Validation US Designation¶

In this page, we validate the section properties of some US designations. All W, S, M, WT, ST, MT, HP, HSS designations, which are compiled and well documented in the AISC Shapes Database v16.0, are included.

Some Utilities¶

The spreadsheet is loaded directly via the url.

In [1]:

import pandas

section_table = pandas.read_excel(
    "https://www.aisc.org/globalassets/product-files-not-searched/manuals/aisc-shapes-database-v16.0.xlsx",
    sheet_name=1,
    storage_options={"User-Agent": "Mozilla/5.0"},
    usecols="A:CF",
)
print(section_table.head())

import pandas section_table = pandas.read_excel( "https://www.aisc.org/globalassets/product-files-not-searched/manuals/aisc-shapes-database-v16.0.xlsx", sheet_name=1, storage_options={"User-Agent": "Mozilla/5.0"}, usecols="A:CF", ) print(section_table.head())

  Type EDI_Std_Nomenclature AISC_Manual_Label T_F      W      A     d    ddet  \
0    W              W44X408           W44X408   T  408.0  120.0  44.8   44.75   
1    W              W44X368           W44X368   F  368.0  108.0  44.4  44.375   
2    W              W44X335           W44X335   F  335.0   98.5    44      44   
3    W              W44X290           W44X290   F  290.0   85.4  43.6  43.625   
4    W              W44X262           W44X262   F  262.0   77.2  43.3   43.25   

  Ht  h  ...   rts    ho   PA PA2   PB   PC   PD   T  WGi WGo  
0  –  –  ...  4.33  42.6  134   –  150  106  122  38  5.5   3  
1  –  –  ...  4.28  42.4  133   –  149  105  121  38  5.5   3  
2  –  –  ...  4.24  42.2  132   –  148  104  120  38  5.5   3  
3  –  –  ...   4.2    42  131   –  147  103  119  38  5.5   3  
4  –  –  ...  4.17  41.9  131   –  147  102  118  38  5.5   3  

[5 rows x 84 columns]

We define a function to get the area, moment of inertia about the strong and weak axes.

In [2]:

def get_properties(designation: str):
    section = section_table[section_table["AISC_Manual_Label"] == designation]
    return [section[x].values[0] for x in ("A", "Ix", "Iy")]

def get_properties(designation: str): section = section_table[section_table["AISC_Manual_Label"] == designation] return [section[x].values[0] for x in ("A", "Ix", "Iy")]

Analysis Template¶

Next, we define the function to run the analysis and extract the result.

The following is the template model file that will be used. A few things to note:

1. The material is assumed to be elastic with a unit elastic modulus.
2. The default integration scheme is used for each designation.
3. A unit displacement load is applied to axial, strong axis bending and weak axis bending.
4. The US3DC category is used, it automatically recentre the section to its barycentre if it is not symmetric.

In [3]:

template = """
node 1 0 0 0

material Elastic1D 1 1

section US3DC $designation$ 1 1 1

element SingleSection3D 1 1 1

displacement 1 0 1 1 1
displacement 2 0 1 2 1
displacement 3 0 1 3 1

step static 1 1
set ini_step_size 1

analyze

peek node 1

exit
"""

template = """ node 1 0 0 0 material Elastic1D 1 1 section US3DC $designation$ 1 1 1 element SingleSection3D 1 1 1 displacement 1 0 1 1 1 displacement 2 0 1 2 1 displacement 3 0 1 3 1 step static 1 1 set ini_step_size 1 analyze peek node 1 exit """

By using the above settings, the resistances on three DoFs are effectively the area and moments of inertia.

Extract Results¶

To extract the data, we process the output.

In [4]:

import subprocess
import tempfile


def run_analysis(designation: str):
    with tempfile.NamedTemporaryFile() as fp:
        with open(fp.name, "w") as f:
            f.write(template.replace("$designation$", designation))

        result = (
            subprocess.check_output(["suanpan", "-nu", "-nc", "-f", fp.name])
            .decode("utf-8")
            .splitlines()
        )

    for i, line in enumerate(result):
        if line.startswith("Resistance"):
            return [float(x) for x in result[i + 1].split()]

import subprocess import tempfile def run_analysis(designation: str): with tempfile.NamedTemporaryFile() as fp: with open(fp.name, "w") as f: f.write(template.replace("$designation$", designation)) result = ( subprocess.check_output(["suanpan", "-nu", "-nc", "-f", fp.name]) .decode("utf-8") .splitlines() ) for i, line in enumerate(result): if line.startswith("Resistance"): return [float(x) for x in result[i + 1].split()]

The ratio between numerical result and the reference value given in the database is stored. Ideally, this ratio shall be close to unity, meaning a good match.

In [5]:

all_results = {}


def validate(designation: str):
    if result := run_analysis(designation):
        all_results[designation] = [
            x / y for x, y in zip(result, get_properties(designation))
        ]

all_results = {} def validate(designation: str): if result := run_analysis(designation): all_results[designation] = [ x / y for x, y in zip(result, get_properties(designation)) ]

Collect All Sections¶

We can now iterate over all sections.

