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ChangeLog
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2015-11-06 NOTE
This Changelog is now abandoned. Use git log instead.
2015-11-06 Gerrit Holl <[email protected]>
* pyatmlab-0-0-96
* pyatmlab/constants.py: Add nano and giga
* pyatmlab/datasets/tovs.py: Add clarification comment
* pyatmlab/db.py: Initialise fromDir from existing argdict.
Fix bug with db clear.
* pyatmlab/physics.py(SRF): Add methods for string representation and
SRF shift
* pyatmlab/tools.py(mutable_cache): Comment out unreachable code and
fix bug
2015-09-15 Gerrit Holl <[email protected]>
* pyatmlab-0-0-95
* pyatmlab/db.py:
- Use progressbars, yahoo!
2015-08-25 Gerrit Holl <[email protected]>
* pyatmlab-0-0-94
* doc/source/index.rst: Small fixes
* pyatmlab/arts/_handlers(Matrix):
- Correct order of dimensions
* pyatmlab/arts/xml.py:
- Remove unused classes
* pyatmlab/collocations.py(SamePlatformCollocatedDataset):
- Start skeleton class for AVHRR/HIRS. No content yet.
* pyatmlab/constants.py:
- Add constant for tera
* pyatmlab/dataset.py(MultiFileDataset):
- In preparating for HIRS, use and propagate an **extra set of
keyword arguments, to be used to pass meta-information such as what
satellite a sensor part of a series belongs to.
* pyatmlab/datasets/tovs.py:
(HIRS):
- Copy over some information on headers and line. Not very tested
yet.
(IASI):
- Introduce tolerance in wavenumber equivalence testing, due to loss
of precision when storing this information in text on disk and going
back and forth to and from frequencies.
* pyatmlab/db.py:
- Add binning based on PCA. This affects many methods in several
classes.
* pyatmlab/tools.py(find_next_time_instant):
- Started work on new function, unfinished and untested.
2015-08-07 Gerrit Holl <[email protected]>
* pyatmlab-0-0-93
* pyatmlab/arts/*.py:
- New package with functionality to read ArtsXML data.
* doc/source/index.rst:
- Add new package arts and new module arts.xml
* pyatmlab/datasets/tovs.py(IASI):
- Bugfix
* pyatmlab/db.py:
- Reimplement lookup table. Functionality now distributed over a
number of different classes, depending on small (in-memory) or large
(on-disk) and on what is done with the cells (store all, store one,
store stats).
* pyatmlab/physics.py:
- Several small bugfixes
* setup.py:
- Also consider pyatmlab.arts package
2015-07-21 Gerrit Holl <[email protected]>
* pyatmlab-0-0-92
* pyatmlab/instruments.py:
- Point out those are theoretical/idealised instruments, not suitable
for actual SRFs.
* pyatmlab/physics.py(SRF):
- Added class where I consolidate functionality related to real SRFs.
2015-07-20 Gerrit Holl <[email protected]>
* pyatmlab-0-0-91
* pyatmlab/io.py(read_arts_srf):
- Also return centres
* pyatmlab/physics:
(planck_f):
- Add function to calculate Planck function (per frequency)
(estimate_effective_temperature):
- Calculate effective temperature according to Weinreb et al. (1981).
This is to be used in polychromatic radiance to brightness
temperature conversions.
2015-07-16 Gerrit Holl <[email protected]>
* pyatmlab-0-0-90
* pyatmlab/physics.py(spectral_to_channel_bt):
- Added note that the physics here is incorrect and that the
calculation needs to change.
- Added missing return statement, oops.
2015-07-14 Gerrit Holl <[email protected]>
* pyatmlab-0-0-89
* pyatmlab/constants.py: Add micro=1e-6
* pyatmlab/datasets.tovs(HIRS*): Add satellites
* pyatmlab/physics.py(specrad_frequency_to_planck_bt): Bugfix
2015-07-13 Gerrit Holl <[email protected]>
* pyatmlab-0-0-88
* pyatmlab/datasets/tovs.py(IASI._read):
- Be more verbose with DEBUG logging
* pyatmlab/physics.py:
- Moved constants out of 'c.' module again, to aid numexpr.
(specrad_frequency_to_brightness_temperature):
- Severe speedup using numexpr. For a single IASI granule (145,190,760
radiances), wall time to run this on a JASMIN node is reduced from 25
seconds to 2 seconds.
(spectral_to_channel_bt):
- Similar speedup as above, but rather from ~2 seconds to ~0.2
seconds. As this may need to be run for each channel the total
speedup is similar.
