSTEM_STEPS), best represented as an Exbi/Exabyte
* 0 < result < len(SYSTEM_STEPS), best represented as SYSTEM_PREFIXES[result-1]
"""
# Use absolute value so we don't return Bit's for *everything*
# less than Byte(1). From github issue #55
if abs(self) < Byte(1):
return Bit.from_other(self)
else:
if type(self) is Byte: # pylint: disable=unidiomatic-typecheck
_inst = self
else:
_inst = Byte.from_other(self)
# Which table to consult? Was a preferred system provided?
if system is None:
# No preference. Use existing system
if self.system == 'NIST':
_STEPS = NIST_PREFIXES
_BASE = 1024
elif self.system == 'SI':
_STEPS = SI_PREFIXES
_BASE = 1000
# Anything else would have raised by now
else:
# Preferred system provided.
if system == NIST:
_STEPS = NIST_PREFIXES
_BASE = 1024
elif system == SI:
_STEPS = SI_PREFIXES
_BASE = 1000
else:
raise ValueError("Invalid value given for 'system' parameter."
" Must be one of NIST or SI")
# Index of the string of the best prefix in the STEPS list
_index = int(math.log(abs(_inst.bytes), _BASE))
# Recall that the log() function returns >= 0. This doesn't
# map to the STEPS list 1:1. That is to say, 0 is handled with
# special care. So if the _index is 1, we actually want item 0
# in the list.
if _index == 0:
# Already a Byte() type, so return it.
return _inst
elif _index >= len(_STEPS):
# This is a really big number. Use the biggest prefix we've got
_best_prefix = _STEPS[-1]
elif 0 < _index < len(_STEPS):
# There is an appropriate prefix unit to represent this
_best_prefix = _STEPS[_index - 1]
_conversion_method = getattr(
self,
'to_%sB' % _best_prefix)
return _conversion_method()
|
Optional parameter, `system`, allows you to prefer NIST or SI in
the results. By default, the current system is used (Bit/Byte default
to NIST).
Logic discussion/notes:
Base-case, does it need converting?
If the instance is less than one Byte, return the instance as a Bit
instance.
Else, begin by recording the unit system the instance is defined
by. This determines which steps (NIST_STEPS/SI_STEPS) we iterate over.
If the instance is not already a ``Byte`` instance, convert it to one.
NIST units step up by powers of 1024, SI units step up by powers of
1000.
Take integer value of the log(base=STEP_POWER) of the instance's byte
value. E.g.:
>>> int(math.log(Gb(100).bytes, 1000))
3
This will return a value >= 0. The following determines the 'best
prefix unit' for representation:
* result == 0, best represented as a Byte
* result >= len(SYSTEM_STEPS), best represented as an Exbi/Exabyte
* 0 < result < len(SYSTEM_STEPS), best represented as SYSTEM_PREFIXES[result-1]
|
entailment
|
def _norm(self, value):
"""Normalize the input value into the fundamental unit for this prefix
type"""
self._bit_value = value * self._unit_value
self._byte_value = self._bit_value / 8.0
|
Normalize the input value into the fundamental unit for this prefix
type
|
entailment
|
def calc_crc(raw):
"""Calculate cyclic redundancy check (CRC)."""
crc = 0
for sym in raw:
crc = crc ^ int(sym)
return crc
|
Calculate cyclic redundancy check (CRC).
|
entailment
|
def extract_from_frame(data):
"""Extract payload and command from frame."""
if len(data) <= 4:
raise PyVLXException("could_not_extract_from_frame_too_short", data=data)
length = data[0] * 256 + data[1] - 1
if len(data) != length + 3:
raise PyVLXException("could_not_extract_from_frame_invalid_length", data=data, current_length=len(data), expected_length=length + 3)
if calc_crc(data[:-1]) != data[-1]:
raise PyVLXException("could_not_extract_from_frame_invalid_crc", data=data, expected_crc=calc_crc(data[:-1]), current_crc=data[-1])
payload = data[4:-1]
try:
command = Command(data[2] * 256 + data[3])
except ValueError:
raise PyVLXException("could_not_extract_from_frame_command", data=data)
return command, payload
|
Extract payload and command from frame.
|
entailment
|
def get_payload(self):
"""Return Payload."""
payload = bytes([self.node_id])
payload += string_to_bytes(self.name, 64)
payload += bytes([self.order >> 8 & 255, self.order & 255])
payload += bytes([self.placement])
payload += bytes([self.node_variation.value])
return payload
|
Return Payload.
|
entailment
|
def from_payload(self, payload):
"""Init frame from binary data."""
self.node_id = payload[0]
self.name = bytes_to_string(payload[1:65])
self.order = payload[65] * 256 + payload[66]
self.placement = payload[67]
self.node_variation = NodeVariation(payload[68])
|
Init frame from binary data.
|
entailment
|
def from_payload(self, payload):
"""Init frame from binary data."""
self.status = NodeInformationStatus(payload[0])
self.node_id = payload[1]
|
Init frame from binary data.
|
entailment
|
def _get_meta(obj):
"""Extract metadata, if any, from given object."""
if hasattr(obj, 'meta'): # Spectrum or model
meta = deepcopy(obj.meta)
elif isinstance(obj, dict): # Metadata
meta = deepcopy(obj)
else: # Number
meta = {}
return meta
|
Extract metadata, if any, from given object.
|
entailment
|
def _merge_meta(left, right, result, clean=True):
"""Merge metadata from left and right onto results.
This is used during class initialization.
This should also be used by operators to merge metadata after
creating a new instance but before returning it.
Result's metadata is modified in-place.
Parameters
----------
left, right : number, `BaseSpectrum`, or `~astropy.modeling.models`
Inputs of an operation.
result : `BaseSpectrum`
Output spectrum object.
clean : bool
Remove ``'header'`` and ``'expr'`` entries from inputs.
"""
# Copies are returned because they need some clean-up below.
left = BaseSpectrum._get_meta(left)
right = BaseSpectrum._get_meta(right)
# Remove these from going into result to avoid mess.
# header = FITS header metadata
# expr = ASTROLIB PYSYNPHOT expression
if clean:
for key in ('header', 'expr'):
for d in (left, right):
if key in d:
del d[key]
mid = metadata.merge(left, right, metadata_conflicts='silent')
result.meta = metadata.merge(result.meta, mid,
metadata_conflicts='silent')
|
Merge metadata from left and right onto results.
This is used during class initialization.
This should also be used by operators to merge metadata after
creating a new instance but before returning it.
Result's metadata is modified in-place.
Parameters
----------
left, right : number, `BaseSpectrum`, or `~astropy.modeling.models`
Inputs of an operation.
result : `BaseSpectrum`
Output spectrum object.
clean : bool
Remove ``'header'`` and ``'expr'`` entries from inputs.
|
entailment
|
def _process_generic_param(pval, def_unit, equivalencies=[]):
"""Process generic model parameter."""
if isinstance(pval, u.Quantity):
outval = pval.to(def_unit, equivalencies).value
else: # Assume already in desired unit
outval = pval
return outval
|
Process generic model parameter.
|
entailment
|
def _process_wave_param(self, pval):
"""Process individual model parameter representing wavelength."""
return self._process_generic_param(
pval, self._internal_wave_unit, equivalencies=u.spectral())
|
Process individual model parameter representing wavelength.
|
entailment
|
def waveset(self):
"""Optimal wavelengths for sampling the spectrum or bandpass."""
w = get_waveset(self.model)
if w is not None:
utils.validate_wavelengths(w)
w = w * self._internal_wave_unit
return w
|
Optimal wavelengths for sampling the spectrum or bandpass.
|
entailment
|
def waverange(self):
"""Range of `waveset`."""
if self.waveset is None:
x = [None, None]
else:
x = u.Quantity([self.waveset.min(), self.waveset.max()])
return x
|
Range of `waveset`.
|
entailment
|
def _validate_wavelengths(self, wave):
"""Validate wavelengths for sampling."""
if wave is None:
if self.waveset is None:
raise exceptions.SynphotError(
'self.waveset is undefined; '
'Provide wavelengths for sampling.')
wavelengths = self.waveset
else:
w = self._process_wave_param(wave)
utils.validate_wavelengths(w)
wavelengths = w * self._internal_wave_unit
return wavelengths
|
Validate wavelengths for sampling.
|
entailment
|
def _validate_other_mul_div(other):
"""Conditions for other to satisfy before mul/div."""
if not isinstance(other, (u.Quantity, numbers.Number,
BaseUnitlessSpectrum, SourceSpectrum)):
raise exceptions.IncompatibleSources(
'Can only operate on scalar number/Quantity or spectrum')
elif (isinstance(other, u.Quantity) and
(other.unit.decompose() != u.dimensionless_unscaled or
not np.isscalar(other.value) or
not isinstance(other.value, numbers.Real))):
raise exceptions.IncompatibleSources(
'Can only operate on real scalar dimensionless Quantity')
elif (isinstance(other, numbers.Number) and
not (np.isscalar(other) and isinstance(other, numbers.Real))):
raise exceptions.IncompatibleSources(
'Can only operate on real scalar number')
|
Conditions for other to satisfy before mul/div.
|
entailment
|
def integrate(self, wavelengths=None, **kwargs):
"""Perform integration.
