How does one set the power spectral density (PSD) from file and is it possible to use a different PSD for generating the data and for likelihood evaluation?
Question asked by Vivien Raymond by email.
Setting the PSD from file
To set the PSD from a file, first initialise a list of interferometers, here we just use Hanford:
>>> ifos = bilby.gw.detector.InterferometerList(['H1'])
Every element of the list is initialised with a default PSD using the advanced LIGO noise curve, to check this
>>> ifos[0].power_spectral_density
PowerSpectralDensity(psd_file='/home/user1/miniconda3/lib/python3.6/site-packages/bilby-0.3.5-py3.6.egg/bilby/gw/noise_curves/aLIGO_ZERO_DET_high_P_psd.txt', asd_file='None')
Note, no data has yet been generated. To overwrite the PSD,simply create a new PowerSpectralDensity object and assign it (if you have multiple detectors, you'll need to do this for every element of the list)
ifos[0].power_spectral_density = bilby.gw.detector.PowerSpectralDensity(psd_file=PATH_TO_FILE)
Nest, generate an instance of the strain data from the PSD:
ifos.set_strain_data_from_power_spectral_densities(
sampling_frequency=4096, duration=4,
start_time=-3)
You can check what the data looks like by doing
ifos[0].plot_data()
Note, you can also inject signals using the ifos.inject_signal method.
Using a different PSD for likelihood evaluation
Each ifo in the ifos list contains both the data and a PSD (or equivalent ASD). For inference, we pass that list into the bilby.gw.GravitationalWaveLikelihood object as the first argument and the PSD for each element of the list is used in calculating the likelihood.
So, if you want to use a different PSD for likelihood estimate. First generate the data (as above). Then, assign the PSD you want to use for sampling to each element of ifos and pass that object into the likelihood instead. This won't overwrite the data (provided you don't call set_strain_data_from_power_spectral_densities of course).
Related
I know gdb has several means of exploring data, some of them quite convenient. However, I cannot combine them to get that I need/want. I would like to display some custom string based on the first n values of a big array starting at <PT_arr>, and the last m values of the same array at a distance (in this case) 4096. Looking something like this:
table beginning:
0x804cfe0 <PT_arr>: 0x00100300 0x00200300 0x00300300 0x00400300
table end:
0x804cfe0 <PT_arr+4064>: 0x00500300 0x00600300 0x00700300 0x00800300
printf let's me add custom text (like table beginning)
the examine x gives me that nice alignment, let's me read many elements and group them by byte, words, etc; and shows addresses at the left (which is ideal for my case).
x aligns the content of regions of memory in an easy to read manner with the size and unit parameters. (what I want)
display is constantly printing. (what I want).
The issue with display (manual), is that unlike examine x (manual) it doesn't have a size or unit parameter.
Is there a way to accomplish that?
Thanks.
Is it possible to inject a signal by itself with no coloured Gaussian noise?
Question asked by Arunava Mukherjee via email
Yes. There are two easy ways to do this.
1) Use the existing helper functions
When generating an interferometer object, bilby provides several helper routines denoted by bilby.gw.detector.get_interferometer_with.... In this case, you'll want to use this function (I've truncated the doctring)
bilby.gw.detector.get_interferometer_with_fake_noise_and_injection(
name, injection_parameters, injection_polarizations=None,
waveform_generator=None, sampling_frequency=4096, duration=4,
start_time=None, outdir='outdir', label=None, plot=True, save=True,
zero_noise=False)
Docstring:
Helper function to obtain an Interferometer instance with appropriate
power spectral density and data, given an center_time.
Note: by default this generates an Interferometer with a power spectral
density based on advanced LIGO.
Parameters
----------
name: str
Detector name, e.g., 'H1'.
...
zero_noise: bool
If true, set noise to zero.
So you just pass the flag in and it will create an interferometer with just the injection signal (you'll then need to make one for each interferometer you want in the list of interferometers passed in to the likelihood.
2) Use the low level set strain data methods
Alternatively, you may instead wish to use the low level methods themselves. As a general rule of thumb, you can always look at the source code for the generic helper functions to figure out how this should be done. Here, we create a H1 interferometer set the strain data with zero noise and inject a signal:
interferometer = get_empty_interferometer("H1")
interferometer.power_spectral_density = PowerSpectralDensity.from_aligo()
interferometer.set_strain_data_from_zero_noise(
sampling_frequency=sampling_frequency, duration=duration,
start_time=start_time)
injection_polarizations = interferometer.inject_signal(
parameters=injection_parameters,
waveform_generator=waveform_generator)
Information correct as of v.0.3.5
I am using Paraview 5.0.1. If any solution requires updating, I can try.
I want to programmatically obtain field plots (and corresponding PlotOverLine) of displacements and stresses in rotated coordinate systems.
What are appropriate/convenient/possible ways of doing this?
So far, I have created one Calculator filter for each component of displacements and stresses.
