The package herein helps visualise the relationship between the uniaxial compressive strength (UCS), Young's Modulus (E), and the in-direct tensile strength, commonly known as the Brazilian Disc (BD). The Modulus Ratio (MR) [[1]](#1) is the correlation between the UCS and E while the Strength Ratio (SR) [[2]](#2) is the correlation between the BD and UCS.
## pyrockmodulus.modulus_ratio()
Loads the digitized Deere_Miller clusters and plots them based on the major rock type *(i.e., Igneous / Metamorphic / Sedimentary)*. Two options are available to plot his information:
- Individually.
- All major rock types in one figure.
**Modulus Ratio [[1]](#1) Example**
1. Plot the MR of just the Sedimentary clusters with the ISRM 1979 [[3]](#3) category classification.
```python
import pyrockmodulus
import matplotlib.pyplot as plt
mr_mod_plot = pyrockmodulus.modulus_ratio()
mr_mod_plot.initial_processing(plot_all_clusters=False, rock_type_to_plot='Sedimentary', ucs_class_type="ISRMCAT\n1979")
plt.ylabel("E (GPa)")
plt.xlabel("UCS (MPa)")
plt.show()
```
2. Plot the MR with all the categories without the classification. Legend enabled.
```python
import pyrockmodulus
import matplotlib.pyplot as plt
mr_mod_plot = pyrockmodulus.modulus_ratio()
mr_mod_plot.initial_processing(plot_all_clusters=True)
plt.ylabel("E (GPa)")
plt.xlabel("UCS (MPa)")
plt.legend()
plt.show()
```
3. Plot the MR of just the Sedimentary clusters overlaid with data from tests.
```python
import pyrockmodulus
import matplotlib.pyplot as plt
# Data Set
ucs_data = [75.33, 99.03, 111.69, 30.17, 73.76, 41.69, 42.09, 60.99, 39.65, 94.52, 104.6, 102.03]
E_data = [18.31, 21.85, 20.51, 8.62, 25.72, 18.68, 9.2, 14.67, 7.38, 8.48, 8.7, 8.82]
mr_mod_plot = pyrockmodulus.modulus_ratio()
mr_mod_axis = mr_mod_plot.initial_processing(rock_type_to_plot='Sedimentary')
# Plot the data on the Deere-Miller axis
mr_mod_axis.scatter(ucs_data, E_data, label='Test Results', marker='.')
plt.ylabel("E (GPa)")
plt.xlabel("UCS (MPa)")
plt.legend()
plt.show()
```
## pyrockmodulus.strength_ratio()
Loads the constructed Strength Ratio clusters [[2]](#2) and plots them based on the major rock type *(i.e., Igneous / Metamorphic / Sedimentary)*. Two options are available to plot his information:
- Individually.
- All major rock types in one figure.
The functionality is similar to that of the modulus ratio.
```python
import pyrockmodulus
import matplotlib.pyplot as plt
sr_mod_plot = pyrockmodulus.strength_ratio()
sr_mod_plot.initial_processing(plot_all_clusters=False, rock_type_to_plot='Sedimentary')
plt.ylabel("UCS (MPa)")
plt.xlabel("BDS (MPa)")
plt.show()
```
## pyrockmodulus.poisson_density()
Plot the most common ranges of density and poisson's ratio for rock. This data can then be overlaid with data from a specific source to show comparison.
```python
import matplotlib.pyplot as plt
import pyrockmodulus
poi_den = pyrockmodulus.poisson_density()
df_data = poi_den.initial_processing()
ax1 = poi_den.plot_span_chart(df_data, ['Min_D', 'Max_D'], 'Density', r'$\rho$ g/cm$^{3}$')
ax1.axvline(2.0, lw=1, ls='--')
plt.show()
```
## UCS_Descriptions.py
This file holds the dictionaries for the various UCS classification systems available. References for those systems are within the file. All values **must** be in **MPa**.
