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def _fix_bias_shape(self, op_name, inputs, attrs): """A workaround to reshape bias term to (1, num_channel).""" if (op_name == 'Add' or op_name == 'Mul') and (int(len(self._params)) > 0) and \ ('broadcast' in attrs and attrs['broadcast'] == 1): assert len(list(inputs)) == 2 ...
def _fix_channels(self, op, attrs, inputs): """A workaround for getting 'channels' or 'units' since onnx don't provide these attributes. We check the shape of weights provided to get the number. """ if op not in [mx.sym.Convolution, mx.sym.Deconvolution, mx.sym.FullyConnected]: ...
def run(self, inputs, **kwargs): """Run model inference and return the result Parameters ---------- inputs : numpy array input to run a layer on Returns ------- params : numpy array result obtained after running the inference on mxnet ...
def _parse_default(self, target): """Helper function to parse default values.""" if not isinstance(target, (list, tuple)): k, v, t = target, None, lambda x: x elif len(target) == 1: k, v, t = target[0], None, lambda x: x elif len(target) == 2: k, v, t ...
def _parse_bool(self, value): """Helper function to parse default boolean values.""" if isinstance(value, string_types): return value.strip().lower() in ['true', '1', 't', 'y', 'yes'] return bool(value)
def _required_attr(self, attr, key): """Wrapper for getting required attributes.""" assert isinstance(attr, dict) if key not in attr: raise AttributeError("Required attribute {} not found.".format(key)) return attr[key]
def make_graph(node, inputs): """ Created ONNX GraphProto from node""" initializer = [] tensor_input_info = [] tensor_output_info = [] # Adding input tensor info. for index in range(len(node.input)): tensor_input_info.append( helper.make_tenso...
def run_node(cls, node, inputs, device='CPU'): # pylint: disable=arguments-differ """Running individual node inference on mxnet engine and return the result to onnx test infrastructure. Parameters ---------- node : onnx node object loaded onnx node (individual lay...
def prepare(cls, model, device='CPU', **kwargs): """For running end to end model(used for onnx test backend) Parameters ---------- model : onnx ModelProto object loaded onnx graph device : 'CPU' specifying device to run test on kwargs : ...
def _revert_caffe2_pad(attr): """Removing extra padding from Caffe2.""" if len(attr) == 4: attr = attr[:2] elif len(attr) == 2: pass else: raise ValueError("Invalid caffe2 type padding: {}".format(attr)) return attr
def _pad_sequence_fix(attr, kernelDim=None): """Changing onnx's pads sequence to match with mxnet's pad_width mxnet: (x1_begin, x1_end, ... , xn_begin, xn_end) onnx: (x1_begin, x2_begin, ... , xn_end, xn_end)""" new_attr = () if len(attr) % 2 == 0: for index in range(int(len(attr) / 2)): ...
def import_model(model_file): """Imports the supplied ONNX model file into MXNet symbol and parameters. Parameters ---------- model_file : ONNX model file name Returns ------- sym : mx.symbol Compatible mxnet symbol params : dict of str to mx.ndarray Dict of converted ...
def generate_hash(filepath): """Public function that reads a local file and generates a SHA256 hash digest for it""" fr = FileReader(filepath) data = fr.read_bin() return _calculate_sha256(data)
def generate_tar_files(directory_list): """Public function that reads a list of local directories and generates tar archives from them""" tar_file_list = [] for directory in directory_list: if dir_exists(directory): _generate_tar(directory) # create the tar archive...
def remove_tar_files(file_list): """Public function that removes temporary tar archive files in a local directory""" for f in file_list: if file_exists(f) and f.endswith('.tar'): os.remove(f)
def _generate_tar(dir_path): """Private function that reads a local directory and generates a tar archive from it""" try: with tarfile.open(dir_path + '.tar', 'w') as tar: tar.add(dir_path) except tarfile.TarError as e: stderr("Error: tar archive creation failed [" + str(e) + "]"...
def encrypt_file(self, inpath, force_nocompress=False, force_compress=False, armored=False, checksum=False): """public method for single file encryption with optional compression, ASCII armored formatting, and file hash digest generation""" if armored: if force_compress: comm...