This uses any analytical integral that the
underlying model has (i.e., ``self.model.integral``).
If unavailable, it uses the default fall-back integrator
set in the ``default_integrator`` configuration item.
If wavelengths are provided, flux or throughput is first resampled.
This is useful when user wants to integrate at specific end points
or use custom spacing; In that case, user can pass in desired
sampling array generated with :func:`numpy.linspace`,
:func:`numpy.logspace`, etc.
If not provided, then `waveset` is used.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
kwargs : dict
Optional keywords to ``__call__`` for sampling.
Returns
-------
result : `~astropy.units.quantity.Quantity`
Integrated result.
Raises
------
NotImplementedError
Invalid default integrator.
synphot.exceptions.SynphotError
`waveset` is needed but undefined or cannot integrate
natively in the given ``flux_unit``.
"""
# Cannot integrate per Hz units natively across wavelength
# without converting them to per Angstrom unit first, so
# less misleading to just disallow that option for now.
if 'flux_unit' in kwargs:
self._validate_flux_unit(kwargs['flux_unit'], wav_only=True)
x = self._validate_wavelengths(wavelengths)
# TODO: When astropy.modeling.models supports this, need to
# make sure that this actually works, and gives correct unit.
# https://github.com/astropy/astropy/issues/5033
# https://github.com/astropy/astropy/pull/5108
try:
m = self.model.integral
except (AttributeError, NotImplementedError):
if conf.default_integrator == 'trapezoid':
y = self(x, **kwargs)
result = abs(np.trapz(y.value, x=x.value))
result_unit = y.unit
else: # pragma: no cover
raise NotImplementedError(
'Analytic integral not available and default integrator '
'{0} is not supported'.format(conf.default_integrator))
else: # pragma: no cover
start = x[0].value
stop = x[-1].value
result = (m(stop) - m(start))
result_unit = self._internal_flux_unit
# Ensure final unit takes account of integration across wavelength
if result_unit != units.THROUGHPUT:
if result_unit == units.PHOTLAM:
result_unit = u.photon / (u.cm**2 * u.s)
elif result_unit == units.FLAM:
result_unit = u.erg / (u.cm**2 * u.s)
else: # pragma: no cover
raise NotImplementedError(
'Integration of {0} is not supported'.format(result_unit))
else:
# Ideally flux can use this too but unfortunately this
# operation results in confusing output unit for flux.
result_unit *= self._internal_wave_unit
return result * result_unit
|
Perform integration.
This uses any analytical integral that the
underlying model has (i.e., ``self.model.integral``).
If unavailable, it uses the default fall-back integrator
set in the ``default_integrator`` configuration item.
If wavelengths are provided, flux or throughput is first resampled.
This is useful when user wants to integrate at specific end points
or use custom spacing; In that case, user can pass in desired
sampling array generated with :func:`numpy.linspace`,
:func:`numpy.logspace`, etc.
If not provided, then `waveset` is used.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
kwargs : dict
Optional keywords to ``__call__`` for sampling.
Returns
-------
result : `~astropy.units.quantity.Quantity`
Integrated result.
Raises
------
NotImplementedError
Invalid default integrator.
synphot.exceptions.SynphotError
`waveset` is needed but undefined or cannot integrate
natively in the given ``flux_unit``.
|
entailment
|
def avgwave(self, wavelengths=None):
"""Calculate the :ref:`average wavelength <synphot-formula-avgwv>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
avg_wave : `~astropy.units.quantity.Quantity`
Average wavelength.
"""
x = self._validate_wavelengths(wavelengths).value
y = self(x).value
num = np.trapz(y * x, x=x)
den = np.trapz(y, x=x)
if den == 0: # pragma: no cover
avg_wave = 0.0
else:
avg_wave = abs(num / den)
return avg_wave * self._internal_wave_unit
|
Calculate the :ref:`average wavelength <synphot-formula-avgwv>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
avg_wave : `~astropy.units.quantity.Quantity`
Average wavelength.
|
entailment
|
def barlam(self, wavelengths=None):
"""Calculate :ref:`mean log wavelength <synphot-formula-barlam>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
bar_lam : `~astropy.units.quantity.Quantity`
Mean log wavelength.
"""
x = self._validate_wavelengths(wavelengths).value
y = self(x).value
num = np.trapz(y * np.log(x) / x, x=x)
den = np.trapz(y / x, x=x)
if num == 0 or den == 0: # pragma: no cover
bar_lam = 0.0
else:
bar_lam = np.exp(abs(num / den))
return bar_lam * self._internal_wave_unit
|
Calculate :ref:`mean log wavelength <synphot-formula-barlam>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
bar_lam : `~astropy.units.quantity.Quantity`
Mean log wavelength.
|
entailment
|
def pivot(self, wavelengths=None):
"""Calculate :ref:`pivot wavelength <synphot-formula-pivwv>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
pivwv : `~astropy.units.quantity.Quantity`
Pivot wavelength.
"""
x = self._validate_wavelengths(wavelengths).value
y = self(x).value
num = np.trapz(y * x, x=x)
den = np.trapz(y / x, x=x)
if den == 0: # pragma: no cover
pivwv = 0.0
else:
pivwv = np.sqrt(abs(num / den))
return pivwv * self._internal_wave_unit
|
Calculate :ref:`pivot wavelength <synphot-formula-pivwv>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
pivwv : `~astropy.units.quantity.Quantity`
Pivot wavelength.
|
entailment
|
def force_extrapolation(self):
"""Force the underlying model to extrapolate.
An example where this is useful: You create a source spectrum
with non-default extrapolation behavior and you wish to force
the underlying empirical model to extrapolate based on nearest point.
.. note::
This is only applicable to `~synphot.models.Empirical1D` model
and should still work even if the source spectrum has been
redshifted.
Returns
-------
is_forced : bool
`True` if the model is successfully forced to be extrapolated,
else `False`.
"""
# We use _model here in case the spectrum is redshifted.
if isinstance(self._model, Empirical1D):
self._model.fill_value = np.nan
is_forced = True
else:
is_forced = False
return is_forced
|
Force the underlying model to extrapolate.
An example where this is useful: You create a source spectrum
with non-default extrapolation behavior and you wish to force
the underlying empirical model to extrapolate based on nearest point.
.. note::
This is only applicable to `~synphot.models.Empirical1D` model
and should still work even if the source spectrum has been
redshifted.
Returns
-------
is_forced : bool
`True` if the model is successfully forced to be extrapolated,
else `False`.
|
entailment
|
def taper(self, wavelengths=None):
"""Taper the spectrum or bandpass.
The wavelengths to use for the first and last points are
calculated by using the same ratio as for the 2 interior points.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for tapering.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
sp : `BaseSpectrum`
Tapered empirical spectrum or bandpass.
``self`` is returned if already tapered (e.g., box model).
"""
x = self._validate_wavelengths(wavelengths)
# Calculate new end points for tapering
w1 = x[0] ** 2 / x[1]
w2 = x[-1] ** 2 / x[-2]
# Special handling for empirical data.
# This is to be compatible with ASTROLIB PYSYNPHOT behavior.
if isinstance(self._model, Empirical1D):
y1 = self._model.lookup_table[0]
y2 = self._model.lookup_table[-1]
# Other models can just evaluate at new end points
else:
y1 = self(w1)
y2 = self(w2)
# Nothing to do
if y1 == 0 and y2 == 0:
return self # Do we need a deepcopy here?
y = self(x)
if y1 != 0:
x = np.insert(x, 0, w1)
y = np.insert(y, 0, 0.0)
if y2 != 0:
x = np.insert(x, x.size, w2)
y = np.insert(y, y.size, 0.0)
return self.__class__(Empirical1D, points=x, lookup_table=y)
|
Taper the spectrum or bandpass.
