Mathematica - Dynamic - ListPlot - baseline - wolfram-mathematica
I am performing baseline fitting to a raw dataset on a two-state equilibrium process. The process involves fitting the sigmoidal curve to an upper and lower linear baseline, and subtracting so that you get a curve going from y=(0) (state 1) to y=(1) (state 2) over your x-value range instead y=(experimental observable values).
I'd like to expedite the baseline selection process through an interactive dynamic approach rather than manually typing in lhs/rhs x-values for each curve. However, I'm noticing that the dynamic values behind the dynamic plots need to be on the screen for the plot to update. Meaning, if I'm dynamic listplotting 4 points, and only three of these dynamic values (the output) are on screen then only three show up. I have to scroll up or down through the notebook to "update" various values and then the plots correct themselves.
I have many calculations downstream after baseline selection, and I'd like to have all these subsequent calculations print up in a neat little grid near the sliders, without have to scroll.
I'm new to Dynamic, and also having trouble combining multiple plots (similar to Show) when held under the Dynamic functions. I'd like to dynamically in one graphic plot the ListPlot of my rawData, the four baseline points, and then the fitted linear function through the selected rawData in the baseline area. Next to this, I'll plot the two-state equilibrium plot (y=0 to 1) and then a single point representing the transition point of 50/50 state1/state2 (y=0.5). All of these downstream processes are highly dependent on baseline selection, so I'd like to have the slider there and final plots to immediately see the results of various choices for baselines.
In summary, two questions:
1) screen refresh needed of output from dynamic values for updating dynamic plots not in the same input section
2) multiple plot types within a single graphic, dynamically
Best regards,
Kurtis
ramp1FCelsiusXRFUSmooth[
1] = {{5.2, 171.5576923076923}, {5.4, 171.4583916083916}, {5.6,
171.36804195804197}, {5.8, 171.31552447552448}, {6,
171.31125874125877}, {6.2, 171.35321678321677}, {6.4,
171.41783216783216}, {6.6, 171.5072027972028}, {6.8,
171.61223776223778}, {7, 171.74020979020978}, {7.2,
171.8802097902098}, {7.4, 172.01412587412588}, {7.6,
172.1367832167832}, {7.8, 172.25818181818184}, {8,
172.37916083916082}, {8.2, 172.52223776223775}, {8.4,
172.65797202797202}, {8.6, 172.81475524475525}, {8.8,
172.97706293706293}, {9, 173.16314685314686}, {9.2,
173.35531468531468}, {9.4, 173.56958041958043}, {9.6,
173.7951048951049}, {9.8, 174.03153846153847}, {10,
174.2748951048951}, {10.2, 174.51762237762236}, {10.4,
174.7634265734266}, {10.6, 174.9851048951049}, {10.8,
175.1865034965035}, {11, 175.3864335664336}, {11.2,
175.59503496503498}, {11.4, 175.81916083916082}, {11.6,
176.02797202797203}, {11.8, 176.2442657342657}, {12,
176.45391608391608}, {12.2, 176.6886013986014}, {12.4,
176.9281118881119}, {12.6, 177.19}, {12.8, 177.47}, {13,
177.7390909090909}, {13.2, 178.01503496503494}, {13.4,
178.2923076923077}, {13.6, 178.60461538461539}, {13.8,
178.92685314685315}, {14, 179.24713286713288}, {14.2,
179.5781818181818}, {14.4, 179.93076923076922}, {14.6,
180.32083916083917}, {14.8, 180.71741258741258}, {15,
181.124965034965}, {15.2, 181.55125874125875}, {15.4,
181.97825174825175}, {15.6, 182.41020979020982}, {15.8,
182.8441258741259}, {16, 183.3011188811189}, {16.2,
183.77636363636367}, {16.4, 184.26951048951048}, {16.6,
184.80447552447555}, {16.8, 185.37951048951047}, {17,
185.97846153846154}, {17.2, 186.58356643356643}, {17.4,
187.19545454545454}, {17.6, 187.81587412587407}, {17.8,
188.44538461538463}, {18, 189.08426573426573}, {18.2,
189.73111888111887}, {18.4, 190.38111888111888}, {18.6,
191.04258741258744}, {18.8, 191.7199300699301}, {19,
192.43076923076922}, {19.2, 193.16111888111888}, {19.4,
193.91048951048953}, {19.6, 194.68713286713282}, {19.8,
195.4913286713287}, {20, 196.32006993006993}, {20.2,
197.17510489510488}, {20.4, 198.05881118881118}, {20.6,
198.95755244755247}, {20.8, 199.8584615384615}, {21,