In [6]:

for _, row in section_table[
    section_table["AISC_Manual_Label"].str.startswith(("W", "M", "S", "HP", "HSS"))
].iterrows():
    designation = row["AISC_Manual_Label"]
    # ignore C sections
    if designation.startswith("MC"):
        continue

    validate(designation)

for _, row in section_table[ section_table["AISC_Manual_Label"].str.startswith(("W", "M", "S", "HP", "HSS")) ].iterrows(): designation = row["AISC_Manual_Label"] # ignore C sections if designation.startswith("MC"): continue validate(designation)

In [7]:

import matplotlib.pyplot as plt


fig = plt.figure(figsize=(90, 50), tight_layout=True)


rhs_results = {
    k: v for k, v in all_results.items() if k.startswith("HSS") and k.count("X") == 2
}
chs_results = {
    k: v for k, v in all_results.items() if k.startswith("HSS") and k.count("X") == 1
}
i_results = {
    k: v for k, v in all_results.items() if not k.startswith("HSS") and "T" not in k
}
t_results = {
    k: v for k, v in all_results.items() if not k.startswith("HSS") and "T" in k
}
chs_t_results = {**chs_results, **t_results}

total = 3 * (int(bool(rhs_results)) + int(bool(i_results)) + int(bool(chs_t_results)))

counter = 0


def plot(title, index, results):
    if not results:
        return
    values = [x[index] for x in results.values()]
    min_value = min(values)
    max_value = max(values)
    colors = ["red" if abs(x - 1) > 0.05 else "green" for x in values]
    global counter
    counter += 1
    ax = fig.add_subplot(total, 1, counter)
    ax.bar(results.keys(), values, color=colors)
    ax.set_ylabel("Numerical/Analytical")
    ax.set_xlabel("Section")
    ax.set_ybound(min_value - 0.02, max_value + 0.01)
    ax.set_xlim(-1, len(results))
    ax.grid()

    for i, v in enumerate(values):
        ax.text(
            i, min_value - 0.01, f"{v:.3f}", horizontalalignment="center", rotation=90
        )

    ax.set_title(title)
    ax.set_xticks(ax.get_xticks())
    ax.set_xticklabels(ax.get_xticklabels(), rotation=90)


plot("HSS (Rectangle) Area", 0, rhs_results)
plot("HSS (Rectangle) Strong Axis Moment of Inertia", 1, rhs_results)
plot("HSS (Rectangle) Weak Axis Moment of Inertia", 2, rhs_results)
plot("I-Section Area", 0, i_results)
plot("I-Section Strong Axis Moment of Inertia", 1, i_results)
plot("I-Section Weak Axis Moment of Inertia", 2, i_results)
plot("HSS (Circle) and T-Section Area", 0, chs_t_results)
plot(
    "HSS (Circle) and T-Section Strong Axis Moment of Inertia",
    1,
    chs_t_results,
)
plot("HSS (Circle) and T-Section Weak Axis Moment of Inertia", 2, chs_t_results)

import matplotlib.pyplot as plt fig = plt.figure(figsize=(90, 50), tight_layout=True) rhs_results = { k: v for k, v in all_results.items() if k.startswith("HSS") and k.count("X") == 2 } chs_results = { k: v for k, v in all_results.items() if k.startswith("HSS") and k.count("X") == 1 } i_results = { k: v for k, v in all_results.items() if not k.startswith("HSS") and "T" not in k } t_results = { k: v for k, v in all_results.items() if not k.startswith("HSS") and "T" in k } chs_t_results = {**chs_results, **t_results} total = 3 * (int(bool(rhs_results)) + int(bool(i_results)) + int(bool(chs_t_results))) counter = 0 def plot(title, index, results): if not results: return values = [x[index] for x in results.values()] min_value = min(values) max_value = max(values) colors = ["red" if abs(x - 1) > 0.05 else "green" for x in values] global counter counter += 1 ax = fig.add_subplot(total, 1, counter) ax.bar(results.keys(), values, color=colors) ax.set_ylabel("Numerical/Analytical") ax.set_xlabel("Section") ax.set_ybound(min_value - 0.02, max_value + 0.01) ax.set_xlim(-1, len(results)) ax.grid() for i, v in enumerate(values): ax.text( i, min_value - 0.01, f"{v:.3f}", horizontalalignment="center", rotation=90 ) ax.set_title(title) ax.set_xticks(ax.get_xticks()) ax.set_xticklabels(ax.get_xticklabels(), rotation=90) plot("HSS (Rectangle) Area", 0, rhs_results) plot("HSS (Rectangle) Strong Axis Moment of Inertia", 1, rhs_results) plot("HSS (Rectangle) Weak Axis Moment of Inertia", 2, rhs_results) plot("I-Section Area", 0, i_results) plot("I-Section Strong Axis Moment of Inertia", 1, i_results) plot("I-Section Weak Axis Moment of Inertia", 2, i_results) plot("HSS (Circle) and T-Section Area", 0, chs_t_results) plot( "HSS (Circle) and T-Section Strong Axis Moment of Inertia", 1, chs_t_results, ) plot("HSS (Circle) and T-Section Weak Axis Moment of Inertia", 2, chs_t_results)

Area¶

In general, the area can be relatively accurately computed. However, as all those sections are internally modelled by three flat pieces, the root fillet cannot be accounted for. As a result, the numerical area is often smaller than the reference value.