The wavelengths to use for the first and last points are
calculated by using the same ratio as for the 2 interior points.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for tapering.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
Returns
-------
sp : `BaseSpectrum`
Tapered empirical spectrum or bandpass.
``self`` is returned if already tapered (e.g., box model).
|
entailment
|
def _get_arrays(self, wavelengths, **kwargs):
"""Get sampled spectrum or bandpass in user units."""
x = self._validate_wavelengths(wavelengths)
y = self(x, **kwargs)
if isinstance(wavelengths, u.Quantity):
w = x.to(wavelengths.unit, u.spectral())
else:
w = x
return w, y
|
Get sampled spectrum or bandpass in user units.
|
entailment
|
def _do_plot(x, y, title='', xlog=False, ylog=False,
left=None, right=None, bottom=None, top=None,
save_as=''): # pragma: no cover
"""Plot worker.
Parameters
----------
x, y : `~astropy.units.quantity.Quantity`
Wavelength and flux/throughput to plot.
kwargs
See :func:`plot`.
"""
try:
import matplotlib.pyplot as plt
except ImportError:
log.error('No matplotlib installation found; plotting disabled '
'as a result.')
return
fig, ax = plt.subplots()
ax.plot(x, y)
# Custom wavelength limits
if left is not None:
ax.set_xlim(left=left)
if right is not None:
ax.set_xlim(right=right)
# Custom flux/throughput limit
if bottom is not None:
ax.set_ylim(bottom=bottom)
if top is not None:
ax.set_ylim(top=top)
xu = x.unit
if xu.physical_type == 'frequency':
ax.set_xlabel('Frequency ({0})'.format(xu))
else:
ax.set_xlabel('Wavelength ({0})'.format(xu))
yu = y.unit
if yu is u.dimensionless_unscaled:
ax.set_ylabel('Unitless')
else:
ax.set_ylabel('Flux ({0})'.format(yu))
if title:
ax.set_title(title)
if xlog:
ax.set_xscale('log')
if ylog:
ax.set_yscale('log')
plt.draw()
if save_as:
plt.savefig(save_as)
log.info('Plot saved as {0}'.format(save_as))
|
Plot worker.
Parameters
----------
x, y : `~astropy.units.quantity.Quantity`
Wavelength and flux/throughput to plot.
kwargs
See :func:`plot`.
|
entailment
|
def plot(self, wavelengths=None, **kwargs): # pragma: no cover
"""Plot the spectrum.
.. note:: Uses ``matplotlib``.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
title : str
Plot title.
xlog, ylog : bool
Plot X and Y axes, respectively, in log scale.
Default is linear scale.
left, right : `None` or number
Minimum and maximum wavelengths to plot.
If `None`, uses the whole range. If a number is given,
must be in Angstrom.
bottom, top : `None` or number
Minimum and maximum flux/throughput to plot.
If `None`, uses the whole range. If a number is given,
must be in internal unit.
save_as : str
Save the plot to an image file. The file type is
automatically determined by given file extension.
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
"""
w, y = self._get_arrays(wavelengths)
self._do_plot(w, y, **kwargs)
|
Plot the spectrum.
.. note:: Uses ``matplotlib``.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
title : str
Plot title.
xlog, ylog : bool
Plot X and Y axes, respectively, in log scale.
Default is linear scale.
left, right : `None` or number
Minimum and maximum wavelengths to plot.
If `None`, uses the whole range. If a number is given,
must be in Angstrom.
bottom, top : `None` or number
Minimum and maximum flux/throughput to plot.
If `None`, uses the whole range. If a number is given,
must be in internal unit.
save_as : str
Save the plot to an image file. The file type is
automatically determined by given file extension.
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
|
entailment
|
def _validate_flux_unit(new_unit, wav_only=False):
"""Make sure flux unit is valid."""
new_unit = units.validate_unit(new_unit)
acceptable_types = ['spectral flux density wav',
'photon flux density wav']
acceptable_names = ['PHOTLAM', 'FLAM']
if not wav_only: # Include per Hz units
acceptable_types += ['spectral flux density',
'photon flux density']
acceptable_names += ['PHOTNU', 'FNU', 'Jy']
if new_unit.physical_type not in acceptable_types:
raise exceptions.SynphotError(
'Source spectrum cannot operate in {0}. Acceptable units: '
'{1}'.format(new_unit, ','.join(acceptable_names)))
return new_unit
|
Make sure flux unit is valid.
|
entailment
|
def normalize(self, renorm_val, band=None, wavelengths=None, force=False,
area=None, vegaspec=None):
"""Renormalize the spectrum to the given Quantity and band.
.. warning::
Redshift attribute (``z``) is reset to 0 in the normalized
spectrum even if ``self.z`` is non-zero.
This is because the normalization simply adds a scale
factor to the existing composite model.
This is confusing but should not affect the flux sampling.
Parameters
----------
renorm_val : number or `~astropy.units.quantity.Quantity`
Value to renormalize the spectrum to. If not a Quantity,
assumed to be in internal unit.
band : `SpectralElement`
Bandpass to use in renormalization.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for renormalization.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
force : bool
By default (`False`), renormalization is only done
when band wavelength limits are within ``self``
or at least 99% of the flux is within the overlap.
Set to `True` to force renormalization for partial overlap
(this changes the underlying model of ``self`` to always
extrapolate, if applicable).
Disjoint bandpass raises an exception regardless.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
Returns
-------
sp : obj
Renormalized spectrum.
Raises
------
synphot.exceptions.DisjointError
Renormalization band does not overlap with ``self``.
synphot.exceptions.PartialOverlap
Renormalization band only partially overlaps with ``self``
and significant amount of flux falls outside the overlap.
synphot.exceptions.SynphotError
Invalid inputs or calculation failed.
"""
warndict = {}
if band is None:
sp = self
else:
if not isinstance(band, SpectralElement):
raise exceptions.SynphotError('Invalid bandpass.')
stat = band.check_overlap(self, wavelengths=wavelengths)
if stat == 'none':
raise exceptions.DisjointError(
'Spectrum and renormalization band are disjoint.')
elif 'partial' in stat:
if stat == 'partial_most':
warn_str = 'At least'
elif stat == 'partial_notmost' and force:
warn_str = 'Less than'
else:
raise exceptions.PartialOverlap(
'Spectrum and renormalization band do not fully '
'overlap. You may use force=True to force the '
'renormalization to proceed.')
warn_str = (
'Spectrum is not defined everywhere in renormalization '
'bandpass. {0} 99% of the band throughput has '
'data. Spectrum will be').format(warn_str)
if self.force_extrapolation():
warn_str = ('{0} extrapolated at constant '
'value.').format(warn_str)
else:
warn_str = ('{0} evaluated outside pre-defined '
'waveset.').format(warn_str)
warnings.warn(warn_str, AstropyUserWarning)
warndict['PartialRenorm'] = warn_str
elif stat != 'full': # pragma: no cover
raise exceptions.SynphotError(
'Overlap result of {0} is unexpected.'.format(stat))
sp = self.__mul__(band)
if not isinstance(renorm_val, u.Quantity):
renorm_val = renorm_val * self._internal_flux_unit
renorm_unit_name = renorm_val.unit.to_string()
w = sp._validate_wavelengths(wavelengths)
if (renorm_val.unit == u.count or
renorm_unit_name == units.OBMAG.to_string()):
# Special handling for non-density units
flux_tmp = sp(w, flux_unit=u.count, area=area)
totalflux = flux_tmp.sum().value
stdflux = 1.0
else:
totalflux = sp.integrate(wavelengths=wavelengths).value
# VEGAMAG
if renorm_unit_name == units.VEGAMAG.to_string():
if not isinstance(vegaspec, SourceSpectrum):
raise exceptions.SynphotError(
'Vega spectrum is missing.')
stdspec = vegaspec
# Magnitude flux-density units
elif renorm_val.unit in (u.STmag, u.ABmag):
stdspec = SourceSpectrum(
ConstFlux1D, amplitude=(0 * renorm_val.unit))
# Linear flux-density units
else:
stdspec = SourceSpectrum(
ConstFlux1D, amplitude=(1 * renorm_val.unit))
if band is None:
# TODO: Cannot get this to agree with results
# from using a very large box bandpass.
# stdflux = stdspec.integrate(wavelengths=w).value
raise NotImplementedError('Must provide a bandpass')
else:
up = stdspec * band
stdflux = up.integrate(wavelengths=wavelengths).value
utils.validate_totalflux(totalflux)
# Renormalize in magnitudes
if (renorm_val.unit.decompose() == u.mag or
isinstance(renorm_val.unit, u.LogUnit)):
const = renorm_val.value + (2.5 *
np.log10(totalflux / stdflux))
newsp = self.__mul__(10**(-0.4 * const))
# Renormalize in linear flux units
else:
const = renorm_val.value * (stdflux / totalflux)
newsp = self.__mul__(const)
newsp.warnings = warndict
return newsp
|
Renormalize the spectrum to the given Quantity and band.
