diff --git a/charts/models.py b/charts/models.py index 8abd96b..118ba43 100644 --- a/charts/models.py +++ b/charts/models.py @@ -5,12 +5,12 @@ from django.db import models # Create your models here. class Coin(models.Model): - name = models.CharField(max_length=4) - date = models.DateField() - priceusd = models.FloatField() - pricebtc = models.FloatField() - inflation = models.FloatField() - transactions = models.FloatField() + name = models.CharField(max_length=4, default="0") + date = models.DateField(default="0") + priceusd = models.FloatField(default="0") + pricebtc = models.FloatField(default="0") + inflation = models.FloatField(default="0") + transactions = models.FloatField(default="0") hashrate = models.FloatField(default="0") stocktoflow = models.FloatField(default="0") supply = models.FloatField(default="0") diff --git a/charts/templates/charts/base.html b/charts/templates/charts/base.html index 343447a..2518179 100644 --- a/charts/templates/charts/base.html +++ b/charts/templates/charts/base.html @@ -123,7 +123,7 @@
@@ -133,8 +133,7 @@ Price in Dollars (Lin.) Price in Sats (Lin.) Fractal Multiple - Inflation-Adjusted - Fractal + Inflation-Adjusted Fractal Golden Ratio Multiplier Performance ($, Log.) Performance ($, Lin.) @@ -146,6 +145,7 @@ Thermocap Multiple Sharpe Ratio Price Deviation + Market Cycle
@@ -174,7 +174,7 @@
@@ -193,6 +193,7 @@ Metcalfe's Deviation ($) Transacted Price Deviation Transaction Dominance + Shielded Transactions
diff --git a/charts/templates/charts/marketcycle.html b/charts/templates/charts/marketcycle.html index fe4f375..d390c13 100644 --- a/charts/templates/charts/marketcycle.html +++ b/charts/templates/charts/marketcycle.html @@ -35,31 +35,6 @@ - - -
- -
-
-
-
- Current Stock-to-flow Multiple
-
{{ now_cycle }}
-
-
-
- -
-
-
-
- Top Stock-to-flow Multiple Last Cycle
-
{{ maximum }}
-
-
-
- -
@@ -98,11 +73,7 @@
- This chart shows the Stock-to-flow Multiple, which is the comparison between its current price against - its supposed value. When the indicator reaches 100, it suggests - the coin is at the end of its cycle and will now begin a bear market. This indicator is my own - aprimoration of PlanB's model, since for this one I also considered - the coin's supply. The formula is XMR-Supply*Price/(SF-Value*1.500.000);
+ This chart shows an estimated Market Cycle for Monero, based on its price agains Bitcoin. The lower the more devaluated the coin is, and closer to the end of its Bear Market. Chart provided as courtesy from Cake Wallet and Monero.com. Link.
@@ -235,7 +206,7 @@ var layout = { xanchor: 'auto', y: 0.98, yanchor: 'auto', - text: 'Moneroj
https://www.moneroj.net', + text: 'Moneroj
https://www.moneroj.net
Chart provided as courtesy from Cake Wallet and Monero.com', showarrow: false, borderwidth: 1, bordercolor: '#5f5f5f', @@ -268,7 +239,7 @@ var layout = { yaxis: { type: "linear", title: { - text: 'Price / Stock-to-flow', + text: 'Cycle', font: { size: 20, color: 'white' diff --git a/charts/templates/charts/shielded.html b/charts/templates/charts/shielded.html new file mode 100644 index 0000000..02b3c5e --- /dev/null +++ b/charts/templates/charts/shielded.html @@ -0,0 +1,412 @@ +{% extends 'charts/base.html' %} + +{% block header %} +Moneroj.net - Dread Subscribers +{% endblock %} + +{% block content %} + + +
+ + +
+ + +

+
+
+
+
+
Shielded Transactions
+
+ + + +
+
+
+
+
+
+
+
+
+ + + +
+ + +
