Eliminate one list according to another list in Python - python-3.x
I have two dimensional list like that
x_irp_group = [['x1_1_4', 'x1_2_4', 'x1_3_4', 'x1_4_4', 'x1_5_4', 'x1_6_4', 'x1_7_4', 'x1_8_4', 'x1_9_4', 'x1_10_4', 'x1_1_5', 'x1_2_5', 'x1_3_5', 'x1_4_5', 'x1_5_5', 'x1_6_5', 'x1_7_5', 'x1_8_5', 'x1_9_5', 'x1_10_5', 'x1_1_6', 'x1_2_6', 'x1_3_6', 'x1_4_6', 'x1_5_6', 'x1_6_6', 'x1_7_6', 'x1_8_6', 'x1_9_6', 'x1_10_6', 'x1_1_7', 'x1_2_7', 'x1_3_7', 'x1_4_7', 'x1_5_7', 'x1_6_7', 'x1_7_7', 'x1_8_7', 'x1_9_7', 'x1_10_7', 'x1_1_8', 'x1_2_8', 'x1_3_8', 'x1_4_8', 'x1_5_8', 'x1_6_8', 'x1_7_8', 'x1_8_8', 'x1_9_8', 'x1_10_8'], ['x1_1_8', 'x1_2_8', 'x1_3_8', 'x1_4_8', 'x1_5_8', 'x1_6_8', 'x1_7_8', 'x1_8_8', 'x1_9_8', 'x1_10_8', 'x1_1_9', 'x1_2_9', 'x1_3_9', 'x1_4_9', 'x1_5_9', 'x1_6_9', 'x1_7_9', 'x1_8_9', 'x1_9_9', 'x1_10_9', 'x1_1_10', 'x1_2_10', 'x1_3_10', 'x1_4_10', 'x1_5_10', 'x1_6_10', 'x1_7_10', 'x1_8_10', 'x1_9_10', 'x1_10_10', 'x1_1_11', 'x1_2_11', 'x1_3_11', 'x1_4_11', 'x1_5_11', 'x1_6_11', 'x1_7_11', 'x1_8_11', 'x1_9_11', 'x1_10_11', 'x1_1_12', 'x1_2_12', 'x1_3_12', 'x1_4_12', 'x1_5_12', 'x1_6_12', 'x1_7_12', 'x1_8_12', 'x1_9_12', 'x1_10_12']]
I wanna eliminate this two dimensional list if the elements in another one dimensional list like that
x_irp_eliminated_list = ['x1_1_4', 'x1_1_8', 'x1_1_12', 'x1_1_16', 'x1_1_19', 'x1_1_22', 'x1_1_26', 'x1_1_30', 'x1_1_34', 'x1_1_37', 'x1_1_43', 'x1_1_49', 'x1_1_55', 'x1_1_61', 'x1_1_68', 'x1_1_75', 'x1_1_81', 'x1_1_87', 'x1_1_92', 'x1_1_96', 'x1_1_101', 'x1_1_107', 'x1_1_112', 'x1_1_116', 'x1_1_121', 'x1_1_126', 'x1_1_131', 'x1_1_134', 'x1_1_137', 'x1_1_141', 'x1_1_145', 'x1_1_149', 'x1_1_152', 'x1_1_155', 'x1_1_160', 'x1_1_164', 'x1_1_169', 'x1_1_173', 'x1_1_181', 'x1_1_189', 'x1_1_197', 'x1_1_205', 'x1_2_8', 'x1_2_10', 'x1_2_13', 'x1_2_17', 'x1_2_21', 'x1_2_25', 'x1_2_28', 'x1_2_30', 'x1_2_34', 'x1_2_40', 'x1_2_45', 'x1_2_51', 'x1_2_58', 'x1_2_66', 'x1_2_71', 'x1_2_77', 'x1_2_82', 'x1_2_86', 'x1_2_91', 'x1_2_97', 'x1_2_102', 'x1_2_106', 'x1_2_111', 'x1_2_117', 'x1_2_122', 'x1_2_125', 'x1_2_129', 'x1_2_132', 'x1_2_135', 'x1_2_139', 'x1_2_143', 'x1_2_147', 'x1_2_151', 'x1_2_154', 'x1_2_157', 'x1_2_161', 'x1_2_166', 'x1_2_172', 'x1_2_177', 'x1_2_181', 'x1_2_189', 'x1_2_197', 'x1_2_205', 'x1_2_214', 'x1_3_1', 'x1_3_4', 'x1_3_8', 'x1_3_11', 'x1_3_15', 'x1_3_18', 'x1_3_22', 'x1_3_25', 'x1_3_28', 'x1_3_32', 'x1_3_35', 'x1_3_39', 'x1_3_42', 'x1_3_46', 'x1_3_49', 'x1_3_52', 'x1_3_56', 'x1_3_59', 'x1_3_63', 'x1_3_66', 'x1_3_70', 'x1_3_73', 'x1_3_77', 'x1_3_81', 'x1_3_85', 'x1_3_88', 'x1_3_91', 'x1_3_94', 'x1_3_97', 'x1_3_101', 'x1_3_105', 'x1_3_109', 'x1_3_112', 'x1_3_115', 'x1_3_118', 'x1_3_122', 'x1_3_126', 'x1_3_130', 'x1_3_134', 'x1_3_137', 'x1_3_140', 'x1_3_143', 'x1_3_147', 'x1_3_151', 'x1_3_156', 'x1_3_159', 'x1_3_163']
