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< h1 > pyFTS.data package< a class = "headerlink" href = "#pyfts-data-package" title = "Permalink to this headline" > ¶< / a > < / h1 >
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< / div >
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< section id = "module-pyFTS.data" >
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< span id = "module-contents" > < / span > < h2 > Module contents< a class = "headerlink" href = "#module-pyFTS.data" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Module for pyFTS standard datasets facilities< / p >
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< / section >
< section id = "submodules" >
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< h2 > Submodules< a class = "headerlink" href = "#submodules" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< / section >
< section id = "module-pyFTS.data.common" >
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< span id = "pyfts-data-common-module" > < / span > < h2 > pyFTS.data.common module< a class = "headerlink" href = "#module-pyFTS.data.common" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.common.get_dataframe" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.common.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > filename< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > url< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sep< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > ';'< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > compression< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'infer'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/common.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.common.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > This method check if filename already exists, read the file and return its data.
If the file don’ < / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > filename< / strong > – < / p > < / li >
< li > < p > < strong > url< / strong > – < / p > < / li >
< li > < p > < strong > sep< / strong > – < / p > < / li >
< li > < p > < strong > compression< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > Pandas dataset< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "datasets" >
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< h2 > Datasets< a class = "headerlink" href = "#datasets" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< / section >
< section id = "module-pyFTS.data.artificial" >
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< span id = "artificial-and-synthetic-data-generators" > < / span > < h2 > Artificial and synthetic data generators< a class = "headerlink" href = "#module-pyFTS.data.artificial" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Facilities to generate synthetic stochastic processes< / p >
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< dl class = "py class" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator" >
< em class = "property" > < span class = "pre" > class< / span > < span class = "w" > < / span > < / em > < span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > SignalEmulator< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "o" > < span class = "pre" > **< / span > < / span > < span class = "n" > < span class = "pre" > kwargs< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Bases: < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#object" title = "(in Python v3.11)" > < code class = "xref py py-class docutils literal notranslate" > < span class = "pre" > object< / span > < / code > < / a > < / p >
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< p > Emulate a complex signal built from several additive and non-additive components< / p >
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< dl class = "py method" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.blip" >
< span class = "sig-name descname" > < span class = "pre" > blip< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "o" > < span class = "pre" > **< / span > < / span > < span class = "n" > < span class = "pre" > kwargs< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator.blip" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.blip" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Creates an outlier greater than the maximum or lower then the minimum previous values of the signal,
and insert it on a random location of the signal.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > the current SignalEmulator instance, for method chaining< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py attribute" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.components" >
< span class = "sig-name descname" > < span class = "pre" > components< / span > < / span > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.components" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Components of the signal< / p >
< / dd > < / dl >
< dl class = "py method" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.incremental_gaussian" >
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< span class = "sig-name descname" > < span class = "pre" > incremental_gaussian< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "o" > < span class = "pre" > **< / span > < / span > < span class = "n" > < span class = "pre" > kwargs< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator.incremental_gaussian" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.incremental_gaussian" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Creates an additive gaussian interference on a previous signal< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > mu< / strong > – < / p > < / li >
< li > < p > < strong > sigma< / strong > – < / p > < / li >
< li > < p > < strong > start< / strong > – < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > length< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > the current SignalEmulator instance, for method chaining< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py method" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.periodic_gaussian" >
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< span class = "sig-name descname" > < span class = "pre" > periodic_gaussian< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > type< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > period< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_min< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_min< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_max< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_max< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "o" > < span class = "pre" > **< / span > < / span > < span class = "n" > < span class = "pre" > kwargs< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator.periodic_gaussian" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.periodic_gaussian" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Creates an additive periodic gaussian interference on a previous signal< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > type< / strong > – ‘ ’ ‘ ’ < / p > < / li >
< li > < p > < strong > period< / strong > – < / p > < / li >
< li > < p > < strong > mu< / strong > – < / p > < / li >
< li > < p > < strong > sigma< / strong > – < / p > < / li >
< li > < p > < strong > start< / strong > – < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > length< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > the current SignalEmulator instance, for method chaining< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py method" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.run" >
< span class = "sig-name descname" > < span class = "pre" > run< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator.run" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.run" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Render the signal< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > a list of float values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py method" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.SignalEmulator.stationary_gaussian" >
