### Install PySPEDAS Package

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Install the PySPEDAS package from PyPI. This is the recommended way to get started.

```bash
pip install pyspedas
```

--------------------------------

### Install individual package with pip

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_vscode.md

If a package fails to install with 'pdm sync', use pip to install it directly. Repeat for any other problematic packages.

```bash
pip install astropy
```

--------------------------------

### Install Jupyter Support

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

Install the 'jupyter' and 'ipympl' packages to support running PySPEDAS examples in Jupyter notebooks. These packages are essential for interactive notebook environments.

```bash
pip install jupyter
```

```bash
pip install ipympl
```

--------------------------------

### Install Development Tools with pip

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_pycharm.md

Use pip to install the pdm package manager, the uv dependency installer, and pdm-bump for version management. Ensure your terminal is configured to use these installations.

```bash
pip install pdm
pip install uv
pip install pdm-bump
```

--------------------------------

### Install PySPEDAS with specific extras

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/pyspedas_2_migration.md

Install PySPEDAS with selected optional dependencies. For example, install 'maps' (basemap) and 'mth5' extras, but not 'viresclient'. Use quotes if your shell interprets square brackets as special characters.

```bash
pip install 'pyspedas[maps,mth5]'
```

--------------------------------

### Install pdm-bump for versioning

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_vscode.md

Install the pdm-bump plugin, useful for managing version bumps during release workflows.

```bash
pip install pdm-bump
```

--------------------------------

### Install Basemap Toolkit

Source: https://github.com/spedas/pyspedas/blob/master/pyspedas/projects/secs/README.md

Use pip to install the basemap toolkit, a requirement for the SECS module. Refer to the official matplotlib documentation for detailed installation instructions.

```bash
pip install basemap
```

--------------------------------

### Install uv resolver

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_vscode.md

Install the uv package resolver, which is used by pdm, into the virtual environment.

```bash
pip install uv
```

--------------------------------

### Install Python 3.10 Executable

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_vscode.md

Run this command in Windows Command Prompt to install Python 3.10. Adjust the version number as needed.

```bash
winget install python.python.3.10
```

--------------------------------

### Install PySPEDAS Dependencies with PDM

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_pycharm.md

Run this command in the terminal to install all runtime, optional, and development dependencies for PySPEDAS. Ensure PDM is installed and configured for the project.

```bash
pdm sync
```

--------------------------------

### Install PySPEDAS

Source: https://context7.com/spedas/pyspedas/llms.txt

Install PySPEDAS using pip. Optional extras can be included for additional functionalities.

```bash
pip install pyspedas
# With optional extras (e.g. HAPI, VirES, MTH5)
pip install "pyspedas[hapi,vires,mth5]"
```

--------------------------------

### Load and Plot THEMIS FGM Data with PySPEDAS

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

This example demonstrates loading THEMIS FGM data for a specified time range and plotting a specific variable. Ensure PySPEDAS is installed and configured.

```python
from pyspedas import tplot
from pyspedas.projects.themis import fgm

trange=['2007-03-23' , '2007-03-24']
fgm_vars = fgm(probe='a',trange=trange)
print(fgm_vars)
tplot('tha_fgl_dsl')
```

--------------------------------

### Example Plotting with Boundaries

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/plotting.md

This example demonstrates how to plot THEMIS and ARTEMIS orbits and add the bow shock, magnetopause, and AEN neutral sheet locations to the plots.

```APIDOC
## Example Plotting with Boundaries

### Description
This example displays THEMIS and ARTEMIS orbits using tplotxy3, then adds the bow shock, magnetopause, and AEN neutral sheet location to the plots.

### Code
```python
import pyspedas
from pyspedas import tplotxy3, tplotxy3_add_mpause, tplotxy3_add_neutral_sheet
from pyspedas.analysis.neutral_sheet import neutral_sheet
from pyspedas import bshock_2, mpause_2, get_data, store_data, set_coords, set_units, cotrans
import numpy as np