I write a code like that but it did not work well.
x_final = [i for i, j in zip(x_irp_group, x_irp_eliminated_list) if i == j]
I shorten the lists. Normally their sizes are much bigger than that
the list comprehension you have isn't working because you are zipping the elements together, which isn't what the operation represents (they are not parallel arrays) what you want is something along the lines of:
x_final = [i for i in x_irp_group[0] if (i not in x_irp_eliminated_list)]
Note that for a 2d list you may need to nest this like:
# writing normal loops you'd write:
# for row in x_irp_group:
# for i in row:
# if (...):
# so I typically try to indent the loops similarly since nested array comprehension
# gets complicated, honestly I'd likely prefer using generator functions for this anyway
x_final = [[i for i in row
if (i not in x_irp_eliminated_list)
]for row in x_irp_group
]
although know that i not in x_irp_eliminated_list will be very slow for a list, changing it to a set would improve performance:
x_irp_eliminated_set = set(x_irp_eliminated_list)
x_final = [i for i in x_irp_group[0] if (i not in x_irp_eliminated_set)]
Or if the lists are trivially sorted, then you could convert them both to sets, do a subtraction then sort it again:
x_final = [ sorted(set(x_irp_group[0]) - set(x_irp_eliminated_list)) ]
although if you have super giant lists this would probably be less desirable.
x_irp_eliminated_list_set = set(x_irp_eliminated_list)
x_last = [i for row in x_irp_group
for i in row
if (i in x_irp_eliminated_list_set)]
print(x_last[:30])
I used this for faster operation. Set approach made it faster. Thanks for that information. I learn one new thing. But it creates one dimensional list. I would like to create two dimensional list like original x_irp_group
Related
kdb/q: How to apply a string manipulation function to a vector of strings to output a vector of strings?
Thanks in advance for the help. I am new to kdb/q, coming from a Python and C++ background.
Just a simple syntax question: I have a string with fields and their corresponding values
pp_str: "field_1:abc field_2:xyz field_3:kdb"
I wrote an atomic (scalar) function to extract the value of a given field.