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< span class = "sig-name descname" > < span class = "pre" > stationary_gaussian< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "o" > < span class = "pre" > **< / span > < / span > < span class = "n" > < span class = "pre" > kwargs< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#SignalEmulator.stationary_gaussian" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.SignalEmulator.stationary_gaussian" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Creates a continuous Gaussian signal with mean mu and variance sigma.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > mu< / strong > – < / p > < / li >
< li > < p > < strong > sigma< / strong > – < / p > < / li >
< li > < p > < strong > additive< / strong > –
this signal is added to the previous one< / p > < / li >
< li > < p > < strong > start< / strong > – < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > length< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > the current SignalEmulator instance, for method chaining< / p >
< / dd >
< / dl >
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< / dd > < / dl >
< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.generate_gaussian_linear" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > generate_gaussian_linear< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_ini< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_ini< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_inc< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_inc< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > it< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 100< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > num< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 10< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmin< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmax< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#generate_gaussian_linear" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.generate_gaussian_linear" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Generate data sampled from Gaussian distribution, with constant or linear changing parameters< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > mu_ini< / strong > – < / p > < / li >
< li > < p > < strong > sigma_ini< / strong > – < / p > < / li >
< li > < p > < strong > mu_inc< / strong > – ‘ ’ < / p > < / li >
< li > < p > < strong > sigma_inc< / strong > – ‘ ’ < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > num< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > A list of it*num float values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.generate_linear_periodic_gaussian" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > generate_linear_periodic_gaussian< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > period< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_min< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_min< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_max< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_max< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > it< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 100< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > num< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 10< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmin< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmax< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#generate_linear_periodic_gaussian" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.generate_linear_periodic_gaussian" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Generates a periodic linear variation on mean and variance< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > period< / strong > – < / p > < / li >
< li > < p > < strong > mu_min< / strong > – < / p > < / li >
< li > < p > < strong > sigma_min< / strong > – < / p > < / li >
< li > < p > < strong > mu_max< / strong > – < / p > < / li >
< li > < p > < strong > sigma_max< / strong > – < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > num< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > A list of it*num float values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.generate_sinoidal_periodic_gaussian" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > generate_sinoidal_periodic_gaussian< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > period< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_min< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_min< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > mu_max< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > sigma_max< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > it< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 100< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > num< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 10< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmin< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmax< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#generate_sinoidal_periodic_gaussian" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.generate_sinoidal_periodic_gaussian" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Generates a periodic sinoidal variation on mean and variance< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > period< / strong > – < / p > < / li >
< li > < p > < strong > mu_min< / strong > – < / p > < / li >
< li > < p > < strong > sigma_min< / strong > – < / p > < / li >
< li > < p > < strong > mu_max< / strong > – < / p > < / li >
< li > < p > < strong > sigma_max< / strong > – < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > num< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > A list of it*num float values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.generate_uniform_linear" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > generate_uniform_linear< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > min_ini< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > max_ini< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > min_inc< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > max_inc< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > it< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 100< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > num< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 10< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmin< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > vmax< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > None< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#generate_uniform_linear" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.generate_uniform_linear" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Generate data sampled from Uniform distribution, with constant or linear changing bounds< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > mu_ini< / strong > – < / p > < / li >
< li > < p > < strong > sigma_ini< / strong > – < / p > < / li >
< li > < p > < strong > mu_inc< / strong > – ‘ ’ < / p > < / li >
< li > < p > < strong > sigma_inc< / strong > – ‘ ’ < / p > < / li >
< li > < p > < strong > it< / strong > – < / p > < / li >
< li > < p > < strong > num< / strong > – < / p > < / li >
< li > < p > < strong > vmin< / strong > – < / p > < / li >
< li > < p > < strong > vmax< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > A list of it*num float values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.random_walk" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > random_walk< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > n< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 500< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > type< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 'gaussian'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#random_walk" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.random_walk" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Simple random walk< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > n< / strong > – < / p > < / li >
