Fixed documentation issues

Signed-off-by: Devansh Agarwal <[email protected]>
thepetabyteproject · Jan 20, 2021 · 726c3b9 · 726c3b9
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diff --git a/README.md b/README.md
@@ -78,7 +78,7 @@ Here are some [tutorial notebooks](https://github.com/devanshkv/your/tree/master
 We welcome all types of code contribution. Please have a look at our [guideline](CONTRIBUTING.md) and [code of conduct](CODE_OF_CONDUCT.md).
 
 # Citation
-If you use `Your`, please cite our [JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.02750): [![status](https://joss.theoj.org/papers/798844ebd352f563de28bb75515da674/status.svg?style=flat-square)](https://joss.theoj.org/papers/798844ebd352f563de28bb75515da674)
+If you use `Your`, please cite our [JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.02750):
 
 ```bash
 @article{Aggarwal2020,

diff --git a/docs/autogen.py b/docs/autogen.py
@@ -153,7 +153,7 @@
 mdFile.create_md_file()
 
 # Convert all note tabs so that it looks cooler with the material theme
-linebreaker_list = ["Args:", "Examples:", "Returns:", "Attributes:"]
+linebreaker_list = ["Args:", "Examples:", "Returns:", "Attributes:", "Raises:"]
 
 for dname, dirs, files in os.walk("sources"):
     for fname in files:

diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml
@@ -22,7 +22,7 @@ nav:
   - Reference API:
       - Core:
           - Your: your.md
-          - Candiate: candidate.md
+          - Candidate: candidate.md
           - Writer: writer.md
       - Formats:
           - Psrdada: formats/psrdada.md

diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -1,5 +1,5 @@
-keras-autodoc>=0.6.0
+keras-autodoc>=0.7.0
 mkdocs>=1.1.2
-mkdocs-material>=6.0
+mkdocs-material>=6.2.5
 argmark>=0.1
-mkdocs-jupyter>=0.13.0
+mkdocs-jupyter>=0.15.1
diff --git a/your/__init__.py b/your/__init__.py
@@ -1,4 +1,4 @@
 from your.writer import *
 from your.your import *
 
-__version__ = "0.6.0"
+__version__ = "0.6.1"
diff --git a/your/candidate.py b/your/candidate.py
@@ -16,7 +16,7 @@ class Candidate(Your):
     Candidate Class
 
     Args:
-        fp Union[str, List]: String or a list of files. It can either filterbank or psrfits files.
+        fp Union[str, list]: String or a list of files. It can either filterbank or psrfits files.
         dm (float): Dispersion Measure of the candidate
         tcand (float): start time of the candidate in seconds at the highest frequency channel
         width (int): pulse width of the candidate in samples
@@ -134,7 +134,7 @@ def dispersion_delay(self, dms=None):
         Calculate the dispersion delay for the candidate DM or at given dispersion DM
 
         Args:
-            dms (Union[float,np.ndarray]) : DM or a list of DMs
+            dms (Union[float,np.ndarray]): DM or a list of DMs
 
         Returns:
             Union[float, np.ndarray]: dispersion delay in seconds
@@ -342,7 +342,7 @@ def dmtime(self, dmsteps=256, target="CPU"):
             Our method rolls the data around while dedispersing it.
 
         Args:
-            dmsteps (int) : Number of DMs to dedisperse at.
+            dmsteps (int): Number of DMs to dedisperse at.
             target (str): 'CPU' to run the code on the CPU or 'GPU' to run it on a GPU.
 
         """
@@ -361,7 +361,7 @@ def get_snr(self, time_series=None):
         Calculates the SNR of the candidate
 
         Args:
-            time_series (np.ndarray) : time series array to calculate the SNR of
+            time_series (np.ndarray): time series array to calculate the SNR of
 
         Returns:
             float: SNR
@@ -387,7 +387,7 @@ def optimize_dm(self):
             This function has not been fully tested.
 
         Returns:
-            optimnised DM, optimised SNR
+            Optimized DM, optimised SNR
         """
         if self.data is None:
             return None
@@ -457,7 +457,7 @@ def resize(self, key, size, axis, **kwargs):
         Args:
             key (str): Keywords to chose which data to resize ('dmt' or 'ft')
             size: Final size of the data array required
-            axis (int) : Axis to resize alone
+            axis (int): Axis to resize alone
             **kwargs: Arguments for skimage.transform resize function
 
         """

diff --git a/your/formats/dada.py b/your/formats/dada.py
@@ -18,9 +18,7 @@ class DadaManager:
     Args:
 
         size (int): size of each buffer (in bytes)
-
         key (hex): hexadecimal dada key
-
         n_readers (int): Number of dada readers.
     """
 
@@ -58,7 +56,6 @@ def dump_data(self, data_input):
         Dump the data to the buffer
 
         Args:
-
             data_input (numpy.ndarray): Numpy array of the data.
 
         """

diff --git a/your/formats/filwriter.py b/your/formats/filwriter.py
@@ -94,25 +94,25 @@ def make_sigproc_object(
     Create a Sigprocfile from scratch.