.. warning::
Redshift attribute (``z``) is reset to 0 in the normalized
spectrum even if ``self.z`` is non-zero.
This is because the normalization simply adds a scale
factor to the existing composite model.
This is confusing but should not affect the flux sampling.
Parameters
----------
renorm_val : number or `~astropy.units.quantity.Quantity`
Value to renormalize the spectrum to. If not a Quantity,
assumed to be in internal unit.
band : `SpectralElement`
Bandpass to use in renormalization.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for renormalization.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
force : bool
By default (`False`), renormalization is only done
when band wavelength limits are within ``self``
or at least 99% of the flux is within the overlap.
Set to `True` to force renormalization for partial overlap
(this changes the underlying model of ``self`` to always
extrapolate, if applicable).
Disjoint bandpass raises an exception regardless.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
Returns
-------
sp : obj
Renormalized spectrum.
Raises
------
synphot.exceptions.DisjointError
Renormalization band does not overlap with ``self``.
synphot.exceptions.PartialOverlap
Renormalization band only partially overlaps with ``self``
and significant amount of flux falls outside the overlap.
synphot.exceptions.SynphotError
Invalid inputs or calculation failed.
|
entailment
|
def _process_flux_param(self, pval, wave):
"""Process individual model parameter representing flux."""
if isinstance(pval, u.Quantity):
self._validate_flux_unit(pval.unit)
outval = units.convert_flux(self._redshift_model(wave), pval,
self._internal_flux_unit).value
else: # Assume already in internal unit
outval = pval
return outval
|
Process individual model parameter representing flux.
|
entailment
|
def model(self):
"""Model of the spectrum with given redshift."""
if self.z == 0:
m = self._model
else:
# wavelength
if self._internal_wave_unit.physical_type == 'length':
rs = self._redshift_model.inverse
# frequency or wavenumber
# NOTE: This will never execute as long as internal wavelength
# unit remains Angstrom.
else: # pragma: no cover
rs = self._redshift_model
if self.z_type == 'wavelength_only':
m = rs | self._model
else: # conserve_flux
m = rs | self._model | self._redshift_flux_model
return m
|
Model of the spectrum with given redshift.
|
entailment
|
def z(self, what):
"""Change redshift."""
if not isinstance(what, numbers.Real):
raise exceptions.SynphotError(
'Redshift must be a real scalar number.')
self._z = float(what)
self._redshift_model = RedshiftScaleFactor(self._z)
if self.z_type == 'wavelength_only':
self._redshift_flux_model = None
else: # conserve_flux
self._redshift_flux_model = Scale(1 / (1 + self._z))
|
Change redshift.
|
entailment
|
def _validate_other_add_sub(self, other):
"""Conditions for other to satisfy before add/sub."""
if not isinstance(other, self.__class__):
raise exceptions.IncompatibleSources(
'Can only operate on {0}.'.format(self.__class__.__name__))
|
Conditions for other to satisfy before add/sub.
|
entailment
|
def plot(self, wavelengths=None, flux_unit=None, area=None, vegaspec=None,
**kwargs): # pragma: no cover
"""Plot the spectrum.
.. note:: Uses :mod:`matplotlib`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit for plotting.
If not given, internal unit is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
kwargs : dict
See :func:`BaseSpectrum.plot`.
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
"""
w, y = self._get_arrays(wavelengths, flux_unit=flux_unit, area=area,
vegaspec=vegaspec)
self._do_plot(w, y, **kwargs)
|
Plot the spectrum.
.. note:: Uses :mod:`matplotlib`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit for plotting.
If not given, internal unit is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
kwargs : dict
See :func:`BaseSpectrum.plot`.
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
|
entailment
|
def to_fits(self, filename, wavelengths=None, flux_unit=None, area=None,
vegaspec=None, **kwargs):
"""Write the spectrum to a FITS file.
Parameters
----------
filename : str
Output filename.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit before written out.
If not given, internal unit is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
kwargs : dict
Keywords accepted by :func:`~synphot.specio.write_fits_spec`.
"""
w, y = self._get_arrays(wavelengths, flux_unit=flux_unit, area=area,
vegaspec=vegaspec)
# There are some standard keywords that should be added
# to the extension header.
bkeys = {'tdisp1': 'G15.7', 'tdisp2': 'G15.7'}
if 'expr' in self.meta:
bkeys['expr'] = (self.meta['expr'], 'synphot expression')
if 'ext_header' in kwargs:
kwargs['ext_header'].update(bkeys)
else:
kwargs['ext_header'] = bkeys
specio.write_fits_spec(filename, w, y, **kwargs)
|
Write the spectrum to a FITS file.
Parameters
----------
filename : str
Output filename.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit before written out.
If not given, internal unit is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
kwargs : dict
Keywords accepted by :func:`~synphot.specio.write_fits_spec`.
|
entailment
|
def from_file(cls, filename, keep_neg=False, **kwargs):
"""Create a spectrum from file.
If filename has 'fits' or 'fit' suffix, it is read as FITS.
Otherwise, it is read as ASCII.
Parameters
----------
filename : str
Spectrum filename.
keep_neg : bool
See `~synphot.models.Empirical1D`.
kwargs : dict
Keywords acceptable by
:func:`~synphot.specio.read_fits_spec` (if FITS) or
:func:`~synphot.specio.read_ascii_spec` (if ASCII).
Returns
-------
sp : `SourceSpectrum`
Empirical spectrum.
"""
header, wavelengths, fluxes = specio.read_spec(filename, **kwargs)
return cls(Empirical1D, points=wavelengths, lookup_table=fluxes,
keep_neg=keep_neg, meta={'header': header})
|
Create a spectrum from file.
If filename has 'fits' or 'fit' suffix, it is read as FITS.
Otherwise, it is read as ASCII.
Parameters
----------
filename : str
Spectrum filename.
keep_neg : bool
See `~synphot.models.Empirical1D`.
kwargs : dict
Keywords acceptable by
:func:`~synphot.specio.read_fits_spec` (if FITS) or
:func:`~synphot.specio.read_ascii_spec` (if ASCII).
Returns
-------
sp : `SourceSpectrum`
Empirical spectrum.
|
entailment
|
def from_vega(cls, **kwargs):
"""Load :ref:`Vega spectrum <synphot-vega-spec>`.
Parameters
----------
kwargs : dict
Keywords acceptable by :func:`~synphot.specio.read_remote_spec`.
Returns
-------
vegaspec : `SourceSpectrum`
Empirical Vega spectrum.
"""
filename = conf.vega_file
header, wavelengths, fluxes = specio.read_remote_spec(
filename, **kwargs)
header['filename'] = filename
meta = {'header': header,
'expr': 'Vega from {0}'.format(os.path.basename(filename))}
return cls(Empirical1D, points=wavelengths, lookup_table=fluxes,
meta=meta)
|
Load :ref:`Vega spectrum <synphot-vega-spec>`.
Parameters
----------
kwargs : dict
Keywords acceptable by :func:`~synphot.specio.read_remote_spec`.
Returns
-------
vegaspec : `SourceSpectrum`
Empirical Vega spectrum.
|
entailment
|
def _validate_flux_unit(new_unit): # pragma: no cover
"""Make sure flux unit is valid."""
new_unit = units.validate_unit(new_unit)
if new_unit.decompose() != u.dimensionless_unscaled:
raise exceptions.SynphotError(
'Unit {0} is not dimensionless'.format(new_unit))
return new_unit
|
Make sure flux unit is valid.
|
entailment
|
def check_overlap(self, other, wavelengths=None, threshold=0.01):
"""Check for wavelength overlap between two spectra.
