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comment tracer un chandelier ohlc avec datetime dans matplotlib?

Je dois tracer des données commerciales toutes les 5 minutes (une bougie)

Voici ce que j'ai jusqu'à présent:

from matplotlib.finance import candlestick2_ohlc
fig, ax = plt.subplots()
candlestick2_ohlc(ax,quotes['open'],quotes['high'],quotes['low'],quotes['close'],width=0.6)

Et cela ressemble à ceci:

result

Je dois l'améliorer:

  1. La marque bleue indique que xticks s'affiche avec int, je voudrais qu'ils soient au format datetime.

  2. La marque rouge indique la valeur x dans la barre d'état. Je voudrais que ce soit également au format datetime.

Voici les données de démonstration de quotes:

array([ (1459388100, 29.799999237060547, 29.799999237060547, 29.799999237060547, 29.799999237060547, 148929.0, 450030016.0),
   (1459388400, 29.799999237060547, 29.979999542236328, 29.709999084472656, 29.920000076293945, 10395.0, 31069984.0),
   (1459388700, 29.959999084472656, 30.18000030517578, 29.719999313354492, 30.149999618530273, 38522.0, 114999968.0),
   (1459389000, 30.170000076293945, 30.479999542236328, 30.0, 30.149999618530273, 29823.0, 90220032.0),
   (1459389300, 30.149999618530273, 30.75, 30.1299991607666, 30.549999237060547, 38903.0, 118620032.0),
   (1459389600, 30.59000015258789, 30.93000030517578, 30.559999465942383, 30.65999984741211, 42308.0, 130000000.0),
   (1459389900, 30.6200008392334, 30.690000534057617, 30.3799991607666, 30.3799991607666, 20209.0, 61689984.0),
   (1459390200, 30.3700008392334, 30.489999771118164, 30.18000030517578, 30.18000030517578, 18491.0, 56169984.0),
   (1459390500, 30.190000534057617, 30.329999923706055, 30.010000228881836, 30.010000228881836, 17641.0, 53200000.0),
   (1459390800, 30.030000686645508, 30.399999618530273, 30.030000686645508, 30.280000686645508, 9526.0, 28899968.0),
   (1459391100, 30.299999237060547, 30.31999969482422, 30.200000762939453, 30.209999084472656, 9282.0, 28100096.0),
   (1459391400, 30.190000534057617, 30.280000686645508, 30.049999237060547, 30.1200008392334, 8663.0, 26099968.0),
   (1459391700, 30.110000610351562, 30.110000610351562, 29.959999084472656, 30.100000381469727, 15677.0, 47099904.0),
   (1459392000, 30.1200008392334, 30.260000228881836, 30.0, 30.059999465942383, 5649.0, 17000064.0),
   (1459392300, 30.079999923706055, 30.299999237060547, 30.0, 30.280000686645508, 6057.0, 18199936.0),
   (1459392600, 30.290000915527344, 30.34000015258789, 30.1200008392334, 30.1200008392334, 7914.0, 24000000.0),
   (1459392900, 30.1299991607666, 30.15999984741211, 30.079999923706055, 30.139999389648438, 4521.0, 13600000.0),
   (1459393200, 30.139999389648438, 30.139999389648438, 29.829999923706055, 29.899999618530273, 16255.0, 48600064.0),
   (1459393500, 29.93000030517578, 30.1200008392334, 29.889999389648438, 30.1200008392334, 6877.0, 20600064.0),
   (1459393800, 30.1299991607666, 30.15999984741211, 29.979999542236328, 30.030000686645508, 3803.0, 11499904.0),
   (1459394100, 30.040000915527344, 30.1299991607666, 30.0, 30.030000686645508, 4421.0, 13300096.0),
   (1459394400, 29.989999771118164, 30.389999389648438, 29.989999771118164, 30.389999389648438, 7011.0, 21099904.0),
   (1459394700, 30.399999618530273, 30.450000762939453, 30.270000457763672, 30.299999237060547, 12095.0, 36800000.0),
   (1459395000, 30.34000015258789, 30.450000762939453, 30.280000686645508, 30.43000030517578, 9284.0, 28099968.0),
   (1459400700, 30.510000228881836, 30.729999542236328, 30.5, 30.600000381469727, 17139.0, 52500096.0),
   (1459401000, 30.600000381469727, 30.799999237060547, 30.530000686645508, 30.790000915527344, 11888.0, 36400000.0),
   (1459401300, 30.809999465942383, 31.100000381469727, 30.809999465942383, 31.049999237060547, 30692.0, 95099904.0),
   (1459401600, 31.06999969482422, 31.559999465942383, 30.93000030517578, 31.559999465942383, 24473.0, 76200064.0),
   (1459401900, 31.600000381469727, 31.860000610351562, 31.299999237060547, 31.450000762939453, 34497.0, 109200000.0),
   (1459402200, 31.43000030517578, 31.600000381469727, 31.18000030517578, 31.18000030517578, 18525.0, 58200064.0),
   (1459402500, 31.18000030517578, 31.350000381469727, 31.040000915527344, 31.18000030517578, 10153.0, 31599872.0),
   (1459402800, 31.200000762939453, 31.399999618530273, 31.010000228881836, 31.389999389648438, 9668.0, 30100096.0),
   (1459403100, 31.399999618530273, 31.399999618530273, 31.110000610351562, 31.360000610351562, 8445.0, 26499968.0),
   (1459403400, 31.360000610351562, 31.399999618530273, 31.040000915527344, 31.100000381469727, 9538.0, 29799936.0),
   (1459403700, 31.1200008392334, 31.399999618530273, 31.100000381469727, 31.270000457763672, 7996.0, 25000064.0),
   (1459404000, 31.270000457763672, 31.399999618530273, 31.15999984741211, 31.399999618530273, 6760.0, 21100032.0),
   (1459404300, 31.389999389648438, 32.400001525878906, 31.389999389648438, 32.189998626708984, 26108.0, 83700096.0),
   (1459404600, 32.209999084472656, 32.400001525878906, 31.860000610351562, 32.29999923706055, 15736.0, 50599936.0),
   (1459404900, 32.29999923706055, 32.310001373291016, 31.489999771118164, 31.489999771118164, 12945.0, 41399808.0),
   (1459405200, 31.5, 32.0, 31.40999984741211, 31.81999969482422, 11901.0, 37700096.0),
   (1459405500, 31.809999465942383, 31.940000534057617, 31.719999313354492, 31.770000457763672, 6503.0, 20700160.0),
   (1459405800, 31.760000228881836, 31.790000915527344, 31.399999618530273, 31.790000915527344, 10103.0, 31899904.0),
   (1459406100, 31.780000686645508, 32.029998779296875, 31.780000686645508, 31.850000381469727, 12033.0, 38500096.0),
   (1459406400, 31.809999465942383, 33.310001373291016, 31.809999465942383, 33.029998779296875, 58238.0, 192199936.0),
   (1459406700, 33.029998779296875, 33.310001373291016, 32.79999923706055, 32.79999923706055, 36689.0, 121900032.0),
   (1459407000, 32.79999923706055, 32.869998931884766, 32.61000061035156, 32.70000076293945, 15245.0, 49799936.0),
   (1459407300, 32.68000030517578, 32.689998626708984, 31.799999237060547, 32.0099983215332, 20507.0, 65999872.0),
   (1459407600, 32.02000045776367, 32.02000045776367, 31.760000228881836, 31.799999237060547, 29610.0, 94300160.0)], 
  dtype=[('time', '<i4'), ('open', '<f4'), ('high', '<f4'), ('low', '<f4'), ('close', '<f4'), ('volume', '<f4'), ('amount', '<f4')])
pythonnumpymatplotlib
14
dindom