 
     Args:
-        rawdatafile (str) : Raw file name
-        source_name (str) : Source Name
-        nchans (int) : Number of channels
-        foff (float) : Channel Bandwidth (MHz)
-        fch1 (float) : Frequncy of first channel (MHz)
-        tsamp (float) : Sampling interval (seconds)
-        tstart (float) : MJD of the start sample
-        src_raj (float) : RA of the source in format HHMMSS.SS
-        src_dej (float) : Dec of source in format DDMMSS.SS
-        machine_id (int) : Machine ID
-        nbeams (int) : Number of beams in the rcvr
-        ibeam (int) : Beam number
-        nbits (int) : Number of bits
-        nifs (int) : Number of IFs
-        barycentric (int) : 0 for not barycentered data, 1 otherwise.
-        pulsarcentric (int) : 0 for not pulsarcentered data, 1 otherwise.
-        telescope_id (int) : Telescope ID
-        data_type (int) : Data Type
-        az_start (float) : Azimuth Angle start
+        rawdatafile (str): Raw file name
+        source_name (str): Source Name
+        nchans (int): Number of channels
+        foff (float): Channel Bandwidth (MHz)
+        fch1 (float): Frequncy of first channel (MHz)
+        tsamp (float): Sampling interval (seconds)
+        tstart (float): MJD of the start sample
+        src_raj (float): RA of the source in format HHMMSS.SS
+        src_dej (float): Dec of source in format DDMMSS.SS
+        machine_id (int): Machine ID
+        nbeams (int): Number of beams in the rcvr
+        ibeam (int): Beam number
+        nbits (int): Number of bits
+        nifs (int): Number of IFs
+        barycentric (int): 0 for not barycentered data, 1 otherwise.
+        pulsarcentric (int): 0 for not pulsarcentered data, 1 otherwise.
+        telescope_id (int): Telescope ID
+        data_type (int): Data Type
+        az_start (float): Azimuth Angle start
         za_start (float):  Zenith Angle start
 
     Returns:

diff --git a/your/formats/psrfits.py b/your/formats/psrfits.py
@@ -34,7 +34,7 @@ def unpack_2bit(data):
     Unpack 2-bit data that has been read in as bytes.
 
     Args:
-        data (np.ndarray) : array of unsigned 2-bit ints packed into an array of bytes.
+        data (np.ndarray): array of unsigned 2-bit ints packed into an array of bytes.
 
     Returns:
         np.ndarray: unpacked array. The size of this array will be four times the size of the input data.
@@ -52,7 +52,7 @@ def unpack_4bit(data):
     Unpack 4-bit data that has been read in as bytes.
 
     Args:
-        data (np.ndarray) : array of unsigned 4-bit ints packed into an array of bytes.
+        data (np.ndarray): array of unsigned 4-bit ints packed into an array of bytes.
 
     Returns:
         np.ndarray: unpacked array. The size of this array will be twice the size of the input data.
@@ -81,7 +81,7 @@ class PsrfitsFile(object):
         specinfo (obj): Object of class SpectraInfo for the given file list
         header (list): Header of the fits file
         source_name (str): Source Name
-        machine_id (int) : Machine ID
+        machine_id (int): Machine ID
         barycentric (int): If 1 the data is barycentered
         pulsarcentric (int): Is the data in pulsar's frame of reference?
         src_raj (float): RA of the source (HHMMSS.SS)
@@ -143,7 +143,7 @@ def nspectra(self):
         """
 
         Returns:
-            int : Total number of spectra in all files in filelist
+            int: Total number of spectra in all files in filelist
 
         """
         return int(self.specinfo.spectra_per_subint * np.sum(self.specinfo.num_subint))
@@ -153,7 +153,7 @@ def native_nspectra(self):
         Native number of total spectra in all the files. This will be made a property so that it can't be overwritten
 
         Returns:
-            int : Total number of spectra in all files in filelist
+            int: Total number of spectra in all files in filelist
 
         """
         return int(self.specinfo.spectra_per_subint * np.sum(self.specinfo.num_subint))
@@ -163,7 +163,7 @@ def native_tsamp(self):
         This will be made a property so that it can't be overwritten.
 
         Returns:
-            float : Native sampling time of the file.
+            float: Native sampling time of the file.
 
         """
         return self.specinfo.dt
@@ -173,7 +173,7 @@ def native_foff(self):
         This will be made a property so that it can't be overwritten.
 
         Returns:
-             float : Native channel bandwidth
+             float: Native channel bandwidth
 
         """
         return self.bw / self.nchan
@@ -196,13 +196,13 @@ def read_subint(
         Applys scales, weights, and offsets to the data.
 
         Args:
-            isub (int) : index of subint (first subint is 0)
-            apply_weights (bool) : If True, apply weights. (Default: apply weights)
-            apply_scales (bool) : If True, apply scales. (Default: apply scales)
-            apply_offsets (bool) : If True, apply offsets. (Default: apply offsets)
+            isub (int): index of subint (first subint is 0)
+            apply_weights (bool): If True, apply weights. (Default: apply weights)
+            apply_scales (bool): If True, apply scales. (Default: apply scales)
+            apply_offsets (bool): If True, apply offsets. (Default: apply offsets)
 
         Returns:
-            np.ndarray : Subint data with scales, weights, and offsets applied in float32 dtype with shape (nsamps,nchan).
