tawhiri package¶

Submodules¶

tawhiri.dataset module¶

Open a wind dataset from file by memory-mapping

Datasets downloaded from the NOAA are stored as large binary files that are memmapped into the predictor process and thereby treated like a huge array.

Dataset contains some utility methods to find/list datasets in a directory, and can open (& create) dataset files.

Note: once opened, the dataset is mmaped as Dataset.array, which by itself is not particularly useful. tawhiri.interpolate casts it (via a memory view) to a pointer in Cython.

class tawhiri.dataset.Dataset[source]¶

A wind dataset

__init__(ds_time, directory='/srv/tawhiri-datasets', new=False)[source]¶

Open the dataset file for ds_time, in directory

Parameters:	directory (string) – directory containing the dataset ds_time (`datetime.datetime`) – forecast time new (bool) – should a new (blank) dataset be created (overwriting any file that happened to already be there), or should an existing dataset be opened?

See also

open_latest()

After initalisation, the following attributes are available:

array¶: A mmap.mmap object; the entire dataset mapped into memory.

ds_time¶: The forecast time of this dataset (datetime.datetime).

…and this method:

close()[source]¶

Close the dataset

This deletes array, thereby releasing (a) reference to it. Note that other objects may very well hold a reference to the array, keeping it open.

(The file descriptor is closed as soon as the dataset is mapped.)

The following attributes are class attributes:

shape = (65, 47, 3, 361, 720)¶

The dimensions of the dataset

Note len(axes[i]) == shape[i].

axes¶

The values of the points on each axis: a 5-(named)tuple (hour, pressure variable, latitude, longitude).

For example, axes.pressure[4] is 900—points in cells dataset.array[a][4][b][c][d] correspond to data at 900mb.

element_type = 'float32'¶: The data type of dataset elements

element_size = 4¶: The size in bytes of element_type

size = 9528667200¶: The size in bytes of the entire dataset

SUFFIX_GRIBMIRROR = '.gribmirror'¶: The filename suffix for “grib mirror” files

DEFAULT_DIRECTORY = '/srv/tawhiri-datasets'¶: The default location of wind data

These “utility” class methods are available:

classmethod filename(ds_time, directory='/srv/tawhiri-datasets', suffix='')[source]¶

Returns the filename under which we expect to find a dataset

... for forecast time ds_time, in directory with an optional suffix

Parameters:	directory (string) – directory in which dataset resides/will reside ds_time (`datetime.datetime`) – forecast time
Return type:	string

classmethod listdir(directory='/srv/tawhiri-datasets', only_suffices=None)[source]¶

Scan for datasets in directory

... with filenames matching those generated by filename() and (optionally) filter by only looking for certian suffices.

Parameters:	directory (string) – directory to search in only_suffices (set) – if not `None`, only return results with a suffix contained in this set
Return type:	(named) tuples `(dataset time, suffix, filename, full path)`

classmethod open_latest(directory='/srv/tawhiri-datasets', persistent=False)[source]¶

Find the most recent datset in directory, and open it

Parameters:	directory (string) – directory to search persistent (bool) – should the latest dataset be cached, and re-used?
Return type:	`Dataset`

tawhiri.download module¶

tawhiri.interpolate module¶

tawhiri.interpolate.make_interpolator(dataset)¶

Produce a function that can get wind data from dataset (a tawhiri.dataset.Dataset).

This function returns a closure:

closure.f(hour, alt, lat, lng)¶

Returns:	delta lat, lon and alt

tawhiri.models module¶

Provide all the balloon models, termination conditions and functions to combine models and termination conditions.

tawhiri.models.float_profile(ascent_rate, float_altitude, stop_time, dataset)[source]¶: Make a model chain for the typical floating balloon situation of ascent at constant altitude to a float altitude which persists for some amount of time before stopping. Descent is in general not modelled.

tawhiri.models.make_any_terminator(terminators)[source]¶: Return a terminator that terminates when any of terminators would terminate.

tawhiri.models.make_burst_termination(burst_altitude)[source]¶: Return a burst-termination criteria, which terminates integration when the altitude reaches burst_altitude.

tawhiri.models.make_constant_ascent(ascent_rate)[source]¶: Return a constant-ascent model at ascent_rate (m/s)

tawhiri.models.make_drag_descent(sea_level_descent_rate)[source]¶

Return a descent-under-parachute model with sea level descent sea_level_descent_rate (m/s). Descent rate at altitude is determined using an altitude model courtesy of NASA: http://www.grc.nasa.gov/WWW/K-12/airplane/atmosmet.html

For a given altitude the air density is computed, a drag coefficient is estimated from the sea level descent rate, and the resulting terminal velocity is computed by the returned model function.

tawhiri.models.make_elevation_data_termination(dataset=None)[source]¶: A termination criteria which terminates integration when the altitude goes below ground level, using the elevation data in dataset (which should be a ruaumoko.Dataset).

tawhiri.models.make_linear_model(models)[source]¶: Return a model that returns the sum of all the models in models.

tawhiri.models.make_time_termination(max_time)[source]¶: A time based termination criteria, which terminates integration when the current time is greater than max_time (a UNIX timestamp).

tawhiri.models.make_wind_velocity(dataset)[source]¶: Return a wind-velocity model, which gives lateral movement at the wind velocity for the current time, latitude, longitude and altitude. The dataset argument is the wind dataset in use.

tawhiri.models.sea_level_termination(t, lat, lng, alt)[source]¶

A termination criteria which terminates integration when the altitude is less than (or equal to) zero.

Note that this is not a model factory.

tawhiri.models.standard_profile(ascent_rate, burst_altitude, descent_rate, wind_dataset, elevation_dataset)[source]¶

Make a model chain for the standard high altitude balloon situation of ascent at a constant rate followed by burst and subsequent descent at terminal velocity under parachute with a predetermined sea level descent rate.

Requires the balloon ascent_rate, burst_altitude and descent_rate, and additionally requires the dataset to use for wind velocities.

Returns a tuple of (model, terminator) pairs.

tawhiri.solver module¶

tawhiri.solver.solve(t, lat, lng, alt, chain)¶: Solve from initial conditions t, lat, lng and alt, using models and termination criteria from chain, an iterable of (model, terminator) pairs which make up each stage of the flight.