Thermobar

https://thermobar.readthedocs.io/en/latest/
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Thermobar is a Python package for thermobarometry calculations using mineral-melt and...
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### Example: Installing Thermobar

Source: https://thermobar.readthedocs.io/en/latest

A commented-out line showing how to install the Thermobar package.

```python
# pip install -U thermobar

```

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

### Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest

Instructions on how to install the Thermobar package.

```python
# You need to install Thermobar once on your machine, if you haven’t done this yet, uncomment the line below (remove the #)
# pip install Thermobar
```

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

### Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest

Instructions on how to install the Thermobar package, with a commented-out line for uncommenting if installation is needed.

```python
# You need to install Thermobar once on your machine, if you haven’t done this yet, uncomment the line below (remove the #)
```

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

### Install Pyrolite

Source: https://thermobar.readthedocs.io/en/latest

Instructions on how to install the pyrolite package, with a commented-out line for uncommenting if installation is needed.

```python
# You will also need to install pyrolite for this example, if you haven’t done so already, uncomment the line below
```

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

### Get Thermobar version

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Retrieves and displays the installed version of the Thermobar package.

```python
pt.__version__
```

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

### Get help on specific equations

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Demonstrates how to use the `help()` function to get detailed information about a specific thermobarometry equation, including its parameters and documentation.

```python
help(pt.T_Put2008_eq33)
```

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

### Example: Olivine-Liquid thermometry (All Models)

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates calculating Olivine-Liquid temperatures using all available models.

```python
from thermobar.calculate import calculate_ol_liquid

# Assuming 'ol_liq_data' is a pandas DataFrame with appropriate columns
temps_K = calculate_ol_liquid(data=ol_liq_data, equation= "all")

```

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

### Pip Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest

Instructions on how to install Thermobar using pip.

```python
# First, pip install Thermobar if you haven’t already
```

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

### Getting Help on a Function

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

This snippet demonstrates how to use the help() function to get detailed information about a specific Thermobar function, in this case, calculate_cpx_liq_temp.

```python
help(pt.calculate_cpx_liq_temp)
```

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

### Example: Cpx-Liq temps calculation

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates calculating Cpx-Liq temperatures and shows the output as a pandas Series.

```python
import pandas as pd
from thermobar.calculate import calculate_cpx_liquid

data = pd.read_excel("your_data.xlsx") # Load your data

temps = calculate_cpx_liquid(data=data)

print(temps.head())

```

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

### Example: Calculating Mg# for liquids

Source: https://thermobar.readthedocs.io/en/latest

Shows how to calculate the Mg# for liquids.

```python
from thermobar.calculate import calculate_liquid_compositions

# Assuming 'liquid_data' is a pandas DataFrame with appropriate columns
liquid_compositions = calculate_liquid_compositions(data=liquid_data)

print(liquid_compositions['Mg_number'].head())

```

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

### Example: Olivine-Liquid thermometry (Toplis, 2005)

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates using Toplis, 2005 equation for Olivine-Liquid thermometry.

```python
from thermobar.calculate import calculate_ol_liquid

# Assuming 'ol_liq_data' is a pandas DataFrame with appropriate columns
temps_K = calculate_ol_liquid(data=ol_liq_data, equation= "Toplis_2005")

```

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

### Example: Calculating Olivine Fo contents

Source: https://thermobar.readthedocs.io/en/latest

Shows how to calculate the Fo contents of olivines.

```python
from thermobar.calculate import calculate_olivine_fo

# Assuming 'olivine_data' is a pandas DataFrame with appropriate columns
olivine_fo = calculate_olivine_fo(data=olivine_data)

print(olivine_fo.head())

```

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

### Example: Olivine-Liquid thermometry (Putirka, 2016)

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates using Putirka, 2016 equation for Olivine-Liquid thermometry.

```python
from thermobar.calculate import calculate_ol_liquid

# Assuming 'ol_liq_data' is a pandas DataFrame with appropriate columns
temps_K = calculate_ol_liquid(data=ol_liq_data, equation= "Putirka_2016")

```

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

### Install pyrolite

Source: https://thermobar.readthedocs.io/en/latest/Examples/Error_propagation/Cpx_only_contour_plot.html