Only wavelengths where ``self`` throughput is non-zero
are considered.
Example of full overlap::
|---------- other ----------|
|------ self ------|
Examples of partial overlap::
|---------- self ----------|
|------ other ------|
|---- other ----|
|---- self ----|
|---- self ----|
|---- other ----|
Examples of no overlap::
|---- self ----| |---- other ----|
|---- other ----| |---- self ----|
Parameters
----------
other : `BaseSpectrum`
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
threshold : float
If less than this fraction of flux or throughput falls
outside wavelength overlap, the *lack* of overlap is
*insignificant*. This is only used when partial overlap
is detected. Default is 1%.
Returns
-------
result : {'full', 'partial_most', 'partial_notmost', 'none'}
* 'full' - ``self`` coverage is within or same as ``other``
* 'partial_most' - Less than ``threshold`` fraction of
``self`` flux is outside the overlapping wavelength
region, i.e., the *lack* of overlap is *insignificant*
* 'partial_notmost' - ``self`` partially overlaps with
``other`` but does not qualify for 'partial_most'
* 'none' - ``self`` does not overlap ``other``
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
"""
if not isinstance(other, BaseSpectrum):
raise exceptions.SynphotError(
'other must be spectrum or bandpass.')
# Special cases where no sampling wavelengths given and
# one of the inputs is continuous.
if wavelengths is None:
if other.waveset is None:
return 'full'
if self.waveset is None:
return 'partial_notmost'
x1 = self._validate_wavelengths(wavelengths)
y1 = self(x1)
a = x1[y1 > 0].value
b = other._validate_wavelengths(wavelengths).value
result = utils.overlap_status(a, b)
if result == 'partial':
# If there is no need to extrapolate or taper other
# (i.e., other is zero at self's wave limits),
# then we consider it as a full coverage.
# This logic assumes __call__ never returns mag or count!
if ((isinstance(other.model, Empirical1D) and
other.model.is_tapered() or
not isinstance(other.model,
(Empirical1D, _CompoundModel))) and
np.allclose(other(x1[::x1.size - 1]).value, 0)):
result = 'full'
# Check if the lack of overlap is significant.
else:
# Get all the flux
totalflux = self.integrate(wavelengths=wavelengths).value
utils.validate_totalflux(totalflux)
a_min, a_max = a.min(), a.max()
b_min, b_max = b.min(), b.max()
# Now get the other two pieces
excluded = 0.0
if a_min < b_min:
excluded += self.integrate(
wavelengths=np.array([a_min, b_min])).value
if a_max > b_max:
excluded += self.integrate(
wavelengths=np.array([b_max, a_max])).value
if excluded / totalflux < threshold:
result = 'partial_most'
else:
result = 'partial_notmost'
return result
|
Check for wavelength overlap between two spectra.
Only wavelengths where ``self`` throughput is non-zero
are considered.
Example of full overlap::
|---------- other ----------|
|------ self ------|
Examples of partial overlap::
|---------- self ----------|
|------ other ------|
|---- other ----|
|---- self ----|
|---- self ----|
|---- other ----|
Examples of no overlap::
|---- self ----| |---- other ----|
|---- other ----| |---- self ----|
Parameters
----------
other : `BaseSpectrum`
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for integration.
If not a Quantity, assumed to be in Angstrom.
If `None`, `waveset` is used.
threshold : float
If less than this fraction of flux or throughput falls
outside wavelength overlap, the *lack* of overlap is
*insignificant*. This is only used when partial overlap
is detected. Default is 1%.
Returns
-------
result : {'full', 'partial_most', 'partial_notmost', 'none'}
* 'full' - ``self`` coverage is within or same as ``other``
* 'partial_most' - Less than ``threshold`` fraction of
``self`` flux is outside the overlapping wavelength
region, i.e., the *lack* of overlap is *insignificant*
* 'partial_notmost' - ``self`` partially overlaps with
``other`` but does not qualify for 'partial_most'
* 'none' - ``self`` does not overlap ``other``
Raises
------
synphot.exceptions.SynphotError
Invalid inputs.
|
entailment
|
def unit_response(self, area, wavelengths=None):
"""Calculate :ref:`unit response <synphot-formula-uresp>`
of this bandpass.
Parameters
----------
area : float or `~astropy.units.quantity.Quantity`
Area that flux covers. If not a Quantity, assumed to be in
:math:`cm^{2}`.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
uresp : `~astropy.units.quantity.Quantity`
Flux (in FLAM) of a star that produces a response of
one photon per second in this bandpass.
"""
a = units.validate_quantity(area, units.AREA)
# Only correct if wavelengths are in Angstrom.
x = self._validate_wavelengths(wavelengths).value
y = self(x).value * x
int_val = abs(np.trapz(y, x=x))
uresp = units.HC / (a.cgs * int_val)
return uresp.value * units.FLAM
|
Calculate :ref:`unit response <synphot-formula-uresp>`
of this bandpass.
Parameters
----------
area : float or `~astropy.units.quantity.Quantity`
Area that flux covers. If not a Quantity, assumed to be in
:math:`cm^{2}`.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
uresp : `~astropy.units.quantity.Quantity`
Flux (in FLAM) of a star that produces a response of
one photon per second in this bandpass.
|
entailment
|
def rmswidth(self, wavelengths=None, threshold=None):
"""Calculate the :ref:`bandpass RMS width <synphot-formula-rmswidth>`.
Not to be confused with :func:`photbw`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
threshold : float or `~astropy.units.quantity.Quantity`, optional
Data points with throughput below this value are not
included in the calculation. By default, all data points
are included.
Returns
-------
rms_width : `~astropy.units.quantity.Quantity`
RMS width of the bandpass.
Raises
------
synphot.exceptions.SynphotError
Threshold is invalid.
"""
x = self._validate_wavelengths(wavelengths).value
y = self(x).value
if threshold is None:
wave = x
thru = y
else:
if (isinstance(threshold, numbers.Real) or
(isinstance(threshold, u.Quantity) and
threshold.unit == self._internal_flux_unit)):
mask = y >= threshold
else:
raise exceptions.SynphotError(
'{0} is not a valid threshold'.format(threshold))
wave = x[mask]
thru = y[mask]
a = self.avgwave(wavelengths=wavelengths).value
num = np.trapz((wave - a) ** 2 * thru, x=wave)
den = np.trapz(thru, x=wave)
if den == 0: # pragma: no cover
rms_width = 0.0
else:
rms_width = np.sqrt(abs(num / den))
return rms_width * self._internal_wave_unit
|
Calculate the :ref:`bandpass RMS width <synphot-formula-rmswidth>`.
Not to be confused with :func:`photbw`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
threshold : float or `~astropy.units.quantity.Quantity`, optional
Data points with throughput below this value are not
included in the calculation. By default, all data points
are included.
Returns
-------
rms_width : `~astropy.units.quantity.Quantity`
RMS width of the bandpass.
Raises
------
synphot.exceptions.SynphotError
Threshold is invalid.
|
entailment
|
def fwhm(self, **kwargs):
"""Calculate :ref:`synphot-formula-fwhm` of equivalent gaussian.
Parameters
----------
kwargs : dict
See :func:`photbw`.
Returns
-------
fwhm_val : `~astropy.units.quantity.Quantity`
FWHM of equivalent gaussian.
"""
return np.sqrt(8 * np.log(2)) * self.photbw(**kwargs)
|
Calculate :ref:`synphot-formula-fwhm` of equivalent gaussian.
Parameters
----------
kwargs : dict
See :func:`photbw`.
Returns
-------
fwhm_val : `~astropy.units.quantity.Quantity`
FWHM of equivalent gaussian.
|
entailment
|
def tpeak(self, wavelengths=None):
"""Calculate :ref:`peak bandpass throughput <synphot-formula-tpeak>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
tpeak : `~astropy.units.quantity.Quantity`
Peak bandpass throughput.
"""
x = self._validate_wavelengths(wavelengths).value
return self(x).max()
|
Calculate :ref:`peak bandpass throughput <synphot-formula-tpeak>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
tpeak : `~astropy.units.quantity.Quantity`
Peak bandpass throughput.
|
entailment
|
def wpeak(self, wavelengths=None):
"""Calculate
:ref:`wavelength at peak throughput <synphot-formula-tpeak>`.