2015-07-10 Gerrit Holl <[email protected]>
* pyatmlab-0-0-87
* pyatmlab/physics.py(specrad_to_channel_bt):
- Added function to calculate channel BT from spectral radiances
2015-07-09 Gerrit Holl <[email protected]>
* pyatmlab-0-0-86
* pyatmlab/config.py:
- Use extended interpolation
- Always load configuration
* pyatmlab/constants.py:
- Add centi
* pyatmlab/dataset.py:
(Dataset.setlocal()):
- In this method, called from __init__(), go through configuration
file and set attributes from it. This will be used for any localised
settings such as basedir, subdir, etc.
(Hyperspectral):
- New mixin class for any hyperspectral instrument, such as IASI.
* pyatmlab/dataset/tovs.py:
(IASI):
- Added class with reader for IASI data
* pyatmlab/physics.py:
(wavelength2wavenumber): Added
(wavenumber2wavelength): Added
(specrad_wavenumber2frequency): Added
(specrad_frequency_to_planck_bt): Added
2015-07-07 Gerrit Holl <[email protected]>
* pyatmlab-0-0-85
* pyatmlab/io.py(read_arts_srf):
- Added small function to read SRF from ARTS XML format. Eventually
this should be superseded by more generic functionality to interact
with ARTS XML, like was present in PyARTS.
2015-07-06 Gerrit Holl <[email protected]>
* pyatmlab-0-0-84
* doc/source/index.rst:
- Added missing modules
* pyatmlab/{collocations,dataset,db,io,physics,tools}.py:
- Fix docstring syntax errors
2015-07-02 Gerrit Holl <[email protected]>
* pyatmlab-0-0-83
* pyatmlab/datasets/tovs.py(HIRS):
- Fix typos
2015-07-02 Gerrit Holl <[email protected]>
* pyatmlab-0-0-82
* pyatmlab/datasets/tovs.py(HIRS):
- Fix typo
2015-07-02 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-81
* LICENSE: Updated years
* setup.py: Added new package pyatmlab.datasets
* pyatmlab/dataset.py: Use logging.error instead of print
* pyatmlab/io.py:
- Move collect_values function here
* pyatmlab/tools.py:
- Added a safe_eval function, inspired by
http://stackoverflow.com/a/9558001/974555
* pyatmlab/datasets.py:
- Removed this module
* pyatmlab/datasets/{__init__,groundbased,tanso}.py:
- Moved contents of datasets.py to this new package
* pyatmlab/datasets/tovs.py:
- Started working on HIRS reading routine
2015-04-28 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-80
* doc/source/index.rst:
- Added missing modules, pointed out dependencies
* pyatmlab/collocations.py(ProfileCollocationDescriber):
- When summarising partial column differences, also show percentages
2015-04-16 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-79
* pyatmlab/collocations.py(ProfileCollocationDescriber):
- Also show median primary, secondary
* pyatmlab/graphics.py:
- Move plotdatadir back to io
- Accomodate 3d array writing
* pyatmlab/io.py:
- Move plotdatadir back here
- Added function savetxt_3d that is like savetxt but writes in 3D
* pyatmlab/physics.py:
- Accommodate 3D array writing for sensitivity densities
2015-04-14 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-78
* pyatmlab/collocations.py(ProfileCollocationDescriber):
- Write DOFs for partial columns
- Use rounder number to normalise linear regression so I can easily
denormalise it after
2015-04-10 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-77
* pyatmlab/collocations.py:
(CollocatedDataset):
- Incorporate the ability to flag data
(ProfileCollocationDescriber):
- Fix bugs regarding conversion factors
- Fix bug in processing uncollapsed data
* pyatmlab/dataset.py:
- Incorporate flagging. Implement by child making a flag() method.
- More flexible matching for 'unique fields', now both self and
other_obj have this set and the intersection is used. Allows for
different fields to be used when matching DMPs or flags.
* pyatmlab/datasets.py(ACEFTS):
- Implement flagging method and set unique_fields accordingly.
2015-04-08 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-76
* pyatmlab/collocations.py:
(ProfileCollocationDescriber):
- Calculate full range of nd based on different p/T alternatives, take
the mean and range.
- Correctly divide secondary error by √N. Requires quite some
recoding.
- Correctly calculate regression confidence band using statsmodels
standard method
(collapse):
- Return sort order, needed by some
2015-04-06 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-75
* pyatmlab/collocations.py:
(ProfileCollocationDescriber):
- Start working to estimating error propagation of T and p into
partial columns
- Use sqrt(0.05) rather than 0.05 for confidence interval for partial
column linear regression, and write all estimates to datafile for
pgfplots
(collapse):
- Collapse both ways!