Install the pyrolite library if you haven't already.

```shell
#!pip install pyrolite
```

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

### Import Libraries and Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code block imports necessary Python libraries (numpy, pandas, matplotlib) and installs Thermobar if not already present. It also shows the output of the installation.

```python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

!pip install Thermobar
import Thermobar as pt
```

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

### Example 2 - Kspar-Liquid calculations

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Liq_Matching.html

Loads Kspar and liquid data from an Excel file and performs calculations.

```python
# Load in the Kspars
out_Kspar=pt.import_excel('Feldspar_Liquid.xlsx', sheet_name="Kspar_only")
Kspars=out_Kspar['Kspars']

# Load in the liquids you want to match with
out_Liq2=pt.import_excel('Feldspar_Liquid.xlsx', sheet_name="Evolved_Liq_only")
Liqs=out_Liq2['Liqs']
```

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

### Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liq_Thermobarometry.html

This code snippet shows how to install the Thermobar package using pip. It is presented as a command to be uncommented and run.

```bash
#!pip install Thermobar

```

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

### Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Pyroxene_Ternary_Cpx_Example.html

Install the Thermobar package if you haven't already done so.

```python
# if you havent already done it, pip install Thermobar
#!pip install Thermobar
```

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

### Example: Olivine-Liquid thermometry (Roeder and Emslie, 1970)

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates using the Roeder and Emslie, 1970 equation for Olivine-Liquid thermometry.

```python
from thermobar.calculate import calculate_ol_liquid

# Assuming 'ol_liq_data' is a pandas DataFrame with appropriate columns
temps_K = calculate_ol_liquid(data=ol_liq_data, equation= "Roeder_Emslie_1970")

```

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

### Getting help for the calculation function

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code snippet demonstrates how to access the documentation for the `calculate_cpx_liq_press_temp_matching` function to understand its parameters and usage.

```python
help(pt.calculate_cpx_liq_press_temp_matching)
```

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

### Example: Olivine-Liquid thermometry (Putirka eq 22)

Source: https://thermobar.readthedocs.io/en/latest

Demonstrates using Putirka's equation 22 for Olivine-Liquid thermometry.

```python
from thermobar.calculate import calculate_ol_liquid

# Assuming 'ol_liq_data' is a pandas DataFrame with appropriate columns
temps_K = calculate_ol_liquid(data=ol_liq_data, equation= "Putirka_2008_22")

```

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

### Install ONNX models for Machine Learning

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/MachineLearning_Cpx_Liq_Thermobarometry.html

Installs pre-trained machine learning models saved as .pkl files from a specific GitHub repository. This is done to keep the main Thermobar library smaller.

```python
#!pip install "https://github.com/PennyWieser/Thermobar_onnx/archive/refs/tags/v.0.05.zip"
```

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

### Example: Cpx-Liq temps calculation with Eq_Tests=True

Source: https://thermobar.readthedocs.io/en/latest

Shows the output when performing the same calculation with 'Eq_Tests=True', resulting in a pandas DataFrame.

```python
import pandas as pd
from thermobar.calculate import calculate_cpx_liquid

data = pd.read_excel("your_data.xlsx") # Load your data

temps_df = calculate_cpx_liquid(data=data, eq_tests=True)

print(temps_df.head())

```

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

### Example 2d - Writing the Entire DataFrame to Excel

Source: https://thermobar.readthedocs.io/en/latest/Examples/Exporting_to_Excel.html

Demonstrates how to save an entire DataFrame to an Excel file.

```python
Temp_eq33_5kbar_Eq_tests.to_excel('Calc4.xlsx')
```

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

### Example 1c - Iterating T and H2O for all possible Plag-Liq matches

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Liq_Matching.html

Iterates through temperature and H2O content for all possible Plag-Liq matches.

```python
T_H_Iter_dict=pt.calculate_fspar_liq_temp_hygr_matching(liq_comps=Liqs, plag_comps=RealPlags,
        equationT="T_Put2008_eq24a", equationH="H_Waters2015", P=5)
T_H_Calc_Av=T_H_Iter_dict.get('Av_HTs')
T_H_Calc_All=T_H_Iter_dict.get('All_HTs')
T_H_Evol=T_H_Iter_dict.get('T_H_Evolution')
```

```python
# Maybe you want to plot a histogram of H2O contents
plt.hist(T_H_Calc_Av['Mean_H2O_calc'])
plt.xlabel('H$_2$O Calc (wt%)')
```