If there are multiple data points with peak throughput
value, only the first match is returned.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
wpeak : `~astropy.units.quantity.Quantity`
Wavelength at peak throughput.
"""
x = self._validate_wavelengths(wavelengths)
return x[self(x) == self.tpeak(wavelengths=wavelengths)][0]
|
Calculate
:ref:`wavelength at peak throughput <synphot-formula-tpeak>`.
If there are multiple data points with peak throughput
value, only the first match is returned.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
wpeak : `~astropy.units.quantity.Quantity`
Wavelength at peak throughput.
|
entailment
|
def rectwidth(self, wavelengths=None):
"""Calculate :ref:`bandpass rectangular width <synphot-formula-rectw>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
rectw : `~astropy.units.quantity.Quantity`
Bandpass rectangular width.
"""
equvw = self.equivwidth(wavelengths=wavelengths)
tpeak = self.tpeak(wavelengths=wavelengths)
if tpeak.value == 0: # pragma: no cover
rectw = 0.0 * self._internal_wave_unit
else:
rectw = equvw / tpeak
return rectw
|
Calculate :ref:`bandpass rectangular width <synphot-formula-rectw>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
rectw : `~astropy.units.quantity.Quantity`
Bandpass rectangular width.
|
entailment
|
def efficiency(self, wavelengths=None):
"""Calculate :ref:`dimensionless efficiency <synphot-formula-qtlam>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
qtlam : `~astropy.units.quantity.Quantity`
Dimensionless efficiency.
"""
x = self._validate_wavelengths(wavelengths).value
y = self(x).value
qtlam = abs(np.trapz(y / x, x=x))
return qtlam * u.dimensionless_unscaled
|
Calculate :ref:`dimensionless efficiency <synphot-formula-qtlam>`.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
Returns
-------
qtlam : `~astropy.units.quantity.Quantity`
Dimensionless efficiency.
|
entailment
|
def emflx(self, area, wavelengths=None):
"""Calculate
:ref:`equivalent monochromatic flux <synphot-formula-emflx>`.
Parameters
----------
area, wavelengths
See :func:`unit_response`.
Returns
-------
em_flux : `~astropy.units.quantity.Quantity`
Equivalent monochromatic flux.
"""
t_lambda = self.tlambda(wavelengths=wavelengths)
if t_lambda == 0: # pragma: no cover
em_flux = 0.0 * units.FLAM
else:
uresp = self.unit_response(area, wavelengths=wavelengths)
equvw = self.equivwidth(wavelengths=wavelengths).value
em_flux = uresp * equvw / t_lambda
return em_flux
|
Calculate
:ref:`equivalent monochromatic flux <synphot-formula-emflx>`.
Parameters
----------
area, wavelengths
See :func:`unit_response`.
Returns
-------
em_flux : `~astropy.units.quantity.Quantity`
Equivalent monochromatic flux.
|
entailment
|
def from_file(cls, filename, **kwargs):
"""Creates a bandpass from file.
If filename has 'fits' or 'fit' suffix, it is read as FITS.
Otherwise, it is read as ASCII.
Parameters
----------
filename : str
Bandpass filename.
kwargs : dict
Keywords acceptable by
:func:`~synphot.specio.read_fits_spec` (if FITS) or
:func:`~synphot.specio.read_ascii_spec` (if ASCII).
Returns
-------
bp : `SpectralElement`
Empirical bandpass.
"""
if 'flux_unit' not in kwargs:
kwargs['flux_unit'] = cls._internal_flux_unit
if ((filename.endswith('fits') or filename.endswith('fit')) and
'flux_col' not in kwargs):
kwargs['flux_col'] = 'THROUGHPUT'
header, wavelengths, throughput = specio.read_spec(filename, **kwargs)
return cls(Empirical1D, points=wavelengths, lookup_table=throughput,
keep_neg=True, meta={'header': header})
|
Creates a bandpass from file.
If filename has 'fits' or 'fit' suffix, it is read as FITS.
Otherwise, it is read as ASCII.
Parameters
----------
filename : str
Bandpass filename.
kwargs : dict
Keywords acceptable by
:func:`~synphot.specio.read_fits_spec` (if FITS) or
:func:`~synphot.specio.read_ascii_spec` (if ASCII).
Returns
-------
bp : `SpectralElement`
Empirical bandpass.
|
entailment
|
def from_filter(cls, filtername, **kwargs):
"""Load :ref:`pre-defined filter bandpass <synphot-predefined-filter>`.
Parameters
----------
filtername : str
Filter name. Choose from 'bessel_j', 'bessel_h', 'bessel_k',
'cousins_r', 'cousins_i', 'johnson_u', 'johnson_b', 'johnson_v',
'johnson_r', 'johnson_i', 'johnson_j', or 'johnson_k'.
kwargs : dict
Keywords acceptable by :func:`~synphot.specio.read_remote_spec`.
Returns
-------
bp : `SpectralElement`
Empirical bandpass.
Raises
------
synphot.exceptions.SynphotError
Invalid filter name.
"""
filtername = filtername.lower()
# Select filename based on filter name
if filtername == 'bessel_j':
cfgitem = Conf.bessel_j_file
elif filtername == 'bessel_h':
cfgitem = Conf.bessel_h_file
elif filtername == 'bessel_k':
cfgitem = Conf.bessel_k_file
elif filtername == 'cousins_r':
cfgitem = Conf.cousins_r_file
elif filtername == 'cousins_i':
cfgitem = Conf.cousins_i_file
elif filtername == 'johnson_u':
cfgitem = Conf.johnson_u_file
elif filtername == 'johnson_b':
cfgitem = Conf.johnson_b_file
elif filtername == 'johnson_v':
cfgitem = Conf.johnson_v_file
elif filtername == 'johnson_r':
cfgitem = Conf.johnson_r_file
elif filtername == 'johnson_i':
cfgitem = Conf.johnson_i_file
elif filtername == 'johnson_j':
cfgitem = Conf.johnson_j_file
elif filtername == 'johnson_k':
cfgitem = Conf.johnson_k_file
else:
raise exceptions.SynphotError(
'Filter name {0} is invalid.'.format(filtername))
filename = cfgitem()
if 'flux_unit' not in kwargs:
kwargs['flux_unit'] = cls._internal_flux_unit
if ((filename.endswith('fits') or filename.endswith('fit')) and
'flux_col' not in kwargs):
kwargs['flux_col'] = 'THROUGHPUT'
header, wavelengths, throughput = specio.read_remote_spec(
filename, **kwargs)
header['filename'] = filename
header['descrip'] = cfgitem.description
meta = {'header': header, 'expr': filtername}
return cls(Empirical1D, points=wavelengths, lookup_table=throughput,
meta=meta)
|
Load :ref:`pre-defined filter bandpass <synphot-predefined-filter>`.
Parameters
----------
filtername : str
Filter name. Choose from 'bessel_j', 'bessel_h', 'bessel_k',
'cousins_r', 'cousins_i', 'johnson_u', 'johnson_b', 'johnson_v',
'johnson_r', 'johnson_i', 'johnson_j', or 'johnson_k'.
kwargs : dict
Keywords acceptable by :func:`~synphot.specio.read_remote_spec`.
Returns
-------
bp : `SpectralElement`
Empirical bandpass.
Raises
------
synphot.exceptions.SynphotError
Invalid filter name.
|
entailment
|
async def handle_frame(self, frame):
"""Handle incoming API frame, return True if this was the expected frame."""
if isinstance(frame, FrameActivateSceneConfirmation) and frame.session_id == self.session_id:
if frame.status == ActivateSceneConfirmationStatus.ACCEPTED:
self.success = True
return not self.wait_for_completion
if isinstance(frame, FrameCommandRemainingTimeNotification) and frame.session_id == self.session_id:
# Ignoring FrameCommandRemainingTimeNotification
return False
if isinstance(frame, FrameCommandRunStatusNotification) and frame.session_id == self.session_id:
# At the moment I don't reall understand what the FrameCommandRunStatusNotification is good for.
# Ignoring these packets for now
return False
if isinstance(frame, FrameSessionFinishedNotification) and frame.session_id == self.session_id:
return True
return False
|
Handle incoming API frame, return True if this was the expected frame.
|
entailment
|
def request_frame(self):
"""Construct initiating frame."""
self.session_id = get_new_session_id()
return FrameActivateSceneRequest(scene_id=self.scene_id, session_id=self.session_id)
|
Construct initiating frame.
|
entailment
|
def _init_bins(self, binset):
"""Calculated binned wavelength centers, edges, and flux.