2015-04-05 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-74
* pyatmlab/collocations.py:
(ProfileCollocationDescriber):
- Improve collapsing. Consider that the primary is being smoothed by
the secondary, for a set of N (prim, sec) collocations where all
secondaries are different and all primary are supposed to be
identical, they no longer are if the primary is being smoothed by the
secondary. Therefore, we need to average not only the secondary but
also the primary.
- Implement a weighted least squares fit for the partial column
difference visualisation. Should consider using ODR instead as there
is an error on the x-value too.
2015-04-03 Gerrit Holl <[email protected]>:
* pyatlmlab-0-0-73
* pyatmlab/collocations.py:
(ProfileCollocationDescriber): Implement collapsing. Required updates
in several places as it means I need to postpone applying the mask
until the end, because prior to collapsing I need to combine
information from the core collocations with whathever has been
regridded, smoothed, and processed, so I should not thin the latter
yet.
(collapse): Improve
* pyatmlab/physics.py(AKStats):
- Write out datetimes in form pgfplots can understand
2015-03-24 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-72
* pyatmlab/collocations.py(ProfileCollocationDescriber):
(.partial_columns):
- Optionally also return profiles with partial columns and other stuff
appended, this is useful/essential for some visualisations, such as
the dof-dependency.
(.plot_aks):
- Write aks along with diagonal ('nominal height') using the
somewhat new io.write_data_to_files function. Fix bug in writing AK
stats, pass on right info to summarise.
* pyatmlab/io.py(write_data_to_files): Improve docs
* pyatmlab/physics.py(AKStats): Use colourmap Spectral_r as a
colourmap
2015-03-23 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-71
* pyatmlab/collocations.py(ProfileCollocationDescriber.visualise_pc_comparison):
- Also write error estimates
2015-03-20 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-70
* pyatmlab/collocations.py:
(CollocatedDataset.read_aggregated_pairs):
- When a granule contains time both inside and outside the requested
time interval, select only those collocations within the time (in case
of primary) or within the time +/- the interval (in case of secondary)
and report on this.
(ProfileCollocationDescriber):
- Fix bug in dataname_compare_profiles leading to the targ being eaten
up.
(ProfileCollocationDescriber.visualise_profile_comparison):
- Fix bug, move data writing to correct level of indentation
2015-03-16 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-69
* pyatmlab/collocations.py(collapse):
- Added function to collapse secondary upon primary
2015-03-06 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-68
* pyatmlab/collocations.py(ProfileCollocationDescriber):
(.partial_columns):
- Bugfix, make sure callee has parcols
(._get_xa_ak):
- Bugfix, avoid sending datetime64 to joblib.Memory
(_get_smoothing_error):
- Don't pass unsmoothed data on to get_additional_field,
use smoothed data to choose error estimates to obtain.
2015-03-03 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-67
* pyatmlab/collocations.py(collocations.py):
(CollocatedDataset.__repr__): Add method
(CollocationDescriber):
- Use joblib.Memory for several methods
- Move fignames to ProfileCollocationDescriber as they're only
relevant there
(regrid_profiles, compare_profiles_raw):
- Rather than altering state, return z, so this can be cached
(smooth):
- Return hash rather than tuple
(partial_columns, compare_profiles_smooth):
- Adapt for changed signature in smooth
* pyatmlab/dataset.py:
(Dataset):
- Implement memoisation for several methods
(MultiFileDataset):
- Part of this, implement __getstate__ and __setstate__ so we can skip
self.granule_start_times. Move _open_granule_file code to its own
method.
* pyatmlab/datasets.py(Eureka_PRL_CH4_HDF):
- Implemented timezone corrections again but finally it looks like
we're back in UTC
* pyatmlab/io.py(write_data_to_files):
- Dedicated function to write data to files (for pgfplots), rather
than relying on the patchy addition to graphics.print_or_show.
* pyatmlab/tools.py:
(mark_for_disk_cache): Mark method for caching with joblib.Memory, so
that it can be actually applied after object initialisation
(setmem): helper to be called from relevant __init__ method
2015-02-20 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-66
* pyatmlab/collocations.py(ProfileCollocationDescriber):
(interpolate_profiles):
- Add interpolation matrices to the returned p_int, s_int objects so
that they will not be lost later.
(smooth):
- Be more verbose as to keep track of what is going on
- DISABLE limiting to shared range, as this causes problems in keeping
track of interpolation matrices that can be consistently used if error
covariances are obtained only later. Instead, flag interpolation
matrices with nans where extrapolation would be going on.