get_field_value: {[field; pp_str] pp_fields: " " vs pp_str; pid_field: pp_fields[where like[pp_fields; field,":*"]]; start_i: (pid_field[0] ss ":")[0] + 1; end_i: count pid_field[0]; indices: start_i + til (end_i - start_i); pid_field[0][indices]}
show get_field_value["field_1"; pp_str]
"abc"
show get_field_value["field_3"; pp_str]
"kdb"
Now how do I generalize this so that if I input a vector of fields, I get a vector of values? I want to input ("field_1"; "field_2"; "field_3") and output ("abc"; "xyz"; "kdb"). I tried multiple approaches (below) but I just don't understand kdb/q's syntax well enough to vectorize my function:
/ Attempt 1 - Fail
get_field_value[enlist ("field_1"; "field_2"); pp_str]
/ Attempt 2 - Fail
get_field_value[; pp_str] /. enlist ("field_1"; "field_3")
/ Attempt 3 - Fail
fields: ("field_1"; "field_2")
get_field_value[fields; pp_str]
To run your function for each you could project the pp_str variable and use each for the others
q)get_field_value[;pp_str]each("field_1";"field_3")
"abc"
"kdb"
Kdb actually has built-in functionality to handle this: https://code.kx.com/q/ref/file-text/#key-value-pairs
q){#[;x](!/)"S: "0:y}[`field_1;pp_str]
"abc"
q)
q){#[;x](!/)"S: "0:y}[`field_1`field_3;pp_str]
"abc"
"kdb"
I think this might be the syntax you're looking for.
q)get_field_value[; pp_str]each("field_1";"field_2")
"abc"
"xyz"
Numerical integration of a numpy array in incremental time steps
I have two arrays. The first one is time in terms of Age (yrs) and the second one is a parameter that needs to be integrated with respect to time. age = [5.00000e+08, 5.60322e+08, 6.27922e+08, 7.03678e+08, 7.88572e+08, 8.83709e+08, 9.90324e+08, 1.10980e+09, 1.24369e+09, 1.39374e+09, 1.56188e+09, 1.75032e+09, 1.96148e+09, 2.19813e+09, 2.46332e+09, 2.76050e+09, 3.09354e+09, 3.46676e+09, 3.88501e+09, 4.35371e+09, 4.87897e+09, 5.46759e+09, 6.12722e+09, 6.86644e+09, 7.69484e+09, 8.62318e+09, 9.66352e+09, 1.08294e+10, 1.21359e+10, 1.36000e+10] sfr = [1.86120543e-02, 1.46680445e-02, 1.07275184e-02, 8.56960274e-03, 6.44041855e-03, 4.93194263e-03, 3.69203448e-05, 2.69813985e-04, 6.17644783e-04, 1.00780427e-02, 1.20645391e-02, 3.05009362e-02, 3.91535011e-02, 5.35479858e-02, 7.36489068e-02, 9.63931263e-02, 1.11108326e-01, 1.47781221e-01, 1.63057763e-01, 2.27429626e-01, 2.20941333e-01, 2.74413180e-01, 2.72010867e-01, 4.32215233e-01, 5.79654549e-01, 7.39362218e-01, 9.41168727e-01, 1.18868347e+00, 1.42839043e+00, 1.91326333e+00] I want to perform integration of sfr array with respect to age array, but in steps. For example, the first integration should contain only the first elements of both arrays, the second integration should contain the first 2 elements of both arrays, the third should have first 3 elements of both arrays and so on and so forth. And save the integration result for each step in a single output array.