def encrypt_files(self, file_list, force_nocompress=False, force_compress=False, armored=False, checksum=False): """public method for multiple file encryption with optional compression, ASCII armored formatting, and file hash digest generation""" for the_file in file_list: self.encrypt_file(...
def _is_compress_filetype(self, inpath): """private method that performs magic number and size check on file to determine whether to compress the file""" # check for common file type suffixes in order to avoid the need for file reads to check magic number for binary vs. text file if self._is_com...
def _is_common_binary(self, inpath): """private method to compare file path mime type to common binary file types""" # make local variables for the available char numbers in the suffix types to be tested two_suffix = inpath[-3:] three_suffix = inpath[-4:] four_suffix = inpath[-5:...
def _is_common_text(self, inpath): """private method to compare file path mime type to common text file types""" # make local variables for the available char numbers in the suffix types to be tested one_suffix = inpath[-2:] two_suffix = inpath[-3:] three_suffix = inpath[-4:] ...
def knn_impute_few_observed( X, missing_mask, k, verbose=False, print_interval=100): """ Seems to be the fastest kNN implementation. Pre-sorts each rows neighbors and then filters these sorted indices using each columns mask of observed values. Important detail: If k observed values are not...
def knn_initialize( X, missing_mask, verbose=False, min_dist=1e-6, max_dist_multiplier=1e6): """ Fill X with NaN values if necessary, construct the n_samples x n_samples distance matrix and set the self-distance of each row to infinity. Returns contents of X laid...
def knn_impute_optimistic( X, missing_mask, k, verbose=False, print_interval=100): """ Fill in the given incomplete matrix using k-nearest neighbor imputation. This version assumes that most of the time the same neighbors will be used so first performs the weight...
def all_pairs_normalized_distances(X): """ We can't really compute distances over incomplete data since rows are missing different numbers of entries. The next best thing is the mean squared difference between two vectors (a normalized distance), which gets computed only over the columns that tw...
def all_pairs_normalized_distances_reference(X): """ Reference implementation of normalized all-pairs distance, used for testing the more efficient implementation above for equivalence. """ n_samples, n_cols = X.shape # matrix of mean squared difference between between samples D = np.ones((n...
def knn_impute_with_argpartition( X, missing_mask, k, verbose=False, print_interval=100): """ Fill in the given incomplete matrix using k-nearest neighbor imputation. This version is a simpler algorithm meant primarily for testing but surprisingly it's faster for...
def knn_impute_reference( X, missing_mask, k, verbose=False, print_interval=100): """ Reference implementation of kNN imputation logic. """ n_rows, n_cols = X.shape X_result, D, effective_infinity = \ knn_initialize(X, missing_mask, verbose=verbose) ...
def active(self, registered_only=True): "Returns all active users, e.g. not logged and non-expired session." visitors = self.filter( expiry_time__gt=timezone.now(), end_time=None ) if registered_only: visitors = visitors.filter(user__isnull=False) ...
def stats(self, start_date, end_date, registered_only=False): """Returns a dictionary of visits including: * total visits * unique visits * return ratio * pages per visit (if pageviews are enabled) * time on site for all users, registered use...
def stats(self, start_date=None, end_date=None, registered_only=False): """Returns a dictionary of pageviews including: * total pageviews for all users, registered users and guests. """ pageviews = self.filter( visitor__start_time__lt=end_date, visit...
def dashboard(request): "Counts, aggregations and more!" end_time = now() start_time = end_time - timedelta(days=7) defaults = {'start': start_time, 'end': end_time} form = DashboardForm(data=request.GET or defaults) if form.is_valid(): start_time = form.cleaned_data['start'] en...
def geoip_data(self): """Attempt to retrieve MaxMind GeoIP data based on visitor's IP.""" if not HAS_GEOIP or not TRACK_USING_GEOIP: return if not hasattr(self, '_geoip_data'): self._geoip_data = None try: gip = GeoIP(cache=GEOIP_CACHE_TYPE) ...