< li > < p > < strong > type< / strong > – ‘ ’ ‘ ’ < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > < / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.artificial.white_noise" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.artificial.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > white_noise< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > n< / span > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "default_value" > < span class = "pre" > 500< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < a class = "reference internal" href = "_modules/pyFTS/data/artificial.html#white_noise" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.artificial.white_noise" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Simple Gaussian noise signal
:param n: number of samples
:return:< / p >
< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.AirPassengers" >
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< span id = "airpassengers-dataset" > < / span > < h2 > AirPassengers dataset< a class = "headerlink" href = "#module-pyFTS.data.AirPassengers" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > Monthly totals of a airline passengers from USA, from January 1949 through December 1960.< / p >
< p > Source: Hyndman, R.J., Time Series Data Library, < a class = "reference external" href = "http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/" > http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/< / a > .< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.AirPassengers.get_data" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.AirPassengers.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/AirPassengers.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.AirPassengers.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get a simple univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.AirPassengers.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.AirPassengers.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/AirPassengers.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.AirPassengers.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.Bitcoin" >
2018-09-06 21:36:08 +04:00
< span id = "bitcoin-dataset" > < / span > < h2 > Bitcoin dataset< a class = "headerlink" href = "#module-pyFTS.data.Bitcoin" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Bitcoin to USD quotations< / p >
< p > Daily averaged index, by business day, from 2010 to 2018.< / p >
< p > Source: < a class = "reference external" href = "https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD" > https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD< / a > < / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Bitcoin.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Bitcoin.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'AVG'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Bitcoin.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Bitcoin.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Bitcoin.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Bitcoin.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Bitcoin.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Bitcoin.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.DowJones" >
2018-09-06 21:36:08 +04:00
< span id = "dowjones-dataset" > < / span > < h2 > DowJones dataset< a class = "headerlink" href = "#module-pyFTS.data.DowJones" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > DJI - Dow Jones< / p >
< p > Daily averaged index, by business day, from 1985 to 2017.< / p >
< p > Source: < a class = "reference external" href = "https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC" > https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC< / a > < / p >
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< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.DowJones.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.DowJones.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'AVG'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/DowJones.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.DowJones.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.DowJones.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.DowJones.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/DowJones.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.DowJones.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.Enrollments" >
2018-09-06 21:36:08 +04:00
< span id = "enrollments-dataset" > < / span > < h2 > Enrollments dataset< a class = "headerlink" href = "#module-pyFTS.data.Enrollments" title = "Permalink to this headline" > ¶< / a > < / h2 >
2018-08-30 23:04:52 +04:00
< p > Yearly University of Alabama enrollments from 1971 to 1992.< / p >
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< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Enrollments.get_data" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Enrollments.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Enrollments.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Enrollments.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get a simple univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > numpy array< / p >
< / dd >
< / dl >
2018-08-30 09:05:29 +04:00
< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Enrollments.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Enrollments.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Enrollments.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Enrollments.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.Ethereum" >
2018-09-06 21:36:08 +04:00
< span id = "ethereum-dataset" > < / span > < h2 > Ethereum dataset< a class = "headerlink" href = "#module-pyFTS.data.Ethereum" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Ethereum to USD quotations< / p >
< p > Daily averaged index, by business day, from 2016 to 2018.< / p >
< p > Source: < a class = "reference external" href = "https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD" > https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD< / a > < / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Ethereum.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Ethereum.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'AVG'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Ethereum.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Ethereum.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Ethereum.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Ethereum.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Ethereum.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Ethereum.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
2023-05-25 02:46:07 +04:00
< / section >
< section id = "module-pyFTS.data.EURGBP" >
2018-09-06 21:36:08 +04:00
< span id = "eur-gbp-dataset" > < / span > < h2 > EUR-GBP dataset< a class = "headerlink" href = "#module-pyFTS.data.EURGBP" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > FOREX market EUR-GBP pair.< / p >
< p > Daily averaged quotations, by business day, from 2016 to 2018.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.EURGBP.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.EURGBP.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'avg'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/EURGBP.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.EURGBP.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.EURGBP.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.EURGBP.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/EURGBP.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.EURGBP.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
2018-09-06 21:36:08 +04:00
< / dd > < / dl >
2023-05-25 02:46:07 +04:00
< / section >
< section id = "module-pyFTS.data.EURUSD" >
2018-09-06 21:36:08 +04:00