Some very light M shapes cannot be well approximated.

Strong Axis Bending¶

Some very heavy T sections tend to have poor strong axis moment of inertia. In this shapes, the thickness of flange accounts for a significant portion of the overall depth. The normal stress in the flange presents gradient. In the meantime, there is only one layer of integration points along the thickness of flange, which is not accurate enough in this case.

Weak Axis Bending¶

The tapered shapes tend to have more material towards the center, as a result, the weak axis moment of inertia is smaller. It is modelled by a flat rectangle in numerical models, this overestimate the moment of inertia, mainly for S and ST shapes.

In [8]:

fig.savefig("US.pdf")

fig.savefig("US.pdf")

The figures can be downloaded: us.

Automation Utilities¶

The following is the script to generate autocompletion. Readers can safely ignore it.

In [9]:

us_section = {}
for key, value in all_results.items():
    num_ip = 10 if "HSS" in key and key.count("X") == 1 else 6

    us_section[f"{key}-2D"] = {
        "prefix": key,
        "description": f"US 2D section {key}, accuracy: {value[0]:.2f}/{value[1]:.2f}",
        "body": [
            f"section US2D {key} " + "${1:(1)} ${2:(2)} ${3:[3]} ${4:[4]} ${5:[5]}",
            "# (1) int, unique tag",
            "# (2) int, material tag",
            "# [3] double, scale, default: 1.0",
            f"# [4] int, number of integration points, default: {num_ip}",
            "# [5] double, eccentricity, default: 0.0",
            "",
        ],
    }
    us_section[f"{key}-3D"] = {
        "prefix": key,
        "description": f"US 3D section {key}, accuracy: {value[0]:.2f}/{value[1]:.2f}/{value[2]:.2f}",
        "body": [
            f"section US3D {key} "
            + "${1:(1)} ${2:(2)} ${3:[3]} ${4:[4]} ${5:[5]} ${6:[6]}",
            "# (1) int, unique tag",
            "# (2) int, material tag",
            "# [3] double, scale, default: 1.0",
            f"# [4] int, number of integration points, default: {num_ip}",
            "# [5] double, eccentricity of y axis, default: 0.0",
            "# [6] double, eccentricity of z axis, default: 0.0",
            "",
        ],
    }

us_section = {} for key, value in all_results.items(): num_ip = 10 if "HSS" in key and key.count("X") == 1 else 6 us_section[f"{key}-2D"] = { "prefix": key, "description": f"US 2D section {key}, accuracy: {value[0]:.2f}/{value[1]:.2f}", "body": [ f"section US2D {key} " + "${1:(1)} ${2:(2)} ${3:[3]} ${4:[4]} ${5:[5]}", "# (1) int, unique tag", "# (2) int, material tag", "# [3] double, scale, default: 1.0", f"# [4] int, number of integration points, default: {num_ip}", "# [5] double, eccentricity, default: 0.0", "", ], } us_section[f"{key}-3D"] = { "prefix": key, "description": f"US 3D section {key}, accuracy: {value[0]:.2f}/{value[1]:.2f}/{value[2]:.2f}", "body": [ f"section US3D {key} " + "${1:(1)} ${2:(2)} ${3:[3]} ${4:[4]} ${5:[5]} ${6:[6]}", "# (1) int, unique tag", "# (2) int, material tag", "# [3] double, scale, default: 1.0", f"# [4] int, number of integration points, default: {num_ip}", "# [5] double, eccentricity of y axis, default: 0.0", "# [6] double, eccentricity of z axis, default: 0.0", "", ], }

In [10]:

import json

with open("us_sections_completion.json", "w") as f:
    json.dump({k: v for k, v in sorted(us_section.items())}, f, indent=4)

import json with open("us_sections_completion.json", "w") as f: json.dump({k: v for k, v in sorted(us_section.items())}, f, indent=4)

In [11]:

highlighting = []
for key in sorted(all_results.keys()):
    highlighting.append(
        {
            "name": "support.constant.section",
            "match": "\\b(?i)" + key.replace(".", "\\.") + "\\b",
        },
    )

with open("us_sections_highlight.json", "w") as f:
    json.dump(highlighting, f, indent=4)

print(
    r"\b(?i)("
    + "|".join([x.replace(".", r"\.") for x in sorted(all_results.keys())])
    + r")\b"
)

highlighting = [] for key in sorted(all_results.keys()): highlighting.append( { "name": "support.constant.section", "match": "\\b(?i)" + key.replace(".", "\\.") + "\\b", }, ) with open("us_sections_highlight.json", "w") as f: json.dump(highlighting, f, indent=4) print( r"\b(?i)(" + "|".join([x.replace(".", r"\.") for x in sorted(all_results.keys())]) + r")\b" )