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

### Example 1a - All possible Liq-Plag matches, An-Ab equilibrium

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Liq_Matching.html

Calculates Liq-Plag temperature matches using the An-Ab equilibrium test of Putirka (2008).

```python
MM_dict=pt.calculate_fspar_liq_temp_matching(liq_comps=Liqs,
                                             plag_comps=RealPlags,
                                             equationT="T_Put2008_eq24a", P=5,
                                                Ab_An_P2008=True, H2O_Liq=2)
Av_Matches=MM_dict['Av_PTs']
All_Matches=MM_dict['All_PTs']
```

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

### Example 3: Displaying head of results

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code snippet displays the first few rows of the 'All_PTs' DataFrame from the `MM3` results, which contains detailed calculations for clinopyroxene-liquid melt matching using the Masotta Kd model.

```python
MM3_All.head()
```

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

### Example 6: Plotting Pressures and Temperatures

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code snippet visualizes the calculated pressures and temperatures for Cpx-Liq matches. It compares results filtered at 1 sigma and 2 sigma, showing individual matches as faint dots and averaged results with error bars as diamonds.

```python
fig, ((ax1, ax2)) = plt.subplots(1, 2, figsize=(12, 5))

# Subplot1
# This plots every Cpx-Liq match, with an opacity of 0.5
ax1.plot(MM1_All['T_K_calc']-273.15,  MM1_All['P_kbar_calc'], '.c', alpha=0.5)

# This plots a diamond and error bar for each Cpx averaged with as many liquids as it matches too
ax1.errorbar(MM1_Av['Mean_T_K_calc']-273.15,  MM1_Av['Mean_P_kbar_calc'],
             xerr=MM1_Av['Std_T_K_calc'].fillna(0), yerr=MM1_Av['Std_P_kbar_calc'].fillna(0),
             fmt='d', ecolor='k', elinewidth=0.8, mfc='cyan', ms=8, mec='k')
ax1.set_xlabel('Temperature (°C)')
ax1.set_ylabel('Pressure (kbar)')
ax1.set_title('1 sigma')

# Subplot2 - As above, butmatches with less stringent equilibrium filters
ax2.plot(MM1_2s_All['T_K_calc']-273.15,  MM1_2s_All['P_kbar_calc'], '.r', alpha=0.3)

ax2.errorbar(MM1_2s_Av['Mean_T_K_calc']-273.15,  MM1_2s_Av['Mean_P_kbar_calc'],
             xerr=MM1_2s_Av['Std_T_K_calc'].fillna(0), yerr=MM1_2s_Av['Std_P_kbar_calc'].fillna(0),
             fmt='d', ecolor='k', elinewidth=0.8, mfc='red', ms=8, mec='k')
ax2.set_xlabel('Temperature (°C)')
ax2.set_ylabel('Pressure (kbar)')
ax2.set_title('2 sigma')
ax1.invert_yaxis()
ax2.invert_yaxis()
```