200.76384615384615}, {21.2, 201.68461538461537}, {21.4,
202.62685314685316}, {21.6, 203.66496503496504}, {21.8,
204.81300699300698}, {22, 205.96062937062936}, {22.2,
206.8897902097902}, {22.4, 207.50202797202797}, {22.6,
207.81699300699304}, {22.8, 207.95888111888112}, {23,
208.02839160839162}, {23.2, 208.14692307692306}, {23.4,
208.4265734265734}, {23.6, 208.94608391608392}, {23.8,
209.81937062937064}, {24, 211.1255244755245}, {24.2,
212.82013986013985}, {24.4, 214.7145454545455}, {24.6,
216.61958041958042}, {24.8, 218.50860139860137}, {25,
220.42069930069928}, {25.2, 222.4111888111888}, {25.4,
224.48314685314682}, {25.6, 226.616013986014}, {25.8,
228.8025874125874}, {26, 231.0102097902098}, {26.2,
233.26111888111888}, {26.4, 235.54636363636362}, {26.6,
237.8906293706294}, {26.8, 240.30881118881118}, {27,
242.80363636363634}, {27.2, 245.37720279720278}, {27.4,
248.0467132867133}, {27.6, 250.82118881118885}, {27.8,
253.69622377622377}, {28, 256.65937062937064}, {28.2,
259.7168531468531}, {28.4, 262.8809090909091}, {28.6,
266.136083916084}, {28.8, 269.48853146853145}, {29,
272.9494405594406}, {29.2, 276.5634265734266}, {29.4,
280.31496503496504}, {29.6, 284.1983916083916}, {29.8,
288.2063636363637}, {30, 292.3523076923077}, {30.2,
296.6392307692308}, {30.4, 301.0708391608391}, {30.6,
305.62391608391613}, {30.8, 310.3113286713287}, {31,
315.11034965034963}, {31.2, 320.04965034965034}, {31.4,
325.1569230769231}, {31.6, 330.4420979020979}, {31.8,
335.90902097902097}, {32, 341.55034965034963}, {32.2,
347.37482517482516}, {32.4, 353.38538461538457}, {32.6,
359.5694405594406}, {32.8, 365.93888111888117}, {33,
372.4761538461538}, {33.2, 379.2182517482518}, {33.4,
386.1609790209791}, {33.6, 393.32629370629365}, {33.8,
400.7041958041958}, {34, 408.26265734265735}, {34.2,
416.02657342657346}, {34.4, 423.96489510489516}, {34.6,
432.1181818181819}, {34.8, 440.4820979020979}, {35,
448.6806293706294}, {35.2, 456.86342657342664}, {35.4,
465.53755244755246}, {35.6, 475.66034965034964}, {35.8,
487.5865734265734}, {36, 501.1653146853147}, {36.2,
516.0813286713288}, {36.4, 531.9086013986014}, {36.6,
548.2587412587412}, {36.8, 564.6713986013987}, {37,
580.6118881118881}, {37.2, 595.7270629370629}, {37.4,
609.4006293706293}, {37.6, 622.2286013986014}, {37.8,
634.5355944055943}, {38, 647.2777622377623}, {38.2,
660.156153846154}, {38.4, 673.3221678321679}, {38.6,
686.4862237762237}, {38.8, 699.9664335664336}, {39,
713.5155244755244}, {39.2, 727.4389510489511}, {39.4,
741.0336363636363}, {39.6, 755.0702097902098}, {39.8,
769.5217482517482}, {40, 785.5246153846156}, {40.2,
802.3835664335664}, {40.4, 820.4558741258742}, {40.6,
838.8953146853147}, {40.8, 858.1897202797202}, {41,
877.5658741258741}, {41.2, 897.573986013986}, {41.4,
917.3868531468532}, {41.6, 937.4052447552448}, {41.8,
956.7482517482517}, {42, 976.6904895104893}, {42.2,
997.0346153846153}, {42.4, 1018.8477622377623}, {42.6,
1041.1142657342657}, {42.8, 1064.3213286713287}, {43,
1088.1560139860142}, {43.2, 1112.473986013986}, {43.4,
1137.4900699300697}, {43.6, 1164.0341958041959}, {43.8,
1192.6026573426573}, {44, 1223.4609090909091}, {44.2,
1255.9941258741258}, {44.4, 1290.8709790209791}, {44.6,
1327.0130769230768}, {44.8, 1364.6239860139858}, {45,
1402.7880419580417}, {45.2, 1442.381118881119}, {45.4,
1482.7290909090907}, {45.6, 1523.66013986014}, {45.8,
1565.570979020979}, {46, 1609.5718881118883}, {46.2,
1656.1732867132866}, {46.4, 1705.5791608391607}, {46.6,
1757.082797202797}, {46.8, 1811.405664335664}, {47,
1867.7601398601398}, {47.2, 1927.0214685314686}, {47.4,
1988.903566433566}, {47.6, 2053.9727272727273}, {47.8,
2121.3558741258735}, {48, 2191.253076923077}, {48.2,
2263.4567132867137}, {48.4, 2338.992097902097}, {48.6,
2417.6206293706296}, {48.8, 2499.507062937063}, {49,
2584.0679020979014}, {49.2, 2672.40048951049}, {49.4,
2764.2509090909093}, {49.6, 2860.08972027972}, {49.8,
2958.8880419580414}, {50, 3061.5296503496506}, {50.2,
3167.954475524476}, {50.4, 3279.3267132867136}, {50.6,
3394.996363636363}, {50.8, 3514.5386013986017}, {51,
3637.8941958041955}, {51.2, 3767.8172727272727}, {51.4,
3907.369160839161}, {51.6, 4057.940839160839}, {51.8,