\b(?i)(HP10X42|HP10X57|HP12X53|HP12X63|HP12X74|HP12X84|HP12X89|HP14X102|HP14X117|HP14X73|HP14X89|HP16X101|HP16X121|HP16X141|HP16X162|HP16X183|HP16X88|HP18X135|HP18X157|HP18X181|HP18X204|HP8X36|M10X7\.5|M10X8|M10X9|M12\.5X11\.6|M12\.5X12\.4|M12X10|M12X10\.8|M12X11\.8|M3X2\.9|M4X4\.08|M4X6|M5X18\.9|M6X3\.7|M6X4\.4|M8X6\.2|M8X6\.5|MT2\.5X9\.45|MT2X3|MT3X1\.85|MT3X2\.2|MT4X3\.1|MT4X3\.25|MT5X3\.75|MT5X4|MT5X4\.5|MT6\.25X5\.8|MT6\.25X6\.2|MT6X5|MT6X5\.4|MT6X5\.9|S10X25\.4|S10X35|S12X31\.8|S12X35|S12X40\.8|S12X50|S15X42\.9|S15X50|S18X54\.7|S18X70|S20X66|S20X75|S20X86|S20X96|S24X100|S24X106|S24X121|S24X80|S24X90|S3X5\.7|S3X7\.5|S4X7\.7|S4X9\.5|S5X10|S6X12\.5|S6X17\.25|S8X18\.4|S8X23|ST1\.5X2\.85|ST1\.5X3\.75|ST10X33|ST10X37\.5|ST10X43|ST10X48|ST12X40|ST12X45|ST12X50|ST12X53|ST12X60\.5|ST2\.5X5|ST2X3\.85|ST2X4\.75|ST3X6\.25|ST3X8\.6|ST4X11\.5|ST4X9\.2|ST5X12\.7|ST5X17\.5|ST6X15\.9|ST6X17\.5|ST6X20\.4|ST6X25|ST7\.5X21\.45|ST7\.5X25|ST9X27\.35|ST9X35|W10X100|W10X112|W10X12|W10X15|W10X17|W10X19|W10X22|W10X26|W10X30|W10X33|W10X39|W10X45|W10X49|W10X54|W10X60|W10X68|W10X77|W10X88|W12X106|W12X120|W12X136|W12X14|W12X152|W12X16|W12X170|W12X19|W12X190|W12X210|W12X22|W12X230|W12X252|W12X26|W12X279|W12X30|W12X305|W12X336|W12X35|W12X40|W12X45|W12X50|W12X53|W12X58|W12X65|W12X72|W12X79|W12X87|W12X96|W14X109|W14X120|W14X132|W14X145|W14X159|W14X176|W14X193|W14X211|W14X22|W14X233|W14X257|W14X26|W14X283|W14X30|W14X311|W14X34|W14X342|W14X370|W14X38|W14X398|W14X426|W14X43|W14X455|W14X48|W14X500|W14X53|W14X550|W14X605|W14X61|W14X665|W14X68|W14X730|W14X74|W14X808|W14X82|W14X873|W14X90|W14X99|W16X100|W16X26|W16X31|W16X36|W16X40|W16X45|W16X50|W16X57|W16X67|W16X77|W16X89|W18X106|W18X119|W18X130|W18X143|W18X158|W18X175|W18X192|W18X211|W18X234|W18X258|W18X283|W18X311|W18X35|W18X40|W18X46|W18X50|W18X55|W18X60|W18X65|W18X71|W18X76|W18X86|W18X97|W21X101|W21X111|W21X122|W21X132|W21X147|W21X166|W21X182|W21X201|W21X223|W21X248|W21X275|W21X44|W21X48|W21X50|W21X55|W21X57|W21X62|W21X68|W21X73|W21X83|W21X93|W24X103|W24X104|W24X117|W24X131|W24X146|W24X162|W24X176|W24X192|W24X207|W24X229|W24X250|W24X279|W24X306|W24X335|W24X370|W24X55|W24X62|W24X68|W24X76|W24X84|W24X94|W27X102|W27X114|W27X129|W27X146|W27X161|W27X178|W27X194|W27X217|W27X235|W27X258|W27X281|W27X307|W27X336|W27X368|W27X539|W27X84|W27X94|W30X108|W30X116|W30X124|W30X132|W30X148|W30X173|W30X191|W30X211|W30X235|W30X261|W30X292|W30X326|W30X357|W30X391|W30X90|W30X99|W33X118|W33X130|W33X141|W33X152|W33X169|W33X201|W33X221|W33X241|W33X263|W33X291|W33X318|W33X354|W33X387|W36X135|W36X150|W36X160|W36X170|W36X182|W36X194|W36X210|W36X231|W36X232|W36X247|W36X256|W36X262|W36X282|W36X302|W36X330|W36X361|W36X395|W36X441|W36X487|W36X529|W36X652|W36X723|W36X802|W36X853|W36X925|W40X149|W40X167|W40X183|W40X199|W40X211|W40X215|W40X235|W40X249|W40X264|W40X277|W40X278|W40X294|W40X297|W40X324|W40X327|W40X331|W40X362|W40X372|W40X392|W40X397|W40X431|W40X503|W40X593|W40X655|W44X230|W44X262