< span id = "eur-usd-dataset" > < / span > < h2 > EUR-USD dataset< a class = "headerlink" href = "#module-pyFTS.data.EURUSD" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > FOREX market EUR-USD pair.< / p >
< p > Daily averaged quotations, by business day, from 2016 to 2018.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.EURUSD.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.EURUSD.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'avg'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/EURUSD.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.EURUSD.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.EURUSD.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.EURUSD.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/EURUSD.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.EURUSD.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.GBPUSD" >
2018-09-06 21:36:08 +04:00
< span id = "gbp-usd-dataset" > < / span > < h2 > GBP-USD dataset< a class = "headerlink" href = "#module-pyFTS.data.GBPUSD" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > FOREX market GBP-USD pair.< / p >
< p > Daily averaged quotations, by business day, from 2016 to 2018.< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.GBPUSD.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.GBPUSD.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'avg'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/GBPUSD.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.GBPUSD.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.GBPUSD.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.GBPUSD.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/GBPUSD.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.GBPUSD.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-09-06 21:36:08 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.INMET" >
2018-09-06 21:36:08 +04:00
< span id = "inmet-dataset" > < / span > < h2 > INMET dataset< a class = "headerlink" href = "#module-pyFTS.data.INMET" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > INMET - Instituto Nacional Meteorologia / Brasil< / p >
< p > Belo Horizonte station, from 2000-01-01 to 31/12/2012< / p >
< p > Source: < a class = "reference external" href = "http://www.inmet.gov.br" > http://www.inmet.gov.br< / a > < / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.INMET.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.INMET.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/INMET.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.INMET.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.Malaysia" >
2018-11-07 17:31:46 +04:00
< span id = "malaysia-dataset" > < / span > < h2 > Malaysia dataset< a class = "headerlink" href = "#module-pyFTS.data.Malaysia" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Hourly Malaysia eletric load and tempeature< / p >
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< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.Malaysia.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Malaysia.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'load'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Malaysia.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Malaysia.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-11-07 17:31:46 +04:00
< dd > < p > Get the univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.Malaysia.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.Malaysia.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/Malaysia.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.Malaysia.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-11-07 17:31:46 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.NASDAQ" >
2018-09-06 21:36:08 +04:00
< span id = "nasdaq-module" > < / span > < h2 > NASDAQ module< a class = "headerlink" href = "#module-pyFTS.data.NASDAQ" title = "Permalink to this headline" > ¶< / a > < / h2 >
2018-08-30 23:04:52 +04:00
< p > National Association of Securities Dealers Automated Quotations - Composite Index (NASDAQ IXIC)< / p >
< p > Daily averaged index by business day, from 2000 to 2016.< / p >
< p > Source: < a class = "reference external" href = "http://www.nasdaq.com/aspx/flashquotes.aspx?symbol=IXIC&selected=IXIC" > http://www.nasdaq.com/aspx/flashquotes.aspx?symbol=IXIC& selected=IXIC< / a > < / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.NASDAQ.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.NASDAQ.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 'avg'< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/NASDAQ.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.NASDAQ.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get a simple univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.NASDAQ.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.NASDAQ.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/NASDAQ.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.NASDAQ.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.SONDA" >
2018-09-06 21:36:08 +04:00
< span id = "sonda-dataset" > < / span > < h2 > SONDA dataset< a class = "headerlink" href = "#module-pyFTS.data.SONDA" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > SONDA - Sistema de Organização Nacional de Dados Ambientais, from INPE - Instituto Nacional de Pesquisas Espaciais, Brasil.< / p >
< p > Brasilia station< / p >
< p > Source: < a class = "reference external" href = "http://sonda.ccst.inpe.br/" > http://sonda.ccst.inpe.br/< / a > < / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.SONDA.get_data" >
2023-05-25 02:46:07 +04:00
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.SONDA.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > field< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/SONDA.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.SONDA.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get a simple univariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > field< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
2018-08-30 09:05:29 +04:00
< / dd > < / dl >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
2022-04-10 21:32:24 +04:00
< dt class = "sig sig-object py" id = "pyFTS.data.SONDA.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.SONDA.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/SONDA.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.SONDA.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
2018-08-30 09:05:29 +04:00
< dd > < p > Get the complete multivariate time series data.< / p >
2020-08-19 00:06:41 +04:00
< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
2018-08-30 09:05:29 +04:00
< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.SP500" >
2018-09-06 21:36:08 +04:00
< span id = "s-p-500-dataset" > < / span > < h2 > S& P 500 dataset< a class = "headerlink" href = "#module-pyFTS.data.SP500" title = "Permalink to this headline" > ¶< / a > < / h2 >
2018-08-30 23:04:52 +04:00
< p > S& P500 - Standard & Poor’ < / p >
< p > Daily averaged index, by business day, from 1950 to 2017.< / p >
< p > Source: < a class = "reference external" href = "https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC" > https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC< / a > < / p >
2020-08-19 00:06:41 +04:00
< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.SP500.get_data" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.SP500.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/SP500.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.SP500.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get the univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.SP500.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.SP500.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/SP500.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.SP500.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get the complete multivariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.TAIEX" >