def escape(s): """Convert the characters &, <, >, ' and " in string s to HTML-safe sequences. Use this if you need to display text that might contain such characters in HTML. Marks return value as markup string. """ if hasattr(s, '__html__'): return s.__html__() if isinstance(s, six.bi...
def iteration(obj, num_keys): """ Jade iteration supports "for 'value' [, key]?" iteration only. PyJade has implicitly supported value unpacking instead, without the list indexes. Trying to not break existing code, the following rules are applied: 1. If the object is a mapping type, return it...
def do_evaluate(parser, token): '''Calls an arbitrary method on an object.''' code = token.contents firstspace = code.find(' ') if firstspace >= 0: code = code[firstspace+1:] return Evaluator(code)
def do_set(parser, token): '''Calls an arbitrary method on an object.''' code = token.contents firstspace = code.find(' ') if firstspace >= 0: code = code[firstspace+1:] return Setter(code)
def render(self, context): '''Evaluates the code in the page and returns the result''' modules = { 'pyjade': __import__('pyjade') } context['false'] = False context['true'] = True try: return six.text_type(eval('pyjade.runtime.attrs(%s)'%self.code,modules,context)) except NameE...
def render(self, context): '''Evaluates the code in the page and returns the result''' modules = { } context['false'] = False context['true'] = True new_ctx = eval('dict(%s)'%self.code,modules,context) context.update(new_ctx) return ''
def sprite_filepath_build(sprite_type, sprite_id, **kwargs): """returns the filepath of the sprite *relative to SPRITE_CACHE*""" options = parse_sprite_options(sprite_type, **kwargs) filename = '.'.join([str(sprite_id), SPRITE_EXT]) filepath = os.path.join(sprite_type, *options, filename) return ...
def _make_obj(obj): """Takes an object and returns a corresponding API class. The names and values of the data will match exactly with those found in the online docs at https://pokeapi.co/docsv2/ . In some cases, the data may be of a standard type, such as an integer or string. For those cases, the...
def _load(self): """Function to collect reference data and connect it to the instance as attributes. Internal function, does not usually need to be called by the user, as it is called automatically when an attribute is requested. :return None """ data = get_...
def safe_make_dirs(path, mode=0o777): """Create a leaf directory and all intermediate ones in a safe way. A wrapper to os.makedirs() that handles existing leaf directories while avoiding os.path.exists() race conditions. :param path: relative or absolute directory tree to create :param mode: direc...
def get_default_cache(): """Get the default cache location. Adheres to the XDG Base Directory specification, as described in https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html :return: the default cache directory absolute path """ xdg_cache_home = os.environ.get('XDG_CACH...
def set_cache(new_path=None): """Simple function to change the cache location. `new_path` can be an absolute or relative path. If the directory does not exist yet, this function will create it. If None it will set the cache to the default cache directory. If you are going to change the cache direc...
def attach(self, lun_or_snap, skip_hlu_0=False): """ Attaches lun, snap or member snap of cg snap to host. Don't pass cg snapshot in as `lun_or_snap`. :param lun_or_snap: the lun, snap, or a member snap of cg snap :param skip_hlu_0: whether to skip hlu 0 :return: the hlu number...
def has_hlu(self, lun_or_snap, cg_member=None): """Returns True if `lun_or_snap` is attached to the host. :param lun_or_snap: can be lun, lun snap, cg snap or a member snap of cg snap. :param cg_member: the member lun of cg if `lun_or_snap` is cg snap. :return: True - if `lu...
def get_host_lun(self, lun_or_snap, cg_member=None): """Gets the host lun of a lun, lun snap, cg snap or a member snap of cg snap. :param lun_or_snap: can be lun, lun snap, cg snap or a member snap of cg snap. :param cg_member: the member lun of cg if `lun_or_snap` is cg sna...
def get_hlu(self, resource, cg_member=None): """Gets the hlu number of a lun, lun snap, cg snap or a member snap of cg snap. :param resource: can be lun, lun snap, cg snap or a member snap of cg snap. :param cg_member: the member lun of cg if `lun_or_snap` is cg snap. ...