# Load THEMIS state data
default_trange = ["2020-01-01", "2020-01-02"]
pyspedas.projects.themis.state(trange=default_trange, probe=['a','b','c','d','e'])
# Calculate bow shock and magnetopause boundaries
bs = bshock_2()
mp = mpause_2()
# The neutral sheet is a little more complicated, since it's time-dependent. We'll pick the midpoint
# of the time interval
d=get_data('tha_pos_gse')
mid_time = (d.times[-1] - d.times[0])/2.0
# Generate a set of points along the -X axis (night side of Earth), units of Re
ns_x_re = -1.0*np.arange(0.0,375.0, 5.0)
# We need replicate the timestamps to make a proper tplot variable
times=np.zeros(len(ns_x_re))
times[:] = mid_time
ns_gsm_pos=np.zeros((len(ns_x_re),3))
ns_gsm_pos[:,0] = ns_x_re
# Generate the neutral sheet Z-axis values corresponding to the inputs
ns = neutral_sheet(times, ns_gsm_pos, model="aen", sc2NS=False)
# Add the Z component to the input positions, store it as a tplot variable
ns_gsm_pos[:,2] = ns
store_data('ns_gsm_pos', data={'x':times, 'y':ns_gsm_pos})
# We're making a GSE plot, but the neutral sheet is generated in GSM, so we do a cotrans
set_coords('ns_gsm_pos','GSM')
set_units('ns_gsm_pos', 're')
cotrans('ns_gsm_pos', 'ns_gse_pos',coord_in='gsm', coord_out='gse')
# Finally, we have the neutral sheet Z positions along the X axis on the night side.
gse_dat = get_data('ns_gse_pos')

# Plot the orbits and capture the resulting figure
fig = tplotxy3('th?_pos_gse',title='THEMIS_ARTEMIS orbit plot 2020-01-01, all planes, extras, sun left, units re', legend_names=['THEMIS-A','THEMIS-B', 'THEMIS-C', 'THEMIS-D', 'THEMIS-E'], reverse_x=True, plot_units='re', display=False)
# Add bow shock to figure
tplotxy3_add_mpause(bs[0],bs[1],fig=fig,legend_name="Bow Shock",color='k',linestyle='dotted',linewidth=1,display=False)
# Add magnetopause to figure
tplotxy3_add_mpause(mp[0],mp[1],fig=fig,legend_name="Magnetopause",color='k',linestyle='dashed',linewidth=1,display=False)
# Add neutral sheet to figure, then display the plot, and save it to a file
tplotxy3_add_neutral_sheet(gse_dat.y[:,0],gse_dat.y[:,2],fig=fig, legend_name="Neutral sheet",color='k',linestyle='dashdot',linewidth=1,display=True,save_png='orbits_thm_art_re_legends_extras_3planes.png')
```
```

--------------------------------

### Install pdm package manager

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_vscode.md

Install the pdm package manager into the activated virtual environment using pip.

```bash
pip install pdm
```

--------------------------------

### Install PySPEDAS

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Install the PySPEDAS package using pip.

```APIDOC
## Install PySPEDAS

To get started, install the `pyspedas` package using PyPI:

```bash
pip install pyspedas
```
```

--------------------------------

### Start Jupyter Notebook Server

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

Run this command in a terminal to launch the Jupyter notebook interface. This allows for the creation and management of Jupyter notebooks.

```bash
jupyter notebook
```

--------------------------------

### Install Package with Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/devguide.md

Use this command to install a package if 'pip install' fails due to missing binary wheels. This is particularly useful for Mac users.

```bash
conda install -c conda-forge <package>
```

--------------------------------

### Install PySPEDAS in Google Colab

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/examples_and_tutorials.md

Use this command in a Google Colab notebook to install PySPEDAS. Skip if PySPEDAS is already installed in your environment.

```bash
!pip install pyspedas
```

--------------------------------

### Install PySPEDAS with All Extras

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

Install PySPEDAS along with all optional dependencies. This command ensures all features, including mapping and data loading capabilities, are available. Ensure quotes are used if your shell interprets brackets specially.

```bash
pip install 'pyspedas[all]'
```

--------------------------------

### Install Jupyter Kernel for Virtual Environment

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Install the ipykernel package and register your virtual environment with Jupyter for notebook integration.

```bash
pip install ipykernel
python -m ipykernel install --user --name pyspedas --display-name "Python (pySPEDAS)"
```