The exact form of your desired result is not so clear. So, here are 2 posibilities: age = [5.00000e+08, 5.60322e+08, 6.27922e+08, 7.03678e+08, 7.88572e+08, 8.83709e+08, 9.90324e+08, 1.10980e+09, 1.24369e+09, 1.39374e+09, 1.56188e+09, 1.75032e+09, 1.96148e+09, 2.19813e+09, 2.46332e+09, 2.76050e+09, 3.09354e+09, 3.46676e+09, 3.88501e+09, 4.35371e+09, 4.87897e+09, 5.46759e+09, 6.12722e+09, 6.86644e+09, 7.69484e+09, 8.62318e+09, 9.66352e+09, 1.08294e+10, 1.21359e+10, 1.36000e+10] sfr = [1.86120543e-02, 1.46680445e-02, 1.07275184e-02, 8.56960274e-03, 6.44041855e-03, 4.93194263e-03, 3.69203448e-05, 2.69813985e-04, 6.17644783e-04, 1.00780427e-02, 1.20645391e-02, 3.05009362e-02, 3.91535011e-02, 5.35479858e-02, 7.36489068e-02, 9.63931263e-02, 1.11108326e-01, 1.47781221e-01, 1.63057763e-01, 2.27429626e-01, 2.20941333e-01, 2.74413180e-01, 2.72010867e-01, 4.32215233e-01, 5.79654549e-01, 7.39362218e-01, 9.41168727e-01, 1.18868347e+00, 1.42839043e+00, 1.91326333e+00] integr_pairs = [[(a, s) for a, s in zip(age[:i], sfr[:i])] for i in range(1, len(age))] print(integr_pairs) # [[(500000000.0, 0.0186120543)], [(500000000.0, 0.0186120543), (560322000.0, 0.0146680445)], .... integr_list = [[item for t in [(a, s) for a, s in zip(age[:i], sfr[:i])] for item in t ]for i in range(1, len(age))] print(integr_list) # [[500000000.0, 0.0186120543], [500000000.0, 0.0186120543, 560322000.0, 0.0146680445],
Why this code doesn't print the single index?
We have the eng_stress and eng_strain arrays taken from excel file eng_stress = np.array(eng_stress) eng_strain = np.array(strain_percent / 100) eng_strain = eng_strain + 1 true_stress = np.multiply(eng_stress, eng_strain) true_strain = np.log(eng_strain) print(true_stress[10]) When I try to acces to a certain index, something like the following happens instead of single outcome. [466.12834181 466.2044319 466.27916323 466.35480041 466.43043758 466.50562183 466.58125901 466.65689618 466.73208043 466.80771761 466.8838077 466.95853903 467.03508204 467.10981338 467.18545055 467.26108772 467.33627198 467.41145623 467.48709341 467.56273058 467.63882067 467.71355201 467.78918918 467.86482635 467.94001061 468.0161007 468.09083203 468.16692212 468.2425593 468.31774355 468.39292781 468.4690179 468.54374923 468.61983932 468.69502358 468.77020783 468.84629792 468.92148218 468.99666643 469.07275652 469.14794078 469.22357795 469.29966804 469.37439938 469.45048947 469.52522081 469.6013109 469.67649515 469.75167941 469.82731658 469.90295375 469.97813801 470.05377518 470.12895943 470.20459661 470.2806867 470.35541803 470.43196104 470.50669238 470.58232955 470.65796672 470.7336039 470.80833523 470.88442532 470.95960958 471.03524675 471.11088392 471.18606818 471.26170535 471.33688961 471.41252678 471.48771103 471.56380112 471.63898538 471.71507547 471.78980681 471.8658969 471.94108115 472.01626541 472.09190258 472.16753975 472.24272401 472.3188141 472.39354543 472.46918261 472.5452727 472.62000403 472.69654704 472.77127838 472.84736847 472.92209981 472.99773698 473.07337415 473.14901132 473.22419558 473.30028567 473.37501701 473.45065418 473.52629135 473.60102269 473.6775657 473.75229703 473.82884004 473.9040243 473.97920855 474.05439281 474.1304829 474.20521423 474.28130432 474.35648858 474.43167283 474.50776292 474.58294718 474.65813143 474.73376861 474.80940578 474.88459003 474.96113304 475.03586438 475.11195447 475.18668581 475.2627759 475.33796015 475.41314441 475.48878158 475.56441875 475.63960301 475.7156931 475.79087735 475.86606161 475.9421517 476.01688303 476.09342604 476.16815738 476.24379455 476.31943172 476.3950689 476.46980023 476.54589032 476.62107458 476.69716467 476.77234892 476.84753318 476.92317035 476.99835461 477.0744447 477.14962895 477.22526612 477.30045038 477.37654047 477.45127181 477.5273619 477.60209323 477.67773041 477.75336758 477.82855183 477.90464192 477.9802791 478.05501043 478.13064761 478.20628478 478.28146903 478.35801204 478.43274338 478.50883347 478.58356481 478.65920198 478.73483915 478.81002341 478.88566058 478.96175067 479.03648201 479.1125721 479.18775635 479.26294061 479.3390307 479.41376203 479.48985212 479.5650363......... 532]
Maybe eng_stress is a 2D array? Try: print(eng_stress.shape) to find out the shape of the arrays you are working with :) If your array has the shape (X,1) then it might be in the wrong direction and you could do a quick fix by changing your code to: eng_stress = np.array(eng_stress).T[0] eng_strain = np.array(strain_percent / 100) eng_strain = eng_strain + 1 true_stress = np.multiply(eng_stress, eng_strain) true_strain = np.log(eng_strain) print(true_stress[10])
Your numpy arrays may be 2-dimensional. That's why it's printing an array rather than a value. To access a single value of column x, try print(true_stress[10][x]). The other thing you can do is multiply two 1D numpy arrays. In that case, you'll get a single value.