def update_initiators(self, iqns=None, wwns=None): """Primarily for puppet-unity use. Update the iSCSI and FC initiators if needed. """ # First get current iqns iqns = set(iqns) if iqns else set() current_iqns = set() if self.iscsi_host_initiators: cu...
def list_files(tag=None, sat_id=None, data_path=None, format_str=None, supported_tags=None, fake_daily_files_from_monthly=False, two_digit_year_break=None): """Return a Pandas Series of every file for chosen satellite data. This routine is intended to be used by pysat instrume...
def load(fnames, tag=None, sat_id=None, fake_daily_files_from_monthly=False, flatten_twod=True): """Load NASA CDAWeb CDF files. This routine is intended to be used by pysat instrument modules supporting a particular NASA CDAWeb dataset. Parameters ------------ fnames : (...
def download(supported_tags, date_array, tag, sat_id, ftp_site='cdaweb.gsfc.nasa.gov', data_path=None, user=None, password=None, fake_daily_files_from_monthly=False): """Routine to download NASA CDAWeb CDF data. This routine is intended to be used by pysat instrumen...
def from_response(response, method, url): """Returns an instance of :class:`HttpError` or subclass based on response. :param response: instance of `requests.Response` class :param method: HTTP method used for request :param url: URL used for request """ req_id = response.headers.get("x-opensta...
def create_pool(self, name, raid_groups, description=None, **kwargs): """Create pool based on RaidGroupParameter. :param name: pool name :param raid_groups: a list of *RaidGroupParameter* :param description: pool description :param alert_threshold: Threshold at which the system ...
def get_file_port(self): """Returns ports list can be used by File File ports includes ethernet ports and link aggregation ports. """ eths = self.get_ethernet_port(bond=False) las = self.get_link_aggregation() return eths + las
def create_remote_system(self, management_address, local_username=None, local_password=None, remote_username=None, remote_password=None, connection_type=None): """ Configures a remote system for remote replication. ...
def create_replication_interface(self, sp, ip_port, ip_address, netmask=None, v6_prefix_length=None, gateway=None, vlan_id=None): """ Creates a replication interface. :param sp: `UnityStorageProcessor` object. Storage pro...
def geo2mag(incoord): """geographic coordinate to magnetic coordinate (coarse): Parameters ---------- incoord : numpy.array of shape (2,*) array([[glat0,glat1,glat2,...],[glon0,glon1,glon2,...]), where glat, glon are geographic latitude and longitude (or if you have only one po...
def restore(self, res_id, backup_snap=None): """ Restores a snapshot. :param res_id: the LUN number of primary LUN or snapshot mount point to be restored. :param backup_snap: the name of a backup snapshot to be created before restoring. """ name = ...
def list_files(tag='', sat_id=None, data_path=None, format_str=None): """Return a Pandas Series of every file for chosen SuperMAG data Parameters ----------- tag : (string or NoneType) Denotes type of file to load. Accepted types are 'indices', 'all', 'stations', and '' (for just magne...
def load(fnames, tag='', sat_id=None): """ Load the SuperMAG files Parameters ----------- fnames : (list) List of filenames tag : (str or NoneType) Denotes type of file to load. Accepted types are 'indices', 'all', 'stations', and '' (for just magnetometer measurements). (d...
def load_csv_data(fname, tag): """Load data from a comma separated SuperMAG file Parameters ------------ fname : (str) CSV SuperMAG file name tag : (str) Denotes type of file to load. Accepted types are 'indices', 'all', 'stations', and '' (for just magnetometer measurement...
def load_ascii_data(fname, tag): """Load data from a self-documenting ASCII SuperMAG file Parameters ------------ fname : (str) ASCII SuperMAG filename tag : (str) Denotes type of file to load. Accepted types are 'indices', 'all', 'stations', and '' (for just magnetometer m...
def update_smag_metadata(col_name): """Update SuperMAG metadata Parameters ----------- col_name : (str) Data column name Returns -------- col_dict : (dict) Dictionary of strings detailing the units and long-form name of the data """ smag_units = {'IAGA':'non...
def format_baseline_list(baseline_list): """Format the list of baseline information from the loaded files into a cohesive, informative string Parameters ------------ baseline_list : (list) List of strings specifying the baseline information for each SuperMAG file Returns --...