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< span id = "taiex-dataset" > < / span > < h2 > TAIEX dataset< a class = "headerlink" href = "#module-pyFTS.data.TAIEX" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX)< / p >
< p > Daily averaged index by business day, from 1995 to 2014.< / p >
< p > Source: < a class = "reference external" href = "http://www.twse.com.tw/en/products/indices/Index_Series.php" > http://www.twse.com.tw/en/products/indices/Index_Series.php< / a > < / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.TAIEX.get_data" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.TAIEX.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/TAIEX.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.TAIEX.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get the univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.TAIEX.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.TAIEX.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/TAIEX.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.TAIEX.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get the complete multivariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.henon" >
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< span id = "henon-chaotic-time-series" > < / span > < h2 > Henon chaotic time series< a class = "headerlink" href = "#module-pyFTS.data.henon" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< ol class = "upperalpha simple" start = "13" >
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< li > < p > Hénon. “A two-dimensional mapping with a strange attractor”. Commun. Math. Phys. 50, 69-77 (1976)< / p > < / li >
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< / ol >
< p > dx/dt = a + by(t-1) - x(t-1)^2
dy/dt = x< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.henon.get_data" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.henon.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > var< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1.4< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.3< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [1,< / span > < span class = "pre" > 1]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/henon.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.henon.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get a simple univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > var< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.henon.get_dataframe" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.henon.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1.4< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.3< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [1,< / span > < span class = "pre" > 1]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/henon.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.henon.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Return a dataframe with the bivariate Henon Map time series (x, y).< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > a< / strong > – < / p > < / li >
< li > < p > < strong > b< / strong > – < / p > < / li >
< li > < p > < strong > initial_values< / strong > – < / p > < / li >
< li > < p > < strong > iterations< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > Panda dataframe with the x and y values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.logistic_map" >
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< span id = "logistic-map-chaotic-time-series" > < / span > < h2 > Logistic_map chaotic time series< a class = "headerlink" href = "#module-pyFTS.data.logistic_map" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > May, Robert M. (1976). “Simple mathematical models with very complicated dynamics”.
Nature. 261 (5560): 459– < / p >
< p > x(t) = r * x(t-1) * (1 - x(t -1) )< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.logistic_map.get_data" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.logistic_map.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > r< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 4< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_value< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.3< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 100< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/logistic_map.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.logistic_map.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Return a list with the logistic map chaotic time series.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > r< / strong > – < / p > < / li >
< li > < p > < strong > initial_value< / strong > – < / p > < / li >
< li > < p > < strong > iterations< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > < / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.lorentz" >
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< span id = "lorentz-chaotic-time-series" > < / span > < h2 > Lorentz chaotic time series< a class = "headerlink" href = "#module-pyFTS.data.lorentz" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > Lorenz, Edward Norton (1963). “Deterministic nonperiodic flow”. Journal of the Atmospheric Sciences. 20 (2): 130–
< a class = "reference external" href = "https://doi.org/10.1175/1520-0469(1963" > https://doi.org/10.1175/1520-0469(1963< / a > )020< 0130:DNF> 2.0.CO;2< / p >
< p > dx/dt = a(y -x)
dy/dt = x(b - z) - y
dz/dt = xy - cz< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.lorentz.get_data" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.lorentz.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > var< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 10.0< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 28.0< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > c< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 2.6666666666666665< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > dt< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.01< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [0.1,< / span > < span class = "pre" > 0,< / span > < span class = "pre" > 0]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/lorentz.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.lorentz.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get a simple univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > var< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.lorentz.get_dataframe" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.lorentz.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 10.0< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 28.0< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > c< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 2.6666666666666665< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > dt< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.01< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [0.1,< / span > < span class = "pre" > 0,< / span > < span class = "pre" > 0]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/lorentz.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.lorentz.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Return a dataframe with the multivariate Lorenz Map time series (x, y, z).< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > a< / strong > – < / p > < / li >
< li > < p > < strong > b< / strong > – < / p > < / li >
< li > < p > < strong > c< / strong > – < / p > < / li >
< li > < p > < strong > dt< / strong > – < / p > < / li >
< li > < p > < strong > initial_values< / strong > – < / p > < / li >
< li > < p > < strong > iterations< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > Panda dataframe with the x, y and z values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.mackey_glass" >
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< span id = "mackey-glass-chaotic-time-series" > < / span > < h2 > Mackey-Glass chaotic time series< a class = "headerlink" href = "#module-pyFTS.data.mackey_glass" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > Mackey, M. C. and Glass, L. (1977). Oscillation and chaos in physiological control systems.