Pull random results from a database?
I have been coding in Python for a 2 months or so, but I mostly ask for help from a more experienced friend when I run in to these kinds of issues. I should also, before I begin, specify that I use Python solely for a personal project; any questions I ask will relate to each other through that.
With those two things out of the way, I have a database of weaponry items that I created using the following script, made in Python 3.X:
#Start by making a list of every material, weapontype, and upgrade.
Materials=("Unobtanium","IvorySilk","BoneLeather","CottonWood","Tin","Copper","Bronze","Gold","Cobalt","Tungsten")
WeaponTypes=("Knife","Sword","Greatsword","Polearm","Battlestaff","Claw","Cane","Wand","Talis","Slicer","Rod","Bow","Crossbow","Handbow","Pistol","Mechgun","Rifle","Shotgun")
Upgrades=("0","1","2","3","4","5","6","7","8","9","10")
ForgeWInputs=[]
#Go through every material...
for m in Materials:
#And in each material, go through every weapontype...
for w in WeaponTypes:
#And in every weapontype, go through each upgrade...
for u in Upgrades:
ForgeWInputs.append((m,w,u))
#We now have a list "ForgeWInputs", which contains the 3-element list needed to
#Forge any weapon. For example...
MAT={}
MAT["UnobtaniumPD"]=0
MAT["UnobtaniumMD"]=0
MAT["UnobtaniumAC"]=0
MAT["UnobtaniumPR"]=0
MAT["UnobtaniumMR"]=0
MAT["UnobtaniumWT"]=0
MAT["UnobtaniumBuy"]=0
MAT["UnobtaniumSell"]=0
MAT["IvorySilkPD"]=0
MAT["IvorySilkMD"]=12
MAT["IvorySilkAC"]=3
MAT["IvorySilkPR"]=0
MAT["IvorySilkMR"]=3
MAT["IvorySilkWT"]=6
MAT["IvorySilkBuy"]=10
MAT["IvorySilkSell"]=5
MAT["CottonWoodPD"]=8
MAT["CottonWoodMD"]=8
MAT["CottonWoodAC"]=5
MAT["CottonWoodPR"]=0
MAT["CottonWoodMR"]=3
MAT["CottonWoodWT"]=6
MAT["CottonWoodBuy"]=14
MAT["CottonWoodSell"]=7
MAT["BoneLeatherPD"]=12
MAT["BoneLeatherMD"]=0
MAT["BoneLeatherAC"]=3
MAT["BoneLeatherPR"]=3
MAT["BoneLeatherMR"]=0
MAT["BoneLeatherWT"]=6
MAT["BoneLeatherBuy"]=10
MAT["BoneLeatherSell"]=5
MAT["TinPD"]=18
MAT["TinMD"]=6
MAT["TinAC"]=3
MAT["TinPR"]=5
MAT["TinMR"]=2
MAT["TinWT"]=12
MAT["TinBuy"]=20
MAT["TinSell"]=10
MAT["CopperPD"]=6
MAT["CopperMD"]=18
MAT["CopperAC"]=3
MAT["CopperPR"]=2
MAT["CopperMR"]=5
MAT["CopperWT"]=12
MAT["CopperBuy"]=20
MAT["CopperSell"]=10
MAT["BronzePD"]=10
MAT["BronzeMD"]=10
MAT["BronzeAC"]=5
MAT["BronzePR"]=3
MAT["BronzeMR"]=3