Avaliable classificatin systems 'ISRMCAT\n1979' [[3]](#3), 'Bieniawski\n1974' [[4]](#4), 'Jennings\n1973' [[5]](#5), 'Broch & Franklin\n1972' [[6]](#6), 'Geological Society\n1970', 'Deere & Miller\n1966' [[7]](#7), 'Coates\n1964' [[8]](#8), 'Coates & Parsons\n1966' [[9]](#9), 'ISO 14689\n2017' [[10]](#10), 'Anon\n1977' [[11]](#11), 'Anon\n1979' [[12]](#12), 'Ramamurthy\n2004' [[13]](#13)
**UCS Classification System Examples**
1. Display the limits and the classification system default in the script.
```python
import pyrockmodulus.rock_variables as ucs_class
ucs_class.ucs_strength_criteria('ISRMCAT\n1979')
```
Output
```
(['R0', 'R1', 'R2', 'R3', 'R4', 'R5', 'R6'], [0.25, 1, 5, 25, 50, 100, 250, 1000])
```
2. A horizontal bar like plot to show the various uniaxial strength classification systems.
```python
import pyrockmodulus.ucs_bar_chart_plot as ucs_classification_plot
import matplotlib.pyplot as plt
ucs_class = ucs_classification_plot.initial_processing()
plt.show()
```
## References
<a id="1">[1]</a>
Deere D, Miller R (1966) Engineering classification and index properties for intact rock. Tech. Report No AFWL - TR-65-116. Air Force Weapons Lab., Kirtland Air Base, New Mexico.
<a id="2">[2]</a>
Tatone, B.S.A., Abdelaziz, A. & Grasselli, G. Novel Mechanical Classification Method of Rock Based on the Uniaxial Compressive Strength and Brazilian Disc Strength. Rock Mech Rock Eng 55, 2503–2507 (2022). https://doi.org/10.1007/s00603-021-02759-7
<a id="3">[3]</a>
ISRM commission on standardization of laboratory and field tests: "Suggested methods for the quantitative description of discontinuities in rock masses" International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts,Volume 15, Issue 6, 1978, Pages 319-368, ISSN 0148-9062, https://doi.org/10.1016/0148-9062(78)91472-9.
<a id="4">[4]</a>
Bieniawski ZT (1973) Engineering classification of jointed rock masses. The Civil Engineering in Southern Africa 15
<a id="5">[5]</a>
Jennings JE, Brink ABA, Williams AAB (1973) Revised guide to soil profiling for civil engineering purposes in Southern Africa. The Civil Engineering in Southern Africa 15:3–12. https://doi.org/10.1016/0148-9062(74)91296-0
<a id="6">[6]</a>
Broch E, Franklin JA (1972) The point-load strength test. Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 9:669–676. https://doi.org/10.1016/0148-9062(72)90030-7
<a id="7">[7]</a>
Deere & Miller\n1966 = DEERE, D. U. y MILLER, R. P.. Engineering Classification and Index Properties for Intact Rocks. Kirtland Air Force Base, New Mexico: 1966.
<a id="8">[8]</a>
Coates DF (1964) Classification of rocks for rock mechanics. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 1:421–429. https://doi.org/10.1016/0148-9062(64)90008-7
<a id="9">[9]</a>
Coates DF, Parsons RC (1966) Experimental criteria for classification of rock substances. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 3:181–189. https://doi.org/10.1016/0148-9062(66)90022-2
<a id="10">[10]</a>
ISO 14689:2017 "Geotechnical investigation and testing — Identification, description and classification of rock."
<a id="11">[11]</a>
Anon, Q. "The description of rock masses for engineering purposes." J Eng Geol 10 (1977): 355-388.
<a id="12">[12]</a>
Anon, O. H. "Classification of rocks and soils for engineering geological mapping. Part 1: rock and soil materials.".
<a id="13">[13]</a>
Ramamurthy, T. "A geo-engineering classification for rocks and rock masses." International Journal of Rock Mechanics and Mining Sciences 41.1 (2004): 89-101.