Voici du code qui fonctionne.

Tout d'abord, nous convertissons l'horodatage en un objet datetime en utilisant datetime.datetime.fromtimestamp .

Ensuite, nous définissons les emplacements des ticks à l'aide d'un ticker.MaxNLocator .

J'ai ensuite créé une fonction pour alimenter ticker.FuncFormatter Pour utiliser l'objet datetime comme étiquette de tick, et utiliser la valeur entière de la tick pour indexer la liste xdate que nous créé plus tôt.

La clause try... except Est là au cas où il y aurait un tick au-delà de l'horodatage final dans votre tableau quotes, auquel cas la fonction échouerait.

J'ai également ajouté autofmt_xdate() pour faire pivoter les ticks, et tight_layout() pour leur faire de la place

from matplotlib.finance import candlestick2_ohlc
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import datetime as datetime
import numpy as np

quotes = np.array(...)

fig, ax = plt.subplots()
candlestick2_ohlc(ax,quotes['open'],quotes['high'],quotes['low'],quotes['close'],width=0.6)

xdate = [datetime.datetime.fromtimestamp(i) for i in quotes['time']]

ax.xaxis.set_major_locator(ticker.MaxNLocator(6))

def mydate(x,pos):
    try:
        return xdate[int(x)]
    except IndexError:
        return ''

ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))

fig.autofmt_xdate()
fig.tight_layout()

plt.show()

enter image description here

20
tmdavison

Tracer des bougies OHLC SANS matplotlib.finance

En supposant que prix est un Dataframe

import pandas as pd
import matplotlib.pyplot as plt

plt.figure()
width=1
width2=0.1
pricesup=prices[prices.close>=prices.open]
pricesdown=prices[prices.close<prices.open]

plt.bar(pricesup.index,pricesup.close-pricesup.open,width,bottom=pricesup.open,color='g')
plt.bar(pricesup.index,pricesup.high-pricesup.close,width2,bottom=pricesup.close,color='g')
plt.bar(pricesup.index,pricesup.low-pricesup.open,width2,bottom=pricesup.open,color='g')

plt.bar(pricesdown.index,pricesdown.close-pricesdown.open,width,bottom=pricesdown.open,color='r')
plt.bar(pricesdown.index,pricesdown.high-pricesdown.open,width2,bottom=pricesdown.open,color='r')
plt.bar(pricesdown.index,pricesdown.low-pricesdown.close,width2, bottom=pricesdown.close,color='r')
plt.grid()

Les largeurs doivent être ajustées pour différentes périodes

2
Daniele

Vous devez d'abord convertir l'estampille de votre tableau en objet datetime, puis la convertir à l'aide de date2num.

Comme spécifié dans http://matplotlib.org/api/finance_api.html

matplotlib.finance.candlestick_ochl (ax, guillemets , largeur = 0,2, colorup = 'k', colordown = 'r', alpha = 1.0)

guillemets : séquence de (temps, ouverture, fermeture, haut, bas, ...) séquences

Tant que les 5 premiers éléments sont ces valeurs, l'enregistrement peut être aussi long que vous le souhaitez (par exemple, il peut stocker du volume).

l'heure doit être au format float days - voir date2num 

import datetime
from matplotlib.dates import date2num

a = your_array
d = [date2num(datetime.datetime.fromtimestamp(x[0])) for x in a]
1
alec_djinn