MAT["BronzeWT"]=15
MAT["BronzeBuy"]=30
MAT["BronzeSell"]=15
MAT["GoldPD"]=10
MAT["GoldMD"]=30
MAT["GoldAC"]=0
MAT["GoldPR"]=5
MAT["GoldMR"]=10
MAT["GoldWT"]=25
MAT["GoldBuy"]=50
MAT["GoldSell"]=25
MAT["CobaltPD"]=30
MAT["CobaltMD"]=10
MAT["CobaltAC"]=0
MAT["CobaltPR"]=10
MAT["CobaltMR"]=0
MAT["CobaltWT"]=25
MAT["CobaltBuy"]=50
MAT["CobaltSell"]=25
MAT["TungstenPD"]=20
MAT["TungstenMD"]=20
MAT["TungstenAC"]=0
MAT["TungstenPR"]=7
MAT["TungstenMR"]=7
MAT["TungstenWT"]=20
MAT["TungstenBuy"]=70
MAT["TungstenSell"]=35
WEP={}
WEP["KnifePD"]=0.5
WEP["KnifeMD"]=0.5
WEP["KnifeAC"]=1.25
WEP["SwordPD"]=1.0
WEP["SwordMD"]=1.0
WEP["SwordAC"]=1.0
WEP["GreatswordPD"]=1.67
WEP["GreatswordMD"]=0.67
WEP["GreatswordAC"]=0.5
WEP["PolearmPD"]=1.15
WEP["PolearmMD"]=1.15
WEP["PolearmAC"]=1.15
WEP["CanePD"]=1.15
WEP["CaneMD"]=1.15
WEP["CaneAC"]=0.7
WEP["ClawPD"]=1.1
WEP["ClawMD"]=1.1
WEP["ClawAC"]=0.8
WEP["BattlestaffPD"]=1.15
WEP["BattlestaffMD"]=1
WEP["BattlestaffAC"]=1.25
WEP["TalisPD"]=1.15
WEP["TalisMD"]=0.7
WEP["TalisAC"]=1.15
WEP["WandPD"]=0.0
WEP["WandMD"]=1
WEP["WandAC"]=1.33
WEP["RodPD"]=0.0
WEP["RodMD"]=1.67
WEP["RodAC"]=0.67
WEP["SlicerPD"]=0.67
WEP["SlicerMD"]=0.67
WEP["SlicerAC"]=0.67
WEP["BowPD"]=1.15
WEP["BowMD"]=1.15
WEP["BowAC"]=0.85
WEP["CrossbowPD"]=1.4
WEP["CrossbowMD"]=1.4
WEP["CrossbowAC"]=1
WEP["PistolPD"]=0.65
WEP["PistolMD"]=0.65
WEP["PistolAC"]=1.15
WEP["MechgunPD"]=0.2
WEP["MechgunMD"]=0.2
WEP["MechgunAC"]=1.5
WEP["ShotgunPD"]=1.3
WEP["ShotgunMD"]=1.3
WEP["ShotgunAC"]=0.4
WEP["RiflePD"]=0.75
WEP["RifleMD"]=0.75
WEP["RifleAC"]=1.75
WEP["HandbowPD"]=0.8
WEP["HandbowMD"]=0.8
WEP["HandbowAC"]=1.2
UP={}
UP["0PD"]=1.0
UP["1PD"]=1.1
UP["2PD"]=1.2
UP["3PD"]=1.3
UP["4PD"]=1.4
UP["5PD"]=1.5
UP["6PD"]=1.6
UP["7PD"]=1.7
UP["8PD"]=1.8
UP["9PD"]=1.9
UP["10PD"]=2.0
UP["0MD"]=1.0
UP["1MD"]=1.1
UP["2MD"]=1.2
UP["3MD"]=1.3
UP["4MD"]=1.4
UP["5MD"]=1.5
UP["6MD"]=1.6
UP["7MD"]=1.7
UP["8MD"]=1.8
UP["9MD"]=1.9
UP["10MD"]=2.0
UP["0AC"]=1.0
UP["1AC"]=1.1
UP["2AC"]=1.2
UP["3AC"]=1.3
UP["4AC"]=1.4
UP["5AC"]=1.5
UP["6AC"]=1.6
UP["7AC"]=1.7
UP["8AC"]=1.8
UP["9AC"]=1.9
UP["10AC"]=2.0
UP["0PR"]=1.0
UP["1PR"]=1.1
UP["2PR"]=1.2
UP["3PR"]=1.3
UP["4PR"]=1.4
UP["5PR"]=1.5
UP["6PR"]=1.6
UP["7PR"]=1.7
UP["8PR"]=1.8
UP["9PR"]=1.9
UP["10PR"]=2.0
UP["0MR"]=1.0
UP["1MR"]=1.1
UP["2MR"]=1.2
UP["3MR"]=1.3
UP["4MR"]=1.4
UP["5MR"]=1.5
UP["6MR"]=1.6