def download(date_array, tag, sat_id='', data_path=None, user=None, password=None, baseline='all', delta='none', options='all', file_fmt='ascii'): """Routine to download SuperMAG data Parameters ----------- date_array : np.array Array of datetime objects tag : stri...
def append_data(file_strings, file_fmt, tag): """ Load the SuperMAG files Parameters ----------- file_strings : array-like Lists or arrays of strings, where each string contains one file of data file_fmt : str String denoting file type (ascii or csv) tag : string String ...
def append_ascii_data(file_strings, tag): """ Append data from multiple files for the same time period Parameters ----------- file_strings : array-like Lists or arrays of strings, where each string contains one file of data tag : string String denoting the type of file to load, acce...
def append_csv_data(file_strings): """ Append data from multiple csv files for the same time period Parameters ----------- file_strings : array-like Lists or arrays of strings, where each string contains one file of data Returns ------- out_string : string String with all d...
def init(self): """ Adds custom calculations to orbit simulation. This routine is run once, and only once, upon instantiation. Adds quasi-dipole coordiantes, velocity calculation in ECEF coords, adds the attitude vectors of spacecraft assuming x is ram pointing and z is generally nadir, add...
def load(fnames, tag=None, sat_id=None, obs_long=0., obs_lat=0., obs_alt=0., TLE1=None, TLE2=None): """ Returns data and metadata in the format required by pysat. Finds position of satellite in both ECI and ECEF co-ordinates. Routine is directl...
def list_files(tag=None, sat_id=None, data_path=None, format_str=None): """Produce a fake list of files spanning a year""" index = pds.date_range(pysat.datetime(2017,12,1), pysat.datetime(2018,12,1)) # file list is effectively just the date in string format - '%D' works only in Mac. '%x' workins in bo...
def add_sc_attitude_vectors(inst): """ Add attitude vectors for spacecraft assuming ram pointing. Presumes spacecraft is pointed along the velocity vector (x), z is generally nadir pointing (positive towards Earth), and y completes the right handed system (generally southward). ...
def calculate_ecef_velocity(inst): """ Calculates spacecraft velocity in ECEF frame. Presumes that the spacecraft velocity in ECEF is in the input instrument object as position_ecef_*. Uses a symmetric difference to calculate the velocity thus endpoints will be set to NaN. Routine should b...
def add_quasi_dipole_coordinates(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses Apexpy package to add quasi-dipole coordinates to instrument object. The Quasi-Dipole coordinate system includes both the tilt and offset of the geomag...
def add_aacgm_coordinates(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses AACGMV2 package to add AACGM coordinates to instrument object. The Altitude Adjusted Corrected Geomagnetic Coordinates library is used to calculate the latitud...
def add_iri_thermal_plasma(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses IRI (International Reference Ionosphere) model to simulate an ionosphere. Uses pyglow module to run IRI. Configured to use actual solar parameters to run model. ...
def add_hwm_winds_and_ecef_vectors(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses HWM (Horizontal Wind Model) model to obtain neutral wind details. Uses pyglow module to run HWM. Configured to use actual solar parameters to run m...
def add_igrf(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses International Geomagnetic Reference Field (IGRF) model to obtain geomagnetic field values. Uses pyglow module to run IGRF. Configured to use actual solar parameters to run ...
def add_msis(inst, glat_label='glat', glong_label='glong', alt_label='alt'): """ Uses MSIS model to obtain thermospheric values. Uses pyglow module to run MSIS. Configured to use actual solar parameters to run model. Example ------- # f...
def project_ecef_vector_onto_sc(inst, x_label, y_label, z_label, new_x_label, new_y_label, new_z_label, meta=None): """Express input vector using s/c attitude directions x - ram pointing y - generally southward z - generally nadir ...
def scatterplot(inst, labelx, labely, data_label, datalim, xlim=None, ylim=None): """Return scatterplot of data_label(s) as functions of labelx,y over a season. Parameters ---------- labelx : string data product for x-axis labely : string data product for y-axis data_label : s...