- Only return error if requested. In some cases, such as for TANSO, I
can't get S because bucketing is based on partial columns, that can
only be calculated after smoothing. In this case, postpone the
error estimations, but do communicate all information needed to
consistently regrid and smoothen error estimates.
(partial_columns):
- Adapt for changed signature in smooth()
- Don't hardcode for "CH4_profile"
- Rewrite all operations in terms of linear operators
- Apply same linear operators to error estimates, return those as well
(compare_profiles_raw, compare_profiles_smooth):
- Adapt for changed signature of interpolate_profiles()
(_limit_to_shared_range):
- Made changen in order to fix problems elsewhere, but this method is
disabled now anyway...
(_calc_error_propagation):
- Adapt to (properly?) take care of nans in W_1 and S_1. The ones in
W_1 are worst because pinv might hang!
(_get_smoothing_error):
- Move code to calculate the smoothing error out of smooth() because I
might need to call this one separately if TANSO is involved.
* pyatmlab/dataset.py(Dataset):
(extend_with_doy_localtime):
- Add doy and localtime to ndarray
(extend_with_dofs):
- Add dofs to ndarray
* pyatmlab/db.py(SimilarityLookupTable):
(get_index_tuple):
- Return only a single tuple.
(get_index_tuples):
- Yield many tuples.
(lookup):
- Lookup the entry for a single datapoint
(lookup_all):
- Lookup the entries for many datapoints
(lookaround):
- When a particular entry is not found, average neighbouring entries
* pyatmlab/math.py:
(linear_interpolation_matrix):
- Fill extrapolated values with nan, not edges
(regrid_ak):
- Take proper care of nans in z and A
(smooth_profile):
- Take proper care of nans in xa en ak
* pyatmlab/physics.py(AKstats.dofs):
- Adapt to avoid bug, see https://github.com/numpy/numpy/issues/5560
* pyatmlab/stats.py(bin_nd_sparse):
- Make sure we're not binning nans.
2015-02-06 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-65
* pyatmlab/collocations.py(ProfileCollocationDescriber):
(interpolate_profiles):
- Do not consider all negative values invalid, don't want to flag
small negative values that can arise from retrievals. For now fix
arbitrarily at -100
- Bugfix: don't try to extend interpolation matrix to flagged areas of
the z-grid, don't want nans in there. Set W=0 elsewhere.
(smooth):
- For averaging kernel, separately keep track of need for axes
swapping and need for conversion
(partial_columns):
- Rather than calling vmr2nd and integrate_with_height directly, call
those with dummies (either 1 or columns of the unit matrix) so that I
get scalars/vectors that I can use to calculate error propagation.
Secondly, only consider the valid_range at the end, since off-diagonal
errors outside the considered partial column range do propagate into
the actual partial columns.
- Also return estimated errors.
* pyatmlab/dataset.py(ProfileDataset):
- New attribute A_needs_swapping. Defaults to NotTrueNorFalse.
* pyatmlab/datasets.py:
(TansoFTSBase):
- Set A_needs_swapping=False
(ACEFTS.read_single):
- Bugfix: error covariance diagonal should be set to *squares* of the
reported errors, not the reported errors themselves.
(Eureka_PRL_CH4_HDF):
- Set A_needs_swapping = True
(_read):
- Make sure I actually DO turn around all fields that need to be
turned around.
- Make sure all SI conversions are applied exactly as defined in the
source. Except for some.
* pyatmlab/math.py(get_transformation_matrix):
- Obtain standard matrix for the linear transformation for ANY linear
function. This "standard matrix" is m x n (m>0, n>0), so it can also
be a vector in practice. See Lay (2003), Theorem 10 (page 83).
2015-02-02 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-64
* pyatmlab/collocations.py(ProfileCollocationDescriber):
- Fix bug in error propagation under smoothing (S_1, S_2). It appears
to work now! Next step will be to calculate error in profiles and
partial columns, again according to Vigouroux et al.
2015-01-30 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-63
* pyatmlab/collocations.py:
(CollocatedDataset): Bugfix in case when primary granule is much
longer than secondary granule
(ProfileCollocationDescriber):
- Bugfix in flagging interpolation matrix
- More code for error propagation calculations. Not working yet.
* pyatmlab/datasets.py:
(Dataset): Change metaclass. No need to have ABCMeta, was a
misunderstanding. Do use DocStringInheritor.
(ACEFTS): Make fake (diagonal) SA matrix
(Eureka_PRL_CH4_HDF):
- Set necessary attributes: A_needs_converting, range, aliases
- Also read CH4.MIXING.RATIO.VOLUME_ABSORPTION.SOLAR_APRIORI (why was
it missing?)