For instance, I used Calculators in 2D with results
(displacement.iHat)*cos(0.7853981625)+(displacement.jHat)*sin(0.7853981625)
(stress_3-stress_0)*sin(45.0*3.14159265/180)*cos(45.0*3.14159265/180)+stress_1*((cos(45.0*3.14159265/180))^2-(sin(45.0*3.14159265/180))^2)
It works fine, but it is quite cumbersome, in several aspects:
Creating them (one filter per component).
Plotting several of them in a single XY plot
Exporting them (one export per component).
Is there a simple way to do this?
PS: The Transform filter does not accomplish this. It rotates the view, not the fields.
Two solutions:
Ugly, inneficient solution
Use Transform and check "Transform All Input vectors"
Add a calculator and add a dummy array
Use transform the other way around, without checking "Transform All Input vectors"
Correct solution :
Compute the transformation yourself in a programmable filter
input = self.GetUnstructuredGridInput();
output = self.GetUnstructuredGridOutput();
output.ShallowCopy(input)
data = input.GetPointData().GetArray("YourArray")
vec = vtk.vtkDoubleArray();
vec.SetNumberOfComponents(3);
vec.SetName("TransformedVectors");
numPoints = input.GetNumberOfPoints()
for i in xrange(0, numPoints):
tuple = data.GetTuple(i)
transform(tuple) # implement the transform in python
vec.InsertNextTuple(tuple)
output.GetPointData().AddArray(vec)
I'm looking at implementing a Caffe CNN which accepts two input images and a label (later perhaps other data) and was wondering if anyone was aware of the correct syntax in the prototxt file for doing this? Is it simply an IMAGE_DATA layer with additional tops? Or should I use separate IMAGE_DATA layers for each?
Thanks,
James
Edit: I have been using the HDF5_DATA layer lately for this and it is definitely the way to go.
HDF5 is a key value store, where each key is a string, and each value is a multi-dimensional array. Thus, to use the HDF5_DATA layer, just add a new key for each top you want to use, and set the value for that key to store the image you want to use. Writing these HDF5 files from python is easy:
import h5py
import numpy as np
filelist = []
for i in range(100):
image1 = get_some_image(i)
image2 = get_another_image(i)
filename = '/tmp/my_hdf5%d.h5' % i
with hypy.File(filename, 'w') as f:
f['data1'] = np.transpose(image1, (2, 0, 1))
f['data2'] = np.transpose(image2, (2, 0, 1))
filelist.append(filename)
with open('/tmp/filelist.txt', 'w') as f:
for filename in filelist:
f.write(filename + '\n')
Then simply set the source of the HDF5_DATA param to be '/tmp/filelist.txt', and set the tops to be "data1" and "data2".
I'm leaving the original response below:
====================================================
There are two good ways of doing this. The easiest is probably to use two separate IMAGE_DATA layers, one with the first image and label, and a second with the second image. Caffe retrieves images from LMDB or LEVELDB, which are key value stores, and assuming you create your two databases with corresponding images having the same integer id key, Caffe will in fact load the images correctly, and you can proceed to construct your net with the data/labels of both layers.
The problem with this approach is that having two data layers is not really very satisfying, and it doesn't scale very well if you want to do more advanced things like having non-integer labels for things like bounding boxes, etc. If you're prepared to make a time investment in this, you can do a better job by modifying the tools/convert_imageset.cpp file to stack images or other data across channels. For example you could create a datum with 6 channels - the first 3 for your first image's RGB, and the second 3 for your second image's RGB. After reading this in using the IMAGE_DATA layer, you can split the stream into two images using a SLICE layer with a slice_point at index 3 along the slice_dim = 1 dimension. If further down the road, you decide that you want to load even more complex assortments of data, you'll understand the encoding scheme and can write your own decoding layer based off of src/caffe/layers/data_layer.cpp to gain full control of the pipeline.
You may also consider using HDF5_DATA layer with multiple "top"s
I am trying to save an image using opencv cvSaveImage function. The problem is that I am performing a DCT on the image and then changing the coefficients that are obtained after performing the DCT, after that I am performing an inverse DCT to get back the pixel values. But this time I get the pixel values in Decimals(e.g. 254.34576). So when I save this using cvSaveImage function it discards all the values after decimals(e.g. saving 254.34576 as 254) and saves the image. Due to this my result gets affected. Please Help
"The function cvSaveImage saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. If the format, depth or channel order is different, use cvCvtScale and cvCvtColor to convert it before saving, or use universal cvSave to save the image to XML or YAML format."
I'd suggest investigating the cvSave function.
HOWEVER, a much easier way is to just write your own save/load functions, this would be very easy:
f = fopen("image.dat","wb");
fprintf(f,"%d%d",width,height);
for (y=0 to height)
for (x=0 to width)
fprintf(f,"%f",pixelAt(x,y));
And a corresponding mirror function for reading.
P.S. Early morning and I can't remember for the life of me if fprintf works with binary files. But you get the idea. You could use fwrite() instead.