Science, 197(4300):287-289.< / p >
< p > dy/dt = -by(t)+ cy(t - tau) / 1+y(t-tau)^10< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.mackey_glass.get_data" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.mackey_glass.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.1< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > c< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.2< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > tau< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 17< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < span class = "pre" > numpy.ndarray< / span > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > array([0.5,< / span > < span class = "pre" > 0.55882353,< / span > < span class = "pre" > 0.61764706,< / span > < span class = "pre" > 0.67647059,< / span > < span class = "pre" > 0.73529412,< / span > < span class = "pre" > 0.79411765,< / span > < span class = "pre" > 0.85294118,< / span > < span class = "pre" > 0.91176471,< / span > < span class = "pre" > 0.97058824,< / span > < span class = "pre" > 1.02941176,< / span > < span class = "pre" > 1.08823529,< / span > < span class = "pre" > 1.14705882,< / span > < span class = "pre" > 1.20588235,< / span > < span class = "pre" > 1.26470588,< / span > < span class = "pre" > 1.32352941,< / span > < span class = "pre" > 1.38235294,< / span > < span class = "pre" > 1.44117647,< / span > < span class = "pre" > 1.5])< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 1000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#list" title = "(in Python v3.11)" > < span class = "pre" > list< / span > < / a > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/mackey_glass.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.mackey_glass.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Return a list with the Mackey-Glass chaotic time series.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > b< / strong > – < / p > < / li >
< li > < p > < strong > c< / strong > – < / p > < / li >
< li > < p > < strong > tau< / strong > – < / p > < / li >
< li > < p > < strong > initial_values< / strong > – < / p > < / li >
< li > < p > < strong > iterations< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > < / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.rossler" >
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< span id = "rossler-chaotic-time-series" > < / span > < h2 > Rossler chaotic time series< a class = "headerlink" href = "#module-pyFTS.data.rossler" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< ol class = "upperalpha simple" start = "15" >
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< li > < ol class = "upperalpha simple" start = "5" >
< li > < p > Rössler, Phys. Lett. 57A, 397 (1976).< / p > < / li >
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< / ol >
< / li >
< / ol >
< p > dx/dt = -z - y
dy/dt = x + ay
dz/dt = b + z( x - c )< / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.rossler.get_data" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.rossler.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > var< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/stdtypes.html#str" title = "(in Python v3.11)" > < span class = "pre" > str< / span > < / a > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.2< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.2< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > c< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 5.7< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > dt< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.01< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < span class = "pre" > numpy.ndarray< / span > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [0.001,< / span > < span class = "pre" > 0.001,< / span > < span class = "pre" > 0.001]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 5000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/rossler.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.rossler.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get a simple univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < p > < strong > var< / strong > – < / p >
< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.rossler.get_dataframe" >
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< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.rossler.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < em class = "sig-param" > < span class = "n" > < span class = "pre" > a< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.2< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > b< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.2< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > c< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 5.7< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > dt< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#float" title = "(in Python v3.11)" > < span class = "pre" > float< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 0.01< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > initial_values< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < span class = "pre" > numpy.ndarray< / span > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > [0.001,< / span > < span class = "pre" > 0.001,< / span > < span class = "pre" > 0.001]< / span > < / span > < / em > , < em class = "sig-param" > < span class = "n" > < span class = "pre" > iterations< / span > < / span > < span class = "p" > < span class = "pre" > :< / span > < / span > < span class = "w" > < / span > < span class = "n" > < a class = "reference external" href = "https://docs.python.org/3/library/functions.html#int" title = "(in Python v3.11)" > < span class = "pre" > int< / span > < / a > < / span > < span class = "w" > < / span > < span class = "o" > < span class = "pre" > =< / span > < / span > < span class = "w" > < / span > < span class = "default_value" > < span class = "pre" > 5000< / span > < / span > < / em > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/rossler.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.rossler.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Return a dataframe with the multivariate Rössler Map time series (x, y, z).< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Parameters< / dt >