+            np.ndarray: Subint data with scales, weights, and offsets applied in float32 dtype with shape (nsamps,nchan).
 
         """
         sdata = self.fits["SUBINT"].data[isub]["DATA"]
@@ -278,10 +278,10 @@ def get_weights(self, isub):
         Return weights for a particular subint.
 
         Args:
-           isub (int) : index of subint (first subint is 0)
+           isub (int): index of subint (first subint is 0)
 
         Returns:
-            np.ndarray : Subint weights. (There is one value for each channel)
+            np.ndarray: Subint weights. (There is one value for each channel)
 
         """
         return self.fits["SUBINT"].data[isub]["DAT_WTS"]
@@ -291,10 +291,10 @@ def get_scales(self, isub):
         Return scales for a particular subint.
 
         Args:
-             isub (int) : index of subint (first subint is 0)
+             isub (int): index of subint (first subint is 0)
 
         Returns:
-            np.ndarray : Subint scales. (There is one value for each channel)
+            np.ndarray: Subint scales. (There is one value for each channel)
 
         """
         return self.fits["SUBINT"].data[isub]["DAT_SCL"]
@@ -304,10 +304,10 @@ def get_offsets(self, isub):
         Return offsets for a particular subint.
 
         Args:
-            isub (int) : index of subint (first subint is 0)
+            isub (int): index of subint (first subint is 0)
 
         Returns:
-            np.ndarray : Subint offsets. (There is one value for each channel)
+            np.ndarray: Subint offsets. (There is one value for each channel)
 
         """
         return self.fits["SUBINT"].data[isub]["DAT_OFFS"]
@@ -317,12 +317,12 @@ def get_data(self, nstart, nsamp, pol=0):
         Return 2D array of data from PSRFITS files.
 
         Args:
-            nstart (int) : Starting sample
-            nsamp (int) : number of samples to read
-            pol (int) : which polarization to return
+            nstart (int): Starting sample
+            nsamp (int): number of samples to read
+            pol (int): which polarization to return
 
         Returns:
-            np.ndarray : Time-Frequency numpy array
+            np.ndarray: Time-Frequency numpy array
 
         """
         # Calculate starting subint and ending subint
@@ -427,7 +427,7 @@ class SpectraInfo:
     Class to read the header of fits files
 
     Args:
-        filenames (list) : list of fits files
+        filenames (list): list of fits files
     """
 
     def __init__(self, filenames):

diff --git a/your/formats/pysigproc.py b/your/formats/pysigproc.py
@@ -27,7 +27,7 @@ class SigprocFile(object):
 
         rawdatafile (str): Raw data file
         source_name (str): Source Name
-        machine_id (int) : Machine ID
+        machine_id (int): Machine ID
         barycentric (int): If 1 the data is barycentered
         pulsarcentric (int): Is the data in pulsar's frame of reference?
         src_raj (float): RA of the source (HHMMSS.SS)
@@ -230,7 +230,8 @@ def read_header(self, fp=None):
     def dtype(self):
         """
 
-        Returns: dtype of the data
+        Returns:
+            dtype of the data
 
         """
         if self.nbits == 8:
@@ -246,15 +247,17 @@ def dtype(self):
     def bytes_per_spectrum(self):
         """
 
-        Returns: bytes per spectrum
+        Returns:
+            bytes per spectrum
 
         """
         return self.nbits * self.nchans * self.nifs / 8
 
     def nspectra(self):
         """
 
-        Returns: Number of specrta in the file
+        Returns:
+            Number of specrta in the file
 
         """
         return (self._mmdata.size() - self.hdrbytes) / self.bytes_per_spectrum
@@ -264,7 +267,8 @@ def native_nspectra(self):
 
         Native number of spectra in the file. This will be made a property so that it can't be overwritten
 
-        Returns:Number of specrta in the file
+        Returns:
+            Number of specrta in the file
 
         """
 
@@ -378,7 +382,7 @@ def append_spectra(spectra, filename):
         Append spectra to the end of the file
 
         Args:
-            spectra (numpy.ndarray) : numpy array of the data to be dumped into the filterbank file
+            spectra (numpy.ndarray): numpy array of the data to be dumped into the filterbank file
             filename (str): name of the filterbank file
         """
         with open(filename, "ab") as f:

diff --git a/your/utils/heimdall.py b/your/utils/heimdall.py
@@ -58,9 +58,9 @@ class HeimdallManager:
         filename (str): process specified SIGPROC filterbank file
         verbosity (str): v, V, g, G increase verbosity level
         nsamps_gulp (int): number of samples to be read at a time
-        beam (int) : over-ride beam number
+        beam (int): over-ride beam number
         baseline_length (float): number of seconds over which to smooth the baseline
-        output_dir (str) : create all output files in specified path
+        output_dir (str): create all output files in specified path
         dm (list): min and max DM
         dm_tol (float): SNR loss tolerance between each DM trial
         zap_chans (int): zap all channels between start and end channels inclusive