|W44X290|W44X335|W4X13|W5X16|W5X19|W6X12|W6X15|W6X16|W6X20|W6X25|W6X8\.5|W6X9|W8X10|W8X13|W8X15|W8X18|W8X21|W8X24|W8X28|W8X31|W8X35|W8X40|W8X48|W8X58|W8X67|WT10\.5X100\.5|WT10\.5X111\.5|WT10\.5X124|WT10\.5X137\.5|WT10\.5X22|WT10\.5X24|WT10\.5X25|WT10\.5X27\.5|WT10\.5X28\.5|WT10\.5X31|WT10\.5X34|WT10\.5X36\.5|WT10\.5X41\.5|WT10\.5X46\.5|WT10\.5X50\.5|WT10\.5X55\.5|WT10\.5X61|WT10\.5X66|WT10\.5X73\.5|WT10\.5X83|WT10\.5X91|WT12X103\.5|WT12X114\.5|WT12X125|WT12X139\.5|WT12X153|WT12X167\.5|WT12X185|WT12X27\.5|WT12X31|WT12X34|WT12X38|WT12X42|WT12X47|WT12X51\.5|WT12X52|WT12X58\.5|WT12X65\.5|WT12X73|WT12X81|WT12X88|WT12X96|WT13\.5X108\.5|WT13\.5X117\.5|WT13\.5X129|WT13\.5X140\.5|WT13\.5X153\.5|WT13\.5X168|WT13\.5X184|WT13\.5X269\.5|WT13\.5X42|WT13\.5X47|WT13\.5X51|WT13\.5X57|WT13\.5X64\.5|WT13\.5X73|WT13\.5X80\.5|WT13\.5X89|WT13\.5X97|WT15X105\.5|WT15X117\.5|WT15X130\.5|WT15X146|WT15X163|WT15X178\.5|WT15X195\.5|WT15X45|WT15X49\.5|WT15X54|WT15X58|WT15X62|WT15X66|WT15X74|WT15X86\.5|WT15X95\.5|WT16\.5X100\.5|WT16\.5X110\.5|WT16\.5X120\.5|WT16\.5X131\.5|WT16\.5X145\.5|WT16\.5X159|WT16\.5X177|WT16\.5X193\.5|WT16\.5X59|WT16\.5X65|WT16\.5X70\.5|WT16\.5X76|WT16\.5X84\.5|WT18X105|WT18X115\.5|WT18X116|WT18X123\.5|WT18X128|WT18X131|WT18X141|WT18X151|WT18X165|WT18X180\.5|WT18X197\.5|WT18X220\.5|WT18X243\.5|WT18X264\.5|WT18X326|WT18X361\.5|WT18X401|WT18X426\.5|WT18X462\.5|WT18X67\.5|WT18X75|WT18X80|WT18X85|WT18X91|WT18X97|WT2\.5X8|WT2\.5X9\.5|WT20X105\.5|WT20X107\.5|WT20X117\.5|WT20X124\.5|WT20X132|WT20X138\.5|WT20X139|WT20X147|WT20X148\.5|WT20X162|WT20X163\.5|WT20X165\.5|WT20X181|WT20X186|WT20X196|WT20X198\.5|WT20X215\.5|WT20X251\.5|WT20X296\.5|WT20X327\.5|WT20X74\.5|WT20X83\.5|WT20X91\.5|WT20X99\.5|WT22X115|WT22X131|WT22X145|WT22X167\.5|WT2X6\.5|WT3X10|WT3X12\.5|WT3X4\.25|WT3X4\.5|WT3X6|WT3X7\.5|WT3X8|WT4X10\.5|WT4X12|WT4X14|WT4X15\.5|WT4X17\.5|WT4X20|WT4X24|WT4X29|WT4X33\.5|WT4X5|WT4X6\.5|WT4X7\.5|WT4X9|WT5X11|WT5X13|WT5X15|WT5X16\.5|WT5X19\.5|WT5X22\.5|WT5X24\.5|WT5X27|WT5X30|WT5X34|WT5X38\.5|WT5X44|WT5X50|WT5X56|WT5X6|WT5X7\.5|WT5X8\.5|WT5X9\.5|WT6X105|WT6X11|WT6X115|WT6X126|WT6X13|WT6X139\.5|WT6X15|WT6X152\.5|WT6X168|WT6X17\.5|WT6X20|WT6X22\.5|WT6X25|WT6X26\.5|WT6X29|WT6X32\.5|WT6X36|WT6X39\.5|WT6X43\.5|WT6X48|WT6X53|WT6X60|WT6X68|WT6X7|WT6X76|WT6X8|WT6X85|WT6X9\.5|WT6X95|WT7X105\.5|WT7X11|WT7X116\.5|WT7X128\.5|WT7X13|WT7X141\.5|WT7X15|WT7X155\.5|WT7X17|WT7X171|WT7X185|WT7X19|WT7X199|WT7X21\.5|WT7X213|WT7X227\.5|WT7X24|WT7X250|WT7X26\.5|WT7X275|WT7X30\.5|WT7X302\.5|WT7X332\.5|WT7X34|WT7X365|WT7X37|WT7X404|WT7X41|WT7X436\.5|WT7X45|WT7X49\.5|WT7X54\.5|WT7X60|WT7X66|WT7X72\.5|WT7X79\.5|WT7X88|WT7X96\.5|WT8X13|WT8X15\.5|WT8X18|WT8X20|WT8X22\.5|WT8X25|WT8X28\.5|WT8X33\.5|WT8X38\.5|WT8X44\.5|WT8X50|WT9X105\.5|WT9X117|WT9X129|WT9X141\.5|WT9X155\.5|WT9X17\.5|WT9X20|WT9X23|WT9X25|WT9X27\.5|WT9X30|WT9X32\.5|WT9X35\.5|WT9X38|WT9X43|WT9X48\.5|WT9X53|WT9X59\.5|WT9X65|WT9X71\.5|WT9X79|WT9X87\.5|WT9X96)\b