def enable_log(level=logging.DEBUG): """Enable console logging. This is a utils method for try run with storops. :param level: log level, default to DEBUG """ logger = logging.getLogger(__name__) logger.setLevel(level) if not logger.handlers: logger.info('enabling logging to console...
def list_files(tag=None, sat_id=None, data_path=None, format_str=None): """Return a Pandas Series of every file for chosen satellite data Parameters ----------- tag : (string or NoneType) Denotes type of file to load. Accepted types are '' and 'ascii'. If '' is specified, the primary d...
def load_files(files, tag=None, sat_id=None, altitude_bin=None): '''Loads a list of COSMIC data files, supplied by user. Returns a list of dicts, a dict for each file. ''' output = [None]*len(files) drop_idx = [] for (i,file) in enumerate(files): try: #data = net...
def round_60(value): """ round the number to the multiple of 60 Say a random value is represented by: 60 * n + r n is an integer and r is an integer between 0 and 60. if r < 30, the result is 60 * n. otherwise, the result is 60 * (n + 1) The use of this function is that the counter refreshment...
def utilization(prev, curr, counters): """ calculate the utilization delta_busy = curr.busy - prev.busy delta_idle = curr.idle - prev.idle utilization = delta_busy / (delta_busy + delta_idle) :param prev: previous resource :param curr: current resource :param counters: list of two, busy ti...
def delta_ps(prev, curr, counters): """ calculate the delta per second of one counter formula: (curr - prev) / delta_time :param prev: previous resource :param curr: current resource :param counters: the counter to do delta and per second, one only :return: value, NaN if invalid. """ co...
def io_size_kb(prev, curr, counters): """ calculate the io size based on bandwidth and throughput formula: average_io_size = bandwidth / throughput :param prev: prev resource, not used :param curr: current resource :param counters: two stats, bandwidth in MB and throughput count :return: value,...
def list_files(tag='', sat_id=None, data_path=None, format_str=None): """Return a Pandas Series of every file for chosen satellite data Parameters ----------- tag : (string or NoneType) Denotes type of file to load. Accepted types are '' and 'ascii'. If '' is specified, the primary dat...
def load(fnames, tag=None, sat_id=None): """Load CHAMP STAR files Parameters ------------ fnames : (pandas.Series) Series of filenames tag : (str or NoneType) tag or None (default=None) sat_id : (str or NoneType) satellite id or None (default=None) Returns -----...
def _assign_funcs(self, by_name=False, inst_module=None): """Assign all external science instrument methods to Instrument object. """ import importlib # set defaults self._list_rtn = self._pass_func self._load_rtn = self._pass_func self._default_rtn = self...
def _load_data(self, date=None, fid=None): """ Load data for an instrument on given date or fid, dependng upon input. Parameters ------------ date : (dt.datetime.date object or NoneType) file date fid : (int or NoneType) filename index value ...
def _load_next(self): """Load the next days data (or file) without incrementing the date. Repeated calls will not advance date/file and will produce the same data Uses info stored in object to either increment the date, or the file. Looks for self._load_by_date flag. ...
def _load_prev(self): """Load the next days data (or file) without decrementing the date. Repeated calls will not decrement date/file and will produce the same data Uses info stored in object to either decrement the date, or the file. Looks for self._load_by_date flag. ...
def load(self, yr=None, doy=None, date=None, fname=None, fid=None, verifyPad=False): """Load instrument data into Instrument object .data. Parameters ---------- yr : integer year for desired data doy : integer day of year date : date...
def download(self, start, stop, freq='D', user=None, password=None, **kwargs): """Download data for given Instrument object from start to stop. Parameters ---------- start : pandas.datetime start date to download data stop : pandas.datetime ...
def next(self, verifyPad=False): """Manually iterate through the data loaded in Instrument object. Bounds of iteration and iteration type (day/file) are set by `bounds` attribute. Note ---- If there were no previous calls to load then the first...
def _get_var_type_code(self, coltype): '''Determines the two-character type code for a given variable type Parameters ---------- coltype : type or np.dtype The type of the variable Returns ------- str The variable type code for the given ...