4218.387692307691}, {52, 4387.486363636363}, {52.2,
4559.219090909091}, {52.4, 4737.994405594407}, {52.6,
4926.850629370629}, {52.8, 5133.069790209789}, {53,
5351.979300699301}, {53.2, 5580.233216783217}, {53.4,
5815.771258741259}, {53.6, 6059.474335664335}, {53.8,
6310.2300699300695}, {54, 6566.168951048951}, {54.2,
6824.079510489511}, {54.4, 7080.809090909091}, {54.6,
7333.146293706293}, {54.8, 7587.8459440559445}, {55,
7850.626853146852}, {55.2, 8125.57027972028}, {55.4,
8409.073496503495}, {55.6, 8698.83132867133}, {55.8,
8996.236433566435}, {56, 9300.716293706295}, {56.2,
9614.424195804197}, {56.4, 9936.465874125875}, {56.6,
10267.16895104895}, {56.8, 10604.112797202795}, {57,
10948.749580419582}, {57.2, 11300.41020979021}, {57.4,
11659.683006993006}, {57.6, 12023.626783216785}, {57.8,
12392.80202797203}, {58, 12766.768741258744}, {58.2,
13147.152517482516}, {58.4, 13533.405594405594}, {58.6,
13929.522447552448}, {58.8, 14331.496503496504}, {59,
14735.11027972028}, {59.2, 15134.907552447552}, {59.4,
15531.639090909091}, {59.6, 15926.898251748251}, {59.8,
16319.009370629366}, {60, 16708.945804195802}, {60.2,
17100.06636363636}, {60.4, 17496.746923076924}, {60.6,
17899.96601398601}, {60.8, 18310.962377622378}, {61,
18733.114335664337}, {61.2, 19158.742027972025}, {61.4,
19578.491538461538}, {61.6, 19983.563636363637}, {61.8,
20383.41286713287}, {62, 20771.78615384616}, {62.2,
21143.815874125874}, {62.4, 21493.19979020979}, {62.6,
21831.533146853144}, {62.8, 22165.208671328666}, {63,
22497.004265734264}, {63.2, 22829.18895104895}, {63.4,
23165.61839160839}, {63.6, 23505.106223776227}, {63.8,
23845.65895104895}, {64, 24185.918321678324}, {64.2,
24530.909580419582}, {64.4, 24870.472797202798}, {64.6,
25198.522797202797}, {64.8, 25507.47804195804}, {65,
25802.223846153847}, {65.2, 26082.483426573428}, {65.4,
26348.033426573424}, {65.6, 26600.166853146857}, {65.8,
26840.285384615385}, {66, 27072.183286713287}, {66.2,
27294.89937062937}, {66.4, 27510.708951048953}, {66.6,
27720.160139860138}, {66.8, 27922.566853146855}, {67,
28118.26083916084}, {67.2, 28307.706083916084}, {67.4,
28494.77258741259}, {67.6, 28679.58657342657}, {67.8,
28860.11972027972}, {68, 29039.42153846154}, {68.2,
29210.7306993007}, {68.4, 29366.41545454545}, {68.6,
29502.546223776226}, {68.8, 29629.67433566434}, {69,
29744.836363636365}, {69.2, 29836.08020979021}, {69.4,
29898.33790209791}, {69.6, 29933.56769230769}, {69.8,
29959.04762237762}, {70, 29975.020909090912}, {70.2,
29991.388531468532}, {70.4, 30006.784055944052}, {70.6,
30018.964685314684}, {70.8, 30026.687132867133}, {71,
30047.393426573428}, {71.2, 30084.82174825175}, {71.4,
30135.9965034965}, {71.6, 30182.328111888113}, {71.8,
30225.142167832168}, {72, 30268.663566433566}, {72.2,
30319.640629370628}, {72.4, 30372.744545454545}, {72.6,
30427.39160839161}, {72.8, 30477.89188811188}, {73,
30521.84727272727}, {73.2, 30553.777762237765}, {73.4,
30573.294825174824}, {73.6, 30571.749790209793}, {73.8,
30562.458741258743}, {74, 30552.884825174824}, {74.2,
30553.355174825174}, {74.4, 30564.295454545452}, {74.6,
30576.382587412594}, {74.8, 30594.90377622378}, {75,
30610.827692307692}, {75.2, 30633.06699300699}, {75.4,
30653.350000000002}, {75.6, 30666.33594405594}, {75.8,
30668.923426573427}, {76, 30668.75461538462}, {76.2,
30670.575314685306}, {76.4, 30670.93328671329}, {76.6,
30667.266083916085}, {76.8, 30663.819300699302}, {77,
30647.977062937065}, {77.2, 30618.72202797203}, {77.4,
30565.47013986014}, {77.6, 30508.620349650355}, {77.8,
30455.27230769231}, {78, 30410.724055944054}, {78.2,
30383.247272727276}, {78.4, 30363.072377622375}, {78.6,
30355.305034965033}, {78.8, 30342.20923076923}, {79,
30340.65146853147}, {79.2, 30337.188811188807}, {79.4,
30331.158181818184}, {79.6, 30315.162097902103}, {79.8,
30295.13181818182}, {80, 30271.48195804196}, {80.2,
30250.13118881119}, {80.4, 30224.207062937065}, {80.6,
30201.98300699301}, {80.8, 30170.62013986014}, {81,
30157.62923076923}, {81.2, 30143.96188811189}, {81.4,
30141.00909090909}, {81.6, 30117.328741258738}, {81.8,
30092.859790209794}, {82, 30056.212097902095}, {82.2,