--------------------------------

### FGM Example

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/mms.md

An example demonstrating how to load and plot MMS FGM data for a specific time interval, including clipping data to the specified range.

```APIDOC
## FGM Example

### Description
Load and plot MMS FGM data for a specific time interval.

### Method
`pyspedas.projects.mms.fgm`

### Parameters
* **trange** (list of str) - Time range of interest. Example: ['2015-10-16/12:45', '2015-10-16/13:00']
* **time_clip** (bool) - If True, data will be clipped to the exact trange specified.

### Request Example
```python
import pyspedas
from pyspedas import tplot
pyspedas.projects.mms.fgm(trange=['2015-10-16/12:45', '2015-10-16/13:00'], time_clip=True)
tplot(['mms1_fgm_b_gsm_srvy_l2_btot', 'mms1_fgm_b_gsm_srvy_l2_bvec'])
```

### Response
None explicitly documented, but implies data is loaded into tplot variables.
```

--------------------------------

### Install MTH5 package

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/mth5.md

Install the MTH5 package using pip. This is a prerequisite for using the pyspedas.mth5 module.

```bash
pip install mth5
```

--------------------------------

### Install PySPEDAS with Specific Extras

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

Install PySPEDAS with selected optional dependencies. Use this if you only need specific features, such as mapping support or mth5 package for seismographic data. Quotes are recommended for shell compatibility.

```bash
pip install 'pyspedas[maps]'
```

```bash
pip install 'pyspedas[maps,mth5]'
```

--------------------------------

### Load BARREL Fast Spectra Data Example

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/barrel.md

Loads BARREL Fast Spectra (fspc) data for a specific probe and time range. This example demonstrates loading data for probe '1D'.

```python
import pyspedas
from pyspedas import tplot
pyspedas.projects.barrel.fspc(trange=['2013-01-17', '2013-01-19'], probe='1D')
tplot('brl1D_FSPC1')
```

--------------------------------

### Verify PySPEDAS Installation

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/devguide.md

Perform a quick smoke check by importing pyspedas in a Python console. If this works, proceed to run tests in specific directories to ensure all dependencies are correctly installed.

```python
import pyspedas
```

--------------------------------

### L-shell Calculation Example

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/geopack.md

Demonstrates the calculation of L-shell values from position data and plotting the results. Requires the 'state' function for data loading and 'tplot' for visualization.

```python
from pyspedas.projects.themis import state
from pyspedas import calculate_lshell, tplot
state(trange=['2007-03-23', '2007-03-23'], probe='a')
calculate_lshell('tha_pos_gsm','tha_pos_lshell')
tplot('tha_pos_lshell')
```

--------------------------------

### Get CDAWeb Instruments

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/cdaweb.md

Fetches a list of available instruments from the CDAWeb archive. Use this to discover which instruments are available for a given mission.

```python
from pyspedas import CDAWeb
cdaweb_obj = CDAWeb()
obs_names = cdaweb_obj.get_instruments()
```

--------------------------------

### Load and Plot PSP SWEAP/SPAN-i Data

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Example of loading and plotting PSP SWEAP/SPAN-i data for a specific time range, with time clipping enabled.

```python
import pyspedas
from pyspedas import tplot

spi_vars = pyspedas.projects.psp.spi(trange=['2018-11-5', '2018-11-5/06:00'], time_clip=True)

tplot(['DENS', 'VEL', 'T_TENSOR', 'TEMP'])
```

--------------------------------

### Get Time Span of a Tplot Variable

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/utilities.md

Retrieves the start and end times for a specified Tplot Variable. If no name is provided, it returns the global timespan.

```python
>>> # Retrieve the time span from Variable 1
>>> import pyspedas
>>> x_data = [1,2,3,4,5]
>>> y_data = [1,2,3,4,5]
>>> pyspedas.store_data("Variable1", data={'x':x_data, 'y':y_data})
>>> time1, time2 = pyspedas.get_timespan("Variable1")
```