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

### Example 5: Plotting Equilibrium filters

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code snippet generates plots to compare the distribution of Kd, EnFs, DiHd, and CaTs values between matches filtered at 1 sigma (default) and 2 sigma. It uses matplotlib to create histograms showing probability density.

```python
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(12, 10))
# This plots distribution of Kd in matches with probability on the y axis
ax1.hist(MM1_2s_All['Delta_Kd_Put2008'], weights=np.ones_like(MM1_2s_All['Delta_Kd_Put2008']) / len(MM1_2s_All['Delta_Kd_Put2008']),
         label='pass at 2 sigma')
ax1.hist(MM1_All['Delta_Kd_Put2008'], weights=np.ones_like(MM1_All['Delta_Kd_Put2008']) / len(MM1_All['Delta_Kd_Put2008']) ,
         label='pass at 1 sigma', alpha=0.5)
ax1.set_xlabel('ΔKd Putirka 2008')
ax1.set_ylabel('Probability density')
ax1.legend()

# This plots distribution of EnFs  with probability on the y axis
ax2.hist(MM1_2s_All['Delta_EnFs_Mollo13'], weights=np.ones_like(MM1_2s_All['Delta_EnFs_Mollo13']) / len(MM1_2s_All['Delta_EnFs_Mollo13']) )#, label='All filters (2sigma)', color='salmon')
ax2.hist(MM1_All['Delta_EnFs_Mollo13'], weights=np.ones_like(MM1_All['Delta_EnFs_Mollo13']) / len(MM1_All['Delta_EnFs_Mollo13']), alpha=0.5)
ax2.set_xlabel('ΔEnFs')

# This plots distribution of DiHd with probability on the y axis
ax3.hist(MM1_2s_All['Delta_DiHd_Mollo13'], weights=np.ones_like(MM1_2s_All['Delta_DiHd_Mollo13']) / len(MM1_2s_All['Delta_DiHd_Mollo13']) )#, label='All filters (2sigma)', color='salmon')
ax3.hist(MM1_All['Delta_DiHd_Mollo13'], weights=np.ones_like(MM1_All['Delta_DiHd_Mollo13']) / len(MM1_All['Delta_DiHd_Mollo13']) , alpha=0.5)
ax3.set_xlabel('ΔDiHd')
ax3.set_ylabel('Probability density')

# This plots distribution of CaTs values with probability on the y axis
ax4.hist(MM1_2s_All['Delta_CaTs_Put1999'], weights=np.ones_like(MM1_2s_All['Delta_CaTs_Put1999']) / len(MM1_2s_All['Delta_CaTs_Put1999']) )#, label='All filters (2sigma)', color='salmon')
ax4.hist(MM1_All['Delta_CaTs_Put1999'], weights=np.ones_like(MM1_All['Delta_CaTs_Put1999']) / len(MM1_All['Delta_CaTs_Put1999']), alpha=0.5)
ax4.set_xlabel('ΔCaTs')
```

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

### Example 1b - All possible Liq-Plag matches, no filter

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Liq_Matching.html

Calculates all possible Liq-Plag temperature matches without applying an equilibrium filter, useful for developing custom filters.

```python
MM_dict=pt.calculate_fspar_liq_temp_matching(liq_comps=Liqs, plag_comps=RealPlags,
                                             equationT="T_Put2008_eq24a", P=5,
                                                Ab_An_P2008=False, H2O_Liq=2)
Av_Matches=MM_dict['Av_PTs']
All_Matches=MM_dict['All_PTs']
```

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

### Cpx_MeltMatch2_ScruggsPutirka2018 Example

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch2_ScruggsPutirka2018.html

This code snippet visualizes calculated temperatures and pressures from the Cpx_MeltMatch2 model, comparing calculated values with averaged values and their standard deviations.

```python
fig, ((ax1)) = plt.subplots(1, figsize=(8, 6))

ax1.plot(Syn_All['T_K_calc']-273.15, Syn_All['P_kbar_calc'], '.', color='red', alpha=0.1)

ax1.errorbar(Syn_Avs['Mean_T_K_calc']-273.15,  Syn_Avs['Mean_P_kbar_calc'],
             xerr=Syn_Avs['Std_T_K_calc'], yerr=Syn_Avs['Std_P_kbar_calc'],
             fmt='d', ecolor='k', elinewidth=0.8, mfc='red', ms=8, mec='k', label='Pennys code')

ax1.set_xlim([700, 1200])
ax1.set_ylim([-2, 10])
ax1.invert_yaxis()
```

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

### Example 3: Alkaline Systems

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This code snippet shows how to use the updated Kd model from Masotta (calibrated for trachyte and phonolitic magmas) by setting `Kd_Match` to 'Masotta'. It also specifies the pressure and temperature equations to 'P_Mas2013_Palk2012' and 'T_Mas2013_Talk2012' respectively, along with error parameters.

```python
MM3=pt.calculate_cpx_liq_press_temp_matching(liq_comps=myLiquids1, cpx_comps=myCPXs1,
                                    equationP="P_Mas2013_Palk2012", equationT="T_Mas2013_Talk2012",
                                    Kd_Match="Masotta", Kd_Err=0.08, Fe3Fet_Liq=0.15, CaTs_Err=0.06, DiHd_Err=0.12, EnFs_Err=0.06)
MM3_All=MM3['All_PTs']
MM3_Av=MM3['Av_PTs']
```