In [12]:

from itertools import zip_longest


all_w = [x for x in all_results.keys() if x.startswith("W") and not x.startswith("WT")]
all_m = [x for x in all_results.keys() if x.startswith("M")]
all_s = [x for x in all_results.keys() if x.startswith("S") and not x.startswith("ST")]
all_hp = [x for x in all_results.keys() if x.startswith("HP")]
all_wt = [x for x in all_results.keys() if x.startswith("WT")]
all_mt = [x for x in all_results.keys() if x.startswith("MT")]
all_st = [x for x in all_results.keys() if x.startswith("ST")]
all_rhs = [x for x in all_results.keys() if x.startswith("HSS") and x.count("X") == 2]
all_chs = [x for x in all_results.keys() if x.startswith("HSS") and x.count("X") == 1]

md_table = [
    "| W       | M          | S        | HP       | WT           | MT         | ST          | HSS (Rectangle)     | HSS (Circle)    |",
    "|:--------|:-----------|:---------|:---------|:-------------|:-----------|:------------|:--------------------|:----------------|",
]
for w, m, s, hp, wt, mt, st, rhs, chs in zip_longest(
    all_w, all_m, all_s, all_hp, all_wt, all_mt, all_st, all_rhs, all_chs, fillvalue=""
):
    md_table.append(f"|{w}|{m}|{s}|{hp}|{wt}|{mt}|{st}|{rhs}|{chs}|")


print("\n".join(md_table))

from itertools import zip_longest all_w = [x for x in all_results.keys() if x.startswith("W") and not x.startswith("WT")] all_m = [x for x in all_results.keys() if x.startswith("M")] all_s = [x for x in all_results.keys() if x.startswith("S") and not x.startswith("ST")] all_hp = [x for x in all_results.keys() if x.startswith("HP")] all_wt = [x for x in all_results.keys() if x.startswith("WT")] all_mt = [x for x in all_results.keys() if x.startswith("MT")] all_st = [x for x in all_results.keys() if x.startswith("ST")] all_rhs = [x for x in all_results.keys() if x.startswith("HSS") and x.count("X") == 2] all_chs = [x for x in all_results.keys() if x.startswith("HSS") and x.count("X") == 1] md_table = [ "| W | M | S | HP | WT | MT | ST | HSS (Rectangle) | HSS (Circle) |", "|:--------|:-----------|:---------|:---------|:-------------|:-----------|:------------|:--------------------|:----------------|", ] for w, m, s, hp, wt, mt, st, rhs, chs in zip_longest( all_w, all_m, all_s, all_hp, all_wt, all_mt, all_st, all_rhs, all_chs, fillvalue="" ): md_table.append(f"|{w}|{m}|{s}|{hp}|{wt}|{mt}|{st}|{rhs}|{chs}|") print("\n".join(md_table))