UP["7MR"]=1.7
UP["8MR"]=1.8
UP["9MR"]=1.9
UP["10MR"]=2.0
UP["0WT"]=1.0
UP["1WT"]=0.95
UP["2WT"]=0.9
UP["3WT"]=0.85
UP["4WT"]=0.8
UP["5WT"]=0.75
UP["6WT"]=0.7
UP["7WT"]=0.65
UP["8WT"]=0.6
UP["9WT"]=0.55
UP["10WT"]=0.5
def ForgeW(Material,WeaponType,UpgradeLevel):
"""The ForgeW function Forges a Weapon from its base components into a lethal tool."""
#Get the appropriate material stats...
OrePD=MAT[Material+"PD"]
OreMD=MAT[Material+"MD"]
OreAC=MAT[Material+"AC"]
#And weapon type stats...
SmithPD=WEP[WeaponType+"PD"]
SmithMD=WEP[WeaponType+"MD"]
SmithAC=WEP[WeaponType+"AC"]
#And apply the upgrade...
UpgradePD=UP[UpgradeLevel+"PD"]
UpgradeMD=UP[UpgradeLevel+"MD"]
UpgradeAC=UP[UpgradeLevel+"AC"]
#Then, add them all together.
ProductPD=(OrePD*SmithPD)*UpgradePD
ProductMD=(OreMD*SmithMD)*UpgradeMD
ProductAC=(OreAC*SmithAC)*UpgradeAC
return(ProductPD,ProductMD,ProductAC)
#Recall that ForgeW simply needs its three inputs, which we have a list of. So, let's make our
#database of weapon information.
OmniWeapData={}
#Go through every set of inputs we have...
for Inputs in ForgeWInputs:
#And create a key in the dictionary by combining their three names. Then, set that
#key equal to whatever ForgeW returns when those three inputs are put in.
OmniWeapData[Inputs[0]+Inputs[1]+Inputs[2]] = ForgeW(Inputs[0],Inputs[1],Inputs[2])
I would like to refer to the database created by this code and pull out weapons at random, and frankly I have no idea how. As an example of what I would like to do...
Well, hum. The code in question should spit out a certain number of results based on the complete products of the ForgeW function - if I specify, either within the code or through an input, that I would like 3 outputs, it might output a GoldKnife0, a TinPolearm5, and a CobaltGreatsword10. If I were to run the code again, it should dispense new equipment - not the same three every time.
I apologize if this is too much or too little data - it's my first time asking a question here.
"Take this... it may help you on your quest." There is a library called random with a method called choice(). e.g. import random random.choice([1,2,3]) >>> 2 It sounds like you need one item from Materials, one item from WeaponTypes, and one from Upgrades. Also, rarely is there ever a need for a triple nested FOR statement. This should get you started.