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

### Install and Import Ternary Plot Package

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Pyroxene_Ternary_Cpx_Example.html

Install the python-ternary package and import it. It's recommended to use conda for installation to avoid conflicts with other 'ternary' packages.

```python
# pip install python-ternary
import ternary
#  We tested using ternary V.1.0.8
print(ternary.__version__)
```

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

### Import Thermobar

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Imports the Thermobar library and assigns it the alias 'pt' for easier use.

```python
import Thermobar as pt
```

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

### Install Thermobar

Source: https://thermobar.readthedocs.io/en/latest/Examples/Amphibole/Amphibole_Classification_Diagrams.html

Command to install the Thermobar package using pip. This is commented out by default.

```Shell
#!pip install Thermobar
```

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

### Load data from Excel with single phase

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Demonstrates loading data from an Excel file ('Five_min_intro.xlsx') from a sheet named 'Liq_noheader', specifying '_Liq' as the suffix for a single phase (Liquid).

```python
out_noheads=pt.import_excel('Five_min_intro.xlsx', sheet_name="Liq_noheader", suffix="_Liq")
Liqs_noheads=out_noheads['Liqs']
```

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

### Print Ternary Version

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Prints the installed version of the ternary library.

```python
import ternary
#  We tested using ternary V.1.0.8
print(ternary.__version__)
```

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

### Loading Published Barometry

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

Loads published barometry data from an Excel file.

```python
Published=pd.read_excel('Gleeson2020JPET_Input_Pyroxene_Melts.xlsx', sheet_name="NP_Out")
```

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

### Iterate for both pressure and temperature

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Demonstrates how to simultaneously calculate both pressure and temperature when neither is known beforehand, by iterating two specified equations.

```python
PT_iter_30_33=pt.calculate_cpx_liq_press_temp(cpx_comps=Cpxs, liq_comps=Liqs,
                                            equationP="P_Put2008_eq30", equationT="T_Put2008_eq33")
PT_iter_30_33
```

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

### Example: Appending calculated column

Source: https://thermobar.readthedocs.io/en/latest

Illustrates how to append a calculated column to a DataFrame in a specific position.

```python
import pandas as pd
from thermobar.calculate import calculate_cpx_liquid

data = pd.read_excel("your_data.xlsx") # Load your data

temps = calculate_cpx_liquid(data=data)

data.insert(1, 'Cpx_Liq_T_K', temps) # Insert the temps column at index 1

print(data.head())

```

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

### Loading Liquids

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

Loads liquid data from an Excel file and assigns it to variables.

```python
out=pt.import_excel('Gleeson2020JPET_Input_Pyroxene_Melts.xlsx', sheet_name="Melts")
my_input_Liqs=out['my_input']
myLiquids1=out['Liqs']
```

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

### Loading Cpx-Liq data from Excel

Source: https://thermobar.readthedocs.io/en/latest/Examples/Exporting_to_Excel.html

Loads Cpx-Liq data from an Excel file named 'Five_min_intro.xlsx'.

```python
out=pt.import_excel('Five_min_intro.xlsx', sheet_name="Sheet1")
my_input=out['my_input']
Liqs=out['Liqs']
Cpxs=out['Cpxs']
my_input=out['my_input']
```

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

### Check scikit-learn version

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/MachineLearning_Cpx_Liq_Thermobarometry.html

Prints the installed version of the scikit-learn library, which is often a dependency for machine learning functionalities.

```python
import sklearn
print(sklearn.__version__)
```

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

### Displaying Head of DataFrame

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

This command displays the first few rows of the MM1_All_fixedT DataFrame, showing the calculated pressure, temperature, and various equilibrium test results.

```python
MM1_All_fixedT.head()
```

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

### Example 1a - Default Classification Diagram

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Generates a basic feldspar ternary classification diagram using all default settings.

```python
fig, tax = pt.plot_fspar_classification()
fig.tight_layout()
```

