API

ReconJob

class LMRt.reconjob.ReconJob(configs=None, proxydb=None, prior=None, obs=None)

Reconstruction Job

General rule of loading parameters: load from the YAML first if available, then update with the parameters in the function calling,

so the latter has a higher priority

crop_prior(domain_range=None, verbose=False)

Take a smaller domain for reconstruction

domain_rangelist

[lat_min, lat_max, lon_min, lon_max]

gen_Xb(recon_vars=None, verbose=False)

Generate Xb

gen_Ye(proxy_frac=None, nens=None, verbose=False, seed=0)

Generate Ye

load_configs(cfg_path=None, job_dirpath=None, verbose=False)

Load the configuration YAML file

self.configs will be updated

cfg_pathstr

the path of a configuration YAML file

load_obs(path_dict=None, varname_dict=None, verbose=False, anom_period=None)

Load instrumental observations fields

path_dict: dict

a dict of environmental variables

varname_dict: dict

a dict to map variable names, e.g. {‘tas’: ‘sst’} means ‘tas’ is named ‘sst’ in the input NetCDF file

load_prior(path_dict=None, varname_dict=None, verbose=False, anom_period=None)

Load model prior fields

path_dict: dict

a dict of environmental variables

varname_dict: dict

a dict to map variable names, e.g. {‘tas’: ‘sst’} means ‘tas’ is named ‘sst’ in the input NetCDF file

load_proxydb(path=None, verbose=False, load_df_kws=None)

Load the proxy database

self.proxydb will be updated

proxydb_pathstr

if given, should point to a pickle file with a Pandas DataFrame underlying

ReconRes

class LMRt.reconres.ReconRes(job_dirpath, load_num=None, verbose=False)

copy()

Make a copy of the Series object

Series

A copy of the Series object

ReconSeries

class LMRt.reconres.ReconSeries(series_list)

plot(lgd_kws=None, **kws)

Plot multiple timeseries on the same axis

figsizelist, optional

Size of the figure. The default is [10, 4].

markerstr, optional

marker type. The default is None.

markersizefloat, optional

marker size. The default is None.

colorsa list of, or one, Python supported color code (a string of hex code or a tuple of rgba values)

Colors for plotting. If None, the plotting will cycle the ‘tab10’ colormap; if only one color is specified, then all curves will be plotted with that single color; if a list of colors are specified, then the plotting will cycle that color list.

cmapstr

The colormap to use when “colors” is None.

normmatplotlib.colors.Normalize like

The nomorlization for the colormap. If None, a linear normalization will be used.

linestylestr, optional

Line style. The default is None.

linewidthfloat, optional

The width of the line. The default is None.

xlabelstr, optional

x-axis label. The default is None.

ylabelstr, optional

y-axis label. The default is None.

titlestr, optional

Title. The default is None.

legendbool, optional

Wether the show the legend. The default is True.

plot_kwargsdict, optional

Plot parameters. The default is None.

lgd_kwargsdict, optional

Legend parameters. The default is None.

savefig_settingsdictionary, optional

the dictionary of arguments for plt.savefig(); some notes below: - “path” must be specified; it can be any existed or non-existed path,

with or without a suffix; if the suffix is not given in “path”, it will follow “format”

• “format” can be one of {“pdf”, “eps”, “png”, “ps”} The default is None.

axmatplotlib.ax, optional

The matplotlib axis onto which to return the figure. The default is None.

mutebool, optional

if True, the plot will not show; recommend to turn on when more modifications are going to be made on ax

invert_xaxisbool, optional

if True, the x-axis of the plot will be inverted

fig, ax

ReconField

class LMRt.reconres.ReconField(time, lat, lon, field_list, varname=None, verbose=False)

copy()

Make a copy of the Series object

Series

A copy of the Series object

ProxyRecord

class LMRt.proxy.ProxyRecord(pid, lat, lon, time, value, ptype, psm_name=None, psm=None, time_name='Time', value_name=None, time_unit='yr', value_unit=None, label=None, prior_value=None, prior_time=None, obs_value=None, obs_time=None, seasonality=None, ye_time=None, ye_value=None)

copy()

Make a copy of the Series object

Series

A copy of the Series object

forward_psm()

Forward modeling: calculate ye using the PSM according to self.psm

plot(plot_Ye=True, **kws)