< dd class = "field-odd" > < ul class = "simple" >
< li > < p > < strong > a< / strong > – < / p > < / li >
< li > < p > < strong > b< / strong > – < / p > < / li >
< li > < p > < strong > c< / strong > – < / p > < / li >
< li > < p > < strong > dt< / strong > – < / p > < / li >
< li > < p > < strong > initial_values< / strong > – < / p > < / li >
< li > < p > < strong > iterations< / strong > – < / p > < / li >
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< / ul >
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< / dd >
< dt class = "field-even" > Returns< / dt >
< dd class = "field-even" > < p > Panda dataframe with the x, y and z values< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< section id = "module-pyFTS.data.sunspots" >
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< span id = "sunspots-dataset" > < / span > < h2 > Sunspots dataset< a class = "headerlink" href = "#module-pyFTS.data.sunspots" title = "Permalink to this headline" > ¶< / a > < / h2 >
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< p > Monthly sunspot numbers from 1749 to May 2016< / p >
< p > Source: < a class = "reference external" href = "https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SUNSPOT/" > https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SUNSPOT/< / a > < / p >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.sunspots.get_data" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.sunspots.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_data< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > numpy.ndarray< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/sunspots.html#get_data" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.sunspots.get_data" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get a simple univariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > numpy array< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< dl class = "py function" >
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< dt class = "sig sig-object py" id = "pyFTS.data.sunspots.get_dataframe" >
< span class = "sig-prename descclassname" > < span class = "pre" > pyFTS.data.sunspots.< / span > < / span > < span class = "sig-name descname" > < span class = "pre" > get_dataframe< / span > < / span > < span class = "sig-paren" > (< / span > < span class = "sig-paren" > )< / span > < span class = "sig-return" > < span class = "sig-return-icon" > → < / span > < span class = "sig-return-typehint" > < span class = "pre" > pandas.core.frame.DataFrame< / span > < / span > < / span > < a class = "reference internal" href = "_modules/pyFTS/data/sunspots.html#get_dataframe" > < span class = "viewcode-link" > < span class = "pre" > [source]< / span > < / span > < / a > < a class = "headerlink" href = "#pyFTS.data.sunspots.get_dataframe" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Get the complete multivariate time series data.< / p >
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< dl class = "field-list simple" >
< dt class = "field-odd" > Returns< / dt >
< dd class = "field-odd" > < p > Pandas DataFrame< / p >
< / dd >
< / dl >
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< / dd > < / dl >
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< / section >
< / section >
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< div class = "clearer" > < / div >
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< img class = "logo" src = "_static/logo_heading2.png" alt = "Logo" / >
< / a > < / p >
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< h3 > < a href = "index.html" > Table of Contents< / a > < / h3 >
< ul >
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< li > < a class = "reference internal" href = "#" > pyFTS.data package< / a > < ul >
< li > < a class = "reference internal" href = "#module-pyFTS.data" > Module contents< / a > < / li >
< li > < a class = "reference internal" href = "#submodules" > Submodules< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.common" > pyFTS.data.common module< / a > < / li >
< li > < a class = "reference internal" href = "#datasets" > Datasets< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.artificial" > Artificial and synthetic data generators< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.AirPassengers" > AirPassengers dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.Bitcoin" > Bitcoin dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.DowJones" > DowJones dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.Enrollments" > Enrollments dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.Ethereum" > Ethereum dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.EURGBP" > EUR-GBP dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.EURUSD" > EUR-USD dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.GBPUSD" > GBP-USD dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.INMET" > INMET dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.Malaysia" > Malaysia dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.NASDAQ" > NASDAQ module< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.SONDA" > SONDA dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.SP500" > S& P 500 dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.TAIEX" > TAIEX dataset< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.henon" > Henon chaotic time series< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.logistic_map" > Logistic_map chaotic time series< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.lorentz" > Lorentz chaotic time series< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.mackey_glass" > Mackey-Glass chaotic time series< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.rossler" > Rossler chaotic time series< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.data.sunspots" > Sunspots dataset< / a > < / li >
< / ul >
< / li >
< / ul >
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< h4 > Previous topic< / h4 >
< p class = "topless" > < a href = "pyFTS.common.transformations.html"
title="previous chapter">pyFTS.common.transformations package< / a > < / p >
< h4 > Next topic< / h4 >
< p class = "topless" > < a href = "pyFTS.distributed.html"
title="next chapter">pyFTS.distributed package< / a > < / p >
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