vip_hci.config package¶
Submodules¶
vip_hci.config.mem module¶
System memory related functions
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vip_hci.config.mem.check_enough_memory(input_bytes, factor=1, raise_error=True, error_msg='', verbose=True)[source]¶ Check if
input_bytesare larger than system’s available memory timesfactor. This function is used to check the inputs (largest ones such as multi-dimensional cubes) of algorithms and avoid system/Python crashes or heavy swapping.Parameters: - input_bytes (float) – The size in bytes of the inputs of a given function.
- factor (float, optional) – Scales how much memory is needed in terms of the size of input_bytes.
- raise_error (bool, optional) – If True, a RuntimeError is raised when the condition is not met.
- error_msg (str, optional) – [raise_error=True] To be appended to the message of the RuntimeError.
- verbose (bool, optional) – If True, information about the available memory is printed out.
vip_hci.config.param module¶
Dictionaries with telescope/instrument parameters.
Usage¶
from vip_hci.config import VLT_NACO
lbda = VLT_NACO['lambdal']
diameter = VLT_NACO['diam']
pxscale = VLT_NACO['plsc']
resel = lambda/diameter*206265/pxscale
vip_hci.config.timing module¶
Functions for timing other functions/procedures.
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vip_hci.config.timing.time_ini(verbose=True)[source]¶ Set and print the time at which the script started.
Returns: start_time – Starting time. Return type: string
vip_hci.config.utils_conf module¶
Module with utilities.
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class
vip_hci.config.utils_conf.Progressbar[source]¶ Bases:
objectShow progress bars. Supports multiple backends.
Examples
from vip_hci.var import Progressbar Progressbar.backend = "tqdm" from time import sleep for i in Progressbar(range(50)): sleep(0.02) # or: bar = Progressbar(total=50): for i in range(50): sleep(0.02) bar.update() # Progressbar can be disabled globally using Progressbar.backend = "hide" # or locally using the ``verbose`` keyword: Progressbar(iterable, verbose=False)
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backend= 'pyprind'¶
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vip_hci.config.utils_conf.check_array(input_array, dim, msg=None)[source]¶ Checks the dimensionality of input. In case the check is not successful, a TypeError is raised.
Parameters: - input_array (list, tuple or np.ndarray) – Input data.
- dim (int or tuple) – Number of dimensions that
input_arrayshould have.dimcan take one of these values: 1, 2, 3, 4, (1,2), (2,3), (3,4) or (2,3,4). - msg (str, optional) – String to be used in the error message (
input_arrayname).
Module contents¶
Subpackage conf contains configuration functions and internal utilities. It
also contains a dictionary with parameters of high-contrast imaging instruments.