30011.19230769231}, {82.4, 29951.637552447555}, {82.6,
29881.86965034965}, {82.8, 29809.408811188812}, {83,
29743.92013986014}, {83.2, 29687.225244755246}, {83.4,
29650.274545454547}, {83.6, 29609.51027972028}, {83.8,
29570.36111888112}, {84, 29528.284685314688}, {84.2,
29495.74104895105}, {84.4, 29464.83104895105}, {84.6,
29432.034545454546}, {84.8, 29397.90867132867}, {85,
29359.92979020979}, {85.2, 29328.5486013986}, {85.4,
29309.78937062937}, {85.6, 29295.625034965036}, {85.8,
29279.513916083917}, {86, 29255.218671328672}, {86.2,
29234.38566433567}, {86.4, 29227.73384615385}, {86.6,
29216.327202797198}, {86.8, 29201.22685314685}, {87,
29162.052937062937}, {87.2, 29113.863776223774}, {87.4,
29051.34391608391}, {87.6, 28988.94237762238}, {87.8,
28926.36160839161}, {88, 28856.33132867133}, {88.2,
28782.890699300704}, {88.4, 28712.760769230772}, {88.6,
28660.5920979021}, {88.8, 28620.868461538463}, {89,
28583.4386013986}, {89.2, 28546.60818181818}, {89.4,
28502.005384615386}, {89.6, 28462.87916083916}, {89.8,
28422.843076923076}, {90, 28389.142517482516}, {90.2,
28339.938461538462}, {90.4, 28275.94958041958}, {90.6,
28203.151538461538}, {90.8, 28132.62300699301}, {91,
28069.04839160839}, {91.2, 27992.026083916087}, {91.4,
27914.222797202798}, {91.6, 27834.239160839163}, {91.8,
27766.07118881119}, {92, 27716.52062937063}, {92.2,
27679.7613986014}, {92.4, 27652.8013986014}, {92.6,
27618.464055944052}, {92.8, 27588.78923076923}, {93,
27574.388531468536}, {93.2, 27566.27888111888}, {93.4,
27547.25811188811}, {93.6, 27502.117692307693}, {93.8,
27444.676573426572}};
ramp1FSmoothFunc[1] = Interpolation[ramp1FCelsiusXRFUSmooth[1]]
ClearAll[helixMidPoint, helixLineLength, helixLowPoint, \
helixLowPointRFU, helixHighPoint, helixHighPointRFU]
ClearAll[coilMidPoint, coilLineLength, coilLowPoint, coilLowPointRFU, \
coilHighPoint, coilHighPointRFU]
ramp1FCelsiusXRFUSmooth[1];
helixLowBarrier = 10;
helixHighBarrier = 40;
coilLowBarrier = 60;
coilHighBarrier = 90;
{Slider[Dynamic[helixMidPoint], {helixLowBarrier, helixHighBarrier}],
Dynamic[helixMidPoint],
Dynamic[helixMidPointRFU = ramp1FSmoothFunc[1][helixMidPoint]],
Slider[Dynamic[helixLineLength], {5, 25}], Dynamic[helixLineLength]}
{Slider[Dynamic[coilMidPoint], {coilLowBarrier, coilHighBarrier}],
Dynamic[coilMidPoint],
Dynamic[coilMidPointRFU = ramp1FSmoothFunc[1][coilMidPoint]],
Slider[Dynamic[coilLineLength], {5, 25}], Dynamic[coilLineLength]}
Dynamic[{ListPlot[{ramp1FCelsiusXRFUSmooth[
1], {{helixLowPoint, helixLowPointRFU}}, {{helixHighPoint,
helixHighPointRFU}}, {{coilLowPoint,
coilLowPointRFU}}, {{coilHighPoint, coilHighPointRFU}}},
ImageSize -> Medium,
PlotStyle -> {PointSize[Small], PointSize[Large], PointSize[Large],
PointSize[Large], PointSize[Large]}],
Grid[{{, "temperature (C)", "Interpolated RFU"}, {"helix low point",
Dynamic[helixLowPoint = helixMidPoint - helixLineLength/2],
Dynamic[helixLowPointRFU =
ramp1FSmoothFunc[1][helixLowPoint]]}, {"helix high point",
Dynamic[helixHighPoint = helixMidPoint + helixLineLength/2],
Dynamic[helixHighPointRFU =
ramp1FSmoothFunc[1][
helixHighPoint]]}, {, ,}, {"coil low point",
Dynamic[coilLowPoint = coilMidPoint - coilLineLength/2],
Dynamic[coilLowPointRFU =
ramp1FSmoothFunc[1][coilLowPoint]]}, {"coil high point",
Dynamic[coilHighPoint = coilMidPoint + coilLineLength/2],
Dynamic[coilHighPointRFU = ramp1FSmoothFunc[1][coilHighPoint]]}},
Frame -> All]}]
Dynamic[ramp1FBaseLinesTEST =
Plot[{ramp1FHelixLinFitEqTEST[temp],
ramp1FCoilLinFitEqTEST[temp]}, {temp, 1, 100}]]
Dynamic[ramp1FHelixTEST =
Select[ramp1FCelsiusXRFUSmooth[1],
helixLowPoint <= #[[1]] <= helixHighPoint &]]
Dynamic[ramp1FHCoilTEST =
Select[ramp1FCelsiusXRFUSmooth[1],
coilLowPoint <= #[[1]] <= coilHighPoint &]]
Dynamic[ramp1FHelixLinFitTEST =
Fit[ramp1FHelixTEST, {1, temp}, temp]]
Dynamic[ramp1FHelixLinFitEqTEST[temp_] = ramp1FHelixLinFitTEST]
Dynamic[ramp1FCoilLinFitTEST = Fit[ramp1FHCoilTEST, {1, temp}, temp]]
Dynamic[ramp1FCoilLinFitEqTEST[temp_] = ramp1FCoilLinFitTEST]
Look at Manipulate, it should automate what you're trying to do with Dynamic. For example, Manipulate[Show[<plots>], {param, min, max}] should work.