By contrast, the native waveset and flux should be considered
samples of a continuous function.
Thus, it makes sense to interpolate ``self.waveset`` and
``self(self.waveset)``, but not `binset` and `binflux`.
"""
if binset is None:
if self.bandpass.waveset is not None:
self._binset = self.bandpass.waveset
elif self.spectrum.waveset is not None:
self._binset = self.spectrum.waveset
log.info('Bandpass waveset is undefined; '
'Using source spectrum waveset instead.')
else:
raise exceptions.UndefinedBinset(
'Both source spectrum and bandpass have undefined '
'waveset; Provide binset manually.')
else:
self._binset = self._validate_wavelengths(binset)
# binset must be in ascending order for calcbinflux()
# to work properly.
if self._binset[0] > self._binset[-1]:
self._binset = self._binset[::-1]
self._bin_edges = binning.calculate_bin_edges(self._binset)
# Merge bin edges and centers in with the natural waveset
spwave = utils.merge_wavelengths(
self._bin_edges.value, self._binset.value)
if self.waveset is not None:
spwave = utils.merge_wavelengths(spwave, self.waveset.value)
# Throw out invalid wavelengths after merging.
spwave = spwave[spwave > 0]
# Compute indices associated to each endpoint.
indices = np.searchsorted(spwave, self._bin_edges.value)
i_beg = indices[:-1]
i_end = indices[1:]
# Prepare integration variables.
flux = self(spwave)
avflux = (flux.value[1:] + flux.value[:-1]) * 0.5
deltaw = spwave[1:] - spwave[:-1]
# Sum over each bin.
binflux, intwave = binning.calcbinflux(
self._binset.size, i_beg, i_end, avflux, deltaw)
self._binflux = binflux * flux.unit
|
Calculated binned wavelength centers, edges, and flux.
By contrast, the native waveset and flux should be considered
samples of a continuous function.
Thus, it makes sense to interpolate ``self.waveset`` and
``self(self.waveset)``, but not `binset` and `binflux`.
|
entailment
|
def sample_binned(self, wavelengths=None, flux_unit=None, **kwargs):
"""Sample binned observation without interpolation.
To sample unbinned data, use ``__call__``.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `binset` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit.
If not given, internal unit is used.
kwargs : dict
Keywords acceptable by :func:`~synphot.units.convert_flux`.
Returns
-------
flux : `~astropy.units.quantity.Quantity`
Binned flux in given unit.
Raises
------
synphot.exceptions.InterpolationNotAllowed
Interpolation of binned data is not allowed.
"""
x = self._validate_binned_wavelengths(wavelengths)
i = np.searchsorted(self.binset, x)
if not np.allclose(self.binset[i].value, x.value):
raise exceptions.InterpolationNotAllowed(
'Some or all wavelength values are not in binset.')
y = self.binflux[i]
if flux_unit is None:
flux = y
else:
flux = units.convert_flux(x, y, flux_unit, **kwargs)
return flux
|
Sample binned observation without interpolation.
To sample unbinned data, use ``__call__``.
Parameters
----------
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, `binset` is used.
flux_unit : str or `~astropy.units.core.Unit` or `None`
Flux is converted to this unit.
If not given, internal unit is used.
kwargs : dict
Keywords acceptable by :func:`~synphot.units.convert_flux`.
Returns
-------
flux : `~astropy.units.quantity.Quantity`
Binned flux in given unit.
Raises
------
synphot.exceptions.InterpolationNotAllowed
Interpolation of binned data is not allowed.
|
entailment
|
def _get_binned_arrays(self, wavelengths, flux_unit, area=None,
vegaspec=None):
"""Get binned observation in user units."""
x = self._validate_binned_wavelengths(wavelengths)
y = self.sample_binned(wavelengths=x, flux_unit=flux_unit, area=area,
vegaspec=vegaspec)
if isinstance(wavelengths, u.Quantity):
w = x.to(wavelengths.unit, u.spectral())
else:
w = x
return w, y
|
Get binned observation in user units.
|
entailment
|
def binned_waverange(self, cenwave, npix, **kwargs):
"""Calculate the wavelength range covered by the given number
of pixels centered on the given central wavelengths of
`binset`.
Parameters
----------
cenwave : float or `~astropy.units.quantity.Quantity`
Desired central wavelength.
If not a Quantity, assumed to be in Angstrom.
npix : int
Desired number of pixels, centered on ``cenwave``.
kwargs : dict
Keywords accepted by :func:`synphot.binning.wave_range`.
Returns
-------
waverange : `~astropy.units.quantity.Quantity`
Lower and upper limits of the wavelength range,
in the unit of ``cenwave``.
"""
# Calculation is done in the unit of cenwave.
if not isinstance(cenwave, u.Quantity):
cenwave = cenwave * self._internal_wave_unit
bin_wave = units.validate_quantity(
self.binset, cenwave.unit, equivalencies=u.spectral())
return binning.wave_range(
bin_wave.value, cenwave.value, npix, **kwargs) * cenwave.unit
|
Calculate the wavelength range covered by the given number
of pixels centered on the given central wavelengths of
`binset`.
Parameters
----------
cenwave : float or `~astropy.units.quantity.Quantity`
Desired central wavelength.
If not a Quantity, assumed to be in Angstrom.
npix : int
Desired number of pixels, centered on ``cenwave``.
kwargs : dict
Keywords accepted by :func:`synphot.binning.wave_range`.
Returns
-------
waverange : `~astropy.units.quantity.Quantity`
Lower and upper limits of the wavelength range,
in the unit of ``cenwave``.
|
entailment
|
def binned_pixelrange(self, waverange, **kwargs):
"""Calculate the number of pixels within the given wavelength
range and `binset`.
Parameters
----------
waverange : tuple of float or `~astropy.units.quantity.Quantity`
Lower and upper limits of the desired wavelength range.
If not a Quantity, assumed to be in Angstrom.
kwargs : dict
Keywords accepted by :func:`synphot.binning.pixel_range`.
Returns
-------
npix : int
Number of pixels.
"""
x = units.validate_quantity(
waverange, self._internal_wave_unit, equivalencies=u.spectral())
return binning.pixel_range(self.binset.value, x.value, **kwargs)
|
Calculate the number of pixels within the given wavelength
range and `binset`.
Parameters
----------
waverange : tuple of float or `~astropy.units.quantity.Quantity`
Lower and upper limits of the desired wavelength range.
If not a Quantity, assumed to be in Angstrom.
kwargs : dict
Keywords accepted by :func:`synphot.binning.pixel_range`.
Returns
-------
npix : int
Number of pixels.
|
entailment
|
def effective_wavelength(self, binned=True, wavelengths=None,
mode='efflerg'):
"""Calculate :ref:`effective wavelength <synphot-formula-effwave>`.
Parameters
----------
binned : bool
Sample data in native wavelengths if `False`.
Else, sample binned data (default).
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` or `binset` is used, depending
on ``binned``.
mode : {'efflerg', 'efflphot'}
Flux is first converted to the unit below before calculation:
* 'efflerg' - FLAM
* 'efflphot' - PHOTLAM (deprecated)
Returns
-------
eff_lam : `~astropy.units.quantity.Quantity`
Observation effective wavelength.
Raises
------
synphot.exceptions.SynphotError
Invalid mode.
"""
mode = mode.lower()
if mode == 'efflerg':
flux_unit = units.FLAM
elif mode == 'efflphot':
warnings.warn(
'Usage of EFFLPHOT is deprecated.', AstropyDeprecationWarning)
flux_unit = units.PHOTLAM
else:
raise exceptions.SynphotError(
'mode must be "efflerg" or "efflphot"')
if binned:
x = self._validate_binned_wavelengths(wavelengths).value
y = self.sample_binned(wavelengths=x, flux_unit=flux_unit).value
else:
x = self._validate_wavelengths(wavelengths).value
y = units.convert_flux(x, self(x), flux_unit).value
num = np.trapz(y * x ** 2, x=x)
den = np.trapz(y * x, x=x)
if den == 0.0: # pragma: no cover
eff_lam = 0.0
else:
eff_lam = abs(num / den)
return eff_lam * self._internal_wave_unit
|
Calculate :ref:`effective wavelength <synphot-formula-effwave>`.