Plot the timeseries

figsizelist

a list of two integers indicating the figure size

markerstr

e.g., ‘o’ for dots See [matplotlib.markers](https://matplotlib.org/3.1.3/api/markers_api.html) for details

markersizefloat

the size of the marker

colorstr, list

the color for the line plot e.g., ‘r’ for red See [matplotlib colors] (https://matplotlib.org/3.2.1/tutorials/colors/colors.html) for details

linestylestr

e.g., ‘–’ for dashed line See [matplotlib.linestyles](https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/linestyles.html) for details

linewidthfloat

the width of the line

labelstr

the label for the line

xlabelstr

the label for the x-axis

ylabelstr

the label for the y-axis

titlestr

the title for the figure

zorderint

The default drawing order for all lines on the plot

legend{True, False}

plot legend or not

invert_xaxisbool, optional

if True, the x-axis of the plot will be inverted

plot_kwargsdict

the dictionary of keyword arguments for ax.plot() See [matplotlib.pyplot.plot](https://matplotlib.org/3.1.3/api/_as_gen/matplotlib.pyplot.plot.html) for details

lgd_kwargsdict

the dictionary of keyword arguments for ax.legend() See [matplotlib.pyplot.legend](https://matplotlib.org/3.1.3/api/_as_gen/matplotlib.pyplot.legend.html) for details

alphafloat

Transparency setting

savefig_settingsdict

the dictionary of arguments for plt.savefig(); some notes below: - “path” must be specified; it can be any existed or non-existed path,

with or without a suffix; if the suffix is not given in “path”, it will follow “format”

• “format” can be one of {“pdf”, “eps”, “png”, “ps”}

axmatplotlib.axis, optional

the axis object from matplotlib See [matplotlib.axes](https://matplotlib.org/api/axes_api.html) for details.

mute{True,False}

if True, the plot will not show; recommend to turn on when more modifications are going to be made on ax

figmatplotlib.figure

the figure object from matplotlib See [matplotlib.pyplot.figure](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.figure.html) for details.

axmatplotlib.axis

the axis object from matplotlib See [matplotlib.axes](https://matplotlib.org/api/axes_api.html) for details.

When ax is passed, the return will be ax only; otherwise, both fig and ax will be returned.

pyleoclim.utils.plotting.savefig : saving figure in Pyleoclim

Plot the SOI record

Change the line color

Save the figure. Two options available:

• Within the plotting command

• After the figure has been generated

seasonalize(season=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], make_year_mm_nan=False, inplace=False)

Seasonalize the proxy record

ProxyDatabase

class LMRt.proxy.ProxyDatabase(records=None, source=None)

add(records, inplace=False, verbose=False)

Add a list of records into the database

filter_dt(dt=1, inplace=False)

Filter the proxy database according to temporal resolution

filter_pids(pids, inplace=False)

Filter the proxy database according to given pids

filter_ptype(ptype_list, inplace=False)

Filter the proxy database according to given ptype list

ptype_listlist

a list of ptype’s

get_var_from_ds(seasonalized_ds, ptype_season, ds_type=None, verbose=False)

Get environmental variables from prior

load_df(df, pid_column='paleoData_pages2kID', lat_column='geo_meanLat', lon_column='geo_meanLon', time_column='year', value_column='paleoData_values', proxy_type_column='paleoData_proxy', archive_type_column='archiveType', value_name_column='paleoData_variableName', value_unit_column='paleoData_units', ptype_season=None, ptype_psm=None, verbose=False)

Load database from a Pandas DataFrame

dfPandas DataFrame

a Pandas DataFrame include at least lat, lon, time, value, proxy_type

ptype_psmdict

a mapping from ptype to psm

remove(pids, inplace=False, verbose=False)

Remove a list of records from the database regardless existing or not

seasonalize(ptype_season, inplace=False)

Filter the proxy database according to given ptype list

ptype_seasondict

a dict of seasonality for each proxy type

Field

class LMRt.gridded.Field(name, time, lat, lon, value, source=None)

crop(domain_range, inplace=False)

Crop the domain for reconstruction

domain_rangelist

[lat_min, lat_max, lon_min, lon_max] for a square domain or [lat_min, lat_max] to crop the lats only

seasonalize(season=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], make_year_mm_nan=True, inplace=False)

Seasonalize the field

Dataset

class LMRt.gridded.Dataset(fields=None)

crop(domain_range, inplace=False)

Crop the domain for reconstruction

domain_rangelist

[lat_min, lat_max, lon_min, lon_max] for a square domain or [lat_min, lat_max] to crop the lats only

load_nc(path_dict, anom_period=None, varname_dict=None, inplace=False)

Load a NetCDF file that assumed to include time, lat, lon, value

varname_dict: dict

a dict to map variable names, e.g. {‘tas’: ‘tempanomaly’} means ‘tas’ is named ‘tempanomaly’ in the input NetCDF file

PSMs

class LMRt.psm.Linear(proxy_time, proxy_value, obs_tas_time, obs_tas_value, prior_tas_time=None, prior_tas_value=None)

class LMRt.psm.Bilinear(proxy_time, proxy_value, obs_tas_time, obs_tas_value, obs_pr_time, obs_pr_value, prior_tas_time=None, prior_tas_value=None, prior_pr_time=None, prior_pr_value=None)