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counterValues topic content:
“cpu”, 10, “2022-06-03 17:00”
“cpu”, 20, “2022-06-03 18:00”
“cpu”, 30, “2022-06-04 10:00”
“memory”, 40, “2022-06-04 10:00”
and I want to obtain this output:
“cpu”, “2022-06-03”, 15
“cpu”, “2022-06-04”, 30
“memory”, “2022-06-04”, 40
This is a snippet of my code that it doesn’t work (it seems to calculate count)…
Duration windowSize = Duration.ofDays(1);
TimeWindows tumblingWindow = TimeWindows.of(windowSize);
counterValueStream
.groupByKey().windowedBy(tumblingWindow)
.aggregate(StatisticValue::new, (k, counterValue, statisticValue) -> {
statisticValue.setSamplesNumber(statisticValue.getSamplesNumber() + 1);
statisticValue.setSum(statisticValue.getSum() + counterValue.getValue());
return statisticValue;
}, Materialized.with(Serdes.String(), statisticValueSerde))
.toStream().map((Windowed<String> key, StatisticValue sv) -> {
double avgNoFormat = sv.getSum() / (double) sv.getSamplesNumber();
double formattedAvg = Double.parseDouble(String.format("%.2f", avgNoFormat));
return new KeyValue<>(key.key(), formattedAvg) ;
}).to("average", Produced.with(Serdes.String(), Serdes.Double()));
But the aggregation result is:
“cpu”, 1, “2022-06-03 17:00”
“cpu”, 1, “2022-06-03 18:00”
“cpu”, 1, “2022-06-04 10:00”
“memory”, 1, “2022-06-04 10:00”
Note that I use a TimestampExtractor that use counter timestamp instead of kafka record. What am I doing wrong?
Getting max and min from two different sets in json
I haven't found a solution with data set up quite like mine...
var marketshare = [
{"store": "store1", "share": "5.3%", "q1count": 2, "q2count": 4, "q3count": 0},
{"store": "store2","share": "1.9%", "q1count": 5, "q2count": 10, "q3count": 0},
{"store": "store3", "share": "2.5%", "q1count": 3, "q2count": 6, "q3count": 0}
];
Code so far, returning undefined...
var minDataPoint = d3.min( d3.values(marketshare.q1count) ); //Expecting 2 from store 1
var maxDataPoint = d3.max( d3.values(marketshare.q2count) ); //Expecting 10 from store 2
I'm a little overwhelmed by d3.keys, d3.values, d3.maps, converting to array, etc. Any explanations or nudges would be appreciated.
I think you're looking for something like this instead:
d3.min(marketshare, function(d){ return d.q1count; }) // => 2.
You can pass an accessor function as the second argument to d3.min/d3.max.
In Mathematica, how to superpose two ListLinePlot?
I was using ListPlot to draw two smooth lines through some data points. But I want to superpose the plot.I learned that the method used by ListPlot for interpolation is to interpolate each coordinate as a function of the list index. So I can not simply plus two
interpolations of my two points.
thanks,
jzm
Here is some text for copy/paste:
myPoints1 = {{1.4620657889458748`,
335.2985577878116`}, {1.4620965802217518`,
103.38351787529564`}, {1.4621942025270345`,
62.5559208248015`}, {1.462354896492246`,
45.566589506360216`}, {1.4625751467402768`,
36.264281440327565`}, {1.4628516301983985`,
30.399003865053114`}, {1.4631812807492346`,
26.367460111951058`}, {1.4635611902991474`,
23.429554855802188`}, {1.4639886111585874`,
21.195443300677702`}, {1.464460983399038`,
19.440829611123966`}, {1.4649759015994719`,
18.02777886500251`}, {1.4655311109490736`,
16.86675689819105`}, {1.466124470097565`,
15.896899417397284`}, {1.4667539758770534`,
15.075547889029616`}, {1.467417728656181`,
14.37183869811537`}, {1.468113935160521`,
13.76291072113658`}, {1.4688409098827062`,
13.231534377122449`}, {1.4695970390339186`,
12.764290193109172`}, {1.4703808152150737`,
12.350655500316538`}, {1.47119080820051`,
11.982259112096562`}, {1.4720256766729714`,
11.652466731657922`}, {1.4728841551349938`,
11.35608813384227`}, {1.4737650210799367`,
11.088805023428025`}, {1.4746670942175184`,
10.846730689594123`}, {1.4755892711659102`,
10.626599181057326`}, {1.4765305432312286`,
10.425844517518913`}, {1.4774899140433866`,
10.242189544437958`}, {1.4784664768294848`,
10.07388845283117`}, {1.4794593535682306`,
9.91948469998374`}, {1.480467656424019`,
9.777491405153027`}, {1.4814906043125302`,
9.646805534544441`}, {1.4825273964568986`,
9.526291139015447`}, {1.4835772786981303`,
9.414764726544572`}, {1.4846395968104766`,
9.311395888282872`}, {1.4857136927436698`,
9.215545785306015`}, {1.4867989654798728`,
9.12678547130485`}, {1.487894785812934`,
9.0445918653539`}, {1.489000547636927`,
8.968341543739935`}, {1.49011571024499`,
7.71616343700933`}, {1.4912397307928495`,
4.4771368717931965`}, {1.4930948425223702`,
2.7599903709003706`}, {1.4972705714803425`, 2.137733395169292`}};
myPoints2 = {{1.9550995254889463,
0.7164793699550908}, {1.9391287471262355,
0.41710931241140287}, {1.9139528821159193,
0.3490726623599497}, {1.884617534719042,
0.3308820126668058}, {1.8540123750258504,
0.33265450551933234}, {1.8237456098779754,
0.3452794413751484}, {1.7946805323610866,
0.36513934480358856}, {1.7672498634600862,
0.3905924543768967}, {1.7416378319498413,
0.42085584504202456}, {1.717886011205134,
0.45557423825820337}, {1.6959554065943552,
0.49463019895914645}, {1.675763216373194,
0.5380524422510392}, {1.6572047192352064,
0.5859687470445493}, {1.6401662975943239,