| W       | M          | S        | HP       | WT           | MT         | ST          | HSS (Rectangle)     | HSS (Circle)    |
|:--------|:-----------|:---------|:---------|:-------------|:-----------|:------------|:--------------------|:----------------|
|W44X335|M12.5X12.4|S24X121|HP18X204|WT22X167.5|MT6.25X6.2|ST12X60.5|||
|W44X290|M12.5X11.6|S24X106|HP18X181|WT22X145|MT6.25X5.8|ST12X53|||
|W44X262|M12X11.8|S24X100|HP18X157|WT22X131|MT6X5.9|ST12X50|||
|W44X230|M12X10.8|S24X90|HP18X135|WT22X115|MT6X5.4|ST12X45|||
|W40X655|M12X10|S24X80|HP16X183|WT20X327.5|MT6X5|ST12X40|||
|W40X593|M10X9|S20X96|HP16X162|WT20X296.5|MT5X4.5|ST10X48|||
|W40X503|M10X8|S20X86|HP16X141|WT20X251.5|MT5X4|ST10X43|||
|W40X431|M10X7.5|S20X75|HP16X121|WT20X215.5|MT5X3.75|ST10X37.5|||
|W40X397|M8X6.5|S20X66|HP16X101|WT20X198.5|MT4X3.25|ST10X33|||
|W40X372|M8X6.2|S18X70|HP16X88|WT20X186|MT4X3.1|ST9X35|||
|W40X362|M6X4.4|S18X54.7|HP14X117|WT20X181|MT3X2.2|ST9X27.35|||
|W40X324|M6X3.7|S15X50|HP14X102|WT20X162|MT3X1.85|ST7.5X25|||
|W40X297|M5X18.9|S15X42.9|HP14X89|WT20X148.5|MT2.5X9.45|ST7.5X21.45|||
|W40X277|M4X6|S12X50|HP14X73|WT20X138.5|MT2X3|ST6X25|||
|W40X249|M4X4.08|S12X40.8|HP12X89|WT20X124.5||ST6X20.4|||
|W40X215|M3X2.9|S12X35|HP12X84|WT20X107.5||ST6X17.5|||
|W40X199|MT6.25X6.2|S12X31.8|HP12X74|WT20X99.5||ST6X15.9|||
|W40X392|MT6.25X5.8|S10X35|HP12X63|WT20X196||ST5X17.5|||
|W40X331|MT6X5.9|S10X25.4|HP12X53|WT20X165.5||ST5X12.7|||
|W40X327|MT6X5.4|S8X23|HP10X57|WT20X163.5||ST4X11.5|||
|W40X294|MT6X5|S8X18.4|HP10X42|WT20X147||ST4X9.2|||
|W40X278|MT5X4.5|S6X17.25|HP8X36|WT20X139||ST3X8.6|||
|W40X264|MT5X4|S6X12.5||WT20X132||ST3X6.25|||
|W40X235|MT5X3.75|S5X10||WT20X117.5||ST2.5X5|||
|W40X211|MT4X3.25|S4X9.5||WT20X105.5||ST2X4.75|||
|W40X183|MT4X3.1|S4X7.7||WT20X91.5||ST2X3.85|||
|W40X167|MT3X2.2|S3X7.5||WT20X83.5||ST1.5X3.75|||
|W40X149|MT3X1.85|S3X5.7||WT20X74.5||ST1.5X2.85|||
|W36X925|MT2.5X9.45|||WT18X462.5|||||
|W36X853|MT2X3|||WT18X426.5|||||
|W36X802||||WT18X401|||||
|W36X723||||WT18X361.5|||||
|W36X652||||WT18X326|||||
|W36X529||||WT18X264.5|||||
|W36X487||||WT18X243.5|||||
|W36X441||||WT18X220.5|||||
|W36X395||||WT18X197.5|||||
|W36X361||||WT18X180.5|||||
|W36X330||||WT18X165|||||
|W36X302||||WT18X151|||||
|W36X282||||WT18X141|||||
|W36X262||||WT18X131|||||
|W36X247||||WT18X123.5|||||
|W36X231||||WT18X115.5|||||
|W36X256||||WT18X128|||||
|W36X232||||WT18X116|||||
|W36X210||||WT18X105|||||
|W36X194||||WT18X97|||||
|W36X182||||WT18X91|||||
|W36X170||||WT18X85|||||
|W36X160||||WT18X80|||||
|W36X150||||WT18X75|||||
|W36X135||||WT18X67.5|||||
|W33X387||||WT16.5X193.5|||||
|W33X354||||WT16.5X177|||||
|W33X318||||WT16.5X159|||||
|W33X291||||WT16.5X145.5|||||
|W33X263||||WT16.5X131.5|||||
|W33X241||||WT16.5X120.5|||||
|W33X221||||WT16.5X110.5|||||
|W33X201||||WT16.5X100.5|||||
|W33X169||||WT16.5X84.5|||||
|W33X152||||WT16.5X76|||||
|W33X141||||WT16.5X70.5|||||
|W33X130||||WT16.5X65|||||
|W33X118||||WT16.5X59|||||
|W30X391||||WT15X195.5|||||
|W30X357||||WT15X178.5|||||
|W30X326||||WT15X163|||||
|W30X292||||WT15X146|||||
|W30X261||||WT15X130.5|||||
|W30X235||||WT15X117.5|||||
|W30X211||||WT15X105.5|||||
|W30X191||||WT15X95.5|||||
|W30X173||||WT15X86.5|||||
|W30X148||||WT15X74|||||
|W30X132||||WT15X66|||||
|W30X124||||WT15X62|||||
|W30X116||||WT15X58|||||
|W30X108||||WT15X54|||||
|W30X99||||WT15X49.5|||||
|W30X90||||WT15X45|||||
|W27X539||||WT13.5X269.5|||||
|W27X368||||WT13.5X184|||||
|W27X336||||WT13.5X168|||||
|W27X307||||WT13.5X153.5|||||
|W27X281||||WT13.5X140.5|||||
|W27X258||||WT13.5X129|||||
|W27X235||||WT13.5X117.5|||||
|W27X217||||WT13.5X108.5|||||
|W27X194||||WT13.5X97|||||
|W27X178||||WT13.5X89|||||
|W27X161||||WT13.5X80.5|||||
|W27X146||||WT13.5X73|||||
|W27X129||||WT13.5X64.5|||||
|W27X114||||WT13.5X57|||||
|W27X102||||WT13.5X51|||||
|W27X94||||WT13.5X47|||||
|W27X84||||WT13.5X42|||||
|W24X370||||WT12X185|||||
|W24X335||||WT12X167.5|||||
|W24X306||||WT12X153|||||
|W24X279||||WT12X139.5|||||
|W24X250||||WT12X125|||||
|W24X229||||WT12X114.5|||||
|W24X207||||WT12X103.5|||||
|W24X192||||WT12X96|||||
|W24X176||||WT12X88|||||
|W24X162||||WT12X81|||||
|W24X146||||WT12X73|||||
|W24X131||||WT12X65.5|||||