Multi-Threading and Parallel Processing in Matlab
I'm coding a project in Matlab, however I want the great efficiency and speed of my execution, for that sake, I want to use parallel processing threads in Matlab as I have multiple objects working or changing their states in a for loop. Is Multi-Threading is appropriate for this purpose? If so, where can I take start or can create a simple thread? My Code: % P=501x3 array for i=1:length(P) % I used position for example's sake, meaning object changing its state Object1.position=P(i,:); Object2.position=P(i,:); Object3.position=P(i,:); Object4.position=P(i,:); % Mulitple objects changing their state on each iteration, after some calculation/formulation. end What I need is the basic structure of Multi-Threads according to my scenario if Threading is appropriate in my case. More suggestions for Parallel-Execution or fast processing are welcomed. 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13.6080 -9.9046 -0.4344 13.6969 -9.9756 -0.4150 13.7859 -10.0466 -0.3957 13.8751 -10.1177 -0.3765 13.9644 -10.1888 -0.3575 14.0539 -10.2600 -0.3386 14.1436 -10.3313 -0.3198 14.2334 -10.4026 -0.3011 14.3235 -10.4740 -0.2826 14.4137 -10.5454 -0.2641 14.5040 -10.6169 -0.2458 14.5946 -10.6884 -0.2277 14.6853 -10.7600 -0.2096 14.7761 -10.8317 -0.1917 14.8672 -10.9035 -0.1739 14.9584 -10.9753 -0.1562 15.0499 -11.0471 -0.1387 15.1414 -11.1190 -0.1213 15.2332 -11.1910 -0.1040 15.3252 -11.2631 -0.0868 15.4173 -11.3352 -0.0697 15.5096 -11.4073 -0.0528 15.6021 -11.4796 -0.0360 15.6948 -11.5519 -0.0194 15.7876 -11.6242 -0.0029 15.8806 -11.6966 0.0135 15.9739 -11.7691 0.0298 16.0673 -11.8417 0.0459 16.1609 -11.9143 0.0619 16.2547 -11.9869 0.0778 16.3486 -12.0597 0.0936 16.4428 -12.1325 0.1092 16.5371 -12.2053 0.1247 16.6317 -12.2783 0.1400 16.7264 -12.3513 0.1552 16.8213 -12.4243 0.1703 16.9164 -12.4974 0.1853 17.0117 -12.5706 0.2001 17.1072 -12.6439 0.2148 17.2029 -12.7172 0.2293 17.2988 -12.7906 0.2437 17.3949 -12.8640 0.2580 17.4911 -12.9376 0.2721 17.5876 -13.0111 0.2861 17.6843 -13.0848 0.3000
Ahsan,
I think parfor might be what you're looking for. It requires the Parallel Computing Toolbox (PCT) to use. It works like this:
parfor i = 1:length(P)
Object1.position = P(i,:);
end
Also, I would recommend using indexed structure fields, as I've done in the example below, as it increases the flexibility of any code that you write. Let me know if this doesn't work for you, and we'll try something else. I know another technique, but it's much messier. Good luck!
parfor i = 1:length(P)
Object(i).position = P(i,:);
end
Edit: Ok, this may not work because parfor is pretty particular. But it the general concept should apply to the problem you're trying to solve. I can't be more specific without knowing more about your specific problem. The key point is, inside a parfor, you must iterate something (Object, below) by the parfors iterator (i, below) and assign that thing a value. I'm not sure if you can use a for-loop inside a parfor, so the first example below may break. The point is, this is how you do parallel processing in MATLAB. Try this:
parfor i = 1:4
Object(i).position = P(i,:);
end
Edit 2:
parfor i = length(P)
Object1 = struct();
Object1.position = P(i, :);
end
Edit 3: Ok, one last thing. You can't use "sliced" structs (structs with fields) as input or output from a parfor so you have to do this:
parfor i = 1:length(P)
positionArray1(i) = P(i, :);
end
Object1 = struct('position', positionArray1);