0.6385812315738714}, {1.6245331447101943,
0.6961532977719818}, {1.6101937002933333,
0.7590036122922289}, {1.5970420916568349,
0.8275045669571167}, {1.5849793700525658,
0.9020832266507519}, {1.5739139593253322,
0.9832255360102758}, {1.5637616875683809,
1.071482155332956}, {1.5544455489784297,
1.1674755467368436}, {1.5458952859916812,
1.2719109855898907}, {1.538046945587126,
1.3855881585132812}, {1.5308423787211705,
1.5094157124835617}, {1.5242287288899015,
1.6444321762294256}, {1.5181579889629853,
1.7918272163885938}, {1.512586535548833,
1.952969437543702}, {1.5074747129386745,
2.1294427702228105}, {1.5027864632086367,
2.3230885849762424}, {1.4984889655043911,
2.536061738604728}, {1.4945523307439923,
2.7708992557015053}, {1.4909493139037207,
3.0306073328297867}, {1.4876550515968234,
3.3187795649748657}, {1.4846468371914137,
3.6397480437107252}, {1.481903916697491,
3.9987774524193394}, {1.4794072959177726,
4.4023273698572325}, {1.4771395719585305,
4.858408392792459}, {1.4750847772800355,
5.37708563628973}, {1.4732282431253443,
5.971204815109932}, {1.4715564902918326,
6.657415608955233}, {1.4700571242943155,
7.457674059555506}, {1.4687187279247118,
8.40154880208839}, {1.4675307832019475,
9.529729255387132}, {1.4664835796976867,
10.899794007715421}, {1.46556811155878,
12.596323274840168}, {1.4647760611386595,
14.748618559900901}, {1.4640997339059703,
17.564564972128032}, {1.463531979901696,
21.401490423013954}, {1.4630661880201312,
26.92897502098747}, {1.462696204020183,
35.566591773864054}, {1.4624163023794263,
50.94289950596402}, {1.462221186527755,
85.91265697099175}, {1.4621058905589708,
243.1565306412274}, {1.4620657889458748, 335.2985577878116}};
what I want is not
Show[ListPlot[myPoints1, Joined -> True, Mesh -> Full],
ListPlot[myPoints2, Joined -> True, Mesh -> Full]]
don't know how to get the plot of the value's superpostion of the two plot.Please help!:)
The meaning of "superpostion" is to get the plus of the value of the two curves at every x-axis.
Sounds like you want something like this in order to "plus" your lines.
it1 = Interpolation[myPoints1];
it2 = Interpolation[myPoints2];
t1 = Table[it1[i], {i, 1.467, 1.497, 0.001}];
t2 = Table[it2[i], {i, 1.467, 1.497, 0.001}];
t3 = Transpose[{Range[1.467, 1.497, 0.001], t1 + t2}];
ListPlot[{myPoints1, myPoints2, t3}, Joined -> True,
PlotRange -> {{1.467, 1.497}, {0, 30}}, PlotMarkers -> Automatic]
magento - Update product default image to first image in image gallery
I have an import script that imports well over 2000+ products including their images. I run this script via CLI because I feel that this is the best way to go speed-wise even though I have the same import script available and executable at the magento admin as an extension. The script runs pretty well. Almost perfect! However, sometimes the addToImageGallery somehow malfunctions and results into some images having No Image as the default product image and the only other image as not selected as defaults at all. How do I mass-update all products to set the first image in the media gallery for the product to the default 'base', 'image' and 'thumbnail' image(s)?
I found a couple of tricks on doing this (and more) on this link: http://www.magentocommerce.com/boards/viewthread/59440/ (Thanks transio!) Although, for Magento 1.6.2.0 (which I use), the first SQL trick there (Trick 1 - Auto-set default base, thumb, small image to first image.) needs a bit of modification. On the second-to-the last-line there is a AND ev.attribute_id IN (70, 71, 72) part. This should point to attribute ID's which will probably not be relevant in Magento 1.6.2.0 anymore. To fix this, using any MySQL query tool (PHPMyAdmin or MySQL Query Browser), I took a look at the catalog_product_entity_varchar table. There should be entries like: value_id, entity_type_id, attribute_id, store_id, entity_id, value .. 146649, 4, 116, 0, 1, '2' 146650, 4, 76, 0, 1, '' 146651, 4, 78, 0, 1, '' 146652, 4, 79, 0, 1, '/B/0/B05-01.jpg' 146653, 4, 80, 0, 1, '/B/0/B05-01.jpg' 146654, 4, 81, 0, 1, '/B/0/B05-01.jpg' 146655, 4, 96, 0, 1, '' 146656, 4, 100, 0, 1, '' 146657, 4, 102, 0, 1, 'container2' .. My money was on the group of three image paths as possible replacements. So the resulting SQL now should be: UPDATE catalog_product_entity_media_gallery AS mg, catalog_product_entity_media_gallery_value AS mgv, catalog_product_entity_varchar AS ev SET ev.value = mg.value WHERE mg.value_id = mgv.value_id AND mg.entity_id = ev.entity_id AND ev.attribute_id IN (79, 80, 81) # <-- attribute IDs updated here AND mgv.position = 1; So I committed to it, ran it and.. presto! All fixed! You might also want to encapsulate this in a transaction if you want. But this is out of this question's scope. Well, this is the fix that worked for me so far! If there are any more out there, please share!
There was: 146652, 4, 79, 0, 1, '/B/0/B05-01.jpg' 146653, 4, 80, 0, 1, '/B/0/B05-01.jpg' 146654, 4, 81, 0, 1, '/B/0/B05-01.jpg' So it should be: AND ev.attribute_id IN (79, 80, 81) # <-- attribute IDs updated here instead of: AND ev.attribute_id IN (78, 80, 81) # <-- attribute IDs updated here Is looking for something similar.