+
+
+
+ Monero Monthly Transactions
+
{{ monthly }}
+
+
+
+ +
+
+
+
+ Monero Dominance
+
{{ dominance }}%
+
+
+
+ +
+ +
+
+ +
+
+ +
+
+ +
+ + +
+ + +
+ + + + + + + + + + +{% endblock %} \ No newline at end of file diff --git a/charts/templates/charts/translog.html b/charts/templates/charts/translog.html index 733fc47..00d7e6b 100644 --- a/charts/templates/charts/translog.html +++ b/charts/templates/charts/translog.html @@ -140,227 +140,227 @@ }, yaxis: "y2" }; -var data1 = { - type: "scatter", - mode: "lines", - name: 'Price', - x: {{ dates|safe }}, - y: {{ pricexmr|safe }}, - line: { - color: '#444444' - ,width: 1 - } -}; - -var data1_mobile = { - type: "scatter", - mode: "lines", - name: 'Price', - x: {{ dates|safe }}, - y: {{ pricexmr|safe }}, - line: { - color: '#444444' - ,width: 1 - } -}; - -var data = [data3, data1]; -var data_mobile = [data3_mobile, data1_mobile]; - -var layout = { - plot_bgcolor:"#252221", - paper_bgcolor:"#252221", - annotations: [ - { - xref: 'paper', - yref: 'paper', - x: 0.50, - xanchor: 'auto', - y: 0.02, - yanchor: 'auto', - text: 'Moneroj
https://www.moneroj.net', - showarrow: false, - borderwidth: 1, - bordercolor: '#5f5f5f', - bgcolor: '#333333', - borderpad: 5, - align: 'center', - font: { - color: "white", - size: 12 + var data1 = { + type: "scatter", + mode: "lines", + name: 'Price', + x: {{ dates|safe }}, + y: {{ pricexmr|safe }}, + line: { + color: '#444444' + ,width: 1 } - }], - separators: ",.", - legend: { - x: 0.02, - y: 0.98, - bgcolor: '#333333', - bordercolor: '#5f5f5f', - borderwidth: 1, - font: { - color: 'white', + }; + + var data1_mobile = { + type: "scatter", + mode: "lines", + name: 'Price', + x: {{ dates|safe }}, + y: {{ pricexmr|safe }}, + line: { + color: '#444444' + ,width: 1 + } + }; + + var data = [data3, data1]; + var data_mobile = [data3_mobile, data1_mobile]; + + var layout = { + plot_bgcolor:"#252221", + paper_bgcolor:"#252221", + annotations: [ + { + xref: 'paper', + yref: 'paper', + x: 0.50, + xanchor: 'auto', + y: 0.02, + yanchor: 'auto', + text: 'Moneroj
https://www.moneroj.net', + showarrow: false, + borderwidth: 1, + bordercolor: '#5f5f5f', + bgcolor: '#333333', + borderpad: 5, + align: 'center', + font: { + color: "white", size: 12 - }, - traceorder: 'normal', - xanchor: 'auto', - yanchor: 'auto' - }, - hoverlabel: { - namelength: -1 - }, - yaxis: { + } + }], + separators: ",.", + legend: { + x: 0.02, + y: 0.98, + bgcolor: '#333333', + bordercolor: '#5f5f5f', + borderwidth: 1, + font: { + color: 'white', + size: 12 + }, + traceorder: 'normal', + xanchor: 'auto', + yanchor: 'auto' + }, + hoverlabel: { + namelength: -1 + }, + yaxis: { + type: "log", + title: { + text: 'Price (USD)', + font: { + size: 20, + color: 'white' + } + }, + tickformat :",.2f" + ,nticks: 10 + ,tickfont: { + color: "#ffffff" + ,size: 12 + } + ,gridcolor: "#333333" + }, + yaxis2: { type: "log", title: { - text: 'Price (USD)', + text: 'Transactions', font: { size: 20, color: 'white' } }, + tickformat :",.0f" + ,nticks: 10 + ,tickfont: { + color: "#ffffff" + ,size: 12 + } + ,gridcolor: "#252221" + ,side: "right" + ,overlaying: 'y' + }, + xaxis: { + hoverformat: "%Y-%m-%d", + showgrid: true, + type: 'date', + nticks: 10 + ,tickfont: { + color: "#dddddd" + ,size: 13 + } + ,gridcolor: "#333333" + ,range: ['2014-05-01', '2023-01-01'] + ,zeroline: true + }, + margin: { + l: 120, + r: 120, + b: 35, + t: 