Raw data
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"description": "The package herein helps visualise the relationship between the uniaxial compressive strength (UCS), Young's Modulus (E), and the in-direct tensile strength, commonly known as the Brazilian Disc (BD). The Modulus Ratio (MR) [[1]](#1) is the correlation between the UCS and E while the Strength Ratio (SR) [[2]](#2) is the correlation between the BD and UCS.\n\n## pyrockmodulus.modulus_ratio()\n\nLoads the digitized Deere_Miller clusters and plots them based on the major rock type *(i.e., Igneous / Metamorphic / Sedimentary)*. Two options are available to plot his information: \n- Individually.\n- All major rock types in one figure.\n\n**Modulus Ratio [[1]](#1) Example**\n\n1. Plot the MR of just the Sedimentary clusters with the ISRM 1979 [[3]](#3) category classification.\n```python\nimport pyrockmodulus\nimport matplotlib.pyplot as plt\n\nmr_mod_plot = pyrockmodulus.modulus_ratio()\nmr_mod_plot.initial_processing(plot_all_clusters=False, rock_type_to_plot='Sedimentary', ucs_class_type=\"ISRMCAT\\n1979\")\nplt.ylabel(\"E (GPa)\")\nplt.xlabel(\"UCS (MPa)\")\nplt.show()\n```\n\n\n2. Plot the MR with all the categories without the classification. Legend enabled. \n\n```python\nimport pyrockmodulus\nimport matplotlib.pyplot as plt\n\nmr_mod_plot = pyrockmodulus.modulus_ratio()\nmr_mod_plot.initial_processing(plot_all_clusters=True)\nplt.ylabel(\"E (GPa)\")\nplt.xlabel(\"UCS (MPa)\")\nplt.legend()\nplt.show()\n```\n\n\n3. Plot the MR of just the Sedimentary clusters overlaid with data from tests.\n\n```python\nimport pyrockmodulus\nimport matplotlib.pyplot as plt\n# Data Set\nucs_data = [75.33, 99.03, 111.69, 30.17, 73.76, 41.69, 42.09, 60.99, 39.65, 94.52, 104.6, 102.03]\nE_data = [18.31, 21.85, 20.51, 8.62, 25.72, 18.68, 9.2, 14.67, 7.38, 8.48, 8.7, 8.82]\nmr_mod_plot = pyrockmodulus.modulus_ratio()\nmr_mod_axis = mr_mod_plot.initial_processing(rock_type_to_plot='Sedimentary')\n# Plot the data on the Deere-Miller axis\nmr_mod_axis.scatter(ucs_data, E_data, label='Test Results', marker='.')\nplt.ylabel(\"E (GPa)\")\nplt.xlabel(\"UCS (MPa)\")\nplt.legend()\nplt.show()\n```\n \n\n## pyrockmodulus.strength_ratio()\n\nLoads the constructed Strength Ratio clusters [[2]](#2) and plots them based on the major rock type *(i.e., Igneous / Metamorphic / Sedimentary)*. Two options are available to plot his information: \n- Individually.\n- All major rock types in one figure.\n\nThe functionality is similar to that of the modulus ratio. \n\n```python\nimport pyrockmodulus\nimport matplotlib.pyplot as plt\n\nsr_mod_plot = pyrockmodulus.strength_ratio()\nsr_mod_plot.initial_processing(plot_all_clusters=False, rock_type_to_plot='Sedimentary')\nplt.ylabel(\"UCS (MPa)\")\nplt.xlabel(\"BDS (MPa)\")\nplt.show()\n```\n\n\n## pyrockmodulus.poisson_density()\n\nPlot the most common ranges of density and poisson's ratio for rock. This data can then be overlaid with data from a specific source to show comparison. \n\n```python\nimport matplotlib.pyplot as plt\nimport pyrockmodulus\npoi_den = pyrockmodulus.poisson_density()\ndf_data = poi_den.initial_processing()\nax1 = poi_den.plot_span_chart(df_data, ['Min_D', 'Max_D'], 'Density', r'$\\rho$ g/cm$^{3}$')\nax1.axvline(2.0, lw=1, ls='--')\nplt.show()\n```\n\n\n\n## UCS_Descriptions.py\n\nThis file holds the dictionaries for the various UCS classification systems available. References for those systems are within the file. All values **must** be in **MPa**.