UPDATE catalog_product_entity_media_gallery AS mg, catalog_product_entity_media_gallery_value AS mgv, catalog_product_entity_varchar AS ev SET ev.value = mg.value WHERE mg.value_id = mgv.value_id AND mg.entity_id = ev.entity_id AND ev.attribute_id IN (79, 80, 81) # <-- attribute IDs updated here AND mgv.position = 1;
Parallelize behavior
I'm trying to understand some quirks of the Parallelize[] behavior.
If I do:
CloseKernels[];
LaunchKernels[1]
f[n_, g_] :=
First#AbsoluteTiming[
g[Product[Mod[i, 2], {i, 1, n/2}]
Product[Mod[i, 2], {i, n/2 + 1, n}]]];
Clear[a, b];
a = Table[f[i, Identity], {i, 100000, 1500000, 100000}];
LaunchKernels[1]
b = Table[f[i, Parallelize], {i, 100000, 1500000, 100000}];
ListLinePlot[{a, b}, PlotStyle -> {Red, Blue}]
The result is the expected one:
CPU utilization:
But if I do the same, changing the function to evaluate:
CloseKernels[];
LaunchKernels[1]
f[n_, g_] :=
First#AbsoluteTiming[
g[Product[Sin#i, {i, 1, n/2}]
Product[Sin#i, {i, n/2 + 1, n}]]];
Clear[a, b];
a = Table[f[i, Identity], {i, 1000, 15000, 1000}];
LaunchKernels[1]
b = Table[f[i, Parallelize], {i, 1000, 15000, 1000}];
ListLinePlot[{a, b}, PlotStyle -> {Red, Blue}]
The result is:
CPU utilization:
I think I am missing some important knowledge about Parallelize[] to understand this.
Any hints?
My guess is that the problem is not in Parallelize, but in what you are trying to compute. For Mod, the result is always either 1 or 0 and the product as well. For Sin, since you use the integer arithmetic, you accumulate huge symbolic expressions (products of Sin[i]). They are discarded after having been computed, but they need the heap space (memory allocation/deallocation). The quadratic behavior you observe is likely due to the linear complexity of large size memory allocation, "multiplied" by the liner complexity from your iteration. This seems the dominant effect, which shadows the real costs of Parallelize. If you apply N, like Sin#N[i], the results are quite different.
To understand what is going on behind the scenes when using Parallelize, it's a good idea to enable the Parallel Computing Toolkit's debugging mode, i.e.:
Needs["Parallel`Debug`"]
SetOptions[$Parallel, Tracers -> {SendReceive}]
The second example produces a lot of MathLink communication overhead, because the Sin function applied to an integer number is not immediately evaluated by Mathematica (as Leonid Shifrin already mentioned):
Here's a portion of the debugging output:
SendReceive: Receiving from kernel 13: Subscript[iid, 105][Sin[1] Sin[2] Sin[3] Sin[4] Sin[5] Sin[6] Sin[7] Sin[8] Sin[9] Sin[10] Sin[11] Sin[12] Sin[13] Sin[14] Sin[15] Sin[16] Sin[17] Sin[18] Sin[19] Sin[20] Sin[21] Sin[22] Sin[23] Sin[24] Sin[25] Sin[26] Sin[27] Sin[28] Sin[29] Sin[30] Sin[31] Sin[32] Sin[33] Sin[34] Sin[35] Sin[36] Sin[37] Sin[38] Sin[39] Sin[40] Sin[41] Sin[42] Sin[43] Sin[44] Sin[45] Sin[46] Sin[47] Sin[48] Sin[49] Sin[50] Sin[51] Sin[52] Sin[53] Sin[54] Sin[55] Sin[56] Sin[57] Sin[58] Sin[59] Sin[60] Sin[61] Sin[62] Sin[63] Sin[64] Sin[65] Sin[66] Sin[67] Sin[68] Sin[69] Sin[70] Sin[71] Sin[72] Sin[73] Sin[74] Sin[75] Sin[76] Sin[77] Sin[78] Sin[79] Sin[80] Sin[81] Sin[82] Sin[83] Sin[84] Sin[85] Sin[86] Sin[87] Sin[88] Sin[89] Sin[90] Sin[91] Sin[92] Sin[93] Sin[94] Sin[95] Sin[96] Sin[97] Sin[98] Sin[99] Sin[100] Sin[101] Sin[102] Sin[103] Sin[104] Sin[105] Sin[106] Sin[107] Sin[108] Sin[109] Sin[110] Sin[111] Sin[112] Sin[113] Sin[114] Sin[115] Sin[116] Sin[117] Sin[118] Sin[119] Sin[120] Sin[121] Sin[122] Sin[123] Sin[124] Sin[125] Sin[126] Sin[127] Sin[128] Sin[129] Sin[130] Sin[131] Sin[132] Sin[133] Sin[134] Sin[135] Sin[136] Sin[137] Sin[138] Sin[139] Sin[140] Sin[141] Sin[142] Sin[143] Sin[144] Sin[145] Sin[146] Sin[147] Sin[148] Sin[149] Sin[150] Sin[151] Sin[152] Sin[153] Sin[154] Sin[155] Sin[156] Sin[157] Sin[158] Sin[159] Sin[160] Sin[161] Sin[162] Sin[163] Sin[164] Sin[165] Sin[166] Sin[167] Sin[168] Sin[169] Sin[170] Sin[171] Sin[172] Sin[173] Sin[174] Sin[175] Sin[176] Sin[177] Sin[178] Sin[179] Sin[180] Sin[181] Sin[182] Sin[183] Sin[184] Sin[185] Sin[186] Sin[187] Sin[188] Sin[189] Sin[190] Sin[191] Sin[192] Sin[193] Sin[194] Sin[195] Sin[196] Sin[197] Sin[198] Sin[199] Sin[200] Sin[201] Sin[202] Sin[203] Sin[204] Sin[205] Sin[206] Sin[207] Sin[208] Sin[209] Sin[210] Sin[211] Sin[212] Sin[213] Sin[214] Sin[215] Sin[216] Sin[217] Sin[218] Sin[219] Sin[220] Sin[221] Sin[222] Sin[223] Sin[224] Sin[225] Sin[226] Sin[227] Sin[228] Sin[229] Sin[230] Sin[231] Sin[232] Sin[233] Sin[234] Sin[235] Sin[236] Sin[237] Sin[238] Sin[239] Sin[240] Sin[241] Sin[242] Sin[243] Sin[244] Sin[245] Sin[246] Sin[247] Sin[248] Sin[249] Sin[250] Sin[251] Sin[252] Sin[253] Sin[254] Sin[255] Sin[256] Sin[257] Sin[258] Sin[259] Sin[260] Sin[261] Sin[262] Sin[263] Sin[264] Sin[265] Sin[266] Sin[267] Sin[268] Sin[269] Sin[270] Sin[271] Sin[272] Sin[273] Sin[274] Sin[275] Sin[276] Sin[277] Sin[278] Sin[279] Sin[280] Sin[281] Sin[282] Sin[283] Sin[284] Sin[285] Sin[286] Sin[287] Sin[288] Sin[289] Sin[290] Sin[291] Sin[292] Sin[293] Sin[294] Sin[295] Sin[296] Sin[297] Sin[298] Sin[299] Sin[300] Sin[301] Sin[302] Sin[303] Sin[304] Sin[305] Sin[306] Sin[307] Sin[308] Sin[309] Sin[310] Sin[311] Sin[312] Sin[313] Sin[314] Sin[315] Sin[316] Sin[317] Sin[318] Sin[319] Sin[320] Sin[321] Sin[322] Sin[323] Sin[324] Sin[325] Sin[326] Sin[327] Sin[328] Sin[329] Sin[330] Sin[331] Sin[332] Sin[333] Sin[334] Sin[335] Sin[336] Sin[337] Sin[338] Sin[339] Sin[340] Sin[341] Sin[342] Sin[343] Sin[344] Sin[345] Sin[346] Sin[347] Sin[348] Sin[349] Sin[350] Sin[351] Sin[352] Sin[353] Sin[354] Sin[355] Sin[356] Sin[357] Sin[358] Sin[359] Sin[360] Sin[361] Sin[362] Sin[363] Sin[364] Sin[365] Sin[366] Sin[367] Sin[368] Sin[369] Sin[370] Sin[371] Sin[372] Sin[373] Sin[374] Sin[375] Sin[376] Sin[377] Sin[378] Sin[379] Sin[380] Sin[381] Sin[382] Sin[383] Sin[384] Sin[385] Sin[386] Sin[387] Sin[388] Sin[389] Sin[390] Sin[391] Sin[392] Sin[393] Sin[394] Sin[395] Sin[396] Sin[397] Sin[398] Sin[399] Sin[400] Sin[401] Sin[402] Sin[403] Sin[404] Sin[405] Sin[406] Sin[407] Sin[408] Sin[409] Sin[410] Sin[411] Sin[412] Sin[413] Sin[414] Sin[415] Sin[416] Sin[417] Sin[418] Sin[419] Sin[420] Sin[421] Sin[422] Sin[423] Sin[424] Sin[425] Sin[426] Sin[427] Sin[428] Sin[429] Sin[430] Sin[431] Sin[432] Sin[433] Sin[434] Sin[435] Sin[436] Sin[437] Sin[438] Sin[439] Sin[440] Sin[441] Sin[442] Sin[443] Sin[444] Sin[445] Sin[446] Sin[447] Sin[448] Sin[449] Sin[450] Sin[451] Sin[452] Sin[453] Sin[454] Sin[455] Sin[456] Sin[457] Sin[458] Sin[459] Sin[460] Sin[461] Sin[462] Sin[463] Sin[464] Sin[465] Sin[466] Sin[467] Sin[468] Sin[469] Sin[470] Sin[471] Sin[472] Sin[473] Sin[474] Sin[475] Sin[476] Sin[477] Sin[478] Sin[479] Sin[480] Sin[481] Sin[482] Sin[483] Sin[484] Sin[485] Sin[486] Sin[487] Sin[488] Sin[489] Sin[490] Sin[491] Sin[492] Sin[493] Sin[494] Sin[495] Sin[496] Sin[497] Sin[498] Sin[499] Sin[500]] (q=0)
Try this version and I'm sure you will know what's going on.
CloseKernels[];
LaunchKernels[1]
f[n_, g_] :=
First#AbsoluteTiming[
g[Product[Sin#i, {i, 1, n/2}] Product[Sin#i, {i, n/2 + 1, n}]]];
Clear[a, b];
a = Table[f[i, Identity], {i, 1000, 15000, 1000}];
LaunchKernels[1]
b1 = Table[f[i, Parallelize], {i, 1000, 15000, 1000}];
b2 = Table[f[i, Parallelize], {i, 1000., 15000., 1000.}];
ListLinePlot[{a, b1, b2}, PlotStyle -> {Red, Blue, Green}]