Parameters
----------
binned : bool
Sample data in native wavelengths if `False`.
Else, sample binned data (default).
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling.
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` or `binset` is used, depending
on ``binned``.
mode : {'efflerg', 'efflphot'}
Flux is first converted to the unit below before calculation:
* 'efflerg' - FLAM
* 'efflphot' - PHOTLAM (deprecated)
Returns
-------
eff_lam : `~astropy.units.quantity.Quantity`
Observation effective wavelength.
Raises
------
synphot.exceptions.SynphotError
Invalid mode.
|
entailment
|
def effstim(self, flux_unit=None, wavelengths=None, area=None,
vegaspec=None):
"""Calculate :ref:`effective stimulus <synphot-formula-effstim>`
for given flux unit.
Parameters
----------
flux_unit : str or `~astropy.units.core.Unit` or `None`
The unit of effective stimulus.
COUNT gives result in count/s (see :meth:`countrate` for more
options).
If not given, internal unit is used.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling. This must be given if
``self.waveset`` is undefined for the underlying spectrum model(s).
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
Returns
-------
eff_stim : `~astropy.units.quantity.Quantity`
Observation effective stimulus based on given flux unit.
"""
if flux_unit is None:
flux_unit = self._internal_flux_unit
flux_unit = units.validate_unit(flux_unit)
flux_unit_name = flux_unit.to_string()
# Special handling of COUNT/OBMAG.
# This is special case of countrate calculations.
if flux_unit == u.count or flux_unit_name == units.OBMAG.to_string():
val = self.countrate(area, binned=False, wavelengths=wavelengths)
if flux_unit.decompose() == u.mag:
eff_stim = (-2.5 * np.log10(val.value)) * flux_unit
else:
eff_stim = val
return eff_stim
# Special handling of VEGAMAG.
# This is basically effstim(self)/effstim(Vega)
if flux_unit_name == units.VEGAMAG.to_string():
num = self.integrate(wavelengths=wavelengths)
den = (vegaspec * self.bandpass).integrate()
utils.validate_totalflux(num)
utils.validate_totalflux(den)
return (2.5 * (math.log10(den.value) -
math.log10(num.value))) * units.VEGAMAG
# Sample the bandpass
x_band = self.bandpass._validate_wavelengths(wavelengths).value
y_band = self.bandpass(x_band).value
# Sample the observation in FLAM
inwave = self._validate_wavelengths(wavelengths).value
influx = units.convert_flux(inwave, self(inwave), units.FLAM).value
# Integrate
num = abs(np.trapz(inwave * influx, x=inwave))
den = abs(np.trapz(x_band * y_band, x=x_band))
utils.validate_totalflux(num)
utils.validate_totalflux(den)
val = (num / den) * units.FLAM
# Integration should always be done in FLAM and then
# converted to desired units as follows.
if flux_unit.physical_type == 'spectral flux density wav':
if flux_unit == u.STmag:
eff_stim = val.to(flux_unit)
else: # FLAM
eff_stim = val
elif flux_unit.physical_type in (
'spectral flux density', 'photon flux density',
'photon flux density wav'):
w_pivot = self.bandpass.pivot()
eff_stim = units.convert_flux(w_pivot, val, flux_unit)
else:
raise exceptions.SynphotError(
'Flux unit {0} is invalid'.format(flux_unit))
return eff_stim
|
Calculate :ref:`effective stimulus <synphot-formula-effstim>`
for given flux unit.
Parameters
----------
flux_unit : str or `~astropy.units.core.Unit` or `None`
The unit of effective stimulus.
COUNT gives result in count/s (see :meth:`countrate` for more
options).
If not given, internal unit is used.
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling. This must be given if
``self.waveset`` is undefined for the underlying spectrum model(s).
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` is used.
area, vegaspec
See :func:`~synphot.units.convert_flux`.
Returns
-------
eff_stim : `~astropy.units.quantity.Quantity`
Observation effective stimulus based on given flux unit.
|
entailment
|
def countrate(self, area, binned=True, wavelengths=None, waverange=None,
force=False):
"""Calculate :ref:`effective stimulus <synphot-formula-effstim>`
in count/s.
Parameters
----------
area : float or `~astropy.units.quantity.Quantity`
Area that flux covers. If not a Quantity, assumed to be in
:math:`cm^{2}`.
binned : bool
Sample data in native wavelengths if `False`.
Else, sample binned data (default).
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling. This must be given if
``self.waveset`` is undefined for the underlying spectrum model(s).
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` or `binset` is used, depending
on ``binned``.
waverange : tuple of float, Quantity, or `None`
Lower and upper limits of the desired wavelength range.
If not a Quantity, assumed to be in Angstrom.
If `None`, the full range is used.
force : bool
If a wavelength range is given, partial overlap raises
an exception when this is `False` (default). Otherwise,
it returns calculation for the overlapping region.
Disjoint wavelength range raises an exception regardless.
Returns
-------
count_rate : `~astropy.units.quantity.Quantity`
Observation effective stimulus in count/s.
Raises
------
synphot.exceptions.DisjointError
Wavelength range does not overlap with observation.
synphot.exceptions.PartialOverlap
Wavelength range only partially overlaps with observation.
synphot.exceptions.SynphotError
Calculation failed.
"""
# Sample the observation
if binned:
x = self._validate_binned_wavelengths(wavelengths).value
y = self.sample_binned(wavelengths=x, flux_unit=u.count,
area=area).value
else:
x = self._validate_wavelengths(wavelengths).value
y = units.convert_flux(x, self(x), u.count,
area=area).value
# Use entire wavelength range
if waverange is None:
influx = y
# Use given wavelength range
else:
w = units.validate_quantity(waverange, self._internal_wave_unit,
equivalencies=u.spectral()).value
stat = utils.overlap_status(w, x)
w1 = w.min()
w2 = w.max()
if stat == 'none':
raise exceptions.DisjointError(
'Observation and wavelength range are disjoint.')
elif 'partial' in stat:
if force:
warnings.warn(
'Count rate calculated only for wavelengths in the '
'overlap between observation and given range.',
AstropyUserWarning)
w1 = max(w1, x.min())
w2 = min(w2, x.max())
else:
raise exceptions.PartialOverlap(
'Observation and wavelength range do not fully '
'overlap. You may use force=True to force this '
'calculation anyway.')
elif stat != 'full': # pragma: no cover
raise exceptions.SynphotError(
'Overlap result of {0} is unexpected'.format(stat))
if binned:
if wavelengths is None:
bin_edges = self.bin_edges.value
else:
bin_edges = binning.calculate_bin_edges(x).value
i1 = np.searchsorted(bin_edges, w1) - 1
i2 = np.searchsorted(bin_edges, w2)
influx = y[i1:i2]
else:
mask = ((x >= w1) & (x <= w2))
influx = y[mask]
val = math.fsum(influx)
utils.validate_totalflux(val)
return val * (u.count / u.s)
|
Calculate :ref:`effective stimulus <synphot-formula-effstim>`
in count/s.
Parameters
----------
area : float or `~astropy.units.quantity.Quantity`
Area that flux covers. If not a Quantity, assumed to be in
:math:`cm^{2}`.
binned : bool
Sample data in native wavelengths if `False`.
Else, sample binned data (default).
wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None`
Wavelength values for sampling. This must be given if
``self.waveset`` is undefined for the underlying spectrum model(s).
If not a Quantity, assumed to be in Angstrom.
If `None`, ``self.waveset`` or `binset` is used, depending
on ``binned``.
waverange : tuple of float, Quantity, or `None`
Lower and upper limits of the desired wavelength range.
If not a Quantity, assumed to be in Angstrom.
If `None`, the full range is used.
force : bool
If a wavelength range is given, partial overlap raises
an exception when this is `False` (default). Otherwise,
it returns calculation for the overlapping region.
Disjoint wavelength range raises an exception regardless.
Returns
-------
count_rate : `~astropy.units.quantity.Quantity`
Observation effective stimulus in count/s.
Raises
------
synphot.exceptions.DisjointError
Wavelength range does not overlap with observation.
synphot.exceptions.PartialOverlap
Wavelength range only partially overlaps with observation.
synphot.exceptions.SynphotError
Calculation failed.
|
entailment
|
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