--------------------------------

### Load THEMIS ESA Data and Calculate Density

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/themis_analysis.md

Example demonstrating how to load THEMIS ESA data for a specific time range and probe, retrieve relevant variables, and then use `scpot2dens` to calculate plasma density.

```python
import pyspedas
import pyspedas
from pyspedas.projects.themis import scpot2dens

# Define the time range for which to load the data
trange = ['2007-7-20/17:00:00', '2007-7-20/17:20:00']
```

```python
# Load THEMIS ESA data for probe 'c' within the specified time range
pyspedas.projects.themis.esa(trange=trange,
                   probe='c',
                   varnames=['thc_peer_density', 'thc_peir_density', 'thc_peer_sc_pot', 'thc_peer_avgtemp'],
                   level='l2')

# Retrieve electron density
dens_e_time, dens_e = get_data('thc_peer_density')

# Retrieve ion density
dens_i_time, dens_i = get_data('thc_peir_density')

# Retrieve spacecraft potential
sc_pot_time, sc_pot = get_data('thc_peer_sc_pot')

# Retrieve electron temperature
Te_time, Te = get_data('thc_peer_avgtemp')

# Calculate the plasma density from spacecraft potential
Npot = scpot2dens(sc_pot, sc_pot_time, Te, Te_time, dens_e, dens_e_time, dens_i, dens_i_time, 'c')
```

--------------------------------

### Install basemap using Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/pyspedas_2_migration.md

Install the 'basemap' package using Conda for SECS/EICS maps, which may be an alternative if pip installation fails.

```bash
conda install -c conda-forge basemap
```

--------------------------------

### Install mth5 using Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/pyspedas_2_migration.md

Install the 'mth5' package using Conda for loading magnetotelluric/seismographical data, which may be an alternative if pip installation fails.

```bash
conda install -c conda-forge mth5
```

--------------------------------

### Install viresclient using Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/pyspedas_2_migration.md

Install the 'viresclient' package using Conda for downloading SWARM or other ESA data from the VIRES service, which may be an alternative if pip installation fails.

```bash
conda install -c conda-forge viresclient
```

--------------------------------

### Install Dependencies with Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/getting_started.md

Use conda to install specific PySPEDAS dependencies if pip installation fails. This is a workaround for platform-specific issues or compilation problems. The '-c conda-forge' flag specifies the channel for package retrieval.

```bash
conda install -c conda-forge basemap
```

```bash
conda install -c conda-forge mth5
```

```bash
conda install -c conda-forge viresclient
```

--------------------------------

### Load and Plot Magnetometer Data (KOMPSAT)

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/kompsat.md

Imports necessary libraries and loads L2 magnetometer data for a specified time range, then plots it. Ensure ESA server authentication is configured.

```python
import pyspedas
from pyspedas import tplot, options

# Load L2 magnetometer data and plot it
var_names = pyspedas.projects.kompsat.load(trange=["2024-03-31 02:00:00", "2024-03-31 03:00:00"], datatype="1m")
tplot(var_names)
```

--------------------------------

### Install Specific Package with Conda

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_pycharm.md

If a package fails to install with 'pdm sync', use this command to install it with conda. This is particularly useful for packages with complex system dependencies on macOS. Replace 'netcdf4' with the actual failing package name.

```bash
conda install -c conda-forge netcdf4
```

--------------------------------

### Load STEREO Low Energy Telescope (LET) Data

Source: https://github.com/spedas/pyspedas/blob/master/pyspedas/projects/stereo/README.md

Load Low Energy Telescope data for a specified time range.

```python
sit_vars = pyspedas.stereo.let(trange=['2013-1-5', '2013-1-6'])
```

--------------------------------

### Fetch dataset availability with default network and station

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/mth5.md

This example demonstrates fetching dataset availability using only a time range. The function will query for all available datasets within the specified period, without filtering by network or station. Internet access is required.

```python
from pyspedas.mth5.utilities import datasets
valid_dataset = datasets(trange=["2015-06-22", "2015-06-23"])
print(valid_dataset)
```

```text
{'4P': {'ALW48': {('2015-06-18T15:00:36.0000', '2015-07-09T13:45:10.0000'): ['LFE', 'LFN', 'LFZ']}, ...
...
More entries
}
```

--------------------------------

### Launch Interactive CDAWeb Browser

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/cdaweb.md

Starts the interactive CDAWeb archive browser GUI. This tool allows users to visually select missions, instruments, datasets, and time ranges, then download the data.

```python
from pyspedas import cdagui
cdagui()
```