\nAvaliable classificatin systems 'ISRMCAT\\n1979' [[3]](#3), 'Bieniawski\\n1974' [[4]](#4), 'Jennings\\n1973' [[5]](#5), 'Broch & Franklin\\n1972' [[6]](#6), 'Geological Society\\n1970', 'Deere & Miller\\n1966' [[7]](#7), 'Coates\\n1964' [[8]](#8), 'Coates & Parsons\\n1966' [[9]](#9), 'ISO 14689\\n2017' [[10]](#10), 'Anon\\n1977' [[11]](#11), 'Anon\\n1979' [[12]](#12), 'Ramamurthy\\n2004' [[13]](#13)\n\n**UCS Classification System Examples** \n\n1. Display the limits and the classification system default in the script. \n```python\nimport pyrockmodulus.rock_variables as ucs_class\nucs_class.ucs_strength_criteria('ISRMCAT\\n1979')\n```\nOutput\n```\n(['R0', 'R1', 'R2', 'R3', 'R4', 'R5', 'R6'], [0.25, 1, 5, 25, 50, 100, 250, 1000])\n```\n\n2. A horizontal bar like plot to show the various uniaxial strength classification systems.\n\n```python\nimport pyrockmodulus.ucs_bar_chart_plot as ucs_classification_plot\nimport matplotlib.pyplot as plt\n\nucs_class = ucs_classification_plot.initial_processing()\nplt.show()\n```\n\n\n## References\n<a id=\"1\">[1]</a> \nDeere D, Miller R (1966) Engineering classification and index properties for intact rock. Tech. Report No AFWL - TR-65-116. Air Force Weapons Lab., Kirtland Air Base, New Mexico.\n\n<a id=\"2\">[2]</a>\nTatone, B.S.A., Abdelaziz, A. & Grasselli, G. Novel Mechanical Classification Method of Rock Based on the Uniaxial Compressive Strength and Brazilian Disc Strength. Rock Mech Rock Eng 55, 2503\u20132507 (2022). https://doi.org/10.1007/s00603-021-02759-7\n\n<a id=\"3\">[3]</a>\nISRM commission on standardization of laboratory and field tests: \"Suggested methods for the quantitative description of discontinuities in rock masses\" International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts,Volume 15, Issue 6, 1978, Pages 319-368, ISSN 0148-9062, https://doi.org/10.1016/0148-9062(78)91472-9.\n\n<a id=\"4\">[4]</a>\nBieniawski ZT (1973) Engineering classification of jointed rock masses. The Civil Engineering in Southern Africa 15\n\n<a id=\"5\">[5]</a>\nJennings JE, Brink ABA, Williams AAB (1973) Revised guide to soil profiling for civil engineering purposes in Southern Africa. The Civil Engineering in Southern Africa 15:3\u201312. https://doi.org/10.1016/0148-9062(74)91296-0\n\n<a id=\"6\">[6]</a>\nBroch E, Franklin JA (1972) The point-load strength test. Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 9:669\u2013676. https://doi.org/10.1016/0148-9062(72)90030-7\n\n<a id=\"7\">[7]</a>\nDeere & Miller\\n1966 = DEERE, D. U. y MILLER, R. P.. Engineering Classification and Index Properties for Intact Rocks. Kirtland Air Force Base, New Mexico: 1966.\n\n<a id=\"8\">[8]</a>\nCoates DF (1964) Classification of rocks for rock mechanics. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 1:421\u2013429. https://doi.org/10.1016/0148-9062(64)90008-7\n\n<a id=\"9\">[9]</a>\nCoates DF, Parsons RC (1966) Experimental criteria for classification of rock substances. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 3:181\u2013189. https://doi.org/10.1016/0148-9062(66)90022-2\n\n<a id=\"10\">[10]</a>\nISO 14689:2017 \"Geotechnical investigation and testing \u2014 Identification, description and classification of rock.\"\n\n<a id=\"11\">[11]</a>\nAnon, Q. \"The description of rock masses for engineering purposes.\" J Eng Geol 10 (1977): 355-388.\n\n<a id=\"12\">[12]</a>\nAnon, O. H. \"Classification of rocks and soils for engineering geological mapping. Part 1: rock and soil materials.\".\n\n<a id=\"13\">[13]</a>\nRamamurthy, T. \"A geo-engineering classification for rocks and rock masses.\" International Journal of Rock Mechanics and Mining Sciences 41.1 (2004): 89-101.\n",
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