- Turn around profiles when z is descending
* pytmlab/physics.py:
- Don't do dof
* pyamtlab/tools.py(DocStringInheritor):
- Copied metaclass recipe by Paul McGuire with a small addition.
2015-01-28 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-62
* pyatmlab/math.py(regrid_ak):
- Also return interpolation matrices W.
* pyatmlab/collocations.py:
(ProfileCollocationDescriber):
- Split off class with methods relevant only for profiles, from parent
class
- Rearrange methods in source code
(ProfileCollocationDescriber.smooth):
- Make method more generic, no more hardcoded CH4_profile
(ProfileCollocationDescriber._regrid_xa_ak):
- Also return interpolation matrices W.
(ProfileCollocationDescriber.interpolate_profiles):
- When interpolating, keep track of interpolation matrices.
(ProfileCollocationDescriber._calc_error_propagation):
- Calculate error propagation upon smoothing and regridding, following
Vigouroux et al. (2007) and Calisesi et al. (2005)
* pyatmlab/physics.py(AKStats):
- Bugfix, don't bin visualisingly by all bins I use for the db to
Naoko
2015-01-22 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-61
* pyatmlab/dataset.py(SingleFileDataset.read):
- Make sure we pass self.srcfile to super().read() if nothing is
given. This in turn ensures it will be converted from Path to str if
needed.
* pyatmlab/datasets.py(Eureka_PRL_CH4_HDF):
- Adapted from EurekaHDF. Fixed remaining bugs in reading routine.
It appears everything works now.
2015-01-21 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-60
* pyatmlab/db.py(SimilarityLookupTable):
- Added methods for string representations
- Fix bug in pickling in toFile and fromFile
- Don't be fooled by nans
2015-01-20 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-59
* pyatmlab/collocations.py(CollocationsDescriber):
(plot_aks):
- Make sure that partial columns are added before AKStats.summarise is
called, as this data will be needed
(partial_columns):
- Add parcol_CH4 to self.p_col and self.s_col after calculating it.
* pyatmlab/db.py(SimilarityLookupTable):
- New class used to construct a set of diverse TANSO profiles
* pyatmlab/math.py(mad):
- Added function to calculate median absolute deviation
* pyatmlab/physics.py:
(AKStats.summarise_dof_stats):
- Rewrite and improve this method
(mean_local_solar_time):
- Move to new module `time`
* pyatmlab/stats.py:
(bin_nd_sparse):
- Special version of bin_nd for sparse data (i.e. if we want only a
few data points)
(binsnD_t_2D):
- Improved version of bins4D_to_2D, working from any number of
dimensions, but reducing always to 2-D still
* pyatmlab/time.py:
- New module with mean_local_solar_time moved from physics, and
dt_to_doy_mlst newly created to split datetime in doy and mlst.
2015-01-09 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-58
* pyatmlab/collocations.py(CollocationDescriber):
- More consistent with names in plots and files
- Move dof histograms to AKStats
* pyatmlab/dataset.py(Dataset):
- Always have a timezone, defaulting to UTC
* pyatmlab/physics.py:
(AKStats.summarise): Overall function doing all stuff
(plot_histogram): Plot DOF histograms, moved from CollocationDescriber
(summarise_dof_stats): Worked on investigated DOF stats
(mean_local_solar_time): Calc. from lon. and utctime
* pyatmlab/stats.py:
(bins_4D_to_2D): Downmerge 4D bin thingy to 2D. Should be more
generic...
(iter_bins4D): Helper for above
2014-12-?? Gerrit Holl <[email protected]>:
* pyatmlab-0-0-57
* pyatmlab/collocations.py(CollocationDescriber):
- Some very small changes
2014-12-04 Gerrit Holl <[email protected]>:
* pyatmlab-0-0-56
* pyatmlab/collocations.py(CollocationDescriber):
- Fig bug with regridding. No need to "remove data above range". I'm
going to interpolate on the new grid *anyway*. Removing just risks
removing too much and extrapolating where there is no need. It's
extrapolation I want to avoid, the way to do this is to set the target
grid (from z_xh) small enough and not to remove data wherever I'm
above lowest_z_max.
- Write out all DOFs to get a histogram with pgfplots
- Move get_shared_range into its own routine. I might have to look at
lower limits as well.
* pyatmlab/datasets.py(EurekaHDF):
- Remove workaround for reading PEARL HDF4 file, after bugfix in
Python-hdf4.
* pyatmlab/math.py:
(linear_interpolation_matrix):
- Oops, W was turned around. Fixed.