|W24X117||||WT12X58.5|||||
|W24X104||||WT12X52|||||
|W24X103||||WT12X51.5|||||
|W24X94||||WT12X47|||||
|W24X84||||WT12X42|||||
|W24X76||||WT12X38|||||
|W24X68||||WT12X34|||||
|W24X62||||WT12X31|||||
|W24X55||||WT12X27.5|||||
|W21X275||||WT10.5X137.5|||||
|W21X248||||WT10.5X124|||||
|W21X223||||WT10.5X111.5|||||
|W21X201||||WT10.5X100.5|||||
|W21X182||||WT10.5X91|||||
|W21X166||||WT10.5X83|||||
|W21X147||||WT10.5X73.5|||||
|W21X132||||WT10.5X66|||||
|W21X122||||WT10.5X61|||||
|W21X111||||WT10.5X55.5|||||
|W21X101||||WT10.5X50.5|||||
|W21X93||||WT10.5X46.5|||||
|W21X83||||WT10.5X41.5|||||
|W21X73||||WT10.5X36.5|||||
|W21X68||||WT10.5X34|||||
|W21X62||||WT10.5X31|||||
|W21X55||||WT10.5X27.5|||||
|W21X48||||WT10.5X24|||||
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|W21X50||||WT10.5X25|||||
|W21X44||||WT10.5X22|||||
|W18X311||||WT9X155.5|||||
|W18X283||||WT9X141.5|||||
|W18X258||||WT9X129|||||
|W18X234||||WT9X117|||||
|W18X211||||WT9X105.5|||||
|W18X192||||WT9X96|||||
|W18X175||||WT9X87.5|||||
|W18X158||||WT9X79|||||
|W18X143||||WT9X71.5|||||
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|W18X119||||WT9X59.5|||||
|W18X106||||WT9X53|||||
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|W18X86||||WT9X43|||||
|W18X76||||WT9X38|||||
|W18X71||||WT9X35.5|||||
|W18X65||||WT9X32.5|||||
|W18X60||||WT9X30|||||
|W18X55||||WT9X27.5|||||
|W18X50||||WT9X25|||||
|W18X46||||WT9X23|||||
|W18X40||||WT9X20|||||
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|W16X77||||WT8X38.5|||||
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|W16X57||||WT8X28.5|||||
|W16X50||||WT8X25|||||
|W16X45||||WT8X22.5|||||
|W16X40||||WT8X20|||||
|W16X36||||WT8X18|||||
|W16X31||||WT8X15.5|||||
|W16X26||||WT8X13|||||
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|W14X500||||WT7X250|||||
|W14X455||||WT7X227.5|||||
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|W14X370||||WT7X185|||||
|W14X342||||WT7X171|||||
|W14X311||||WT7X155.5|||||
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|W14X233||||WT7X116.5|||||
|W14X211||||WT7X105.5|||||
|W14X193||||WT7X96.5|||||
|W14X176||||WT7X88|||||
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|W14X74||||WT7X37|||||
|W14X68||||WT7X34|||||
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|W14X48||||WT7X24|||||
|W14X43||||WT7X21.5|||||
|W14X38||||WT7X19|||||
|W14X34||||WT7X17|||||
|W14X30||||WT7X15|||||
|W14X26||||WT7X13|||||
|W14X22||||WT7X11|||||
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|W12X305||||WT6X152.5|||||
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|W12X230||||WT6X115|||||
|W12X210||||WT6X105|||||
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|W12X152||||WT6X76|||||
|W12X136||||WT6X68|||||
|W12X120||||WT6X60|||||
|W12X106||||WT6X53|||||
|W12X96||||WT6X48|||||
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|W12X65||||WT6X32.5|||||
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|W12X53||||WT6X26.5|||||
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|W12X40||||WT6X20|||||
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|W12X26||||WT6X13|||||
|W12X22||||WT6X11|||||
|W12X19||||WT6X9.5|||||
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|W10X112||||WT5X56|||||
|W10X100||||WT5X50|||||
|W10X88||||WT5X44|||||
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|W10X60||||WT5X30|||||
|W10X54||||WT5X27|||||
|W10X49||||WT5X24.5|||||
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|W10X30||||WT5X15|||||
|W10X26||||WT5X13|||||
|W10X22||||WT5X11|||||
|W10X19||||WT5X9.5|||||
|W10X17||||WT5X8.5|||||
|W10X15||||WT5X7.5|||||
|W10X12||||WT5X6|||||
|W8X67||||WT4X33.5|||||
|W8X58||||WT4X29|||||
|W8X48||||WT4X24|||||
|W8X40||||WT4X20|||||
|W8X35||||WT4X17.5|||||
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|W8X28||||WT4X14|||||
|W8X24||||WT4X12|||||
|W8X21||||WT4X10.5|||||
|W8X18||||WT4X9|||||
|W8X15||||WT4X7.5|||||
|W8X13||||WT4X6.5|||||
|W8X10||||WT4X5|||||
|W6X25||||WT3X12.5|||||
|W6X20||||WT3X10|||||
|W6X15||||WT3X7.5|||||
|W6X16||||WT3X8|||||
|W6X12||||WT3X6|||||
|W6X9||||WT3X4.5|||||
|W6X8.5||||WT3X4.25|||||
|W5X19||||WT2.5X9.5|||||
|W5X16||||WT2.5X8|||||
|W4X13||||WT2X6.5|||||