--------------------------------

### Store and Retrieve Data with PySPEDAS

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/utilities.md

Demonstrates how to store data with custom time and value arrays and then retrieve it using PySPEDAS. Also shows how to create gaps in the data.

```python
>>> import pyspedas
>>> time = [pyspedas.time_float("2020-01-01") + i for i in [1, 2, 3, 4, 5, 6, 9, 10, 11]]
>>> y = [1, 2, 3, 4, 5, 6, 9, 10, 11]
>>> pyspedas.store_data("a", data={"x": time, "y": y})
>>> a = pyspedas.get_data("a")
>>> print(a)
>>> b = pyspedas.makegap(a)
>>> print(b)
```

--------------------------------

### Get Help with PySPEDAS Instrument Functions

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Use the `help` function to get detailed information about specific instrument functions within PySPEDAS. This is useful for understanding available parameters and options.

```python
import pyspedas

help(pyspedas.projects.themis.fgm)
```

--------------------------------

### Use Wildcards in Library Search

Source: https://github.com/spedas/pyspedas/blob/master/README.md

Demonstrates how to use wildcard characters like '*' and '?' to search for libraries when the exact spelling is unknown. This is useful for flexible library discovery.

```python
libs('wav*pol')
```

--------------------------------

### Install basemap extra for maps

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/pyspedas_2_migration.md

Install only the 'maps' extra, which includes the 'basemap' package, to support EICS and SECS map plotting. Use quotes if your shell interprets square brackets as special characters.

```bash
pip install 'pyspedas[maps]'
```

--------------------------------

### pyspedas.projects.stereo.let

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/stereo.md

Loads data from the Low Energy Telescope (LET).

```APIDOC
## pyspedas.projects.stereo.let

This function loads data from the Low Energy Telescope

### Parameters
#### Path Parameters
- **trange** (list of str) - Required - time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
  Default: [‘2013-11-5’, ‘2013-11-6’]
- **probe** (str) - Optional - Spacecraft probe (‘a’ for ahead, ‘b’ for behind)
  Default: ‘a’
- **level** (str) - Optional - Default: ‘l1’
- **suffix** (str) - Optional - The tplot variable names will be given this suffix.
  Default: ‘’, no suffix is added.
- **prefix** (str) - Optional - The tplot variable names will be given this prefix.
  Default: ‘’, no prefix is added.
- **get_support_data** (bool) - Optional - Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot.
  Default: False. Only loads in data with a “VAR_TYPE” attribute of “data”.
- **varformat** (str) - Optional - The file variable formats to load into tplot.  Wildcard character “*” is accepted.
  Default: None. All variables are loaded in.
- **varnames** (list of str) - Optional - List of variable names to load.
  Default: [], if not specified, all data variables are loaded
- **downloadonly** (bool) - Optional - Set this flag to download the CDF files, but not load them into tplot variables
  Default: False
- **notplot** (bool) - Optional - Return the data in hash tables instead of creating tplot variables
  Default: False
- **no_update** (bool) - Optional - If set, only load data from your local cache
  Default: False
- **time_clip** (bool) - Optional - Time clip the variables to exactly the range specified in the trange keyword
  Default: False

### Return type
List of tplot variables created.

### Example:
```pycon
>>> import pyspedas
>>> from pyspedas import tplot
>>> sit_vars = pyspedas.projects.stereo.let(trange=["2013-1-5", "2013-1-6"])
>>> tplot(sit_vars)
```
```

--------------------------------

### Configure pdm to use uv

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/dev_pycharm.md

Enable the use of the 'uv' tool for dependency management within pdm. This command should be run in your project's terminal after installing pdm and uv.

```bash
pdm config use_uv true
```

--------------------------------

### get_filenames Method

Source: https://github.com/spedas/pyspedas/blob/master/docs/source/cdaweb.md

Get a list of URLs for a specific dataset within a given time range.

```APIDOC
## get_filenames

Return a list of urls for a dataset between dates t0 and t1.

### Method

`get_filenames`

### Parameters

* **dataset_list** (`list` of `str`) – A list of dataset names, as obtained from get_datasets()
* **t0** (`str`) – Start time for data to be retrieved
* **t1** (`str`) – End time for data to be retrieved

### Returns

A list of URLs for the given dataset and time range

### Return type

`list` of `str`

### Example

```pycon
>>> from pyspedas import CDAWeb
>>> cdaweb_obj = CDAWeb()
>>> urllist = cdaweb_obj.get_filenames(['THB_L2_FIT (2007-02-26 to 2020-01-17)'], '2010-01-01 00:00:00', '2010-01-10 00:00:00')
```
```