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

### Load data from Excel

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Loads data from an Excel file named 'Five_min_intro.xlsx' from the 'Sheet1' sheet. It then extracts and assigns dataframes for 'my_input', 'Liqs', and 'Cpxs' from the output dictionary.

```python
out=pt.import_excel('Five_min_intro.xlsx', sheet_name="Sheet1")
my_input=out['my_input']
Liqs=out['Liqs']
Cpxs=out['Cpxs']
```

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

### Example 1g - Disabling Ticks

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Generates a feldspar ternary classification diagram with major and minor grid lines, but without ticks.

```python
fig, tax = pt.plot_fspar_classification(labels=True,  major_grid=True, minor_grid=True, ticks=False)
fig.tight_layout()
```

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

### Example 1c - Customizing Label Text

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Generates a feldspar ternary classification diagram with custom labels, changing 'San' to 'Sanidine'.

```python
fig, tax = pt.plot_fspar_classification(labels=True,
                                    Sanidine_label='Sanidine')
fig.tight_layout()
```

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

### Import Thermobar and VESIcal

Source: https://thermobar.readthedocs.io/en/latest

Importing both Thermobar and VESIcal libraries for integrated use.

```python
import Thermobar as tb
import VESIcal as v
```

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

### Plot Temperature in Celsius

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Demonstrates how to plot temperature in Celsius by subtracting 273.15 from the calculated temperature values before plotting.

```python
plt.plot(PT_iter_30_33['P_kbar_calc'], PT_iter_30_33['T_K_calc']-273.15, 'ok')
plt.xlabel('P (kbar)')
plt.ylabel('T (C)')
```

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

### Example 1d - Adding Major Grid Lines

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Generates a feldspar ternary classification diagram with default major grid lines enabled.

```python
fig, tax = pt.plot_fspar_classification(labels=True,  major_grid=True)
fig.tight_layout()
```

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

### Example 1b - With Default Compositional Labels

Source: https://thermobar.readthedocs.io/en/latest/Examples/Feldspar_Thermobarometry/Fspar_Ternary_Plot.html

Generates a feldspar ternary classification diagram with default compositional labels (e.g., An, Ab, Ol).

```python
fig, tax = pt.plot_fspar_classification(labels=True)
fig.tight_layout()
```

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

### Loading Cpxs

Source: https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/Cpx_Liquid_melt_matching/Cpx_MeltMatch1_Gleeson2020.html

Loads Cpx data from a different sheet in the same Excel file and assigns it to variables.

```python
out2=pt.import_excel('Gleeson2020JPET_Input_Pyroxene_Melts.xlsx', sheet_name="Cpxs")
my_input_Cpxs=out2['my_input']
myCPXs1=out2['Cpxs']
```

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

### Calculate pressure at a known temperature

Source: https://thermobar.readthedocs.io/en/latest/Examples/Five_min_intro.html

Shows how to calculate pressure using a clinopyroxene-liquid barometer when the temperature is known. It specifies the composition dataframes and the pressure equation to use.

```python
# Here performing calculations at 1300 K
Press_eq30_1300K=pt.calculate_cpx_liq_press(cpx_comps=Cpxs, liq_comps=Liqs,
                            equationP="P_Put2008_eq30", T=1300)
```

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

### Example 2c - Appending Multiple Columns to a DataFrame

Source: https://thermobar.readthedocs.io/en/latest/Examples/Exporting_to_Excel.html

Shows how to append multiple columns from one DataFrame to another and save the result to an Excel file.

```python
# First, make a copy
my_input_c3=my_input.copy()
# Allocate a new column to this dataframe, LHS give whatever you to call it,
#RHS is the variable, but now your must specify the colum
my_input_c3['Temp_eq33_5kbar']=Temp_eq33_5kbar_Eq_tests['T_K_calc']
# Append a second column
my_input_c3['Eq Tests Neave2017?']=Temp_eq33_5kbar_Eq_tests['Eq Tests Neave2017?']
# Save to an Excel sheet called "Calc1" using the pandas to excel function
my_input_c3.to_excel('Calc3.xlsx')
```
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