10, + pad: 10 + } + }; + + var layout_mobile = { + plot_bgcolor:"black", + paper_bgcolor:"black", + separators: ",.", + hoverlabel: { + namelength: -1 + }, + legend: { + x: 0.02, + y: 0.98, + bgcolor: '#000000', + bordercolor: '#5f5f5f', + borderwidth: 1, + font: { + color: 'white', + size: 5 + }, + traceorder: 'normal', + xanchor: 'auto', + yanchor: 'auto' + }, + showlegend: false, + yaxis: { + type: "log", + tickformat :",.0f" + ,nticks: 10 + ,tickfont: { + color: "#ffffff" + ,size: 7 + } + ,gridcolor: "#444444" + }, + yaxis2: { + type: "log", tickformat :",.2f" ,nticks: 10 ,tickfont: { - color: "#ffffff" - ,size: 12 + color: "white" } - ,gridcolor: "#333333" - }, - yaxis2: { - type: "log", - title: { - text: 'Transactions', - font: { - size: 20, - color: 'white' + ,gridcolor: "#252221" + ,side: "right" + ,overlaying: 'y' + }, + xaxis: { + hoverformat: "%Y", + showgrid: true, + type: 'date', + nticks: 10 + ,tickfont: { + color: "#dddddd" + ,size: 7 + } + ,gridcolor: "#444444" + ,range: ['2014-05-01', '2023-01-01'] + ,zeroline: true + }, + margin: { + l: 40, + r: 100, + b: 35, + t: 10, + pad: 10 } - }, - tickformat :",.0f" - ,nticks: 10 - ,tickfont: { - color: "#ffffff" - ,size: 12 + }; + + function findBootstrapEnvironment() { + let envs = ['xs', 'sm', 'md', 'lg', 'xl']; + + let el = document.createElement('div'); + document.body.appendChild(el); + + let curEnv = envs.shift(); + + for (let env of envs.reverse()) { + el.classList.add(`d-${env}-none`); + + if (window.getComputedStyle(el).display === 'none') { + curEnv = env; + break; + } } - ,gridcolor: "#252221" - ,side: "right" - ,overlaying: 'y' - }, - xaxis: { - hoverformat: "%Y-%m-%d", - showgrid: true, - type: 'date', - nticks: 10 - ,tickfont: { - color: "#dddddd" - ,size: 13 - } - ,gridcolor: "#333333" - ,range: ['2014-05-01', '2023-01-01'] - ,zeroline: true - }, - margin: { - l: 120, - r: 120, - b: 35, - t: 10, - pad: 10 + + document.body.removeChild(el); + return curEnv; + } -}; - -var layout_mobile = { - plot_bgcolor:"black", - paper_bgcolor:"black", - separators: ",.", - hoverlabel: { - namelength: -1 - }, - legend: { - x: 0.02, - y: 0.98, - bgcolor: '#000000', - bordercolor: '#5f5f5f', - borderwidth: 1, - font: { - color: 'white', - size: 5 - }, - traceorder: 'normal', - xanchor: 'auto', - yanchor: 'auto' - }, - showlegend: false, - yaxis: { - type: "log", - tickformat :",.0f" - ,nticks: 10 - ,tickfont: { - color: "#ffffff" - ,size: 7 - } - ,gridcolor: "#444444" - }, - yaxis2: { - type: "log", - tickformat :",.2f" - ,nticks: 10 - ,tickfont: { - color: "white" + env_size = findBootstrapEnvironment(); + if (env_size == "xs") { + document.getElementById("graph1").style.height="350px"; + Plotly.newPlot('graph', data_mobile, layout_mobile, {responsive: true, modeBarButtonsToRemove: ['toImage', 'hoverCompareCartesian', 'hoverClosest2d', 'toggleSpikelines', 'lasso2d', 'select2d', 'hoverClosestCartesian'], displaylogo: false}); } - ,gridcolor: "#252221" - ,side: "right" - ,overlaying: 'y' - }, - xaxis: { - hoverformat: "%Y", - showgrid: true, - type: 'date', - nticks: 10 - ,tickfont: { - color: "#dddddd" - ,size: 7 - } - ,gridcolor: "#444444" - ,range: ['2014-05-01', '2023-01-01'] - ,zeroline: true - }, - margin: { - l: 40, - r: 100, - b: 35, - t: 10, - pad: 10 + else { + document.getElementById("graph1").style.height="700px"; + Plotly.newPlot('graph', data, layout, {responsive: true, modeBarButtonsToRemove: ['toImage', 'hoverCompareCartesian', 'hoverClosest2d', 'toggleSpikelines', 'lasso2d', 'select2d', 'hoverClosestCartesian'], displaylogo: false}); } -}; - -function findBootstrapEnvironment() { - let envs = ['xs', 'sm', 'md', 'lg', 'xl']; - - let el = document.createElement('div'); - document.body.appendChild(el); - - let curEnv = envs.shift(); - - for (let env of envs.reverse()) { - el.classList.add(`d-${env}-none`); - - if (window.getComputedStyle(el).display === 'none') { - curEnv = env; - break; - } - } - - document.body.removeChild(el); - return curEnv; - -} -env_size = findBootstrapEnvironment(); -if (env_size == "xs") { - document.getElementById("graph1").style.height="350px"; - Plotly.newPlot('graph', data_mobile, layout_mobile, {responsive: true, modeBarButtonsToRemove: ['toImage', 'hoverCompareCartesian', 'hoverClosest2d', 'toggleSpikelines', 'lasso2d', 'select2d', 'hoverClosestCartesian'], displaylogo: false}); -} -else { - document.getElementById("graph1").style.height="700px"; - Plotly.newPlot('graph', data, layout, {responsive: true, modeBarButtonsToRemove: ['toImage', 'hoverCompareCartesian', 'hoverClosest2d', 'toggleSpikelines', 'lasso2d', 'select2d', 'hoverClosestCartesian'], displaylogo: false}); -} - + {% endblock %} \ No newline at end of file diff --git a/charts/urls.py b/charts/urls.py index cfae0d2..c8e9318 100644 --- a/charts/urls.py +++ b/charts/urls.py @@ -91,6 +91,7 @@ urlpatterns = [ path('metcalfesats_deviation/', views.metcalfesats_deviation, name='metcalfesats_deviation'), path('metcalfe_deviation/', views.metcalfe_deviation, name='metcalfe_deviation'), path('marketcycle/', views.marketcycle, name='marketcycle'), + path('shielded/', views.shielded, name='shielded'), # URLs to useful functions on charts/views.py # Only admins can use these diff --git a/charts/views.py b/charts/views.py index 8aefb3b..4c1b4c8 100644 --- a/charts/views.py +++ b/charts/views.py @@ -1026,17 +1026,18 @@ def check_new_social(symbol): # Update database DailyData with most recent coin data def update_database(date_from=None, date_to=None): + date_zero = '2014-05-20' + if not(date_from) or not(date_to): date_to = date.today() date_from = date_to - timedelta(5) + amount = date_from - datetime.datetime.strptime(date_zero, '%Y-%m-%d') else: print(str(date_from) + ' to ' + str(date_to)) date_from = datetime.datetime.strptime(date_from, '%Y-%m-%d') date_to = datetime.datetime.strptime(date_to, '%Y-%m-%d') + amount = date_from - datetime.datetime.strptime(date_zero, '%Y-%m-%d') - all_coins = Coin.objects.filter(name='xmr').all() - amount = int(len(all_coins)) - count = 0 date_aux = date_from while date_aux <= date_to: @@ -1044,14 +1045,24 @@ def update_database(date_from=None, date_to=None): date_aux2 = date_aux - timedelta(1) try: coin_xmr = Coin.objects.filter(name='xmr').get(date=date_aux) - coin_btc = Coin.objects.filter(name='btc').get(date=date_aux) - coin_dash = Coin.objects.filter(name='dash').get(date=date_aux) - coin_zcash = Coin.objects.filter(name='zec').get(date=date_aux) - coin_grin = Coin.objects.filter(name='grin').get(date=date_aux) - coin_xmr2 = Coin.objects.filter(name='xmr').get(date=date_aux2) + coin_btc = Coin.objects.filter(name='btc').get(date=date_aux) coin_btc2 = Coin.objects.filter(name='btc').get(date=date_aux2) + try: + coin_dash = Coin.objects.filter(name='dash').get(date=date_aux) + except: + coin_dash = Coin() + try: + coin_zcash = Coin.objects.filter(name='zec').get(date=date_aux) + except: + coin_zcash = Coin() + try: + coin_grin = Coin.objects.filter(name='grin').get(date=date_aux) + except: + coin_grin = Coin() + + if coin_btc.inflation == 0 or coin_xmr.inflation == 0: return count @@ -1091,11 +1102,10 @@ def update_database(date_from=None, date_to=None): reward = 0.6*(10**12) inflation = 100*reward*720*365/supply data.stocktoflow = (100/(inflation))**1.65 - if data.color == 0: - v0 = 0.002 - delta = (0.015 - 0.002)/(6*365) - data.color = 30*coin_xmr.pricebtc/((amount)*delta + v0) - amount += 1 + v0 = 0.002 + delta = (0.015 - 0.002)/(6*365) + data.color = 30*coin_xmr.pricebtc/((amount.days)*delta + v0) + amount += timedelta(1) data.save() try: @@ -4132,7 +4142,6 @@ def sfmultiple(request): context = {'dates': dates, 'maximum': maximum, 'stock_to_flow': stock_to_flow, 'now_sf': now_sf, 'buy': buy, 'sell': sell, 'color': color} return render(request, 'charts/sfmultiple.html', context) - def marketcycle(request): if request.user.username != "Administrador" and request.user.username != "Morpheus": update_visitors(False) @@ -4146,7 +4155,7 @@ def marketcycle(request): data = Sfmodel.objects.order_by('date') for item in data: if item.color > 0: - color.append(item.color) + color.append(item.color - 5) else: color.append('') @@ -4161,6 +4170,64 @@ def marketcycle(request): context = {'dates': dates, 'color': color, 'sell': sell, 'buy': buy, 'now_cycle': now_cycle} return render(request, 'charts/marketcycle.html', context) +def shielded(request): + if request.user.username != "Administrador" and request.user.username != "Morpheus": + update_visitors(False) + + dt = datetime.datetime.now(timezone.utc).timestamp() + dates = [] + values = [] + values2 = [] + values3 = [] + + gc = pygsheets.authorize(service_file='service_account_credentials.json') + sh = gc.open('zcash_bitcoin') + wks = sh.worksheet_by_title('Sheet1') + + dominance = 0 + monthly = 0 + + values_mat = wks.get_values(start=(3,1), end=(999,5), returnas='matrix') + + for k in range(0,len(values_mat)): + if values_mat[k][0] and values_mat[k][3]: + date = values_mat[k][0] + value = values_mat[k][3] + value3 = values_mat[k][4] + if not(value) or not(value): + break + else: + dates.append(date) + values.append(int(value)) + values3.append(int(value3)) + else: + break + + previous_date = 0 + coins = Coin.objects.order_by('date').filter(name='xmr') + for date in dates: + value2 = 0 + for coin in coins: + aux = str(coin.date) + month = aux.split("-")[0] + '-' + aux.split("-")[1] + if month == date: + if previous_date != coin.date: + value2 += coin.transactions + previous_date = coin.date + + values2.append(int(value2)) + + dominance = 100*int(value2)/(int(value2)+int(value)+int(value3)) + monthly = int(value2) + + monthly = format(int(monthly),',') + dominance = locale.format('%.2f', dominance, grouping=True) + + dt = 'shielded.html ' + locale.format('%.2f', datetime.datetime.now(timezone.utc).timestamp() - dt, grouping=True)+' seconds' + print(dt) + context = {'dates': dates, 'values': values, 'values2': values2, 'values3': values3, "monthly": monthly, "dominance": dominance} + return render(request, 'charts/shielded.html', context) + def thermocap(request): if request.user.username != "Administrador" and request.user.username != "Morpheus": update_visitors(False)